Cortical cell assemblies and their underlying connectivity: anin silicostudy DOI Creative Commons
András Ecker, Daniela Egas Santander, Sirio Bolaños‐Puchet

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 24, 2023

Abstract Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study functional cell assemblies. However, determining patterns synaptic connectivity giving rise to these assemblies remains challenging. To address this, we developed a complementary, simulation-based approach, using detailed, large-scale cortical network model. Using combination established methods detected stimulus-evoked spiking activity 186,665 neurons. We studied how structure underlies assembly composition, quantifying effects thalamic innervation, recurrent connectivity, and spatial arrangement synapses on den-drites. determined that features reduce up 30%, 22%, 10% uncertainty neuron belonging an assembly. The were activated stimulus-specific sequence grouped based their position sequence. found different groups affected degrees by structural considered. Additionally, was more predictive membership if its direction aligned with temporal order activation, it originated strongly interconnected populations, clustered dendritic branches. In summary, reversing Hebb’s postulate, showed cells are wired together, fire interact shape emergence This includes qualitative aspect connectivity: not just amount, but also local matters; subcellular level form clustering presence specific motifs. connectivity-based characterization creates opportunity plasticity at level, beyond strictly pairwise interactions.

Language: Английский

Community-based Reconstruction and Simulation of a Full-scale Model of Region CA1 of Rat Hippocampus DOI Open Access
Armando Romani, Alberto Antonietti, Davide Bella

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: May 17, 2023

Abstract The CA1 region of the hippocampus is one most studied regions rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth experimental data on its structure function, it has been challenging reconcile information obtained from diverse approaches. To address this challenge, we present community-driven, full-scale silico model rat that integrates broad range data, synapse network, including reconstruction principal afferents, Schaffer collaterals, effects acetylcholine system. We tested validated each component final network model, made input assumptions, strategies explicit transparent. unique flexibility allows scientists scientific questions. In article, describe methods used set up simulations reproduce extend vitro vivo experiments. Among several applications focus theta rhythm, prominent hippocampal oscillation associated with various behavioral correlates use our computer findings. Finally, make code available through hippocampushub.eu portal, which also provides extensive analyses user-friendly interface facilitate adoption usage. This neuroscience community-driven represents valuable tool for integrating foundation further research into complex workings region.

Language: Английский

Citations

11
Reconciliation of weak pairwise spike–train correlations and highly coherent local field potentials across space DOI Creative Commons
Johanna Senk, Espen Hagen, Sacha J. van Albada

et al.

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(10)

Published: Sept. 23, 2024

Multi-electrode arrays covering several square millimeters of neural tissue provide simultaneous access to population signals such as extracellular potentials and spiking activity one hundred or more individual neurons. The interpretation the recorded data calls for multiscale computational models with corresponding spatial dimensions signal predictions. Multi-layer neuron network local cortical circuits about $1\,{\text{mm}^{2}}$ have been developed, integrating experimentally obtained neuron-type-specific connectivity reproducing features observed in-vivo statistics. Local field can be computed from simulated activity. We here extend a potential model an area $4\times 4\,{\text{mm}^{2}}$, preserving density introducing distance-dependent connection probabilities conduction delays. find that upscaling procedure preserves overall statistics original reproduces asynchronous irregular across populations weak pairwise spike-train correlations in agreement experimental recordings sensory cortex. Also compatible observations, correlation is strong decays over distance micrometers. Enhanced coherence low-gamma band around $50\,\text{Hz}$ may explain recent report apparent band-pass filter effect reach potential.

Language: Английский

Citations

4
Enhancement of brain atlases with laminar coordinate systems: Flatmaps and barrel column annotations DOI Creative Commons
Sirio Bolaños‐Puchet, Aleksandra Teska, Juan Hernando

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Aug. 26, 2023

Abstract Digital brain atlases define a hierarchy of regions and their locations in three-dimensional Cartesian space. They provide standard coordinate system which diverse datasets can be integrated for visualization analysis. Although this has well-defined anatomical axes, it does not the best context to work with complex geometries layered such as neocortex. To address that, we introduce laminar systems that consider curvature structure region interest. These new consist principal axis, locally aligned vertical direction measuring depth, two other axes describe flatmap, two-dimensional representation horizontal extents layers. The main property flatmap is allows seamless mapping information back forth between 2D 3D spaces, way consistent axis. It involves structured dimensionality reduction where aggregated along depth. We propose method enhance flatmaps based on user specifications set metrics characterize quality flatmaps. applied our an atlas rat somatosensory cortex Paxinos Watson’s atlas, enhancing adapted geometry region. Further, Allen Mouse Brain Atlas Common Coordinate Framework version 3 whole isocortex. used produce annotations 33 individual barrels barrel columns cortex. Thanks properties resulting are non-overlapping follow Additionally, introduced several applications highlighting utility data data-driven modeling. free software implementation methods benefit community.

Language: Английский

Citations

5
Controlling morpho-electrophysiological variability of neurons with detailed biophysical models DOI Open Access
Alexis Arnaudon, Maria Reva, Mickaël Zbili

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: April 6, 2023

Abstract Variability is a universal feature among biological units such as neuronal cells they enable robust encoding of high volume information in circuits and prevent hyper synchronizations epileptic seizures. While most computational studies on electrophysiological variability were done with simplified neuron models, we instead focus the detailed biophysical models neurons. With measures experimental variability, leverage Markov chain Monte Carlo method to generate populations electrical able reproduce from sets recordings. By matching input resistances soma axon initial segments one dendrites, produce compatible set morphologies that faithfully represent given morpho-electrical type. We demonstrate our approach layer 5 pyramidal continuous adapting firing type show morphological insufficient variability. Overall, this provides strong statistical basis create neurons controlled

Language: Английский

Citations

4
A biophysically-detailed model of inter-areal interactions in cortical sensory processing DOI Creative Commons
Sirio Bolaños‐Puchet, Michael W. Reimann

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 13, 2024

Abstract Mechanisms of top-down modulation in sensory perception and their relation to underlying connectivity are not completely understood. We present here a biophysically-detailed computational model two interconnected cortical areas, representing the first steps processing hierarchy, as tool for potential discovery. The integrates large body data from rodent primary somatosensory cortex reproduces biological features across multiple scales: handful ion channels defining diversity electrical types hundreds thousands morphologically detailed neurons, local long-range networks mediated by millions synapses. Notably, incorporates target lamination patterns associated with feed-forward feedback pathways. use study impact inter-areal interactions on processing. First, we exhibit cortico-cortical loop between areas (X Y), wherein input area X produces response components time, driven stimulus second Y. perform structural functional characterization this loop, finding differential layer-specific pathways directions. Second, explore discrimination presenting four different spatially-segregate patterns. observe well-defined temporal sequences cell assembly activation, specificity early but late assemblies X, i.e., stimulus-driven component feedback-driven component. also find earliest Y be specific pairs patterns, consistent topography connections. Finally, examine integration bottom-up signals. When coincident component, an approximate linear superposition responses. implied lack interaction naive absence plasticity mechanisms that would underlie learning influences. This work represents step simulations.

Language: Английский

Citations

1
Neuromodulatory organization in the developing rat somatosensory cortex DOI Open Access
Cristina Colangelo, Alberto Muñoz, Alberto Antonietti

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: Nov. 13, 2022

Abstract The vast majority of cortical synapses are found in the neuropil which is implicated multiple and diverse functions underlying brain computation. Unraveling organizing principles requires an intricate characterization synaptic connections established by excitatory inhibitory axon terminals, intrinsic extrinsic origin from ascending projections that govern function microcircuits through release neuromodulators either point-to-point chemical or diffuse volume transmission (VT). Even though neuromodulatory has been studied for almost a century it still not clear if one modality prevails upon other. hindlimb representation somatosensory cortex (HLS1) two-week old Wistar rats served as model system to dissect microcircuitry neurons their connections. In present study, we quantified fiber length per density varicosities cholinergic, catecholaminergic serotonergic systems using immunocytochemical staining stereological techniques. Acquired data were integrated into novel computational framework reconcile specific modalities predict effects shaping neocortical network activity. We acetylcholine (ACh), dopamine (DA), serotonin (5-HT) desynchronizes activity inhibiting slow oscillations (delta range), 5-HT triggers faster (theta). Moreover, high levels (>40%) VT sufficient induce desynchronization, but also combining with inputs leads more robust stable effects, meaning lower needed achieve same outcome (10%).

Language: Английский

Citations

3
A universal workflow for creation, validation and generalization of detailed neuronal models DOI Creative Commons
Maria Reva, Christian Rössert, Alexis Arnaudon

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: Dec. 13, 2022

Abstract Detailed single neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex vast, most of available computational tools are dedicated reproduction a small set specific features characteristic neuron. Here, we present generalized automated workflow for creation robust electrical models illustrate its performance by building cell rat somatosensory (SSCx). Each model based on 3D morphological reconstruction ionic mechanisms type. We use an evolutionary algorithm optimize passive active parameters match electrophysiological extracted from whole-cell patch-clamp recordings. To shed light which constrained experimental data could be degenerate, perform parameter sensitivity analysis. also validate optimized against additional stimuli assess their generalizability population morphologies with same With this workflow, generate SSCx producing variability responses. Due versatility, our can build biophysical any

Language: Английский

Citations

2
Cortical cell assemblies and their underlying connectivity: anin silicostudy DOI Creative Commons
András Ecker, Daniela Egas Santander, Sirio Bolaños‐Puchet

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 24, 2023

Abstract Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study functional cell assemblies. However, determining patterns synaptic connectivity giving rise to these assemblies remains challenging. To address this, we developed a complementary, simulation-based approach, using detailed, large-scale cortical network model. Using combination established methods detected stimulus-evoked spiking activity 186,665 neurons. We studied how structure underlies assembly composition, quantifying effects thalamic innervation, recurrent connectivity, and spatial arrangement synapses on den-drites. determined that features reduce up 30%, 22%, 10% uncertainty neuron belonging an assembly. The were activated stimulus-specific sequence grouped based their position sequence. found different groups affected degrees by structural considered. Additionally, was more predictive membership if its direction aligned with temporal order activation, it originated strongly interconnected populations, clustered dendritic branches. In summary, reversing Hebb’s postulate, showed cells are wired together, fire interact shape emergence This includes qualitative aspect connectivity: not just amount, but also local matters; subcellular level form clustering presence specific motifs. connectivity-based characterization creates opportunity plasticity at level, beyond strictly pairwise interactions.

Language: Английский

Citations

0