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Hunger, L., Kumar, A. & Schmidt, R. (2020). Abundance Compensates Kinetics: Similar Effect of Dopamine Signals on D1 and D2 Receptor Populations. Journal of Neuroscience, 40(14), 2868-2881
Open this publication in new window or tab >>Abundance Compensates Kinetics: Similar Effect of Dopamine Signals on D1 and D2 Receptor Populations
2020 (English)In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 40, no 14, p. 2868-2881Article in journal (Refereed) Published
Abstract [en]

The neuromodulator dopamine plays a key role in motivation, reward-related learning, and normal motor function. The different affinity of striatal D1 and D2 dopamine receptor types has been argued to constrain the D1 and D2 signaling pathways to phasic and tonic dopamine signals, respectively. However, this view assumes that dopamine receptor kinetics are instantaneous so that the time courses of changes in dopamine concentration and changes in receptor occupation are basically identical. Here we developed a neurochemical model of dopamine receptor binding taking into account the different kinetics and abundance of D1 and D2 receptors in the striatum. Testing a large range of behaviorally-relevant dopamine signals, we found that the D1 and D2 dopamine receptor populations responded very similarly to tonic and phasic dopamine signals. Furthermore, because of slow unbinding rates, both receptor populations integrated dopamine signals over a timescale of minutes. Our model provides a description of how physiological dopamine signals translate into changes in dopamine receptor occupation in the striatum, and explains why dopamine ramps are an effective signal to occupy dopamine receptors. Overall, our model points to the importance of taking into account receptor kinetics for functional considerations of dopamine signaling.

Place, publisher, year, edition, pages
Society for Neuroscience, 2020
Keywords
basal ganglia, computational model, dopamine, motivation, receptor kinetics, reward
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-272791 (URN)10.1523/JNEUROSCI.1951-19.2019 (DOI)000522791300008 ()32071139 (PubMedID)2-s2.0-85082779598 (Scopus ID)
Note

QC 20200504

Available from: 2020-05-04 Created: 2020-05-04 Last updated: 2020-05-04Bibliographically approved
Özcan, O. O., Wang, X., Binda, F., Dorgans, K., De Zeeuw, C. I., Gao, Z., . . . Isope, P. (2020). Differential Coding Strategies in Glutamatergic and GABAergic Neurons in the Medial Cerebellar Nucleus. Journal of Neuroscience, 40(1), 159-170
Open this publication in new window or tab >>Differential Coding Strategies in Glutamatergic and GABAergic Neurons in the Medial Cerebellar Nucleus
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2020 (English)In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 40, no 1, p. 159-170Article in journal (Refereed) Published
Abstract [en]

The cerebellum drives motor coordination and sequencing of actions at the millisecond timescale through adaptive control of cerebellar nuclear output. Cerebellar nuclei integrate high-frequency information from both the cerebellar cortex and the two main excitatory inputs of the cerebellum: the mossy fibers and the climbing fiber collaterals. However, how nuclear cells process rate and timing of inputs carried by these inputs is still debated. Here, we investigate the influence of the cerebellar cortical output, the Purkinje cells, on identified cerebellar nuclei neurons in vivo in male mice. Using transgenic mice expressing Channelrhodopsin2 specifically in Purkinje cells and tetrode recordings in the medial nucleus, we identified two main groups of neurons based on the waveform of their action potentials. These two groups of neurons coincide with glutamatergic and GABAergic neurons identified by optotagging after Chrimson expression in VGLUT2-cre and GAD-cre mice, respectively. The glutamatergic-like neurons fire at high rate and respond to both rate and timing of Purkinje cell population inputs, whereas GABAergic-like neurons only respond to the mean population firing rate of Purkinje cells at high frequencies. Moreover, synchronous activation of Purkinje cells can entrain the glutamatergic-like, but not the GABAergic-like, cells over a wide range of frequencies. Our results suggest that the downstream effect of synchronous and rhythmic Purkinje cell discharges depends on the type of cerebellar nuclei neurons targeted.

Place, publisher, year, edition, pages
NLM (Medline), 2020
Keywords
cerebellar nuclei, cerebellum, electrophysiology in vivo, Purkinje cells, temporal coding
National Category
Neurology
Identifiers
urn:nbn:se:kth:diva-266740 (URN)10.1523/JNEUROSCI.0806-19.2019 (DOI)000505167600015 ()31694963 (PubMedID)2-s2.0-85077476977 (Scopus ID)
Note

QC 20200117

Available from: 2020-01-17 Created: 2020-01-17 Last updated: 2020-01-17Bibliographically approved
Bahuguna, J., Sahasranamam, A. & Kumar, A. (2020). Uncoupling the roles of firing rates and spike bursts in shaping the STN-GPe beta band oscillations. PloS Computational Biology, 16(3)
Open this publication in new window or tab >>Uncoupling the roles of firing rates and spike bursts in shaping the STN-GPe beta band oscillations
2020 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 16, no 3Article in journal (Refereed) Published
Abstract [en]

The excess of 15-30 Hz (beta-band) oscillations in the basal ganglia is one of the key signatures of Parkinson's disease (PD). The STN-GPe network is integral to generation and modulation of beta band oscillations in basal ganglia. However, the role of changes in the firing rates and spike bursting of STN and GPe neurons in shaping these oscillations has remained unclear. In order to uncouple their effects, we studied the dynamics of STN-GPe network using numerical simulations. In particular, we used a neuron model, in which firing rates and spike bursting can be independently controlled. Using this model, we found that while STN firing rate is predictive of oscillations but GPe firing rate is not. The effect of spike bursting in STN and GPe neurons was state-dependent. That is, only when the network was operating in a state close to the border of oscillatory and non-oscillatory regimes, spike bursting had a qualitative effect on the beta band oscillations. In these network states, an increase in GPe bursting enhanced the oscillations whereas an equivalent proportion of spike bursting in STN suppressed the oscillations. These results provide new insights into the mechanisms underlying the transient beta bursts and how duration and power of beta band oscillations may be controlled by an interplay of GPe and STN firing rates and spike bursts. Author summary The STN-GPe network undergoes a change in firing rates as well as increased bursting during excessive beta band oscillations during Parkinson's disease. In this work we uncouple their effects by using a novel neuron model and show that presence of oscillations is contingent on the increase in STN firing rates, however the effect of spike bursting on oscillations depends on the network state. In a network state on the border of oscillatory and non-oscillatory regime, GPe spike bursting strengthens oscillations. The effect of spike bursting in the STN depends on the proportion of GPe neurons bursting. These results suggest a mechanism underlying a transient beta band oscillation bursts often seen in experimental data.

Place, publisher, year, edition, pages
Public Library of Science, 2020
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:kth:diva-272773 (URN)10.1371/journal.pcbi.1007748 (DOI)000523480200028 ()32226014 (PubMedID)2-s2.0-85082760589 (Scopus ID)
Note

QC 20200429

Available from: 2020-04-29 Created: 2020-04-29 Last updated: 2020-04-29Bibliographically approved
Heining, K., Kilias, A., Janz, P., Haeussler, U., Kumar, A., Haas, C. A. & Egert, U. (2019). Bursts with High and Low Load of Epileptiform Spikes Show Contex-Dependent Correlations in Epileptic Mice. ENEURO, 6(5), Article ID UNSP ENEURO.0299-18.2019.
Open this publication in new window or tab >>Bursts with High and Low Load of Epileptiform Spikes Show Contex-Dependent Correlations in Epileptic Mice
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2019 (English)In: ENEURO, ISSN 2373-2822, Vol. 6, no 5, article id UNSP ENEURO.0299-18.2019Article in journal (Refereed) Published
Abstract [en]

Hypersynchronous network activity is the defining hallmark of epilepsy and manifests in a wide spectrum of phenomena, of which electrographic activity during seizures is only one extreme. The aim of this study was to differentiate between different types of epileptiform activity (EA) patterns and investigate their temporal succession and interactions. We analyzed local field potentials (LFPs) from freely behaving male mice that had received an intrahippocampal kainate injection to model mesial temporal lobe epilepsy (MTLE). Epileptiform spikes occurred in distinct bursts. Using machine learning, we derived a scale reflecting the spike load of bursts and three main burst categories that we labeled high-load, medium-load, and low-load bursts. We found that bursts of these categories were non-randomly distributed in time. High-load bursts formed clusters and were typically surrounded by transition phases with increased rates of medium-load and low-load bursts. In apparent contradiction to this, increased rates of low-load bursts were also associated with longer background phases, i.e., periods lacking high-load bursting. Furthermore, the rate of low-load bursts was more strongly correlated with the duration of background phases than the overall rate of epileptiform spikes. Our findings are consistent with the hypothesis that low-level EA could promote network stability but could also participate in transitions towards major epileptiform events, depending on the current state of the network.

Place, publisher, year, edition, pages
SOC NEUROSCIENCE, 2019
Keywords
electrographic seizures, epileptic spikes, epileptiform activity, hippocampus, interictal activity, mesial temporal lobe epilepsy
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-261331 (URN)10.1523/ENEURO.0299-18.2019 (DOI)000486604800014 ()31420348 (PubMedID)2-s2.0-85071788877 (Scopus ID)
Note

QC 20191007

Available from: 2019-10-07 Created: 2019-10-07 Last updated: 2019-10-07Bibliographically approved
Filipovic, M., Ketzef, M., Reig, R., Aertsen, A., Silberberg, G. & Kumar, A. (2019). Direct pathway neurons in mouse dorsolateral striatum in vivo receive stronger synaptic input than indirect pathway neurons. Journal of Neurophysiology, 122(6), 2294-2303
Open this publication in new window or tab >>Direct pathway neurons in mouse dorsolateral striatum in vivo receive stronger synaptic input than indirect pathway neurons
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2019 (English)In: Journal of Neurophysiology, ISSN 0022-3077, E-ISSN 1522-1598, Vol. 122, no 6, p. 2294-2303Article in journal (Refereed) Published
Abstract [en]

Striatal projection neurons, the medium spiny neurons (MSNs), play a crucial role in various motor and cognitive functions. MSNs express either D1- or D2-type dopamine receptors and initiate the direct-pathway (dMSNs) or indirect pathways (iMSNs) of the basal ganglia, respectively. dMSNs have been shown to receive more inhibition than iMSNs from intrastriatal sources. Based on these findings, computational modeling of the suiatal network has predicted that under healthy conditions dMSNs should receive more total input than iMSNs. To test this prediction, we analyzed in vivo whole cell recordings from dMSNs and iMSNs in healthy and dopamine-depleted (60HDA) anaesthetized mice. By comparing their membrane potential fluctuations, we found that dMSNs exhibited considerably larger membrane potential fluctuations over a wide frequency range. Furthermore, by comparing the spike-triggered average membrane potentials. we found that dMSNs depolarized toward the spike threshold significantly faster than iMSNs did. Together, these findings (in particular the STA analysis) corroborate the theoretical prediction that direct-pathway MSNs receive stronger total input than indirect-pathway neurons. Finally, we found that dopamine-depleted mice exhibited no difference between the membrane potential fluctuations of dMSNs and iMSNs. These data provide new insights into the question of how the lack of dopamine may lead to behavioral deficits associated with Parkinson's disease. NEW & NOTEWORTHY The direct and indirect pathways of the basal ganglia originate from the D1- and D2-type dopamine receptor expressing medium spiny neurons (dMSNs and iMSNs). Theoretical results have predicted that dMSNs should receive stronger synaptic input than iMSNs. Using in vivo intracellular membrane potential data, we provide evidence that dMSNs indeed receive stronger input than iMSNs, as has been predicted by the computational model.

Place, publisher, year, edition, pages
AMER PHYSIOLOGICAL SOC, 2019
Keywords
basal ganglia, direct and indirect pathways, dopamine deletion, in vivo membrane potential, striatum
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-265982 (URN)10.1152/jn.00481.2019 (DOI)000500384700008 ()31618095 (PubMedID)2-s2.0-85075813956 (Scopus ID)
Note

QC 20191220

Available from: 2019-12-20 Created: 2019-12-20 Last updated: 2020-01-13Bibliographically approved
Spreizer, S., Aertsen, A. & Kumar, A. (2019). From space to time: Spatial inhomogeneities lead to the emergence of spatiotemporal sequences in spiking neuronal networks. PloS Computational Biology, 15(10), Article ID e1007432.
Open this publication in new window or tab >>From space to time: Spatial inhomogeneities lead to the emergence of spatiotemporal sequences in spiking neuronal networks
2019 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 15, no 10, article id e1007432Article in journal (Refereed) Published
Abstract [en]

Spatio-temporal sequences of neuronal activity are observed in many brain regions in a variety of tasks and are thought to form the basis of meaningful behavior. However, mechanisms by which a neuronal network can generate spatio-temporal activity sequences have remained obscure. Existing models are biologically untenable because they either require manual embedding of a feedforward network within a random network or supervised learning to train the connectivity of a network to generate sequences. Here, we propose a biologically plausible, generative rule to create spatio-temporal activity sequences in a network model of spiking neurons with distance-dependent connectivity. We show that the emergence of spatio-temporal activity sequences requires: (1) individual neurons preferentially project a small fraction of their axons in a specific direction, and (2) the preferential projection direction of neighboring neurons is similar. Thus, an anisotropic but correlated connectivity of neuron groups suffices to generate spatio-temporal activity sequences in an otherwise random neuronal network model. Author summary Here we propose a biologically plausible mechanism to generate temporal sequences of neuronal activity in network of spiking neurons. We show that neuronal networks exhibit temporal sequences of activity when (1) neurons do not connect in all directions with equal probability (asymmetry), and (2) neighboring neurons have similar connection preference (spatial correlations). This mechanism precludes supervised learning or manual wiring to generate network connectivity to produce temporal sequences. Connection asymmetry is consistent with the experimental findings that axonal and dendritic arbors are spatially asymmetric. We predict that networks exhibiting temporal sequences of neuronal activity should have spatially asymmetric but correlated connectivity. Finally, we argue how neuromodulators can play a role in rapid switching among different temporal sequences.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2019
National Category
Basic Medicine
Identifiers
urn:nbn:se:kth:diva-266318 (URN)10.1371/journal.pcbi.1007432 (DOI)000500776600055 ()31652259 (PubMedID)2-s2.0-85074674864 (Scopus ID)
Note

QC 20200107

Available from: 2020-01-07 Created: 2020-01-07 Last updated: 2020-01-13Bibliographically approved
Hahn, G., Ponce-Alvarez, A., Deco, G., Aertsen, A. & Kumar, A. (2019). Portraits of communication in neuronal networks. Nature Reviews Neuroscience, 20(2), 117-127
Open this publication in new window or tab >>Portraits of communication in neuronal networks
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2019 (English)In: Nature Reviews Neuroscience, ISSN 1471-003X, E-ISSN 1471-0048, Vol. 20, no 2, p. 117-127Article, review/survey (Refereed) Published
Abstract [en]

The brain is organized as a network of highly specialized networks of spiking neurons. To exploit such a modular architecture for computation, the brain has to be able to regulate the flow of spiking activity between these specialized networks. In this Opinion article, we review various prominent mechanisms that may underlie communication between neuronal networks. We show that communication between neuronal networks can be understood as trajectories in a two-dimensional state space, spanned by the properties of the input. Thus, we propose a common framework to understand neuronal communication mediated by seemingly different mechanisms. We also suggest that the nesting of slow (for example, alpha-band and theta-band) oscillations and fast (gamma-band) oscillations can serve as an important control mechanism that allows or prevents spiking signals to be routed between specific networks. We argue that slow oscillations can modulate the time required to establish network resonance or entrainment and, thereby, regulate communication between neuronal networks.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-243940 (URN)10.1038/s41583-018-0094-0 (DOI)000456326800008 ()30552403 (PubMedID)2-s2.0-85058631397 (Scopus ID)
Note

QC 20190306

Available from: 2019-03-06 Created: 2019-03-06 Last updated: 2019-06-11Bibliographically approved
Kisner, A., Slocomb, J. E., Sarsfield, S., Zuccoli, M. L., Siemian, J., Gupta, J. F., . . . Aponte, Y. (2018). Electrophysiological properties and projections of lateral hypothalamic parvalbumin positive neurons. PLoS ONE, 13(6), Article ID e0198991.
Open this publication in new window or tab >>Electrophysiological properties and projections of lateral hypothalamic parvalbumin positive neurons
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2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 6, article id e0198991Article in journal (Refereed) Published
Abstract [en]

Cracking the cytoarchitectural organization, activity patterns, and neurotransmitter nature of genetically-distinct cell types in the lateral hypothalamus (LH) is fundamental to develop a mechanistic understanding of how activity dynamics within this brain region are generated and operate together through synaptic connections to regulate circuit function. However, the precise mechanisms through which LH circuits orchestrate such dynamics have remained elusive due to the heterogeneity of the intermingled and functionally distinct cell types in this brain region. Here we reveal that a cell type in the mouse LH identified by the expression of the calcium-binding protein parvalbumin (PVALB; LHPV) is fast-spiking, releases the excitatory neurotransmitter glutamate, and sends long range projections throughout the brain. Thus, our findings challenge long-standing concepts that define neurons with a fast-spiking phenotype as exclusively GABAergic. Furthermore, we provide for the first time a detailed characterization of the electrophysiological properties of these neurons. Our work identifies LHPV neurons as a novel functional component within the LH glutamatergic circuitry.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2018
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-231705 (URN)10.1371/journal.pone.0198991 (DOI)000435030900039 ()29894514 (PubMedID)2-s2.0-85048476842 (Scopus ID)
Note

QC 20180822

Available from: 2018-08-22 Created: 2018-08-22 Last updated: 2018-08-22Bibliographically approved
Grangeray-Vilmint, A., Valera, A. M., Kumar, A. & Isope, P. (2018). Short-Term Plasticity Combines with Excitation-Inhibition Balance to Expand Cerebellar Purkinje Cell Dynamic Range. Journal of Neuroscience, 38(22), 5153-5167
Open this publication in new window or tab >>Short-Term Plasticity Combines with Excitation-Inhibition Balance to Expand Cerebellar Purkinje Cell Dynamic Range
2018 (English)In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 38, no 22, p. 5153-5167Article in journal (Refereed) Published
Abstract [en]

The balance between excitation (E) and inhibition (I) in neuronal networks controls the firing rate of principal cells through simple network organization, such as feedforward inhibitory circuits. Here, we demonstrate in male mice, that at the granule cell (GrC)molecular layer interneuron (MLI)-Purkinje cell (PC) pathway of the cerebellar cortex, E/I balance is dynamically controlled by short-term dynamics during bursts of stimuli, shaping cerebellar output. Using a combination of electrophysiological recordings, optogenetic stimulation, and modeling, we describe the wide range of bidirectional changes in PC discharge triggered by GrC bursts, from robust excitation to complete inhibition. At high frequency (200 Hz), increasing the number of pulses in a burst (from 3 to 7) can switch a net inhibition of PC to a net excitation. Measurements of EPSCs and IPSCs during bursts and modeling showed that this feature can be explained by the interplay between short-term dynamics of the GrC-MLI-PC pathway and E/I balance impinging on PC. Our findings demonstrate that PC firing rate is highly sensitive to the duration of GrC bursts, which may define a temporal-to-rate code transformation in the cerebellar cortex.

Place, publisher, year, edition, pages
SOC NEUROSCIENCE, 2018
Keywords
excitation-inhibition balance, burst coding, feedforward inhibition, Purkinje cell, short-term dynamics
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-231736 (URN)10.1523/JNEUROSCI.3270-17.2018 (DOI)000435410700011 ()29720550 (PubMedID)2-s2.0-85050790868 (Scopus ID)
Note

QC 20180703

Available from: 2018-07-03 Created: 2018-07-03 Last updated: 2020-03-09Bibliographically approved
Bahuguna, J., Tetzlaff, T., Kumar, A., Hellgren Kotaleski, J. & Morrison, A. (2017). Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions. Frontiers in Computational Neuroscience, 11, Article ID 79.
Open this publication in new window or tab >>Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions
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2017 (English)In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 11, article id 79Article in journal (Refereed) Published
Abstract [en]

The classical model of basal ganglia has been refined in recent years with discoveries of subpopulations within a nucleus and previously unknown projections. One such discovery is the presence of subpopulations of arkypallidal and prototypical neurons in external globus pallidus, which was previously considered to be a primarily homogeneous nucleus. Developing a computational model of these multiple interconnected nuclei is challenging, because the strengths of the connections are largely unknown. We therefore use a genetic algorithm to search for the unknown connectivity parameters in a firing rate model. We apply a binary cost function derived from empirical firing rate and phase relationship data for the physiological and Parkinsonian conditions. Our approach generates ensembles of over 1,000 configurations, or homologies, for each condition, with broad distributions for many of the parameter values and overlap between the two conditions. However, the resulting effective weights of connections from or to prototypical and arkypallidal neurons are consistent with the experimental data. We investigate the significance of the weight variability by manipulating the parameters individually and cumulatively, and conclude that the correlation observed between the parameters is necessary for generating the dynamics of the two conditions. We then investigate the response of the networks to a transient cortical stimulus, and demonstrate that networks classified as physiological effectively suppress activity in the internal globus pallidus, and are not susceptible to oscillations, whereas parkinsonian networks show the opposite tendency. Thus, we conclude that the rates and phase relationships observed in the globus pallidus are predictive of experimentally observed higher level dynamical features of the physiological and parkinsonian basal ganglia, and that the multiplicity of solutions generated by our method may well be indicative of a natural diversity in basal ganglia networks. We propose that our approach of generating and analyzing an ensemble of multiple solutions to an underdetermined network model provides greater confidence in its predictions than those derived from a unique solution, and that projecting such homologous networks on a lower dimensional space of sensibly chosen dynamical features gives a better chance than a purely structural analysis at understanding complex pathologies such as Parkinson's disease.

Place, publisher, year, edition, pages
FRONTIERS MEDIA SA, 2017
Keywords
basal ganglia, network models, degeneracy, oscillations, Parkinson's disease
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-214328 (URN)10.3389/fncom.2017.00079 (DOI)000408054600001 ()2-s2.0-85031997295 (Scopus ID)
Note

QC 20170914

Available from: 2017-09-14 Created: 2017-09-14 Last updated: 2018-01-13Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-8044-9195

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