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  • 101. Kremkow, Jens
    et al.
    Aertsen, Ad
    Kumar, Arvind
    University of Freiburg, Germany .
    Gating of signal propagation in spiking neural networks by balanced and correlated excitation and inhibition2010In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 30, no 47, p. 15760-8Article in journal (Refereed)
    Abstract [en]

    Both ongoing and natural stimulus driven neuronal activity are dominated by transients. Selective gating of these transients is mandatory for proper brain function and may, in fact, form the basis of millisecond-fast decision making and action selection. Here we propose that neuronal networks may exploit timing differences between correlated excitation and inhibition (temporal gating) to control the propagation of spiking activity transients. When combined with excitation-inhibition balance, temporal gating constitutes a powerful mechanism to control the propagation of mixtures of transient and tonic neural activity components.

  • 102. Kremkow, Jens
    et al.
    Kumar, Arvind
    Rotter, Stefan
    Aertsen, Ad
    Emergence of population synchrony in a layered network of the cat visual cortex2007In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 70, no 10-12, p. 2069-2073Article in journal (Refereed)
    Abstract [en]

    Recently, a quantitative wiring diagram for the local neuronal network of cat visual cortex was described [T. Binzegger, R.J. Douglas, K.A.C. Martin, A quantitative map of the circuit of the cat primary visual cortex, J. Neurosci. 39 (24) (2004) 8441-8453.] giving the first complete estimate of synaptic connectivity among various types of neurons in different cortical layers. Here we numerically studied the activity dynamics of the resulting heterogeneous layered network of spiking integrate-and-fire neurons, connected with conductance-based synapses. The layered network exhibited, among other states, an interesting asynchronous activity with intermittent population-wide synchronizations. These population bursts (PB) were initiated by a network hot spot, and then spread into the other parts of the network. The cause of this PB is the correlation amplifying nature of recurrent connections, which becomes significant in densely coupled networks. The hot spot was located in layer 2 / 3, the part of the network with the highest number of excitatory recurrent connections. We conclude that in structured networks, regions with a high degree of recurrence and many out-going fibres may be a source for population-wide synchronization.

  • 103.
    Krishnamurthy, Pradeep
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. Stockholm University, Sweden.
    Silberberg, Gilad
    Lansner, Anders
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. Stockholm University, Sweden.
    Long-range recruitment of Martinotti cells causes surround suppression and promotes saliency in an attractor network model2015In: Frontiers in Neural Circuits, ISSN 1662-5110, E-ISSN 1662-5110, Vol. 9, article id 60Article in journal (Refereed)
    Abstract [en]

    Although the importance of long-range connections for cortical information processing has been acknowledged for a long time, most studies focused on the long-range interactions between excitatory cortical neurons. Inhibitory interneurons play an important role in cortical computation and have thus far been studied mainly with respect to their local synaptic interactions within the cortical microcircuitry. A recent study showed that long-range excitatory connections onto Martinotti cells (MC) mediate surround suppression. Here we have extended our previously reported attractor network of pyramidal cells (PC) and MC by introducing long-range connections targeting MC. We have demonstrated how the network with Martinotti cell-mediated long-range inhibition gives rise to surround suppression and also promotes saliency of locations at which simple non-uniformities in the stimulus field are introduced. Furthermore, our analysis suggests that the presynaptic dynamics of MC is only ancillary to its orientation tuning property in enabling the network with saliency detection. Lastly, we have also implemented a disinhibitory pathway mediated by another interneuron type (VIP interneurons), which inhibits MC and abolishes surround suppression.

  • 104.
    Kumar, Arvind
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Reprogramming the striatal stars: A new treatment option for Parkinson's disease2017In: Movement Disorders, ISSN 0885-3185, E-ISSN 1531-8257, Vol. 32, no 7, p. 991-991Article in journal (Refereed)
  • 105.
    Kumar, Arvind
    et al.
    University of Freiburg, Germany .
    Cardanobile, Stefano
    Rotter, Stefan
    Aertsen, Ad
    The role of inhibition in generating and controlling Parkinson’s disease oscillations in the Basal Ganglia2011In: Frontiers in Systems Neuroscience, ISSN 1662-5137, E-ISSN 1662-5137, Vol. OCTOBER 2011, article id 86Article in journal (Refereed)
    Abstract [en]

    Movement disorders in Parkinson’s disease (PD) are commonly associated with slow oscillations and increased synchrony of neuronal activity in the basal ganglia. The neural mechanisms underlying this dynamic network dysfunction, however, are only poorly understood. Here, we show that the strength of inhibitory inputs from striatum to globus pallidus external (GPe) is a key parameter controlling oscillations in the basal ganglia. Specifically, the increase in striatal activity observed in PD is sufficient to unleash the oscillations in the basal ganglia. This finding allows us to propose a unified explanation for different phenomena: absence of oscillation in the healthy state of the basal ganglia, oscillations in dopamine-depleted state and quenching of oscillations under deep-brain-stimulation (DBS). These novel insights help us to better understand and optimize the function of DBS protocols. Furthermore, studying the model behavior under transient increase of activity of the striatal neurons projecting to the indirect pathway, we are able to account for both motor impairment in PD patients and for reduced response inhibition in DBS implanted patients.

  • 106.
    Kumar, Arvind
    et al.
    University of Freiburg, Germany .
    Mehta, Mayank R
    Frequency dependent changes in NMDAR-dependent synaptic plasticity2011In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 5, no 38Article in journal (Refereed)
    Abstract [en]

    The NMDAR-dependent synaptic plasticity is thought to mediate several forms of learning, and can be induced by spike trains containing a small number of spikes occurring with varying rates and timing, as well as with oscillations. We computed the influence of these variables on the plasticity induced at a single NMDAR containing synapse using a reduced model that was analytically tractable, and these findings were confirmed using detailed, multi-compartment model. In addition to explaining diverse experimental results about the rate and timing dependence of synaptic plasticity, the model made several novel and testable predictions. We found that there was a preferred frequency for inducing long-term potentiation (LTP) such that higher frequency stimuli induced lesser LTP, decreasing as 1/f when the number of spikes in the stimulus was kept fixed. Among other things, the preferred frequency for inducing LTP varied as a function of the distance of the synapse from the soma. In fact, same stimulation frequencies could induce LTP or long-term depression depending on the dendritic location of the synapse. Next, we found that rhythmic stimuli induced greater plasticity then irregular stimuli. Furthermore, brief bursts of spikes significantly expanded the timing dependence of plasticity. Finally, we found that in the ~5-15-Hz frequency range both rate- and timing-dependent plasticity mechanisms work synergistically to render the synaptic plasticity most sensitive to spike timing. These findings provide computational evidence that oscillations can have a profound influence on the plasticity of an NMDAR-dependent synapse, and show a novel role for the dendritic morphology in this process.

  • 107.
    Kumar, Arvind
    et al.
    Albert Ludwigs University, Germany; Brown University, United States .
    Rotter, Stefan
    Aertsen, Ad
    Conditions for propagating synchronous spiking and asynchronous firing rates in a cortical network model2008In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 28, no 20, p. 5268-5280Article in journal (Refereed)
    Abstract [en]

    Isolated feedforward networks (FFNs) of spiking neurons have been studied extensively for their ability to propagate transient synchrony and asynchronous firing rates, in the presence of activity independent synaptic background noise (Diesmann et al., 1999; van Rossum et al., 2002). In a biologically realistic scenario, however, the FFN should be embedded in a recurrent network, such that the activity in the FFN and the network activity may dynamically interact. Previously, transient synchrony propagating in an FFN was found to destabilize the dynamics of the embedding network (Mehring et al., 2003). Here, we show that by modeling synapses as conductance transients, rather than current sources, it is possible to embed and propagate transient synchrony in the FFN, without destabilizing the background network dynamics. However, the network activity has a strong impact on the type of activity that can be propagated in the embedded FFN. Global synchrony and high firing rates in the embedding network prohibit the propagation of both, synchronous and asynchronous spiking activity. In contrast, asynchronous low-rate network states support the propagation of both, synchronous spiking and asynchronous, but only low firing rates. In either case, spiking activity tends to synchronize as it propagates, challenging the feasibility to transmit information in asynchronous firing rates. Finally, asynchronous network activity allows to embed more than one FFN, with the amount of cross talk depending on the degree of overlap in the FFNs. This opens the possibility of computational mechanisms using transient synchrony among the activities in multiple FFNs.

  • 108.
    Kumar, Arvind
    et al.
    University of Freiburg,Germany .
    Rotter, Stefan
    Aertsen, Ad
    Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding2010In: Nature Reviews Neuroscience, ISSN 1471-003X, E-ISSN 1471-0048, Vol. 11, no 9, p. 615-627Article in journal (Refereed)
    Abstract [en]

    The brain is a highly modular structure. To exploit modularity, it is necessary that spiking activity can propagate from one module to another while preserving the information it carries. Therefore, reliable propagation is one of the key properties of a candidate neural code. Surprisingly, the conditions under which spiking activity can be propagated have received comparatively little attention in the experimental literature. By contrast, several computational studies in the last decade have addressed this issue. Using feedforward networks (FFNs) as a generic network model, they have identified two dynamical activity modes that support the propagation of either asynchronous (rate code) or synchronous (temporal code) spiking. Here, we review the dichotomy of asynchronous and synchronous propagation in FFNs, propose their integration into a single extended conceptual framework and suggest experimental strategies to test our hypothesis.

  • 109.
    Kumar, Arvind
    et al.
    Bernstein Center for Computational Neuroscience, Germany .
    Schrader, Sven
    Aertsen, Ad
    Rotter, Stefan
    The high-conductance state of cortical networks2008In: Neural Computation, ISSN 0899-7667, E-ISSN 1530-888X, Vol. 20, p. 1-43Article in journal (Refereed)
    Abstract [en]

    We studied the dynamics of large networks of spiking neurons with conductance-based (nonlinear) synapses and compared them to networks with current-based (linear) synapses. For systems with sparse and inhibition-dominated recurrent connectivity, weak external inputs induced asynchronous irregular firing at low rates. Membrane potentials fluctuated a few millivolts below threshold, and membrane conductances were increased by a factor 2 to 5 with respect to the resting state. This combination of parameters characterizes the ongoing spiking activity typically recorded in the cortex in vivo. Many aspects of the asynchronous irregular state in conductance-based networks could be sufficiently well characterized with a simple numerical mean field approach. In particular, it correctly predicted an intriguing property of conductance-based networks that does not appear to be shared by current-based models: they exhibit states of low-rate asynchronous irregular activity that persist for some period of time even in the absence of external inputs and without cortical pacemakers. Simulations of larger networks (up to 350,000 neurons) demonstrated that the survival time of self-sustained activity increases exponentially with network size.

  • 110.
    Kumar, Arvind
    et al.
    University of Freiburg, Germany .
    Vlachos, Ioannis
    Aertsen, Ad
    Boucsein, Clemens
    Challenges of understanding brain function by selective modulation of neuronal subpopulations2013In: TINS - Trends in Neurosciences, ISSN 0166-2236, E-ISSN 1878-108X, Vol. 36, no 10, p. 579-586Article, review/survey (Refereed)
    Abstract [en]

    Neuronal networks confront researchers with an overwhelming complexity of interactions between their elements. A common approach to understanding neuronal processing is to reduce complexity by defining subunits and infer their functional role by selectively modulating them. However, this seemingly straightforward approach may lead to confusing results if the network exhibits parallel pathways leading to recurrent connectivity. We demonstrate limits of the selective modulation approach and argue that, even though highly successful in some instances, the approach fails in networks with complex connectivity. We argue to refine experimental techniques by carefully considering the structural features of the neuronal networks involved. Such methods could dramatically increase the effectiveness of selective modulation and may lead to a mechanistic understanding of principles underlying brain function.

  • 111.
    Lansner, Anders
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Fransén, Erik
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Sandberg, Anders
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Cell assembly dynamics in detailed and abstract attractor models of cortical associative memory2003In: Theory in biosciences, ISSN 1431-7613, E-ISSN 1611-7530, Vol. 122, no 1, p. 19-36Article in journal (Refereed)
    Abstract [en]

    During the last few decades we have seen a convergence among ideas and hypotheses regarding functional principles underlying human memory. Hebb's now more than fifty years old conjecture concerning synaptic plasticity and cell assemblies, formalized mathematically as attractor neural networks, has remained among the most viable and productive theoretical frameworks. It suggests plausible explanations for Gestalt aspects of active memory like perceptual completion, reconstruction and rivalry. We review the biological plausibility of these theories and discuss some critical issues concerning their associative memory functionality in the light of simulation studies of models with palimpsest memory properties. The focus is on memory properties and dynamics of networks modularized in terms of cortical minicolumns and hypercolumns. Biophysical compartmental models demonstrate attractor dynamics that support cell assembly operations with fast convergence and low firing rates. Using a scaling model we obtain reasonable relative connection densities and amplitudes. An abstract attractor network model reproduces systems level psychological phenomena seen in human memory experiments as the Sternberg and von Restorff effects. We conclude that there is today considerable substance in Hebb's theory of cell assemblies and its attractor network formulations, and that they have contributed to increasing our understanding of cortical associative memory function. The criticism raised with regard to biological and psychological plausibility as well as low storage capacity, slow retrieval etc has largely been disproved. Rather, this paradigm has gained further support from new experimental data as well as computational modeling.

  • 112. Larhammar, Martin
    et al.
    Patra, Kalicharan
    Blunder, Martina
    Emilsson, Lina
    Peuckert, Christiane
    Arvidsson, Emma
    Rönnlund, Daniel
    KTH, School of Engineering Sciences (SCI), Applied Physics, Experimental Biomolecular Physics.
    Preobraschenski, Julia
    Birgner, Carolina
    Limbach, Christoph
    Widengren, Jerker
    Blom, Hans
    Jahn, Reinhard
    Wallen-Mackenzie, Asa
    Kullander, Klas
    SLC10A4 Is a Vesicular Amine-Associated Transporter Modulating Dopamine Homeostasis2015In: Biological Psychiatry, ISSN 0006-3223, E-ISSN 1873-2402, Vol. 77, no 6, p. 526-536Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The neuromodulatory transmitters, biogenic amines, have profound effects on multiple neurons and are essential for normal behavior and mental health. Here we report that the orphan transporter SLC10A4, which in the brain is exclusively expressed in presynaptic vesicles of monoaminergic and cholinergic neurons, has a regulatory role in dopamine homeostasis. METHODS: We used a combination of molecular and behavioral analyses, pharmacology, and in vivo amperometry to assess the role of SLC10A4 in dopamine- regulated behaviors. RESULTS: We show that SLC10A4 is localized on the same synaptic vesicles as either vesicular acetylcholine transporter or vesicular monoamine transporter 2. We did not find evidence for direct transport of dopamine by SLC10A4; however, synaptic vesicle preparations lacking SLC10A4 showed decreased dopamine vesicular uptake efficiency. Furthermore, we observed an increased acidification in synaptic vesicles isolated from mice over-expressing SLC10A4. Loss of SLC10A4 in mice resulted in reduced striatal serotonin, noradrenaline, and dopamine concentrations and a significantly higher dopamine turnover ratio. Absence of SLC10A4 led to slower dopamine clearance rates in vivo, which resulted in accumulation of extracellular dopamine. Finally, whereas SLC10A4 null mutant mice were slightly hypoactive, they displayed hypersensitivity to administration of amphetamine and tranylcypromine. CONCLUSIONS: Our results demonstrate that SLC10A4 is a vesicular monoaminergic and cholinergic associated transporter that is important for dopamine homeostasis and neuromodulation in vivo. The discovery of SLC10A4 and its role in dopaminergic signaling reveals a novel mechanism for neuromodulation and represents an unexplored target for the treatment of neurological and mental disorders.

  • 113.
    Leijon, Arne
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Articulation index and Shannon mutual information2007In: HEARING: FROM SENSORY PROCESSING TO PERCEPTION / [ed] Kollmeier, B; Hohmann, V; Mauermann, M; Verhey, J; Klump, G; Langemann, U; Uppenkamp, S, BERLIN: SPRINGER-VERLAG BERLIN , 2007, p. 525-532Conference paper (Refereed)
    Abstract [en]

    The Articulation Index (AI), later revised and standardized as the Speech Intelligibility Index (SII), and the Speech Transmission Index (STI) have been successful in predicting speech intelligibility from acoustic measurements. Both approaches calculate the index as sum of additive audibility contributions from different frequency bands. Allen (2003) noted that a similar additivity property also holds for Shannon’s information-theoretic concept of Channel Capacity. Allen showed that the contributions to channel capacity are (approximately) linearly related to the signal-to-noise ratio (in dB), just like the audibility contributions to the AI, and suggested that the AI is actually a kind of channel-capacity measure. This would be a fundamental information-theoretical basis for the empirical success of AI theory.

  • 114. Lewis, Peter
    et al.
    Rosén, Robert
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Unsbo, Peter
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Gustafsson, Jörgen
    Resolution of static and dynamic stimuli in the peripheral visual field2011In: Vision Research, ISSN 0042-6989, E-ISSN 1878-5646, Vol. 51, no 16, p. 1829-1834Article in journal (Refereed)
    Abstract [en]

    In a clinical setting, emphasis is given to foveal visual function, and tests generally only utilize static stimuli. In this study, we measured static (SVA) and dynamic visual acuity (DVA) in the central and peripheral visual field on healthy, young emmetropic subjects using stationary and drifting Gabor patches. There were no differences between SVA and DVA in the peripheral visual field; however, SVA was superior to DVA in the fovea for both velocities tested. In addition, there was a clear naso-temporal asymmetry for both SVA and DVA for isoeccentric locations in the visual field beyond 10 degrees eccentricity. The lack of difference in visual acuity between static and dynamic stimuli found in this study may reflect the use of drift-motion as opposed to displacement motion used in previous studies.

  • 115. Li, F.
    et al.
    Zhu, H.
    Wu, S.
    Gao, Q.
    Hu, Z.
    Xu, J.
    Xu, G.
    He, Sailing
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. South China Normal University (SCNU).
    Effect of frequent degree of deceiving on the prefrontal cortical response to deception: A functional near-infrared spectroscopy (fNIRS) study2015Conference paper (Refereed)
    Abstract [en]

    Functional near-infrared spectroscopy (fNIRS) is an emerging brain-imaging technique which has been used to various areas. Previous studies have indicated that frequent deceiving would make deceiving easier. In this study, fNIRS was used to explore the effect of frequent degree of deceiving on the prefrontal cortical response to deception. Self-related questions were used in the experiment. The results showed different patterns of neural activation between non-frequent deceiving and frequent deceiving. In Channel 11 (in the left prefrontal cortex), non-frequent deceiving led to a greater neural activation than telling the truth, while this pattern did not appear in frequent deceiving. Our finding suggested that fNIRS has ability to detect deception under different situations.

  • 116. Li, Si
    et al.
    Zhuang, Cheng
    Hao, Manzhao
    He, Xin
    Marquez, Juan C.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Shanghai Jiao Tong University, China.
    Niu, Chuanxin M.
    Lan, Ning
    Coordinated alpha and gamma control of muscles and spindles in movement and posture2015In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 9, article id 122Article in journal (Refereed)
    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.

  • 117.
    Li, Xiaogai
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Improved safety standards are needed to better protect younger children at playgrounds2018In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, no 1, article id 15061Article in journal (Refereed)
    Abstract [en]

    Playground-related traumatic brain injuries (TBIs) in children remain a considerable problem world-wide and current safety standards are being questioned due to historical reasons where the injury thresholds had been perpetuated from automobile industry. Here we investigated head injury mechanisms due to falls on playgrounds using a previously developed and validated age-scalable and positionable whole body child model impacted at front, back and side of the head simulating head-first falls from 1.59 meters (m). The results show that a playground material passing the current testing standards (HIC < 1000 and resultant linear acceleration <200g) resulted in maximum strain in the brain higher than known injury thresholds, thus not offering sufficient protection especially for younger children. The analysis highlights the age dependence of head injuries in children due to playground falls and the youngest have a higher risk of brain injury and skull fracture. Further, the results provide the first biomechanical evidence guiding age-dependent injury thresholds for playground testing standards. The results also have direct implications for novel designs of playground materials for a better protection of children from TBIs. Only making the playground material thicker and more compliant is not sufficient. This study represents the first initiative of using full body human body models of children as a new tool to improve playground testing standards and to better protect the children at playgrounds.

  • 118. Lidbeck, Cecilia
    et al.
    Bartonek, Åsa
    Yadav, Priti
    KTH, School of Engineering Sciences (SCI), Mechanics, Biomechanics.
    Tedroff, Kristina
    Åstrand, Per
    Hellgren, Kerstin
    Gutierrez-Farewik, Elena M.
    KTH, School of Engineering Sciences (SCI), Mechanics, Biomechanics. Karolinska Inst, Sweden.
    The role of visual stimuli on standing posture in children with bilateral cerebral palsy2016In: BMC Neurology, ISSN 1471-2377, E-ISSN 1471-2377, Vol. 16, no 1, article id 151Article in journal (Refereed)
    Abstract [en]

    Background: In children with bilateral cerebral palsy (CP) maintaining a standing position can be difficult. The fundamental motor task of standing independently is achieved by an interaction between the visual, somatosensory, and vestibular systems. In CP, the motor disorders are commonly accompanied by sensory and perceptual disturbances. Our aims were to examine the influence of visual stimuli on standing posture in relation to standing ability. Methods: Three dimensional motion analysis with surface electromyography was recorded to describe body position, body movement, and muscle activity during three standing tasks: in a self-selected position, while blindfolded, and during an attention-demanding task. Participants were twenty-seven typically-developing (TD) children and 36 children with bilateral CP, of which 17 required support for standing (CP-SwS) and 19 stood without support (CP-SwoS). Results: All children with CP stood with a more flexed body position than the TD children, even more pronounced in the children in CP-SwS. While blindfolded, the CP-SwS group further flexed their hips and knees, and increased muscle activity in knee extensors. In contrast, the children in CP-SwoS maintained the same body position but increased calf muscle activity. During the attention-demanding task, the children in CP-SwoS stood with more still head and knee positions and with less muscle activity. Conclusions: Visual input was important for children with CP to maintain a standing position. Without visual input the children who required support dropped into a further crouched position. The somatosensory and vestibular systems alone could not provide enough information about the body position in space without visual cues as a reference frame. In the children who stood without support, an intensified visual stimulus enhanced the ability to maintain a quiet standing position. It may be that impairments in the sensory systems are major contributors to the difficulties to stand erect in children with CP.

  • 119. Liebmann, Thomas
    et al.
    Kruusmägi, Markus
    Sourial-Bassillious, Nermin
    Bondar, Alexander
    Svenningsson, Per
    Flajolet, Marc
    Greengard, Paul
    Scott, Lena
    Brismar, Hjalmar
    KTH, School of Engineering Sciences (SCI), Applied Physics, Cell Physics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Aperia, Anita
    A Noncanonical Postsynaptic Transport Route for a GPCR Belonging to the Serotonin Receptor Family2012In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 32, no 50, p. 17998-18008Article in journal (Refereed)
    Abstract [en]

    Postsynaptic receptor trafficking plays an essential role in tuning neurotransmission and signal plasticity and has emerged as a potential therapeutic target in neuropsychiatric disease. Using a novel application of fluorescence recovery after photobleaching in rat hippocampal neurons, we examined transport from the soma to dendrites of seven G-protein-coupled receptors (GPCRs) implicated in mood disorders. Most GPCRs were delivered to dendrites via lateral diffusion, but one GPCR, the serotonin 1B receptor (5-HT1B), was delivered to the dendrites in secretory vesicles. Within the dendrites, 5-HT1B were stored in a reservoir of accessible vesicles that were recruited to preferential sites in plasma membrane, as observed with superecliptic pHluorin labeling. After membrane recruitment, 5-HT1B transport via lateral diffusion and temporal confinement to inhibitory and excitatory synapses was monitored by single particle tracking. These results suggest an alternative mechanism for control of neuronal activity via a GPCR that has been implicated in mood regulation.

  • 120.
    Lindahl, Mikael
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Computational Dissection of the Basal Ganglia: functions and dynamics in health and disease2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The basal ganglia (BG), a group of nuclei in the forebrain of all vertebrates, are important for behavioral selection. BG receive contextual input from most cortical areas as well as from parts of the thalamus, and provide output to brain systems that are involved in the generation of behavior, i.e. the thalamus and the brain stem. Many neurological disorders such as Parkinson’s disease and Huntington’s disease, and several neuropsychiatric disorders, are related to BG. Studying BG enhances the understanding as to how behaviors are learned and modified. These insights can be used to improve treatments for several BG disorders, and to develop brain-inspired algorithms for solving special information-processing tasks.

     

    In this thesis modeling and simulations have been used to investigate function and dynamics of BG. In the first project a model was developed to explore a new hypothesis about how conflicts between competing actions are resolved in BG. It was proposed that a subsystem named the arbitration system, composed of the subthalamic nucleus (STN), pedunculopontine nucleus (PPN), the brain stem, central medial nucleus of thalamus (CM), globus pallidus interna (GPi) and globus pallidus externa (GPe), resolve basic conflicts between alternative motor programs. On top of the arbitration system there is a second subsystem named the extension systems, which involves the direct and indirect pathway of the striatum. This system can modify the output of the arbitration system to bias action selection towards outcomes dependent on contextual information.

     

    In the second project a model framework was developed in two steps, with the aim to gain a deeper understanding of how synapse dynamics, connectivity and neural excitability in the BG relate to function and dynamics in health and disease. First a spiking model of STN, GPe and substantia nigra pars reticulata (SNr), with emulated inputs from striatal medium spiny neurons (MSNs) and the cortex, was built and used to study how synaptic short-term plasticity affected action selection signaling in the direct-, hyperdirect- and indirect pathways. It was found that the functional consequences of facilitatory synapses onto SNr neurons are substantial, and only a few presynaptic MSNs can suppress postsynaptic SNr neurons. The model also predicted that STN signaling in SNr is mainly effective in a transient manner. The model was later extended with a striatal network, containing MSNs and fast spiking interneurons (FSNs), and modified to represent GPe with two types of neurons: type I, which projects downstream in BG, and type A, which have a back-projection to striatum. Furthermore, dopamine depletion dependent modification of connectivity and neuron excitability were added to the model. Using this extended BG model, it was found that FSNs and GPe type A neurons controlled excitability of striatal neurons during low cortical drive, whereas MSN collaterals have a greater impact at higher cortical drive. The indirect pathway increased the dynamical range over which two possible action commands were competing, while removing intrastriatal inhibition deteriorated action selection capabilities. Dopamine-depletion induced effects on spike synchronization and oscillations in the BG were also investigated here.

     

    For the final project, an abstract spiking BG model which included a hypothesized control of the reward signaling dopamine system was developed. This model incorporated dopamine-dependent synaptic plasticity, and used a plasticity rule based on probabilistic inference called Bayesian Confidence Propagation Neural Network (BCPNN). In this paradigm synaptic connections were controlled by gathering statistics about neural input and output activity. Synaptic weights were inferred using Bayes’ rule to estimate the confidence of future observations from the input. The model exhibits successful performance, measured as a moving average of correct selected actions, in a multiple-choice learning task with a changeable reward schedule. Furthermore, the model predicts a decreased performance upon dopamine lesioning, and suggests that removing the indirect pathway may disrupt learning in profound ways.

  • 121.
    Lindahl, Mikael
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hällgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Untangling basal ganglia network dynamics and function: role of dopamine depletion and inhibition investigated in a spiking network modelManuscript (preprint) (Other academic)
  • 122.
    Lindahl, Mikael
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Sarvestani, Iman Kamali
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Ekeberg, Örjan
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Hällgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Signal enhancement in the output stage of the basal ganglia by synaptic short-term plasticity in the direct, indirect, and hyperdirect pathways2013In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 7, p. UNSP 76-Article in journal (Refereed)
    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.

  • 123.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    A computational theory of visual receptive fields2013In: Biological Cybernetics, ISSN 0340-1200, E-ISSN 1432-0770, Vol. 107, no 6, p. 589-635Article in journal (Refereed)
    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.

  • 124.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    A framework for invariant visual operations based on receptive field responses2013In: SSVM 2013: Fourth International Conference on Scale Space and Variational Methods in Computer Vision, June 2-6, Schloss Seggau, Graz region, Austria: Invited keynote address / [ed] Arjan Kuijper, 2013Conference paper (Other academic)
    Abstract [en]

    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. This talk presents a unified theory for achieving basic invariance properties of visual operations already at the level of receptive fields.

    This generalized framework for invariant receptive field responses comprises:

    • local scaling transformations caused by objects of different size and at different distances to the observer,
    • locally linearized image deformations caused by variations in the viewing direction in relation to the object,
    • locally linearized relative motions between the object and the observer and
    • local multiplicative intensity transformations caused by illumination variations.

    The receptive field model can be derived by necessity from symmetry properties of the environment and leads to predictions about receptive field profiles in good agreement with receptive field profiles measured by cell recordings in mammalian vision. Indeed, the receptive field profiles in the retina, LGN and V1 can be seen as close to ideal to what is motivated by the idealized requirements.

    By complementing receptive field measurements with selection mechanisms over the parameters in the receptive field families, it is shown how true invariance of receptive field responses can be obtained under scaling transformations, affine transformations and Galilean transformations. 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 and support invariant recognition of objects and events under variations in viewpoint, retinal size, object motion and illumination.

    The theory can explain the different shapes of receptive field profiles found in biological vision, which are tuned to different sizes and orientations in the image domain as well as to different image velocities in space-time, from a requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment.

    References:

    • 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, volume 40, number 1, pages 36-81, May 2011.
    • T. Lindeberg (2013) “Invariance of visual operations at the level of receptive fields”, PLoS ONE 8(7): e66990, doi:10.1371/journal.pone.0066990, preprint available from arXiv:1210.0754.
    • T. Lindeberg (2013) "Generalized axiomatic scale-space theory", Advances in Imaging and Electron Physics, (P. Hawkes, ed.), Elsevier, volume 178, pages 1-96, Academic Press: Elsevier Inc., doi: 10.1016/B978-0-12-407701-0.00001-7
  • 125.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Invariance of visual operations at the level of receptive fields2013Conference paper (Refereed)
    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.

  • 126.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Invariance of visual operations at the level of receptive fields2013In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 7, p. e66990-1-e66990-33Article in journal (Refereed)
    Abstract [en]

    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. This paper presents a theory for achieving basic invariance properties already at the level of receptive fields. Specifically, the presented framework comprises (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. The receptive field model can be derived by necessity from symmetry properties of the environment and leads to predictions about receptive field profiles in good agreement with receptive field profiles measured by cell recordings in mammalian vision. Indeed, the receptive field profiles in the retina, LGN and V1 are close to ideal to what is motivated by the idealized requirements. By complementing receptive field measurements with selection mechanisms over the parameters in the receptive field families, it is shown how true invariance of receptive field responses can be obtained under scaling transformations, affine transformations and Galilean transformations. 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 and support invariant recognition of objects and events under variations in viewpoint, retinal size, object motion and illumination. The theory can explain the different shapes of receptive field profiles found in biological vision, which are tuned to different sizes and orientations in the image domain as well as to different image velocities in space-time, from a requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment.

  • 127.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Normative theory of visual receptive fields2017Report (Other academic)
    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.

  • 128.
    Lindeberg, Tony
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Eriksson, Björn
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Johansson, Fredrik
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Roland, Per
    Dept. of Neuroscience, Karolinska Institute.
    Automatic matching of brain images and brain atlases using multi-scale fusion algorithms1997In: / [ed] L. Friberg, A. Gjedde, S. Holm, N.A. Lassen, and M. Novak, 1997, p. 419-Conference paper (Refereed)
    Abstract [en]

    This paper presents a method for automatic matching of brain images using automatic scale selection

  • 129.
    Lindeberg, Tony
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Florack, Luc
    Utrecht University.
    Foveal scale-space and the linear increase of receptive field size as a function of eccentricity1994Report (Other academic)
    Abstract [en]

    This paper addresses the formulation of a foveal scale-space and its relation to the scaling property of receptive field sizes with eccentricity. It is shown how the notion of a fovea can be incorporated into conventional scale-space theory leading to a foveal log-polar scale-space. Natural assumptions about uniform treatment of structures over scales and finite processing capacity imply a linear increase of minimum receptive field size as a function of eccentricity. These assumptions are similar to the ones used for deriving linear scale-space theory and the Gaussian receptive field model for an idealized visual front-end.

  • 130.
    Lindeberg, Tony
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Florack, Luc
    Utrecht University.
    On the decrease of resolution as a function of eccentricity for a foveal vision system1992Report (Other academic)
  • 131.
    Lindeberg, Tony
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Lidberg, Per
    Roland, Per
    Karolinska Institutet.
    Analysis of Brain Activation Patterns Using A 3-D Scale-Space Primal Sketch1997In: : HBM'97, published in Neuroimage, volume 5, number 4, 1997, p. 393-393Conference paper (Refereed)
    Abstract [en]

    This paper presents a method for automatically determining the spatial extent and the significance ofrCBF changes.

  • 132.
    Lindeberg, Tony
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Lidberg, Pär
    Roland, Per
    Analysis of brain activation patterns using a 3-D scale-space primal sketch1999In: Human Brain Mapping, ISSN 1065-9471, E-ISSN 1097-0193, Vol. 7, no 3, p. 166-94Article in journal (Refereed)
    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.

  • 133.
    Llorens, Vicente Charcos
    et al.
    KTH, Superseded Departments (pre-2005), Numerical Analysis and Computer Science, NADA.
    Fransén, Erik
    KTH, Superseded Departments (pre-2005), Numerical Analysis and Computer Science, NADA.
    Intrinsic desynchronization properties of neurons containing dendritic rapidly activating K-currents2004In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 58, p. 137-143Article in journal (Refereed)
    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.

  • 134.
    Lundqvist, Mikael
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Herman, Pawel
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Lansner, Anders
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Effect of Prestimulus Alpha Power, Phase, and Synchronization on Stimulus Detection Rates in a Biophysical Attractor Network Model2013In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 33, no 29, p. 11817-11824Article in journal (Refereed)
    Abstract [en]

    Spontaneous oscillations measured by local field potentials, electroencephalograms and magnetoencephalograms exhibit a pronounced peak in the alpha band (8-12 Hz) in humans and primates. Both instantaneous power and phase of these ongoing oscillations have commonly been observed to correlate with psychophysical performance in stimulus detection tasks. We use a novel model-based approach to study the effect of prestimulus oscillations on detection rate. A previously developed biophysically detailed attractor network exhibits spontaneous oscillations in the alpha range before a stimulus is presented and transiently switches to gamma-like oscillations on successful detection. We demonstrate that both phase and power of the ongoing alpha oscillations modulate the probability of such state transitions. The power can either positively or negatively correlate with the detection rate, in agreement with experimental findings, depending on the underlying neural mechanism modulating the oscillatory power. Furthermore, the spatially distributed alpha oscillators of the network can be synchronized by global nonspecific weak excitatory signals. These synchronization events lead to transient increases in alpha-band power and render the network sensitive to the exact timing of target stimuli, making the alpha cycle function as a temporal mask in line with recent experimental observations. Our results are relevant to several studies that attribute a modulatory role to prestimulus alpha dynamics.

  • 135.
    Lundqvist, Mikael
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Herman, Pawel
    Lansner, Anders
    Theta and Gamma Power Increases and Alpha/Beta Power Decreases with Memory Load in an Attractor Network Model2010In: Journal of cognitive neuroscience, ISSN 0898-929X, E-ISSN 1530-8898, Vol. 23, no 10, p. 3008-3020Article in journal (Refereed)
    Abstract [en]

    Changes in oscillatory brain activity are strongly correlated with performance in cognitive tasks and modulations in specific frequency bands are associated with working memory tasks. Mesoscale network models allow the study of oscillations as an emergent feature of neuronal activity. Here we extend a previously developed attractor network model, shown to faithfully reproduce single-cell activity during retention and memory recall, with synaptic augmentation. This enables the network to function as a multi-item working memory by cyclic reactivation of up to six items. The reactivation happens at theta frequency, consistently with recent experimental findings, with increasing theta power for each additional item loaded in the network's memory. Furthermore, each memory reactivation is associated with gamma oscillations. Thus, single-cell spike trains as well as gamma oscillations in local groups are nested in the theta cycle. The network also exhibits an idling rhythm in the alpha/beta band associated with a noncoding global attractor. Put together, the resulting effect is increasing theta and gamma power and decreasing alpha/beta power with growing working memory load, rendering the network mechanisms involved a plausible explanation for this often reported behavior.

  • 136.
    Lundqvist, Mikael
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Rehn, Martin
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Djurfeldt, Mikael
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Lansner, Anders
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Attractor dynamics in a modular network model of neocortex2006In: Network, ISSN 0954-898X, E-ISSN 1361-6536, Network: Computation in Neural Systems, Vol. 17, no 3, p. 253-276Article in journal (Refereed)
    Abstract [en]

    Starting from the hypothesis that the mammalian neocortex to a first approximation functions as an associative memory of the attractor network type, we formulate a quantitative computational model of neocortical layers 2/3. The model employs biophysically detailed multi-compartmental model neurons with conductance based synapses and includes pyramidal cells and two types of inhibitory interneurons, i.e., regular spiking non-pyramidal cells and basket cells. The simulated network has a minicolumnar as well as a hypercolumnar modular structure and we propose that minicolumns rather than single cells are the basic computational units in neocortex. The minicolumns are represented in full scale and synaptic input to the different types of model neurons is carefully matched to reproduce experimentally measured values and to allow a quantitative reproduction of single cell recordings. Several key phenomena seen experimentally in vitro and in vivo appear as emergent features of this model. It exhibits a robust and fast attractor dynamics with pattern completion and pattern rivalry and it suggests an explanation for the so-called attentional blink phenomenon. During assembly dynamics, the model faithfully reproduces several features of local UP states, as they have been experimentally observed in vitro, as well as oscillatory behavior similar to that observed in the neocortex.

  • 137.
    Maniatis, Silas
    et al.
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA..
    Aijo, Tarmo
    Flatiron Inst, Ctr Computat Biol, New York, NY 10010 USA..
    Vickovic, Sanja
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Braine, Catherine
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA.;Columbia Univ, Mortimer B Zuckerman Mind Brain Behav Inst, New York, NY 10032 USA..
    Kang, Kristy
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA..
    Mollbrink, Annelie
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagegaltier, Delphine
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA..
    Andrusivova, Zaneta
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Saarenpaa, Sami
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Saiz-Castro, Gonzalo
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Cuevas, Miguel
    Columbia Univ, Mortimer B Zuckerman Mind Brain Behav Inst, New York, NY 10032 USA..
    Watters, Aaron
    Flatiron Inst, Ctr Computat Biol, New York, NY 10010 USA..
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Bonneau, Richard
    Flatiron Inst, Ctr Computat Biol, New York, NY 10010 USA.;NYU, Ctr Data Sci, New York, NY 10011 USA..
    Phatnani, Hemali
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA.;Columbia Univ, Mortimer B Zuckerman Mind Brain Behav Inst, New York, NY 10032 USA..
    Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis2019In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 364, no 6435, p. 89-+Article in journal (Refereed)
    Abstract [en]

    Paralysis occurring in amyotrophic lateral sclerosis (ALS) results from denervation of skeletal muscle as a consequence of motor neuron degeneration. Interactions between motor neurons and glia contribute to motor neuron loss, but the spatiotemporal ordering of molecular events that drive these processes in intact spinal tissue remains poorly understood. Here, we use spatial transcriptomics to obtain gene expression measurements of mouse spinal cords over the course of disease, as well as of postmortem tissue from ALS patients, to characterize the underlying molecular mechanisms in ALS. We identify pathway dynamics, distinguish regional differences between microglia and astrocyte populations at early time points, and discern perturbations in several transcriptional pathways shared between murine models of ALS and human postmortem spinal cords.

  • 138. Manninen, Tiina
    et al.
    Hituri, Katri
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Blackwell, Kim T.
    Linne, Marja-Leena
    Postsynaptic signal transduction models for long-term potentiation and depression2010In: FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, ISSN 1662-5188, Vol. 4, p. 152-Article, review/survey (Refereed)
    Abstract [en]

    More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation (LTP) and long-term depression (LTD). To investigate which species and interactions are critical for synaptic plasticity, many computational postsynaptic signal transduction models have been developed. The models range from simple models with a single reversible reaction to detailed models with several hundred kinetic reactions. In this study, more than a hundred models are reviewed, and their features are compared and contrasted so that similarities and differences are more readily apparent. The models are classified according to the type of synaptic plasticity that is modeled (LTP or LTD) and whether they include diffusion or electrophysiological phenomena. Other characteristics that discriminate the models include the phase of synaptic plasticity modeled (induction, expression, or maintenance) and the simulation method used (deterministic or stochastic). We find that models are becoming increasingly sophisticated, by including stochastic properties, integrating with electrophysiological properties of entire neurons, or incorporating diffusion of signaling molecules. Simpler models continue to be developed because they are computationally efficient and allow theoretical analysis. The more complex models permit investigation of mechanisms underlying specific properties and experimental verification of model predictions. Nonetheless, it is difficult to fully comprehend the evolution of these models because (1) several models are not described in detail in the publications, (2) only a few models are provided in existing model databases, and (3) comparison to previous models is lacking. We conclude that the value of these models for understanding molecular mechanisms of synaptic plasticity is increasing and will be enhanced further with more complete descriptions and sharing of the published models.

  • 139.
    Manouchehrinia, A.
    et al.
    Karolinska Inst, Stockholm, Sweden..
    Chachólski, Wojciech
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.). Royal Inst Technol, Stockholm, Sweden..
    Hillert, J.
    Karolinska Inst, Stockholm, Sweden..
    Ramanujam, Ryan
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.). Karolinska Inst, Stockholm, Sweden.;Royal Inst Technol, Stockholm, Sweden..
    Topological data analysis to identify subgroups of multiple sclerosis patients with faster disease progression2018In: Multiple Sclerosis, ISSN 1352-4585, E-ISSN 1477-0970, Vol. 24, p. 342-343Article in journal (Other academic)
  • 140. Meier, Ralph
    et al.
    Kumar, Arvind
    Institute of Biology III, Albert-Ludwigs-University, Germany .
    Schulze-Bonhage, Andreas
    Aertsen, Ad
    Comparison of dynamical states of random networks with human EEG2007In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 70, no 10-12, p. 1843-1847Article in journal (Refereed)
    Abstract [en]

    Existing models of EEG have mainly focused on relations to network dynamics characterized by firing rates [L. de Arcangelis, H.J. Herrmann, C. Perrone-Capano, Activity-dependent brain model explaining EEG spectra, arXiv:q-bio.NC/0411043 v1, 23 Nov 2004; D.T. Liley, D.M. Alexander, J.J. Wright, M.D. Aldous, Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons, Network 10(1) (1999) 79-92; O. David, J.K. Friston, A neural mass model for MEG/EEG: coupling and neuronal dynamics, NeuroImage 20 (2003) 1743-1755]. Generally, these models assume that there exists a linear mapping between network firing rates and EEG states. However, firing rate is only one of several descriptors for network activity states. Other relevant descriptors are synchrony and irregularity of firing patterns [N. Brunel, Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons, J. Comput. Neurosci. 8(3) (2000) 183-208]. To develop a better understanding of the EEG we need to relate these state descriptors to EEG states. Here, we try to go beyond the firing rate based approaches described in [D.T. Liley, D.M. Alexander, J.J. Wright, M.D. Aldous, Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons, Network 10(1) (1999) 79-92; O. David, J.K. Friston, A neural mass model for MEG/EEG: coupling and neuronal dynamics, NeuroImage 20 (2003) 1743-1755] and relate synchronicity and irregularity in the network to EEG states. We show that the transformation between network activity and EEG can be approximately mediated by linear kernel with the shape of an α- or γ-function, allowing us a comparison between EEG states and network activity space. We find that the simulated EEG generated from asynchronous irregular type network activity is closely related to the human EEG recorded in the awake state, evaluated using power spectral density characteristics.

  • 141.
    Mengiste, Simachew
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. University of Freiburg, German.
    Aertsen, Ad
    Kumar, Arvind
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. University of Freiburg, German.
    Effect of edge pruning on structural controllability and observability of complex networks2015In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 5, p. 18145-, article id 18145Article in journal (Refereed)
    Abstract [en]

    Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex systems show dynamic changes in their network connectivity, it is important to understand how perturbations in the connectivity affect the controllability of the system. To this end, we studied the control structure of different types of artificial, social and biological neuronal networks (BNN) as their connections were progressively pruned using four different pruning strategies. We show that the BNNs are more similar to scale-free networks than to small-world networks, when comparing the robustness of their control structure to structural perturbations. We introduce a new graph descriptor, 'the cardinality curve', to quantify the robustness of the control structure of a network to progressive edge pruning. Knowing the susceptibility of control structures to different pruning methods could help design strategies to destroy the control structures of dangerous networks such as epidemic networks. On the other hand, it could help make useful networks more resistant to edge attacks.

  • 142.
    Mohagheghi Nejad, Mohammadreza
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.
    Interaction of sensory and motor signals in the basal ganglia in health and disease2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The basal ganglia, a set of deep forebrain nuclei, are among the brain regions involved in movement initiation and suppression. Although many studies have investigated the neural coding underlying these two aspects of movement, there are still questions that need to be addressed. In this thesis, I used computational models of motor thalamus and the basal ganglia at three different levels to improve the understanding of the neural coding our brain utilises to initiate and suppress movement. I used a Hodgkin-Huxley model of a thalamocortical neuron to investigate the transmission of a motor signal (i.e. movement initiation) from the basal ganglia output to the motor thalamus through post-inhibitory rebound spikes. I investigated the impact of pathological activity of the basal ganglia output (e.g. in Parkinson’s disease) and the impact of sensory responses in the basal ganglia output and cortical excitation to the thalamus on these signals. I showed that correlations in the basal ganglia output (representing pathological activity) disrupt the transmission of motor signals via rebound spikes by decreasing the signal-to-noise ratio and increasing trial-to-trial variability. In addition, I found that both the sensory responses and cortical inputs could either promote or suppress the generation of rebound spikes depending on their timing relative to the motor signal. Finally, in the model rebound spiking occurred despite the presence of moderate levels of excitation, indicating that rebound spiking might be feasible in a parameter regime relevant also in vivo.

    In addition to movement initiation, I investigated the role of basal ganglia in movement suppression using a spiking network model of the basal ganglia. I simulated a stop-signal task in the model by stimulating it with realistic patterns evoking movement-related activity in the striatum and substantia nigra pars reticulata (SNr) and evoking stop-related activity in subthalamic nucleus (STN) and arkypallidal neurons in globus pallidus externa (GPe Arky). I found that a Stop response in STN delayed initiation of movement that was detected by observing SNr activity. In addition, I showed that a Stop response in GPe Arky suppressed movement-related activity in the striatum and via direct pathway in SNr. However, the pattern of these suppressed movement-related activities did not match with previous experimental observations in successful Stop trials. I explained this mismatch using a biophysically detailed multicompartmental model of projection neurons in the striatum. I found that the long-lasting depolarisations at the level of the soma, resulting from dendritic plateau potentials evoked by clustered excitatory inputs at distal dendrites, could evoke movement-related activity in these striatal neurons. The inhibition from GPe Arky targeting the excited dendrites could fully suppress the movement-related activity matching with experimental recordings in successful Stop trials.

    In conclusion, the nigrothalamic model in this thesis provides novel insights into the transmission of motor signals from the basal ganglia to motor thalamus by suggesting new functional roles for active decorrelation and sensory responses in the basal ganglia, as well as cortical excitation of motor thalamus. Moreover, the simulation results of the Stop-signal task support the idea that the basal ganglia suppress movement in two steps: STN delays movement and then GPe Arky cancels movement.

  • 143. Morrison, S. A.
    et al.
    Mirnik, D.
    Korsic, S.
    Eiken, Ola
    KTH, School of Technology and Health (STH), Basic Science and Biomedicine, Environmental Physiology.
    Mekjavic, I. B.
    Groselj, L. Dolenc
    Planetary habitat simulation: interactions between bedrest, hypoxia and confinement on sleep and breathing2014In: Journal of Sleep Research, ISSN 0962-1105, E-ISSN 1365-2869, Vol. 23, p. 196-196Article in journal (Other academic)
  • 144. Mulder, Jan
    et al.
    Spence, Lauren
    Tortoriello, Giuseppe
    DiNieri, Jennifer A.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Shui, Bo
    Kotlikoff, Michael I.
    Yanagawa, Yuchio
    Aujard, Fabienne
    Hokfelt, Tomas
    Hurd, Yasmin L.
    Harkany, Tibor
    Secretagogin is a Ca2+-binding protein identifying prospective extended amygdala neurons in the developing mammalian telencephalon2010In: European Journal of Neuroscience, ISSN 0953-816X, E-ISSN 1460-9568, Vol. 31, no 12, p. 2166-2177Article in journal (Refereed)
    Abstract [en]

    The Ca2+-binding proteins (CBPs) calbindin D28k, calretinin and parvalbumin are phenotypic markers of functionally diverse subclasses of neurons in the adult brain. The developmental dynamics of CBP expression are precisely timed: calbindin and calretinin are present in prospective cortical interneurons from mid-gestation, while parvalbumin only becomes expressed during the early postnatal period in rodents. Secretagogin (scgn) is a CBP cloned from pancreatic beta and neuroendocrine cells. We hypothesized that scgn may be expressed by particular neuronal contingents during prenatal development of the mammalian telencephalon. We find that scgn is expressed in neurons transiting in the subpallial differentiation zone by embryonic day (E)11 in mouse. From E12, scgn+ cells commute towards the extended amygdala and colonize the bed nucleus of stria terminalis, the interstitial nucleus of the posterior limb of the anterior commissure, the dorsal substantia innominata (SI) and the central and medial amygdaloid nuclei. Scgn+ neurons can acquire a cholinergic phenotype in the SI or differentiate into GABA cells in the central amygdala. We also uncover phylogenetic differences in scgn expression as this CBP defines not only neurons destined to the extended amygdala but also cholinergic projection cells and cortical pyramidal cells in the fetal nonhuman primate and human brains, respectively. Overall, our findings emphasize the developmentally shared origins of neurons populating the extended amygdala, and suggest that secretagogin can be relevant to the generation of functional modalities in specific neuronal circuitries.

  • 145. Murans, Girts
    et al.
    Gutierrez-Farewik, Elena M.
    KTH, School of Engineering Sciences (SCI), Mechanics, Structural Mechanics.
    Saraste, Helena
    Kinematic and kinetic analysis of static sitting of patients with neuropathic spine deformity2011In: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 34, no 4, p. 533-538Article in journal (Refereed)
    Abstract [en]

    Wheelchair dependent children with neuropathic and neuromuscular diseases have up to 90% risk for progressive spine deformities. An unbalanced sitting can induce progression of spinal and pelvic deformities. Many current clinical assessment methods of sitting of such patients are semi-quantitative, or questionnaire-based. A 3D movement analysis offers quantitative and objective biomechanical analysis of sitting. The aim was to validate a method to describe quiet sitting and differences between patients and controls as well as to apply the methodology for pre- and post-operative comparison. The analysis was performed on 14 patients and 10 controls. Four patients were retested after spine surgery. Seat load asymmetry was up to 30% in the patient group comparing to maximum 7% in the control group. The asymmetric position of Ground Reaction Force vector between left and right sides was significant. Plumb line of cervical 7th vertebra over sacral 1st was different only in rotation. The location of Common Center of Pressure relative to inter-trochanteric midpoint was more anterior in controls than in patients. Pelvic inclination in patients was smaller, the obliquity and rotation was similar. There were no significant differences between patients and controls of the thorax position. Results with more changes in the seat-loading domain in comparison with posture indicate good postural control compensation of spinal deformity induced disequilibrium despite neuromuscular disease in the background. The comparison of the pelvic obliquity data from kinematics and X-ray showed good correlation. The four patients tested postoperatively improved after surgery.

  • 146. Musunuri, Sravani
    et al.
    Khoonsari, Payam Emami
    Mikus, Maria
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Wetterhall, Magnus
    Häggmark-Mänberg, Anna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lannfelt, Lars
    Erlandsson, Anna
    Bergquist, Jonas
    Ingelsson, Martin
    Shevchenko, Ganna
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kultima, Kim
    Increased Levels of Extracellular Microvesicle Markers and Decreased Levels of Endocytic/Exocytic Proteins in the Alzheimer's Disease Brain2016In: Journal of Alzheimer's Disease, ISSN 1387-2877, E-ISSN 1875-8908, Vol. 54, no 4, p. 1671-1686Article in journal (Refereed)
    Abstract [en]

    Background: Alzheimer's disease (AD) is a chronic neurodegenerative disorder accounting for more than 50% of all dementia cases. AD neuropathology is characterized by the formation of extracellular plaques and intracellular neurofibrillary tangles consisting of aggregated amyloid-beta and tau, respectively. The disease mechanism has only been partially elucidated and is believed to also involve many other proteins. Objective: This study intended to perform a proteomic profiling of post mortem AD brains and compare it with control brains as well as brains from other neurological diseases to gain insight into the disease pathology. Methods: Here we used label-free shotgun mass spectrometry to analyze temporal neocortex samples from AD, other neurological disorders, and non-demented controls, in order to identify additional proteins that are altered in AD. The mass spectrometry results were verified by antibody suspension bead arrays. Results: We found 50 proteins with altered levels between AD and control brains. The majority of these proteins were found at lower levels in AD. Pathway analyses revealed that several of the decreased proteins play a role in exocytic and endocytic pathways, whereas several of the increased proteins are related to extracellular vesicles. Using antibody-based analysis, we verified the mass spectrometry results for five representative proteins from this group of proteins (CD9, HSP72, PI42A, TALDO, and VAMP2) and GFAP, a marker for neuroinflammation. Conclusions: Several proteins involved in exo-endocytic pathways and extracellular vesicle functions display altered levels in the AD brain. We hypothesize that such changes may result in disturbed cellular clearance and a perturbed cell-to-cell communication that may contribute to neuronal dysfunction and cell death in AD.

  • 147.
    Nair, Anu G.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Modeling Biochemical Network Involved in Striatal Dopamine Signaling2018Doctoral thesis, monograph (Other academic)
    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.

  • 148.
    Nair, Anu G.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Modeling receptor induced signaling in MSNs: Interaction between molecules involved in striatal synaptic plasticity2014Licentiate thesis, comprehensive summary (Other academic)
    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.

  • 149.
    Nair, Anu G.
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Bhalla, Upinder S
    Kotaleski, Jeanette Hellgren
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Role of DARPP-32 and ARPP-21 in the Emergence of Temporal Constraints on Striatal Calcium and Dopamine Integration2016In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, no 9, article id e1005080Article in journal (Refereed)
    Abstract [en]

    In reward learning, the integration of NMDA-dependent calcium and dopamine by striatal projection neurons leads to potentiation of corticostriatal synapses through CaMKII/PP1 signaling. In order to elicit the CaMKII/PP1-dependent response, the calcium and dopamine inputs should arrive in temporal proximity and must follow a specific (dopamine after calcium) order. However, little is known about the cellular mechanism which enforces these temporal constraints on the signal integration. In this computational study, we propose that these temporal requirements emerge as a result of the coordinated signaling via two striatal phosphoproteins, DARPP-32 and ARPP-21. Specifically, DARPP-32-mediated signaling could implement an input-interval dependent gating function, via transient PP1 inhibition, thus enforcing the requirement for temporal proximity. Furthermore, ARPP-21 signaling could impose the additional input-order requirement of calcium and dopamine, due to its Ca2+/calmodulin sequestering property when dopamine arrives first. This highlights the possible role of phosphoproteins in the temporal aspects of striatal signal transduction.

  • 150.
    Nair, Anu G.
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Castro, Liliana R. V.
    Sorbonne Univ, CNRS, Biol Adaptat & Ageing, F-75005 Paris, France.;Biopsy Labex, Paris, France..
    El Khoury, Marianne
    Biopsy Labex, Paris, France.;Sorbonne Univ, CNRS, Neurosci Paris Seine, F-75005 Paris, France..
    Gorgievski, Victor
    Biopsy Labex, Paris, France.;Sorbonne Univ, CNRS, Neurosci Paris Seine, F-75005 Paris, France..
    Giros, Bruno
    Biopsy Labex, Paris, France.;Sorbonne Univ, CNRS, Neurosci Paris Seine, F-75005 Paris, France.;McGill Univ, Fac Med, Douglas Mental Hlth Univ Inst, Dept Psychiat, Montreal, PQ, Canada..
    Tzavara, Eleni T.
    Biopsy Labex, Paris, France.;Sorbonne Univ, CNRS, Neurosci Paris Seine, F-75005 Paris, France..
    Hellgren Kotaleski, Jeanette
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Vincent, Pierre
    Sorbonne Univ, CNRS, Biol Adaptat & Ageing, F-75005 Paris, France.;Biopsy Labex, Paris, France..
    The high efficacy of muscarinic M4 receptor in D1 medium spiny neurons reverses striatal hyperdopaminergia2019In: Neuropharmacology, ISSN 0028-3908, E-ISSN 1873-7064, Vol. 146, p. 74-83Article in journal (Refereed)
    Abstract [en]

    The opposing action of dopamine and acetylcholine has long been known to play an important role in basal ganglia physiology. However, the quantitative analysis of dopamine and acetylcholine signal interaction has been difficult to perform in the native context because the striatum comprises mainly two subtypes of medium-sized spiny neurons (MSNs) on which these neuromodulators exert different actions. We used biosensor imaging in live brain slices of dorsomedial striatum to monitor changes in intracellular cAMP at the level of individual MSNs. We observed that the muscarinic agonist oxotremorine decreases cAMP selectively in the MSN sub population that also expresses D-1 dopamine receptors, an action mediated by the M-4 muscarinic receptor. This receptor has a high efficacy on cAMP signaling and can shut down the positive cAMP response induced by dopamine, at acetylcholine concentrations which are consistent with physiological levels. This supports our prediction based on theoretical modeling that acetylcholine could exert a tonic inhibition on striatal cAMP signaling, thus supporting the possibility that a pause in acetylcholine release is required for phasic dopamine to transduce a cAMP signal in D1 MSNs. In vivo experiments with acetylcholinesterase inhibitors donepezil and tacrine, as well as with the positive allosteric modulators of M-4 receptor VU0152100 and VU0010010 show that this effect is sufficient to reverse the increased locomotor activity of DAT-knockout mice. This suggests that M-4 receptors could be a novel therapeutic target to treat hyperactivity disorders.

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