Cortical Representation of Touch in Silico

Huang, Chao; Zeldenrust, Fleur; Celikel, Tansu

doi:10.1007/s12021-022-09576-5

Cited by 6 publications

(7 citation statements)

References 177 publications

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“…Our NetPyNE implementation, together with the original BBP implementation ( Markram et al, 2015 ), constitute the only conductance-based, morphologically-detailed models of S1. These contrast with previous models of S1 ( Huang et al, 2022 ) or of generic sensory cortex ( Potjans and Diesmann, 2014 ) that employ simpler neuron models (leaky integrate and fire point neurons). Models with detailed conductance-based and morphologically-detailed neurons have been developed for other cortical regions, including V1 ( Arkhipov et al, 2018 ; Billeh et al, 2020 ), M1 ( Dura-Bernal et al, 2022b ), A1 ( Dura-Bernal et al, 2022a ), and CA1 ( Bezaire et al, 2016 ; Ecker et al, 2020 ).…”

Section: Discussionmentioning

confidence: 72%

“…Consequently, our port of the S1 model provides a quantitative framework that can be used in several ways. First, it can be used to perform in silico experiments to explore sensory processing under the assumption of various coding paradigms or brain disease, including the representation of whisker motion ( Bosman et al, 2011 ; Huang et al, 2022 ), maximization of sensory dynamic range ( Gautam et al, 2015 ), response to unexpected sensory inputs ( Amsalem et al, 2020 ) schizophrenia ( Metzner et al, 2020 ) and Parkinson’s disease ( Ranieri et al, 2021 ). Second, drug effects can be directly tested in the simulation ( Neymotin et al, 2016 )—this is an advantage of a multiscale model with scales from molecule to network, which is not available in simpler models that elide these details.…”

Section: Discussionmentioning

confidence: 99%

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Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

Borges

Moreira

Takarabe

et al. 2022

Front. Neuroinform.

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The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015, the Blue Brain Project (BBP) developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, and 37 million synapses, incorporating anatomical and physiological information from a wide range of experimental studies. We have implemented this highly detailed and complex S1 model in NetPyNE, using the data available in the Neocortical Microcircuit Collaboration Portal. NetPyNE provides a Python high-level interface to NEURON and allows defining complicated multiscale models using an intuitive declarative standardized language. It also facilitates running parallel simulations, automates the optimization and exploration of parameters using supercomputers, and provides a wide range of built-in analysis functions. This will make the S1 model more accessible and simpler to scale, modify and extend in order to explore research questions or interconnect to other existing models. Despite some implementation differences, the NetPyNE model preserved the original cell morphologies, electrophysiological responses and spatial distribution for all 207 cell types; and the connectivity properties of all 1941 pathways, including synaptic dynamics and short-term plasticity (STP). The NetPyNE S1 simulations produced reasonable physiological firing rates and activity patterns across all populations. When STP was included, the network generated a 1 Hz oscillation comparable to the original model in vitro-like state. By then reducing the extracellular calcium concentration, the model reproduced the original S1 in vivo-like states with asynchronous activity. These results validate the original study using a new modeling tool. Simulated local field potentials (LFPs) exhibited realistic oscillatory patterns and features, including distance- and frequency-dependent attenuation. The model was extended by adding thalamic circuits, including 6 distinct thalamic populations with intrathalamic, thalamocortical (TC) and corticothalamic connectivity derived from experimental data. The thalamic model reproduced single known cell and circuit-level dynamics, including burst and tonic firing modes and oscillatory patterns, providing a more realistic input to cortex and enabling study of TC interactions. Overall, our work provides a widely accessible, data-driven and biophysically-detailed model of the somatosensory TC circuits that can be employed as a community tool for researchers to study neural dynamics, function and disease.

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Section: Discussionmentioning

confidence: 72%

Section: Discussionmentioning

confidence: 99%

Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

Borges

Moreira

Takarabe

et al. 2022

Front. Neuroinform.

View full text Add to dashboard Cite

show abstract

“…Our NetPyNE implementation, together with the original BBP implementation (Markram et al 2015), constitute the only conductance-based, morphologically-detailed models of S1. These contrast with previous models of S1 (Huang, Zeldenrust, and Celikel 2022) or of generic sensory cortex (Potjans and Diesmann 2014) that employ simpler neuron models (leaky integrate and fire point neurons). Models with detailed conductance-based and morphologically-detailed neurons have been developed for other cortical regions, including V1 (Billeh et al 2020; Arkhipov et al 2018), M1 (Dura-Bernal, Neymotin, et al 2022), A1 (Dura-Bernal, Griffith, et al 2022), and CA1 (Bezaire et al 2016; Ecker et al 2020).…”

Section: Discussionmentioning

confidence: 72%

“…Consequently, our port of the S1 model provides a quantitative framework that can be used in several ways. First, it can be used to perform in silico experiments to explore sensory processing under the assumption of various coding paradigms or brain disease, including the representation of whisker motion (Bosman et al 2011; Huang, Zeldenrust, and Celikel 2022), maximization of sensory dynamic range (Gautam et al 2015), response to unexpected sensory inputs, schizophrenia (Metzner et al 2020) and Parkinson’s disease (Ranieri et al 2021). Second, drug effects can be directly tested in the simulation (Neymotin et al 2016) -- this is an advantage of a multiscale model with scales from molecule to network, which is not available in simpler models that elide these details.…”

Section: Discussionmentioning

confidence: 99%

Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

Borges

Moreira

Takarabe

et al. 2022

Preprint

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The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015 the Blue Brain Project developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, and 37 million synapses, incorporating anatomical and physiological information from a wide range of experimental studies. We have implemented this highly-detailed and complex model S1 model in NetPyNE, using the data available in the Neocortical Microcircuit Collaboration Portal. NetPyNE provides a Python high-level interface to NEURON and allows defining complicated multiscale models using an intuitive declarative standardized language. It also facilitates running parallel simulations, automates the optimization and exploration of parameters using supercomputers, and provides a wide range of built-in analysis functions. This will make the S1 model more accessible and simpler to scale, modify and extend in order to explore research questions or interconnect to other existing models. Despite some implementation differences, the NetPyNE model closely reproduced the original cell morphologies, electrophysiological responses, spatial distribution for all 207 cell types; and the connectivity properties of the 1941 pathways, including synaptic dynamics and short-term plasticity (STP). The NetPyNE S1 simulations produced reasonable physiological rates and activity patterns across all populations, and, when STP was included, produced a 1 Hz oscillation comparable to that of the original model. We also extended the model by adding thalamic circuits, including 6 distinct thalamic populations with intrathalamic, thalamocortical and corticothalamic connectivity derived from experimental data. Overall, our work provides a widely accessible, data-driven and biophysically-detailed model of the somatosensory thalamocortical circuits that can be utilized as a community tool for researchers to study neural dynamics, function and disease.

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“…These avant-garde techniques can be also exploited to further explore the system from the inside, allowing the analysis of neural properties thus controlling cell-specific connections and its implication inside a network. For example, Huang et al (2022) applied this innovative approach to reconstruct the barrel cortex to in silico replicate properties of touch representations. This model allows to unveil new principles of information processing through the identification of circuit components and the influence of connectivity on network behavior.…”

Section: Shifting Borders-exploring Cortico-thalamic Development Thro...mentioning

confidence: 99%

Cortico-thalamic development and disease: From cells, to circuits, to schizophrenia

Salavarria

Dell’Amico²,

D’Agostino³

et al. 2023

Front. Neuroanat.

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The human brain is the most complex structure generated during development. Unveiling the ontogenesis and the intrinsic organization of specific neural networks may represent a key to understanding the physio-pathological aspects of different brain areas. The cortico-thalamic and thalamo-cortical (CT-TC) circuits process and modulate essential tasks such as wakefulness, sleep and memory, and their alterations may result in neurodevelopmental and psychiatric disorders. These pathologies are reported to affect specific neural populations but may also broadly alter physiological connections and thus dysregulate brain network generation, communication, and function. More specifically, the CT-TC system is reported to be severely affected in disorders impacting superior brain functions, such as schizophrenia (SCZ), bipolar disorder, autism spectrum disorders or epilepsy. In this review, the focus will be on CT development, and the models exploited to uncover and comprehend its molecular and cellular mechanisms. In parallel to animal models, still fundamental to unveil human neural network establishment, advanced in vitro platforms, such as brain organoids derived from human pluripotent stem cells, will be discussed. Indeed, organoids and assembloids represent unique tools to study and accelerate fundamental research in CT development and its dysfunctions. We will then discuss recent cutting-edge contributions, including in silico approaches, concerning ontogenesis, specification, and function of the CT-TC circuitry that generates connectivity maps in physiological and pathological conditions.

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Cortical Representation of Touch in Silico

Cited by 6 publications

References 177 publications

Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

Cortico-thalamic development and disease: From cells, to circuits, to schizophrenia

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