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  • 151. Li, Si
    et al.
    Zhuang, Cheng
    Hao, Manzhao
    He, Xin
    Marquez, Juan C.
    KTH, Skolan för teknik och hälsa (STH), Medicinsk teknik, Medicinska sensorer, signaler och system. Shanghai Jiao Tong University, China.
    Niu, Chuanxin M.
    Lan, Ning
    Coordinated alpha and gamma control of muscles and spindles in movement and posture2015Inngår i: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 9, artikkel-id 122Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Mounting evidence suggests that both a and gamma motoneurons are active during movement and posture, but how does the central motor system coordinate the alpha-gamma controls in these tasks remains sketchy due to lack of in vivo data. Here a computational model of alpha-gamma control of muscles and spindles was used to investigate a -gamma integration and coordination for movement and posture. The model comprised physiologically realistic spinal circuitry, muscles, proprioceptors, and skeletal biomechanics. In the model, we divided the cortical descending commands into static and dynamic sets, where static commands (alpha(s) and gamma(s)) were for posture maintenance and dynamic commands (alpha(d) and gamma(d)) were responsible for movement. We matched our model to human reaching movement data by straightforward adjustments of descending commands derived from either minimal-jerk trajectories or human EMGs. The matched movement showed smooth reach-to-hold trajectories qualitatively close to human behaviors, and the reproduced EMGs showed the classic tri-phasic patterns. In particular, the function of gamma(d) was to gate the alpha(d) command at the propriospinal neurons (PN) such that antagonistic muscles can accelerate or decelerate the limb with proper timing. Independent control of joint position and stiffness could be achieved by adjusting static commands. Deefferentation in the model indicated that accurate static commands of as and gamma(s) are essential to achieve stable terminal posture precisely, and that the gamma(d) command is as important as the alpha(d) command in controlling antagonistic muscles for desired movements. Deafferentation in the model showed that losing proprioceptive afferents mainly affected the terminal position of movement, similar to the abnormal behaviors observed in human and animals. Our results illustrated that tuning the simple forms of alpha-gamma commands can reproduce a range of human reach-to-hold movements, and it is necessary to coordinate the set of alpha-gamma descending commands for accurate and stable control of movement and posture.

  • 152. Li, Z.
    et al.
    Liu, J.
    Wang, S.
    Li, Shuo
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Mikroelektronik och Informationsteknik, IMIT.
    SoC model analysis for ECG data acquisition with wireless sensor network2009Inngår i: 3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009, 2009, s. 1276-1279Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Mixed signal SoC for ECG waveform acquisition is designed and discussed in this paper. The SoC is a terminal of a special wireless sensor network (WSN) as a data source. Time parameters and communication band width are discussed. Especially, to satisfy the requirements of ECG waveform data acquisition and transmission the relation of sampling rate and communication band width is discussed. Based on the analysis of ECG frequency characteristics and the real time requirements of the WSN, synchronous data acquisition and transmission architecture of the SoC is designed. The DFG (Data flow graphic) model of the architecture is built for time parameters analysis and circuits design as well.

  • 153.
    Lindahl, Mikael
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Sarvestani, Iman Kamali
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Ekeberg, Örjan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Hällgren Kotaleski, Jeanette
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Signal enhancement in the output stage of the basal ganglia by synaptic short-term plasticity in the direct, indirect, and hyperdirect pathways2013Inngår i: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 7, s. UNSP 76-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Many of the synapses in the basal ganglia display short-term plasticity. Still, computational models have not yet been used to investigate how this affects signaling. Here we use a model of the basal ganglia network, constrained by available data, to quantitatively investigate how synaptic short-term plasticity affects the substantia nigra reticulata (SNr), the basal ganglia output nucleus. We find that SNr becomes particularly responsive to the characteristic burst-like activity seen in both direct and indirect pathway striatal medium spiny neurons (MSN). As expected by the standard model, direct pathway MSNs are responsible for decreasing the activity in SNr. In particular, our simulations indicate that bursting in only a few percent of the direct pathway MSNs is sufficient for completely inhibiting SNr neuron activity. The standard model also suggests that SNr activity in the indirect pathway is controlled by MSNs disinhibiting the subthalamic nucleus (STN) via the globus pallidus externa (GPe). Our model rather indicates that SNr activity is controlled by the direct GPe-SNr projections. This is partly because GPe strongly inhibits SNr but also due to depressing STN-SNr synapses. Furthermore, depressing GPe-SNr synapses allow the system to become sensitive to irregularly firing GPe subpopulations, as seen in dopamine depleted conditions, even when the GPe mean firing rate does not change. Similar to the direct pathway, simulations indicate that only a few percent of bursting indirect pathway MSNs can significantly increase the activity in SNr. Finally, the model predicts depressing STN-SNr synapses, since such an assumption explains experiments showing that a brief transient activation of the hyperdirect pathway generates a tri-phasic response in SNr, while a sustained STN activation has minor effects. This can be explained if STN-SNr synapses are depressing such that their effects are counteracted by the (known) depressing GPe-SNr inputs.

  • 154.
    Linde, Oskar
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Composed Complex-Cue Histograms: An Investigation of the Information Content in Receptive Field Based Image Descriptors for Object Recognition2012Inngår i: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 116, nr 4, s. 538-560Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Recent work has shown that effective methods for recognizing objects and spatio-temporal events can be constructed based on histograms of receptive field like image operations.

    This paper presents the results of an extensive study of the performance of different types of receptive field like image descriptors for histogram-based object recognition, based on different combinations of image cues in terms of Gaussian derivatives or differential invariants applied to either intensity information, colour-opponent channels or both. A rich set of composed complex-cue image descriptors is introduced and evaluated with respect to the problems of (i) recognizing previously seen object instances from previously unseen views, and (ii) classifying previously unseen objects into visual categories.

    It is shown that there exist novel histogram descriptors with significantly better recognition performance compared to previously used histogram features within the same class. Specifically, the experiments show that it is possible to obtain more discriminative features by combining lower-dimensional scale-space features into composed complex-cue histograms. Furthermore, different types of image descriptors have different relative advantages with respect to the problems of object instance recognition vs. object category classification. These conclusions are obtained from extensive experimental evaluations on two mutually independent data sets.

    For the task of recognizing specific object instances, combined histograms of spatial and spatio-chromatic derivatives are highly discriminative, and several image descriptors in terms rotationally invariant (intensity and spatio-chromatic) differential invariants up to order two lead to very high recognition rates.

    For the task of category classification, primary information is contained in both first- and second-order derivatives, where second-order partial derivatives constitute the most discriminative cue.

    Dimensionality reduction by principal component analysis and variance normalization prior to training and recognition can in many cases lead to a significant increase in recognition or classification performance. Surprisingly high recognition rates can even be obtained with binary histograms that reveal the polarity of local scale-space features, and which can be expected to be particularly robust to illumination variations.

    An overall conclusion from this study is that compared to previously used lower-dimensional histograms, the use of composed complex-cue histograms of higher dimensionality reveals the co-variation of multiple cues and enables much better recognition performance, both with regard to the problems of recognizing previously seen objects from novel views and for classifying previously unseen objects into visual categories.

  • 155.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    A computational theory of visual receptive fields2013Inngår i: Biological Cybernetics, ISSN 0340-1200, E-ISSN 1432-0770, Vol. 107, nr 6, s. 589-635Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world.

    These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space–time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales.

    It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations.

    There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative agreement are obtained for (i) spatial on-center/off-surround and off-center/on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) spatio-chromatic double-opponent neurons in V1, (iv) space–time separable spatio-temporal receptive fields in the LGN and V1, and (v) non-separable space–time tilted receptive fields in V1, all within the same unified theory. In addition, the paper presents a more general framework for relating and interpreting these receptive fields conceptually and possibly predicting new receptive field profiles as well as for pre-wiring covariance under scaling, affine, and Galilean transformations into the representations of visual stimuli.

    This paper describes the basic structure of the necessity results concerning receptive field profiles regarding the mathematical foundation of the theory and outlines how the proposed theory could be used in further studies and modelling of biological vision. It is also shown how receptive field responses can be interpreted physically, as the superposition of relative variations of surface structure and illumination variations, given a logarithmic brightness scale, and how receptive field measurements will be invariant under multiplicative illumination variations and exposure control mechanisms.

  • 156.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Invariance of visual operations at the level of receptive fields2013Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Receptive field profiles measured by cell recordings have shown that mammalian vision has developed receptive fields tuned to different sizes and orientations in the image domain as well as to different image velocities in space-time [1, 2]. This article presents a theory by which families of idealized receptive field profiles can be derived mathematically from a small set of basic assumptions that correspond to structural properties of the environment [3, 4]. The article also presents a theory for how basic invariance properties to variations in scale, viewing direction and relative motion can be obtained from the output of such receptive fields, using complementary selection mechanisms that operate over the output of families of receptive fields tuned to different parameters [4]. Thereby, the theory shows how basic invariance properties of a visual system can be obtained already at the level of receptive fields, and we can explain the different shapes of receptive field profiles found in biological vision from a requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment.

    Model.

    The brain is able to maintain a stable perception although the visual stimuli vary substantially on the retina due to geometric transformations and lighting variations in the environment. These transformations comprise (i) local scaling transformations caused by objects of different size and at different distances to the observer, (ii) locally linearized image deformations caused by variations in the viewing direction in relation to the object, (iii) locally linearized relative motions between the object and the observer and (iv) local multiplicative intensity transformations caused by illumination variations. Let us assume that receptive fields should be constructed by linear operations that are shift-invariant over space and/or space-time, with an additional requirement that receptive fields must not create new image structures at coarser scales that do not correspond to simplifications of corresponding structures at finer scales.

    Results.

    Given the above structural conditions, we derive idealized families of spatial and spatio-temporal receptive fields that satisfy these structural requirements by necessity, based on Gaussian kernels, Gaussian derivatives or closely related operators [3, 4].  We show that there are very close similarities between the receptive fields predicted from this theory and receptive fields found by cell recordings in biological vision, including (i) spatial on-center-off-surround and off-center-on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) space-time separable spatio-temporal receptive fields in the LGN and V1 and (iv) non-separable space-time tilted receptive fields in V1 [3, 4]. Indeed, from kernels predicted by this theory it is possible to generate receptive fields similar to all the basic types of monocular receptive fields reported by DeAngelis et al [2] in their survey of classical receptive fields.

    By complementing such receptive field measurements with selection mechanisms over the parameters in the receptive field families, we show how true invariance of receptive field responses can be obtained under scaling transformations, affine transformations and Galilean transformations [4]. Thereby, the framework provides a mathematically well-founded and biologically plausible model for how basic invariance properties can be achieved already at the level of receptive fields. In this way, the presented theory supports invariant recognition of objects and events under variations in viewpoint, retinal size, object motion and illumination.

    References.

    1. Hubel DH, Wiesel TN: Brain and Visual Perception, Oxford University Press, 2005. 

    2. DeAngelis GC, Anzai A: A modern view of the classical receptive field: Linear and non-linear spatio-temporal processing by V1 neurons. The Visual Neurosciences, MIT Press, vol 1, 705-719, 2004.

    3. Lindeberg T: Generalized Gaussian scale-space axiomatics comprising linear scale-space, affine scale-space and spatio-temporal scale-space. J Math Imaging Vis, 2011, 40(1):36-81.

    4. Lindeberg T: Invariance of visual operations at the level of receptive fields. PLOS One, in press, doi:10.1371/journal.pone.0066990, preprint available from arXiv:1210.0754.

  • 157.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Normative theory of visual receptive fields2017Rapport (Annet vitenskapelig)
    Abstract [en]

    This article gives an overview of a normative computational theory of visual receptive fields, by which idealized shapes of early spatial, spatio-chromatic and spatio-temporal receptive fields can be derived in an axiomatic way based on structural properties of the environment in combination with assumptions about the internal structure of a vision system to guarantee consistent handling of image representations over multiple spatial and temporal scales. Interestingly, this theory leads to predictions about visual receptive field shapes with qualitatively very good similarity to biological receptive fields measured in the retina, the LGN and the primary visual cortex (V1) of mammals.

  • 158.
    Lindeberg, Tony
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST).
    Provably scale-covariant hierarchical continuous networks based on scale-normalized differential expressions coupled in cascade2019Rapport (Annet vitenskapelig)
    Abstract [en]

    This article presents a theory for constructing continuous hierarchical networks in such a way that the networks are guaranteed to be provably scale covariant. We first present a general sufficiency argument for obtaining scale covariance, which holds for a wide class of networks defined from linear and non-linear differential expressions expressed in terms of scale-normalized scale-space derivatives.Then, we present a more detailed development of one example of such a network constructed from a combination of mathematically derived models of receptive fields and biologically inspired computations. Based on a functional model of complex cells in terms of an oriented quasi quadrature combination of first- and second-order directional Gaussian derivatives, we couple such primitive computations in cascade over combinatorial expansions over image orientations. Scale-space properties of the computational primitives are analysed and we give explicit proofs of how the resulting representation allows for scale and rotation covariance. A prototype application to texture analysis is developed and it is demonstrated that a simplified mean-reduced representation of the resulting QuasiQuadNet leads to promising experimental results on three texture datasets.

  • 159.
    Lindeberg, Tony
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST).
    Provably scale-covariant networks from oriented quasi quadrature measures in cascade2019Inngår i: Scale Space and Variational Methods in Computer Vision / [ed] M. Burger, J. Lellmann and J. Modersitzki, Springer Berlin/Heidelberg, 2019, Vol. 11603, s. 328-340Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This article presents a continuous model for hierarchical networks based on a combination of mathematically derived models of receptive fields and biologically inspired computations.

    Based on a functional model of complex cells in terms of an oriented quasi quadrature combination of first- and second-order directional Gaussian derivatives, we couple such primitive computations in cascade over combinatorial expansions over image orientations. Scale-space properties of the computational primitives are analysed and it is shown that the resulting representation allows for provable scale and rotation covariance.

    A prototype application to texture analysis is developed and it is demonstrated that a simplified mean-reduced representation of the resulting QuasiQuadNet leads to promising experimental results on three texture datasets.

  • 160.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Separable time-causal and time-recursive spatio-temporal receptive fields2015Inngår i: Scale Space and Variational Methods in Computer Vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings / [ed] J.-F. Aujol et al., Springer, 2015, s. 90-102Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We present an improved model and theory for time-causal and time-recursive spatio-temporal receptive fields,obtained by a combination of Gaussian receptive fields over the spatial domain and first-order integrators or equivalently truncated exponential filters coupled in cascade over the temporal domain. Compared to previous spatio-temporal scale-space formulations in terms of non-enhancement of local extrema or scale invariance, these receptive fields are based on different scale-space axiomatics over time by ensuring non-creation of new local extrema or zero-crossings with increasing temporal scale. Specifically, extensions are presented about parameterizing the intermediate temporal scale levels, analysing the resulting temporal dynamics and transferring the theory to a discrete implementation in terms of recursive filters over time.

  • 161.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Time-causal and time-recursive spatio-temporal receptive fields2016Inngår i: Journal of Mathematical Imaging and Vision, ISSN 0924-9907, E-ISSN 1573-7683, Vol. 55, nr 1, s. 50-88Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We present an improved model and theory for time-causal and time-recursive spatio-temporal receptive fields, obtained by a combination of Gaussian receptive fields over the spatial domain and first-order integrators or equivalently truncated exponential filters coupled in cascade over the temporal domain. 

    Compared to previous spatio-temporal scale-space formulations in terms of non-enhancement of local extrema or scale invariance, these receptive fields are based on different scale-space axiomatics over time by ensuring non-creation of new local extrema or zero-crossings with increasing temporal scale. Specifically, extensions are presented about (i) parameterizing the intermediate temporal scale levels, (ii) analysing the resulting temporal dynamics, (iii) transferring the theory to a discrete implementation in terms of recursive filters over time, (iv) computing scale-normalized spatio-temporal derivative expressions for spatio-temporal feature detection and (v) computational modelling of receptive fields in the lateral geniculate nucleus (LGN) and the primary visual cortex (V1) in biological vision. 

    We show that by distributing the intermediate temporal scale levels according to a logarithmic distribution, we obtain a new family of temporal scale-space kernels with better temporal characteristics compared to a more traditional approach of using a uniform distribution of the intermediate temporal scale levels. Specifically, the new family of time-causal kernels has much faster temporal response properties (shorter temporal delays) compared to the kernels obtained from a uniform distribution. When increasing the number of temporal scale levels, the temporal scale-space kernels in the new family do also converge very rapidly to a limit kernel possessing true self-similar scale-invariant properties over temporal scales. Thereby, the new representation allows for true scale invariance over variations in the temporal scale, although the underlying temporal scale-space representation is based on a discretized temporal scale parameter. 

    We show how scale-normalized temporal derivatives can be defined for these time-causal scale-space kernels and how the composed theory can be used for computing basic types of scale-normalized spatio-temporal derivative expressions in a computationally efficient manner.

  • 162.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Time-causal and time-recursive spatio-temporal receptive fields2015Rapport (Annet vitenskapelig)
    Abstract [en]

    We present an improved model and theory for time-causal and time-recursive spatio-temporal receptive fields, obtained by a combination of Gaussian receptive fields over the spatial domain and first-order integrators or equivalently truncated exponential filters coupled in cascade over the temporal domain. 

    Compared to previous spatio-temporal scale-space formulations in terms of non-enhancement of local extrema or scale invariance, these receptive fields are based on different scale-space axiomatics over time by ensuring non-creation of new local extrema or zero-crossings with increasing temporal scale. Specifically, extensions are presented about (i) parameterizing the intermediate temporal scale levels, (ii) analysing the resulting temporal dynamics, (iii) transferring the theory to a discrete implementation in terms of recursive filters over time, (iv) computing scale-normalized spatio-temporal derivative expressions for spatio-temporal feature detection and (v) computational modelling of receptive fields in the lateral geniculate nucleus (LGN) and the primary visual cortex (V1) in biological vision. 

    We show that by distributing the intermediate temporal scale levels according to a logarithmic distribution, we obtain a new family of temporal scale-space kernels with better temporal characteristics compared to a more traditional approach of using a uniform distribution of the intermediate temporal scale levels. Specifically, the new family of time-causal kernels has much faster temporal response properties (shorter temporal delays) compared to the kernels obtained from a uniform distribution. When increasing the number of temporal scale levels, the temporal scale-space kernels in the new family do also converge very rapidly to a limit kernel possessing true self-similar scale-invariant properties over temporal scales. Thereby, the new representation allows for true scale invariance over variations in the temporal scale, although the underlying temporal scale-space representation is based on a discretized temporal scale parameter. 

    We show how scale-normalized temporal derivatives can be defined for these time-causal scale-space kernels and how the composed theory can be used for computing basic types of scale-normalized spatio-temporal derivative expressions in a computationally efficient manner.

  • 163.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Time-causal and time-recursive spatio-temporal receptive fields for computer vision and computational modelling of biological vision2016Inngår i: International Workshop on Geometry, PDE’s and Lie Groups in Image Analysis, Eindhoven, The Netherlands, August 24-26, 2016., 2016Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    When operating on time-dependent image information in real time, a fundamental constraint originates from the fact that image operations must be both time-causal and time-recursive.

    In this talk, we will present an improved model and theory for time-causal and time-recursive spatio-temporal receptive fields, obtained by a combination of Gaussian filters over the spatial domain and first-order integrators or equivalently truncated exponential filters coupled in cascade over the temporal domain. This receptive field family obeys scale-space axiomatics in the sense of non-enhancement of local extrema over the spatial domain and non-creation of new local extrema over time for any purely temporal signal and does in these respects guarantee theoretically well-founded treatment of spatio-temporal image structures at different spatial and temporal scales.

    By a logarithmic distribution of the temporal scale levels in combination with the construction of a time-causal limit kernel based on an infinitely dense distribution of the temporal scale levels towards zero temporal scale, it will be shown that this family allows for temporal scale invariance although the temporal scale levels by the theory have to be discrete. Additionally, the family obeys basic invariance or covariance properties under other classes of natural image transformations including spatial scaling transformations, rotations/affine image deformations over the spatial domain, Galilean transformations of space time and local multiplicative intensity transformations. Thereby, this receptive field family allows for the formulation of multi-scale differential geometric image features with invariance or covariance properties under basic classes of natural image transformations over space-time.

    It is shown how this spatio-temporal scale-space concept (i) allows for efficient computation of different types of spatio-temporal features for purposes in computer vision and (ii) leads to predictions about biological receptive fields with good qualitative similarities to the results of cell recordings in the lateral geniculate nucleus (LGN) and the primary visual cortex (V1) in biological vision.

    References:

    T. Lindeberg (2016) ”Time-causal and time-recursive spatio-temporal receptive fields”, Journal of Mathematical Imaging and Vision, 55(1): 50-88.

    T. Lindeberg (2013) ”A computational theory of visual receptive fields”, Biological Cybernetics, 107(6): 589–635.

    T. Lindeberg (2013) ”Invariance of visual operations at the level of receptive fields”, PLOS One, 8(7): e66990.

    T. Lindeberg (2011) ”Generalized Gaussian scale-space axiomatics comprising linear scale space, affine scale space and spatio-temporal scale space”, Journal of Mathematical Imaging and Vision, 40(1): 36–81.

  • 164.
    Lindeberg, Tony
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Lidberg, Pär
    Roland, Per
    Analysis of brain activation patterns using a 3-D scale-space primal sketch1999Inngår i: Human Brain Mapping, ISSN 1065-9471, E-ISSN 1097-0193, Vol. 7, nr 3, s. 166-94Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A fundamental problem in brain imaging concerns how to define functional areas consisting of neurons that are activated together as populations. We propose that this issue can be ideally addressed by a computer vision tool referred to as the scale-space primal sketch. This concept has the attractive properties that it allows for automatic and simultaneous extraction of the spatial extent and the significance of regions with locally high activity. In addition, a hierarchical nested tree structure of activated regions and subregions is obtained. The subject in this article is to show how the scale-space primal sketch can be used for automatic determination of the spatial extent and the significance of rCBF changes. Experiments show the result of applying this approach to functional PET data, including a preliminary comparison with two more traditional clustering techniques. Compared to previous approaches, the method overcomes the limitations of performing the analysis at a single scale or assuming specific models of the data.

  • 165.
    Lindeberg, Tony
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    ter Haar Romeny, B.
    Utrecht University,.
    Linear Scale-Space II: Early visual operations1994Inngår i: Geometry-Driven Diffusion in Vision, Kluwer Academic Publishers, 1994, s. 43-77Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    Vision deals with the problem of deriving information about the world from the light reflected from it. Although the active and task-oriented nature of vision is only implicit in this formulation, this view captures several of the essential aspects of vision. As Marr (1982) phrased it in his book Vision, vision is an information processing task, in which an internal representation of information is of utmost importance. Only by representation information can be captured and made available to decision processes. The purpose of a representation is to make certain aspects of the information content explicit, that is, immediately accessible without any need for additional processing.

    This introductory chapter deals with a fundamental aspect of early image representation---the notion of scale. As Koenderink (1984) emphasizes, the problem of scale must be faced in any imaging situation. An inherent property of objects in the world and details in images is that they only exist as meaningful entities over certain ranges of scale. A simple example of this is the concept of a branch of a tree, which makes sense only at a scale from, say, a few centimeters to at most a few meters. It is meaningless to discuss the tree concept at the nanometer or the kilometer level. At those scales it is more relevant to talk about the molecules that form the leaves of the tree, or the forest in which the tree grows. Consequently, a multi-scale representation is of crucial importance if one aims at describing the structure of the world, or more specifically the structure of projections of the three-dimensional world onto two-dimensional images.

    The need for multi-scale representation is well understood, for example, in cartography; maps are produced at different degrees of abstraction. A map of the world contains the largest countries and islands, and possibly, some of the major cities, whereas towns and smaller islands appear at first in a map of a country. In a city guide, the level of abstraction is changed considerably to include streets and buildings etc. In other words, maps constitute symbolic multi-scale representations of the world around us, although constructed manually and with very specific purposes in mind.

    To compute any type of representation from image data, it is necessary to extract information, and hence interact with the data using certain operators. Some of the most fundamental problems in low-level vision and image analysis concern: what operators to use, where to apply them, and how large they should be. If these problems are not appropriately addressed, the task of interpreting the output results can be very hard. Ultimately, the task of extracting information from real image data is severely influenced by the inherent measurement problem that real-world structures, in contrast to certain ideal mathematical entities, such as ``points'' or ``lines'', appear in different ways depending upon the scale of observation.

    Phrasing the problem in this way shows the intimate relation to physics. Any physical observation by necessity has to be done through some finite aperture, and the result will, in general, depend on the aperture of observation. This holds for any device that registers physical entities from the real world including a vision system based on brightness data. Whereas constant size aperture functions may be sufficient in many (controlled) physical applications, e.g., fixed measurement devices, and also the aperture functions of the basic sensors in a camera (or retina) may have to determined a priori because of practical design constraints, it is far from clear that registering data at a fixed level of resolution is sufficient. A vision system for handling objects of different sizes and at difference distances needs a way to control the scale(s) at which the world is observed.

    The goal of this chapter is to review some fundamental results concerning a framework known as scale-space that has been developed by the computer vision community for controlling the scale of observation and representing the multi-scale nature of image data. Starting from a set of basic constraints (axioms) on the first stages of visual processing it will be shown that under reasonable conditions it is possible to substantially restrict the class of possible operations and to derive a (unique) set of weighting profiles for the aperture functions. In fact, the operators that are obtained bear qualitative similarities to receptive fields at the very earliest stages of (human) visual processing (Koenderink 1992). We shall mainly be concerned with the operations that are performed directly on raw image data by the processing modules are collectively termed the visual front-end. The purpose of this processing is to register the information on the retina, and to make important aspects of it explicit that are to be used in later stage processes. If the operations are to be local, they have to preserve the topology at the retina; for this reason the processing can be termed retinotopic processing.

    Early visual operationsAn obvious problem concerns what information should be extracted and what computations should be performed at these levels. Is any type of operation feasible? An axiomatic approach that has been adopted in order to restrict the space of possibilities is to assume that the very first stages of visual processing should be able to function without any direct knowledge about what can be expected to be in the scene. As a consequence, the first stages of visual processing should be as uncommitted and make as few irreversible decisions or choices as possible.

    The Euclidean nature of the world around us and the perspective mapping onto images impose natural constraints on a visual system. Objects move rigidly, the illumination varies, the size of objects at the retina changes with the depth from the eye, view directions may change etc. Hence, it is natural to require early visual operations to be unaffected by certain primitive transformations (e.g. translations, rotations, and grey-scale transformations). In other words, the visual system should extract properties that are invariant with respect to these transformations.

    As we shall see below, these constraints leads to operations that correspond to spatio-temporal derivatives which are then used for computing (differential) geometric descriptions of the incoming data flow. Based on the output of these operations, in turn, a large number of feature detectors can be expressed as well as modules for computing surface shape.

    The subject of this chapter is to present a tutorial overview on the historical and current insights of linear scale-space theories as a paradigm for describing the structure of scalar images and as a basis for early vision. For other introductory texts on scale-space; see the monographs by Lindeberg (1991, 1994) and Florack (1993) as well as the overview articles by ter Haar Romeny and Florack (1993) and Lindeberg (1994).

  • 166. Lindskog, M.
    et al.
    Halnes, Geir
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Oliveira, R. F.
    Hellgren Kotaleski, Jeanette
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Blackwell, K. T.
    Biochemical Networks in Psychiatric Disease2010Inngår i: Systems Biology in Psychiatric Research: From High-Throughput Data to Mathematical Modeling, Wiley-VCH Verlagsgesellschaft, 2010, s. 301-320Kapittel i bok, del av antologi (Fagfellevurdert)
  • 167.
    Lindskog, Mats
    KTH, Skolan för bioteknologi (BIO).
    Computational analyses of biological sequences -applications to antibody-based proteomics and gene family characterization2005Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Following the completion of the human genome sequence, post-genomic efforts have shifted the focus towards the analysis of the encoded proteome. Several different systematic proteomics approaches have emerged, for instance, antibody-based proteomics initiatives, where antibodies are used to functionally explore the human proteome. One such effort is HPR (the Swedish Human Proteome Resource), where affinity-purified polyclonal antibodies are generated and subsequently used for protein expression and localization studies in normal and diseased tissues. The antibodies are directed towards protein fragments, PrESTs (Protein Epitope Signature Tags), which are selected based on criteria favourable in subsequent laboratory procedures.

    This thesis describes the development of novel software (Bishop) to facilitate the selection of proper protein fragments, as well as ensuring a high-throughput processing of selected target proteins. The majority of proteins were successfully processed by this approach, however, the design strategy resulted in a number ofnfall-outs. These proteins comprised alternative splice variants, as well as proteins exhibiting high sequence similarities to other human proteins. Alternative strategies were developed for processing of these proteins. The strategy for handling of alternative splice variants included the development of additional software and was validated by comparing the immunohistochemical staining patterns obtained with antibodies generated towards the same target protein. Processing of high sequence similarity proteins was enabled by assembling human proteins into clusters according to their pairwise sequence identities. Each cluster was represented by a single PrEST located in the region of the highest sequence similarity among all cluster members, thereby representing the entire cluster. This strategy was validated by identification of all proteins within a cluster using antibodies directed to such cluster specific PrESTs using Western blot analysis. In addition, the PrEST design success rates for more than 4,000 genes were evaluated.

    Several genomes other than human have been finished, currently more than 300 genomes are fully sequenced. Following the release of the tree model organism black cottonwood (Populus trichocarpa), a bioinformatic analysis identified unknown cellulose synthases (CesAs), and revealed a total of 18 CesA family members. These genes are thought to have arisen from several rounds of genome duplication. This number is significantly higher than previous studies performed in other plant genomes, which comprise only ten CesA family members in those genomes. Moreover, identification of corresponding orthologous ESTs belonging to the closely related hybrid aspen (P. tremula x tremuloides) for two pairs of CesAs suggest that they are actively transcribed. This indicates that a number of paralogs have preserved their functionalities following extensive genome duplication events in the tree’s evolutionary history.

  • 168.
    Lindén, Henrik
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Hagen, E.
    Łeski, S.
    Norheim, E. S.
    Pettersen, K. H.
    Einevoll, G. T.
    LFPy: A tool for biophysical simulation of extracellular potentials generated by detailed model neurons2014Inngår i: Frontiers in Neuroinformatics, ISSN 1662-5196, E-ISSN 1662-5196, Vol. 7, nr Jan, s. 41-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Electrical extracellular recordings, i.e., recordings of the electrical potentials in the extracellular medium between cells, have been a main work-horse in electrophysiology for almost a century. The high-frequency part of the signal (>500 Hz), i.e., the multi-unit activity (MUA), contains information about the firing of action potentials in surrounding neurons, while the low-frequency part, the local field potential (LFP), contains information about how these neurons integrate synaptic inputs. As the recorded extracellular signals arise from multiple neural processes, their interpretation is typically ambiguous and difficult. Fortunately, a precise biophysical modeling scheme linking activity at the cellular level and the recorded signal has been established: the extracellular potential can be calculated as a weighted sum of all transmembrane currents in all cells located in the vicinity of the electrode. This computational scheme can considerably aid the modeling and analysis of MUA and LFP signals. Here, we describe LFPy, an open source Python package for numerical simulations of extracellular potentials. LFPy consists of a set of easy-to-use classes for defining cells, synapses and recording electrodes as Python objects, implementing this biophysical modeling scheme. It runs on top of the widely used NEURON simulation environment, which allows for flexible usage of both new and existing cell models. Further, calculation of extracellular potentials using the line-source-method is efficiently implemented. We describe the theoretical framework underlying the extracellular potential calculations and illustrate by examples how LFPy can be used both for simulating LFPs, i.e., synaptic contributions from single cells as well a populations of cells, and MUAs, i.e., extracellular signatures of action potentials.

  • 169. Liu, J.
    et al.
    Lv, C.
    Li, Z.
    Li, Shuo
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Mikroelektronik och Informationsteknik, IMIT.
    Switch bridge architecture of NoC for wireless ECG data acquisition2009Inngår i: 3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009, 2009, s. 887-890Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A switch bridge is addressed for the interconnection of two CPU systems in the SoC of the ETB (ECG terminal on body) in home healthcare wireless network. The SoC including multi CPU systems can be divided into different parts with data process function. Therefore each part of the system can work independently without influence each other. With the discussion of the performances of HAB and home networking, the switch bridge is a suitable technology for reducing the dies size and power consumption. The switch bridge designed in this paper connects two CPU systems and two others digital circuitry components together. To the CPU systems, common digital circuitry is a part of the CPU system with the bridge. The architecture and logic function of the switch bridge is analyzed in detail and simulated. The simulation results demonstrate that the connection bridge can not only supply the connection of two CPU and two common components, include display module and RAM, but also increased the running speed and system performance.

  • 170.
    Llorens, Vicente Charcos
    et al.
    KTH, Tidigare Institutioner (före 2005), Numerisk analys och datalogi, NADA.
    Fransén, Erik
    KTH, Tidigare Institutioner (före 2005), Numerisk analys och datalogi, NADA.
    Intrinsic desynchronization properties of neurons containing dendritic rapidly activating K-currents2004Inngår i: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 58, s. 137-143Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this work, we investigate the role of the potassium A-current (K-A) in linking network synchrony to cellular excitability and firing frequency. We present an analysis of the notion of synchrony and we describe its conceptual and modeling implications. An full synchronization, K-A enables a control over the timing, or even a suppression, of spikes. For completely desynchronized activity, we show how K-A affects fast changes in amplitude of the summed EPSPs as well as amount of depolarization caused by the input. Simulations at intermediate levels of synchrony suggest that activity resulting from the interaction between cellular excitability and network synchrony could be altered through K-A modulation.

  • 171. Lundin, Carolina
    et al.
    Käll, Lukas
    Stockholm Bioinformatics Center, AlbaNova.
    Kreher, Scott A.
    Kapp, Katja
    Sonnhammer, Erik L.
    Carlson, John R.
    Heijne, Gunnar von
    Nilsson, IngMarie
    Membrane topology of the Drosophila OR83b odorant receptor2007Inngår i: FEBS Letters, ISSN 0014-5793, E-ISSN 1873-3468, Vol. 581, nr 29, s. 5601-5604Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    By analogy to mammals, odorant receptors (ORs) in insects, such as Drosophila melanogaster, have long been thought to belong to the G-protein coupled receptor (GPCR) superfamily. However, recent work has cast doubt on this assumption and has tentatively suggested an inverted topology compared to the canonical N(out) - C(in) 7 transmembrane (TM) GPCR topology, at least for some Drosophila ORs. Here, we report a detailed topology mapping of the Drosophila OR83b receptor using engineered glycosylation sites as topology markers. Our results are inconsistent with a classical GPCR topology and show that OR83b has an intracellular N-terminus, an extracellular C-terminus, and 7TM helices.

  • 172.
    Lundqvist, Mikael
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Herman, Pawel
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Variability of spike firing during theta-coupled replay of memories in a simulated attractor network2012Inngår i: Brain Research, ISSN 0006-8993, E-ISSN 1872-6240, Vol. 1434, s. 152-161Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Simulation work has recently shown that attractor networks can reproduce Poisson-like variability of single cell spiking, with coefficient of variation (Cv(2)) around unity, consistent with cortical data. However, the use of local variability (Lv) measures has revealed area- and layer-specific deviations from Poisson-like firing. In order to test these findings in silico we used a biophysically detailed attractor network model. We show that Lv well above 1, specifically found in superficial cortical layers and prefrontal areas, can indeed be reproduced in such networks and is consistent with periodic replay rather than persistent firing. The memory replay at the theta time scale provides a framework for a multi-item memory storage in the model. This article is part of a Special Issue entitled Neural Coding.

  • 173.
    Lundqvist, Mikael
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm University, Sweden.
    Herman, Pawel
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm University, Sweden.
    Palva, M.
    Palva, S.
    Silverstein, David
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm University, Sweden.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm University, Sweden.
    Stimulus detection rate and latency, firing rates and 1-40Hz oscillatory power are modulated by infra-slow fluctuations in a bistable attractor network model2013Inngår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 83, s. 458-471Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Recordings of membrane and field potentials, firing rates, and oscillation amplitude dynamics show that neuronal activity levels in cortical and subcortical structures exhibit infra-slow fluctuations (ISFs) on time scales from seconds to hundreds of seconds. Similar ISFs are salient also in blood-oxygenation-level dependent (BOLD) signals as well as in psychophysical time series. Functional consequences of ISFs are not fully understood. Here, they were investigated along with dynamical implications of ISFs in large-scale simulations of cortical network activity. For this purpose, a biophysically detailed hierarchical attractor network model displaying bistability and operating in an oscillatory regime was used. ISFs were imposed as slow fluctuations in either the amplitude or frequency of fast synaptic noise. We found that both mechanisms produced an ISF component in the synthetic local field potentials (LFPs) and modulated the power of 1-40. Hz oscillations. Crucially, in a simulated threshold-stimulus detection task (TSDT), these ISFs were strongly correlated with stimulus detection probabilities and latencies. The results thus show that several phenomena observed in many empirical studies emerge concurrently in the model dynamics, which yields mechanistic insight into how infra-slow excitability fluctuations in large-scale neuronal networks may modulate fast oscillations and perceptual processing. The model also makes several novel predictions that can be experimentally tested in future studies.

  • 174. Lundqvist, Mikael
    et al.
    Herman, Pawel
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST).
    Warden, Melissa R.
    Brincat, Scott L.
    Miller, Earl K.
    Gamma and beta bursts during working memory readout suggest roles in its volitional control2018Inngår i: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, artikkel-id 394Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma (similar to 50-120 Hz) and beta (similar to 20-35 Hz) oscillations, the former linked to stimulus information in spiking. We examined these dynamics in relation to readout and control mechanisms of WM. Monkeys held sequences of two objects in WM to match to subsequent sequences. Changes in beta and gamma bursting suggested their distinct roles. In anticipation of having to use an object for the match decision, there was an increase in gamma and spiking information about that object and reduced beta bursting. This readout signal was only seen before relevant test objects, and was related to premotor activity. When the objects were no longer needed, beta increased and gamma decreased together with object spiking information. Deviations from these dynamics predicted behavioral errors. Thus, beta could regulate gamma and the information in WM.

  • 175. Ma, Zhanyu
    et al.
    Chien, Jen-Tzung
    Tan, Zheng-Hua
    Song, Yi-Zhe
    Taghia, Jalil
    Xiao, Ming
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Teknisk informationsvetenskap.
    Recent advances in machine learning for non-Gaussian data processing2018Inngår i: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 278, s. 1-3Artikkel i tidsskrift (Fagfellevurdert)
  • 176. Maes, Alexandre
    et al.
    Céline, Gracia
    Innocenti, Nicolas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Zhang, Kaiyang
    Aalto University, Finland .
    Aurell, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hajnsdorf, Eliane
    Landscape of RNA polyadenylation in E. coli2016Inngår i: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Polyadenylation is involved in degradation and quality control of bacterial RNAs. We used a combination of 5’-tagRACE and RNA-seq to analyse the total RNA content from wild-type strain and from mutant deficient for poly(A)polymerase. We determined that 157 mRNAs were affected as well as non-coding transcripts, up- and downregulated in the mutant when compared to the wild-type strain. Antisense RNAs were also detected and differentially affected by polyadenylation.

    Our results clearly reveal a correlation between the RNA folding energy and the requirement of polyadenylation to achieve the RNA decay. A new algorithm was developed to detect in both strains posttranscriptional modifications based on unmappable 3’-ends to analyse their position and composition. Therefore, any RNA 3'-end can be polyadenylated addressing them to the exoribonucleolytic machinery which is essential to degrade structured RNAs. Importantly, poly(A)polymerase was also upregulating the expression of genes related with the entire FliA regulon and numerous membrane transporters while downregulating the expression of the antigen 43 (flu), numerous sRNAs, antisense transcripts, REP sequences with the accumulation of numerous RNA fragments resulting from the processing of entire transcripts. Altogether we show here that polyadenylation has a broader spectrum of action than was suspected until now.

  • 177.
    Mahmudi, Owais
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Probabilistic Reconciliation Analysis for Genes and Pseudogenes2015Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Phylogeneticists have studied the evolution of life from single celled organisms to the astonishing biodiversity around us for a long time now. The relationship between species is often expressed as a binary tree - the tree of life. Availability of fully sequenced genomes across species provides us the opportunity to investigate and understand the evolutionary processes, and to reconstruct the gene and species phylogeny in greater detail and more accurately. However, the effect of interacting evolutionary processes, such as gene duplications, gene losses, pseudogenizations, and lateral gene transfers, makes the inference of gene phylogenies challenging.

    In this thesis, probabilistic  Bayesian methods are introduced  to infer gene hylogenies in the guidance of species phylogeny. The distinguishing feature f this work from the earlier reconciliation-based methods is that evolutionary vents are mapped to detailed time intervals on the evolutionary time-scale. he proposed probabilistic approach reconciles the evolutionary events to the pecies phylogeny by integrating  gene duplications, gene losses, lateral gene ransfers and sequence evolution under a relaxed molecular clock. Genome- ide gene families for vertebrates and prokaryotes are  analyzed using this pproach that provides interesting insight into the evolutionary processes.

    Finally, a probabilistic  model is introduced that  models evolution  of genes and pseudogenes  simultaneously. The model incorporates birth-death  pro- cess according to which genes are duplicated, pseudogenized and lost under a sequence evolution  model with  a relaxed molecular clock.  To model  the evolutionary scenarios realistically, the model employs two different sequence evolution  models for the  evolution  of genes  and pseudogenes. The recon- ciliation  of evolutionary events to the species phylogenies enable us to infer the evolutionary scenario with  a higher resolution.  Some subfamilies of two interesting gene superfamilies,  i.e.  olfactory receptors and zinc fingers, are analyzed using this approach, which provides interesting insights.

     

  • 178.
    Mahmudi, Owais
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Sennblad, Bengt
    Arvestad, Lars
    Nowick, Katja
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Gene-Pseudogene Evolution: a Probalitistic ApproachManuskript (preprint) (Annet vitenskapelig)
  • 179.
    Mahmudi, Owais
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Sjöstrand, Joel
    Sennblad, Bengt
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Genome-wide probabilistic reconciliation analysis across vertebrates2013Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 14, s. S10-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Gene duplication is considered to be a major driving force in evolution that enables the genome of a species to acquire new functions. A reconciliation - a mapping of gene tree vertices to the edges or vertices of a species tree explains where gene duplications have occurred on the species tree. In this study, we sample reconciliations from a posterior over reconciliations, gene trees, edge lengths and other parameters, given a species tree and gene sequences. We employ a Bayesian analysis tool, based on the probabilistic model DLRS that integrates gene duplication, gene loss and sequence evolution under a relaxed molecular clock for substitution rates, to obtain this posterior. By applying these methods, we perform a genome-wide analysis of a nine species dataset, OPTIC, and conclude that for many gene families, the most parsimonious reconciliation (MPR) - a reconciliation that minimizes the number of duplications - is far from the correct explanation of the evolutionary history. For the given dataset, we observe that approximately 19% of the sampled reconciliations are different from MPR. This is in clear contrast with previous estimates, based on simpler models and less realistic assumptions, according to which 98% of the reconciliations can be expected to be identical to MPR. We also generate heatmaps showing where in the species trees duplications have been most frequent during the evolution of these species.

  • 180. Marco, S.
    et al.
    Gutiérrez-Gálvez, A.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Martinez, D.
    Rospars, J. P.
    Beccherelli, R.
    Perera, A.
    Pearce, T.
    Vershure, P.
    Persaud, K.
    Biologically inspired large scale chemical sensor arrays and embedded data processing2013Inngår i: Smart Sensors, Actuators, And Mems VI, SPIE - International Society for Optical Engineering, 2013, s. 876303-Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

  • 181.
    Marco, Santiago
    et al.
    University Barcelona, IBEC.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Numerisk Analys och Datalogi, NADA.
    Gutierrez Galvez, Agustin
    University Barcelona.
    Exploratory Analysis of the Rat Olfactory Bulb Activity2006Inngår i: Chemical Senses, ISSN 0379-864X, E-ISSN 1464-3553, Vol. 31, nr 8, s. E73-E73Artikkel i tidsskrift (Annet vitenskapelig)
  • 182. Mazzoni, A.
    et al.
    Lindén, Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. University of Copenhagen, Denmark.
    Cuntz, H.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Panzeri, S.
    Einevoll, G. T.
    Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models2015Inngår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 11, nr 12, artikkel-id e1004584Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best “LFP proxy”, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with “ground-truth” LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

  • 183. McIlwain, Sean
    et al.
    Tamura, Kaipo
    Kertesz-Farkas, Attila
    Grant, Charles E.
    Diament, Benjamin
    Frewen, Barbara
    Howbert, J. Jeffry
    Hoopmann, Michael R.
    Käll, Lukas
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Eng, Jimmy K.
    MacCoss, Michael J.
    Noble, William Stafford
    Crux: Rapid Open Source Protein Tandem Mass Spectrometry Analysis2014Inngår i: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 13, nr 10, s. 4488-4491Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Efficiently and accurately analyzing big protein tandem mass spectrometry data sets requires robust software that incorporates state-of-the-art computational, machine learning, and statistical methods. The Crux mass spectrometry analysis software toolkit (http://cruxtoolkit.sourceforge.net) is an open source project that aims to provide users with a cross-platform suite of analysis tools for interpreting protein mass spectrometry data.

  • 184.
    Mehta, Mayank
    et al.
    UCLA.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Coordination in Circuits2010Inngår i: Dynamic Coordination in the Brain: From Neurons to Mind / [ed] C. Von der Malsburg, C., Phillips W. A., Singer W., MIT Press, 2010, s. 133-148Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 185.
    Meli, Cristina
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    A modular attractor associative memory with patchy connectivity and weight pruning2013Rapport (Annet vitenskapelig)
    Abstract [en]

    An important research topic in neuroscience is the study of mechanisms underlying memory and the estimation of the information capacity of the biological system. In this report we investigate the performance of a modular attractor network with recurrent connections similar to the cortical long-range connections extending in the horizontal direction. We considered a single learning rule, the BCPNN, which implements a kind of Hebbian learning and we trained the network with sparse random patterns. The storage capacity was measured experimentally for networks of size between 500 and 46K units with a constant activity level, gradually diluting the connectivity. We show that the storage capacity of the modular network is comparable with the theoretical values estimated for simple associative memories and furthermore we introduce a new technique to reduce the connectivity, which enhances the storage capacity up to the asymptotic value.

  • 186.
    Mengiste, Simachew Abebe
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Computational Approaches to the Degeneration of Brain Networks and Other Complex Networks2017Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Networks are ubiquitous with several levels of complexity, configuration, hierarchy and function. Many micro- and macro-scale biological or non-biological interactions define complex systems. Our most sophisticated organ, the brain, accommodates the interaction of its billions of neurons through trillions of synapses and is a good example of a complex system. Network structure has been shown to be the key to determine network functions. For instance, communities or modules in the network explain functional segregation and modular interactions reveal functional integration. Moreover, the dynamics of cortical networks have been experimentally shown to be linked to the behavioral states of the animal. The level of rate and synchrony have been demonstrated to be related to sleep (inactive) and awake (active) states of animals. The structure of brain networks is not static. New synapses are formed and some existing synapses or neurons die due to neurodegenerative disease, environmental influences, development and learning, etc. Although there are many studies on the function of brain networks, the changes by neuronal and synaptic degeneration have not been so far in focus. In fact, there is no known mathematical model on the progressive pattern of synaptic pruning and neurodegeneration. The goal of this dissertation is to develop various models of progressive network degeneration and analyze their impact on structural and functional features of the networks. In order to expand the often chosen approach of the "random networks", the "small world" and "scale-free" network topologies are considered which have recently been proposed as alternatives. The effect of four progressive synaptic pruning strategies on the size of critical sites of brain networks and other complex networks is analyzed. Different measures are used to estimate the levels of population rate, regularity, synchrony and pair-wise correlation of neuronal networks. Our analysis reveals that the network degree, instead of network topology, highly affects the mean population activity. 

  • 187. Merrihew, Gennifer E.
    et al.
    Davis, Colleen
    Ewing, Brent
    Williams, Gary
    Käll, Lukas
    University of Washington, Department of Genome Sciences.
    Frewen, Barbara E.
    Noble, William Stafford
    Green, Phil
    Thomas, James H.
    MacCoss, Michael J.
    Use of shotgun proteomics for the identification, confirmation, and correction of C. elegans gene annotations2008Inngår i: Genome Research, ISSN 1088-9051, E-ISSN 1549-5469, Vol. 18, nr 10, s. 1660-1669Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We describe a general mass spectrometry-based approach for gene annotation of any organism and demonstrate its effectiveness using the nematode Caenorhabditis elegans. We detected 6779 C. elegans proteins (67,047 peptides), including 384 that, although annotated in WormBase WS150, lacked cDNA or other prior experimental support. We also identified 429 new coding sequences that were unannotated in WS150. Nearly half (192/429) of the new coding sequences were confirmed with RT-PCR data. Thirty-three (approximately 8%) of the new coding sequences had been predicted to be pseudogenes, 151 (approximately 35%) reveal apparent errors in gene models, and 245 (57%) appear to be novel genes. In addition, we verified 6010 exon-exon splice junctions within existing WormBase gene models. Our work confirms that mass spectrometry is a powerful experimental tool for annotating sequenced genomes. In addition, the collection of identified peptides should facilitate future proteomics experiments targeted at specific proteins of interest.

  • 188. Mirzaei, Amin
    et al.
    Kumar, Arvind
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). University of Freiburg, Germany.
    Leventhal, Daniel
    Mallet, Nicolas
    Aertsen, Ad
    Berke, Joshua
    Schmidt, Robert
    Sensorimotor Processing in the Basal Ganglia Leads to Transient Beta Oscillations during Behavior2017Inngår i: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 37, nr 46, s. 11220-11232Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Brief epochs of beta oscillations have been implicated in sensorimotor control in the basal ganglia of task-performing healthy animals. However, which neural processes underlie their generation and how they are affected by sensorimotor processing remains unclear. To determine the mechanisms underlying transient beta oscillations in the LFP, we combined computational modeling of the subthalamo-pallidal network for the generation of beta oscillations with realistic stimulation patterns derived from single-unit data recorded from different basal ganglia subregions in rats performing a cued choice task. In the recordings, we found distinct firing patterns in the striatum, globus pallidus, and subthalamic nucleus related to sensory and motor events during the behavioral task. Using these firing patterns to generate realistic inputs to our network model led to transient beta oscillations with the same time course as the rat LFP data. In addition, our model can account for further nonintuitive aspects of beta modulation, including beta phase resets after sensory cues and correlations with reaction time. Overall, our model can explain how the combination of temporally regulated sensory responses of the subthalamic nucleus, ramping activity of the subthalamic nucleus, and movement-related activity of the globus pallidus leads to transient beta oscillations during behavior.

  • 189. Moruz, Luminita
    et al.
    Tomazela, Daniela
    Käll, Lukas
    Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University; Department of Genome Sciences, University of Washington, Seattle.
    Training, selection, and robust calibration of retention time models for targeted proteomics2010Inngår i: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 9, nr 10, s. 5209-5216Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Most notably such predictions are used to weed out incorrect peptide-spectrum matches, and to design targeted proteomics experiments. In this study, we describe a RT predictor, ELUDE, which can be employed in both applications. ELUDE's predictions are based on 60 features derived from the peptide's amino acid composition and optimally combined using kernel regression. When sufficient data is available, ELUDE derives a retention time index for the condition at hand making it fully portable to new chromatographic conditions. In cases when little training data is available, as often is the case in targeted proteomics experiments, ELUDE selects and calibrates a model from a library of pretrained predictors. Both model selection and calibration are carried out via robust statistical methods and thus ELUDE can handle situations where the calibration data contains erroneous data points. We benchmarked our method against two state-of-the-art predictors and showed that ELUDE outperforms these methods and tracked up to 34% more peptides in a theoretical SRM method creation experiment. ELUDE is freely available under Apache License from http://per-colator.com.

  • 190.
    Muhammad, Sayyed Auwn
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Probabilistic Modelling of Domain and Gene Evolution2016Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Phylogenetic inference relies heavily on statistical models that have been extended and refined over the past years into complex hierarchical models to capture the intricacies of evolutionary processes. The wealth of information in the form of fully sequenced genomes has led to the development of methods that are used to reconstruct the gene and species evolutionary histories in greater and more accurate detail. However, genes are composed of evolutionary conserved sequence segments called domains, and domains can also be affected by duplications, losses, and bifurcations implied by gene or species evolution. This thesis proposes an extension of evolutionary models, such as duplication-loss, rate, and substitution, that have previously been used to model gene evolution, to model the domain evolution.

    In this thesis, I am proposing DomainDLRS: a comprehensive, hierarchical Bayesian method, based on the DLRS model by Åkerborg et al., 2009, that models domain evolution as occurring inside the gene and species tree. The method incorporates a birth-death process to model the domain duplications and losses along with a domain sequence evolution model with a relaxed molecular clock assumption. The method employs a variant of Markov Chain Monte Carlo technique called, Grouped Independence Metropolis-Hastings for the estimation of posterior distribution over domain and gene trees. By using this method, we performed analyses of Zinc-Finger and PRDM9 gene families, which provides an interesting insight of domain evolution.

    Finally, a synteny-aware approach for gene homology inference, called GenFamClust, is proposed that uses similarity and gene neighbourhood conservation to improve the homology inference. We evaluated the accuracy of our method on synthetic and two biological datasets consisting of Eukaryotes and Fungal species. Our results show that the use of synteny with similarity is providing a significant improvement in homology inference.

  • 191.
    Muhammad, Sayyed Auwn
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Sennblad, Bengt
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Species tree aware simultaneous reconstruction of gene and domain evolutionManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Most genes are composed of multiple domains with a common evolutionary history that typically perform a specific function in the resulting protein. As witnessed by many studies of key gene families, it is important to understand how domains have been duplicated, lost, transferred between genes, and rearranged. Similarly to the case of evolutionary events affecting entire genes, these domain events have large consequences for phylogenetic reconstruction and, in addition, they create considerable obstacles for gene sequence alignment algorithms, a prerequisite for phylogenetic reconstruction.

    We introduce the Domain-DLRS model, a hierarchical, generative probabilistic model containing three levels corresponding to species, genes, and domains, respectively. From a dated species tree, a gene tree is generated according to the DL model, which is a birth-death model generalized to occur in a dated tree. Then, from the dated gene tree, a pre-specified number of dated domain trees are generated using the DL model and the molecular clock is relaxed, effectively converting edge times to edge lengths. Finally, for each domain tree and its lengths, domain sequences are generated for the leaves based on a selected model of sequence evolution.

    For this model, we present a MCMC based inference framework called Domain-DLRS that as input takes a dates species tree together with a multiple sequence alignment for each domain family, while it as output provids an estimated posterior distribution over reconciled gene and domain trees. By requiring aligned domains rather than genes, our framework evades the problem of aligning genes that have been exposed to domain duplications, in particular non-tandem domain duplications. We show that Domain-DLRS performs better than MrBayes on synthetic data and that it outperforms MrBayes on biological data. We analyse several zinc-finger genes and show that most domain duplications have been tandem duplications, of which some have involved two or more domains, but non-tandem duplications have also been common, in particular in gene families of complex evolutionary history such as PRDM9.

  • 192. Nadalin, F.
    et al.
    Vezzi, Francesco
    KTH, Skolan för datavetenskap och kommunikation (CSC). KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Policriti, A.
    A multi-objective optimisation approach to the design of experiment in de novo assembly projects2012Inngår i: Database and Expert Systems Applications (DEXA), 2012 23rd International Workshop on, IEEE , 2012, s. 213-217Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Genomics projects are characterised by difficult biological pipelines and high sequencing costs. In particular, de novo assembly projects must go through data production, assembly, and results validation. Early mistakes in the first (and most expensive) step can therefore be detected only at a very late stage and have serious consequences. Our goal is to design a pipeline able to provide the users with the optimal input for the sequencing experiments within a de novo assembly project. We present a new approach, based on multi-objective optimisation, aiming at transforming the design of genomics experiments from a set of "best practices" to an algorithmically controlled procedure. We implemented our model with mode FRONTIER and we show how our method can be used to infer the final quality of a whole genome assembly project from the results obtained on a small but representative sample.

  • 193. Nadalin, Francesca
    et al.
    Vezzi, Francesco
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Policriti, Alberto
    GapFiller: a de novo assembly approach to fill the gap within paired reads2012Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 13, s. S8-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Next Generation Sequencing technologies are able to provide high genome coverages at a relatively low cost. However, due to limited reads' length (from 30 bp up to 200 bp), specific bioinformatics problems have become even more difficult to solve. De novo assembly with short reads, for example, is more complicated at least for two reasons: first, the overall amount of "noisy" data to cope with increased and, second, as the reads' length decreases the number of unsolvable repeats grows. Our work's aim is to go at the root of the problem by providing a pre-processing tool capable to produce (in-silico) longer and highly accurate sequences from a collection of Next Generation Sequencing reads. Results: In this paper a seed-and-extend local assembler is presented. The kernel algorithm is a loop that, starting from a read used as seed, keeps extending it using heuristics whose main goal is to produce a collection of error-free and longer sequences. In particular, GapFiller carefully detects reliable overlaps and operates clustering similar reads in order to reconstruct the missing part between the two ends of the same insert. Our tool's output has been validated on 24 experiments using both simulated and real paired reads datasets. The output sequences are declared correct when the seed-mate is found. In the experiments performed, GapFiller was able to extend high percentages of the processed seeds and find their mates, with a false positives rate that turned out to be nearly negligible. Conclusions: GapFiller, starting from a sufficiently high short reads coverage, is able to produce high coverages of accurate longer sequences (from 300 bp up to 3500 bp). The procedure to perform safe extensions, together with the mate-found check, turned out to be a powerful criterion to guarantee contigs' correctness. GapFiller has further potential, as it could be applied in a number of different scenarios, including the post-processing validation of insertions/deletions detection pipelines, pre-processing routines on datasets for de novo assembly pipelines, or in any hierarchical approach designed to assemble, analyse or validate pools of sequences.

  • 194.
    Nair, Anu G.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST).
    Modeling Biochemical Network Involved in Striatal Dopamine Signaling2018Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    In this thesis, I studied the molecular integration of reward-learning related neuromodulatory inputs by striatal medium-sized projection neurons (MSNs) using mass-action kinetic modeling.

    It is known that, in reward learning, an unexpected reward results in transient elevation in dopamine (peak) whereas omission of an expected reward leads to transient dopamine decrease (dip). In silico experiments performed in the current study indicated that reward-related transient dopamine signals could act differentially on the cAMP/PKA signaling of the two MSN classes, D1 receptor expressing MSNs (D1 MSNs) and D2 receptor expressing MSNs (D2 MSNs). PKA in D1 MSN responded to dopamine peaks, whereas in D2 MSN it was affected by dopamine dips. Simulations further highlighted the possibility that cAMP/PKA signaling in D1 MSNs is tonically inhibited by acetylcholine by activating muscarinic M4 receptors under the basal condition. In this scenario, the D1 receptor activation by a dopamine peak does not have any downstream effect, unless the dopamine peak is accompanied by an acetylcholine dip that could release the M4-mediated inhibition. Such acetylcholine dips accompany dopamine peaks due to the time-locked dopaminergic bursts and cholinergic pauses observed in reward-learning. Thus, an acetylcholine dip could be viewed as a time window for dopamine signaling in D1 MSN. Similarly, the cAMP/PKA signaling in D2 MSN could be tonically inhibited by the dopamine-dependent D2 receptors. In this case, a dopamine dip results in the cAMP/PKA activation, and the strength of the downstream response depends on the level of basal adenosine, acting via A2a receptors. These results highlight how multiple neuromodulators could be integrated by striatal MSNs to produce effective downstream response. Such signal integration scenarios require that the dopamine and acetylcholine-triggered cAMP signaling be sufficiently powerful and sensitive. However, quantitative information regarding the efficacy of dopamine and acetylcholine on cAMP signaling is virtually nonexistent for living MSNs. Therefore, the effects of dopamine and acetylcholine on cAMP signaling were quantitatively characterized in this study by imaging genetically-encoded FRET-based biosensor expressed in mice brain slices. The measurements confirmed that the cAMP signaling in MSNs is quite sensitive and could strongly be influenced by neuromodulators, thus supporting the underlying model requirements, and thereby predictions.

    Another parameter that is important for effective molecular signal integration is the relative timing between various convergent inputs. For example, studies have shown that LTP in D1 MSNs is produced if corticostriatal glutamate synaptic activity is shortly followed by a dopamine peak. However, there is no LTP if the order of the inputs is reversed. This temporal dependence is believed to result in various aspects of reward learning, such as reward causality, and is theoretically represented by the so-called eligibility trace. However, little is known how such temporal constraints emerge at the level of molecular signaling. I investigated the possible molecular mechanism responsible for the emergence of this temporal constraints, using computational modeling. This study proposes a novel molecular mechanism based on the coordinated activity of two striatally enriched phosphoproteins, DARPP-32 and ARPP-21 that could explain the emergence of the timing-dependence for postsynaptic signal integration, and thus a plausible molecular underpinning for the eligibility trace of reward learning.

    In summary, the results presented in this thesis advance our understanding on how the striatal cAMP respond towards reward-related nueromodulator signals, and the downstream effects on synaptic signaling and reward learning.

  • 195.
    Nair, Anu G.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Modeling receptor induced signaling in MSNs: Interaction between molecules involved in striatal synaptic plasticity2014Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Basal Ganglia are evolutionarily conserved brain nuclei involved in several physiologically important animal behaviors like motor control and reward learning. Striatum, which is the input nuclei of basal ganglia, integrates inputs from several neurons, like cortical and thalamic glutamatergic input and local GABAergic inputs. Several neuromodulators, such as dopamine, accetylcholine and serotonin modulate the functional properties of striatal neurons. Aberrations in the intracellular signaling of these neurons lead to several debilitating neurodegenerative diseases, like Parkinson’s disease. In order to understand these aberrations we should first identify the role of different molecular players in the normal physiology.

    The long term goal of this research is to understand the molecular mechanisms responsible for the integration of different neuromodulatory signals by striatal medium spiny neurons (MSN). This signal integration is known to play important role in learning. This is manifested via changes in the synaptic weights between different neurons. The group of synpases taken into consideration for the current work is the corticostriatal one, which are synapses between the cortical projection neurons and MSNs. One of the molecular processes of considerable interest is the interaction between dopaminergic and cholinergic inputs. In this thesis I have investigated the interactions between the biochemical cascades triggered by dopaminergic, cholinergic (ACh) and glutamatergic inputs to the striatal MSN. The dopamine induced signaling increases the levels of cAMP in the striatonigral MSNs. The sources of dopamine and acetylcholine are dopaminergic neurons (DAN) from midbrain and tonically active cholinergic interneurons (TAN) of striatum, respectively. A sub-second burst activity in DAN along with a simultaneous pause in TAN is a characteristic effect elicited by a salient stimulus. This, in turn, leads to a dopamine peak and, possibly, an acetylcholine (ACh) dip in striatum.

    I have looked into the possibility of sensing this ACh dip and the dopamine peak at striatonigral MSNs. These neurons express D1 dopamine receptor (D1R) coupled to Golf and M4 Muscarinic receptor (M4R) coupled to Gi/o . These receptors are expressed significantly in the dendritic spines of these neurons where the Adenylate Cyclase 5 (AC5) is a point of convergence for these two signals. Golf stimulates the production of cAMP by AC5 whereas Gi/o inhibits the Golf mediated cAMP production. I have performed a kinetic-modeling exercise to explore how dopamine and ACh interacts with each other via these receptors and what are the effects on the downstream signaling events.

    The results of model simulation suggest that the striatonigral MSNs are able to sense the ACh dip via M4R. They integrate the dip with the dopamine peak to activate AC5 synergistically. We also found that the ACh tone may act as a potential noise filter against noisy dopamine signals. The parameters for the G-protein GTPase activity indicate towards an important role of GTPase Activating Proteins (GAPs), like RGS, in this process. Besides this we also hypothesize that M4R may have therapeutic potential.

  • 196.
    Nair, Anu G.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Gutierrez-Arenas, Omar
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Eriksson, Olivia
    Department of Numerical Analysis and Computer Science, Stockholm University, Stockholm.
    Hällgren Kotaleski, Jeanette
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Can MSNs listen to the cholinergic pause via M4R?Manuskript (preprint) (Annet vitenskapelig)
  • 197.
    Nair, Anu G.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Gutierrez-Arenas, Omar
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Eriksson, Olivia
    Department of Numerical Analysis and Computer Science, Stockholm University, Stockholm.
    Jauhiainen, Alexandra
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm.
    Blackwell, Kim T.
    Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA.
    Hällgren Kotaleski, Jeanette
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Modeling Intracellular Signaling Underlying Striatal Function in Health and Disease2014Inngår i: Computational Neuroscience / [ed] Blackwell, K.T., Elsevier, 2014, Vol. 123, s. 277-304Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars cornpacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data.

  • 198.
    Nair, Anu G.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Manipal Univ, India.
    Gutierrez-Arenas, Omar
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Eriksson, Olivia
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Vincent, Pierre
    Hellgren Kotaleski, Jeanette
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Univ, Sweden; Karolinska Inst, Sweden.
    Sensing Positive versus Negative Reward Signals through Adenylyl Cyclase-Coupled GPCRs in Direct and Indirect Pathway Striatal Medium Spiny Neurons2015Inngår i: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 35, nr 41, s. 14017-14030Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Transient changes in striatal dopamine (DA) concentration are considered to encode a reward prediction error (RPE) in reinforcement learning tasks. Often, a phasic DA change occurs concomitantly with a dip in striatal acetylcholine (ACh), whereas other neuromodulators, such as adenosine (Adn), change slowly. There are abundant adenylyl cyclase (AC) coupled GPCRs for these neuromodulators in striatal medium spiny neurons (MSNs), which play important roles in plasticity. However, little is known about the interaction between these neuromodulators via GPCRs. The interaction between these transient neuromodulator changes and the effect on cAMP/PKA signaling via Golf- and Gi/o-coupled GPCR are studied here using quantitative kinetic modeling. The simulations suggest that, under basal conditions, cAMP/PKA signaling could be significantly inhibited in D1R+ MSNs via ACh/M4R/Gi/o and an ACh dip is required to gate a subset of D1R/Golf-dependent PKA activation. Furthermore, the interaction between ACh dip and DA peak, via D1R and M4R, is synergistic. In a similar fashion, PKA signaling in D2+ MSNs is under basal inhibition via D2R/Gi/o and a DA dip leads to a PKA increase by disinhibiting A2aR/Golf, but D2+ MSNs could also respond to the DA peak via other intracellular pathways. This study highlights the similarity between the two types of MSNs in terms of high basal AC inhibition by Gi/o and the importance of interactions between Gi/o and Golf signaling, but at the same time predicts differences between them with regard to the sign of RPE responsible for PKA activation.

  • 199.
    Natarajan Arul, Murugan
    et al.
    KTH, Skolan för bioteknologi (BIO), Teoretisk kemi och biologi.
    Apostolov, Rossen Pavlov
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC.
    Rinkevicius, Zilvinas
    KTH, Skolan för bioteknologi (BIO), Teoretisk kemi och biologi.
    Kongsted, Jacob
    epartment of Physics, Chemistry and Pharmacy, University of Southern Denmark.
    Lindahl, Erik
    KTH, Skolan för teknikvetenskap (SCI), Teoretisk fysik, Beräkningsbiofysik.
    Ågren, Hans
    KTH, Skolan för bioteknologi (BIO), Teoretisk kemi och biologi.
    Association dynamics and linear and nonlinear optical properties of an N-acetylaladanamide probe in a POPC membrane2013Inngår i: Journal of the American Chemical Society, ISSN 0002-7863, E-ISSN 1520-5126, Vol. 135, nr 36, s. 13590-13597Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Along with the growing evidence that relates membrane abnormalities to various diseases, biological membranes have been acknowledged as targets for therapy. Any such abnormality in the membrane structure alters the membrane potential which in principle can be captured by measuring properties of specific optical probes. There exists by now many molecular probes with absorption and fluorescence properties that are sensitive to local membrane structure and to the membrane potential. To suggest new high-performance optical probes for membrane-potential imaging it is important to understand in detail the membrane-induced structural changes in the probe, the membrane association dynamics of the probe, and its membrane-specific optical properties. To contribute to this effort, we here study an optical probe, N-acetylaladanamide (NAAA), in the presence of a POPC lipid bilayer using a multiscale integrated approach to assess the probe structure, dynamics, and optical properties in its membrane-bound status and in water solvent. We find that the probe eventually assimilates into the membrane with a specific orientation where the hydrophobic part of the probe is buried inside the lipid bilayer, while the hydrophilic part is exposed to the water solvent. The computed absorption maximum is red-shifted when compared to the gas phase. The computations of the two-photon absorption and second harmonic generation cross sections of the NAAA probe in its membrane-bound state which is of its first kind in the literature suggest that this probe can be used for imaging the membrane potential using nonlinear optical microscopy.

  • 200.
    Navarro, Jose Fernandez
    et al.
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Sjöstrand, Joel
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Salmén, Fredrik
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Lundeberg, Joakim
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Ståhl, Patrik L.
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Karolinska Institutet, Sverige.
    ST Pipeline: an automated pipeline for spatial mapping of unique transcripts2017Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 33, nr 16, s. 2591-2593Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Motivation: In recent years we have witnessed an increase in novel RNA-seq based techniques for transcriptomics analysis. Spatial transcriptomics is a novel RNA-seq based technique that allows spatial mapping of transcripts in tissue sections. The spatial resolution adds an extra level of complexity, which requires the development of new tools and algorithms for efficient and accurate data processing. Results: Here we present a pipeline to automatically and efficiently process RNA-seq data obtained from spatial transcriptomics experiments to generate datasets for downstream analysis.

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