Cortical cell assemblies and their underlying connectivity: an<i>in silico</i>study

Ecker, András; Santander, Daniela Egas; Bolaños-Puchet, Sirio; Isbister, James B.; Reimann, Michael

doi:10.1101/2023.02.24.529863

Cited by 4 publications

(40 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…G3: Correlation of input distances (see Figure 3C1) and output distances on G2. (Similar panels (except A, B, and F) have been shown in Ecker et al, 2023. ) We detected and compared assemblies before and after plasticity across five repetitions.…”

Section: Increased Stimulus-specificity Characterize the Network Afte...supporting

confidence: 81%

“…Membership of neurons in these consensus assemblies was based on the fraction of assembly instances they were part of, normalized by a binomial control and thresholded. As shown in Ecker et al (2023), consensus assemblies are similar to assemblies detected over the average spike trains across repetitions, but with the added benefit of the membership threshold. In rough terms, this threshold can be understood as follows: if a neuron was part of 80% of assembly instances that made up the consensus, then it was also a member of the consensus assembly.…”

Section: Determination Of Consensus Assembliesmentioning

confidence: 79%

“…Therefore, we specifically hypothesized that plasticity of connections may be structured by the membership of participating neurons in Hebbian cell assemblies, i.e., groups of neurons that fire together (Hebb, 1949;Harris, 2005). In a previous analysis (Ecker et al, 2023), and in line with experimental results (Harris, 2005;Song et al, 2005;Perin et al, 2011), we observed that assembly-indegree, i.e., the number of afferent connections from an assembly, is a great predictor of a neuron's membership in an assembly. Strong positive interactions were also found across assemblies, but only when the direction of innervation reflected the temporal order of assembly activation.…”

Section: More Frequent Plastic Changes Within and Across Cell Assembliesmentioning

confidence: 99%

“…The combination of methods from Carrillo-Reid et al (2015) and Herzog et al (2021) yielding the assembly detection pipeline is fully described in Ecker et al (2023), but a minimal description, highlighting the changes applied in this study, can be found below. First, spikes of excitatory cells were binned using 20 ms time bins (Harris et al, 2003).…”

Section: Cell Assembly Detectionmentioning

confidence: 99%

“…Like for any other unsupervised clustering method, the number of optimal clusters cannot be known beforehand, thus potential number of clusters were scanned between five and twenty. In Ecker et al (2023), the one with the lowest Davis-Bouldin index was chosen, which maximizes the similarity within elements of the cluster while maximizing the between cluster similarity (Davies and Bouldin, 1979). For assemblies detected over the 10 minutes-long plastic simulation, this optimal value was overwritten, to have at least one pattern-specific assembly for all ten patterns.…”

Section: Cell Assembly Detectionmentioning

confidence: 99%

See 4 more Smart Citations

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Ecker,

Egas Santander,

Abdellah

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

Synaptic plasticity underlies the brain’s ability to learn and adapt. This process is often studied in small groups of neuronsin vitroor indirectly through its effects on behaviorin vivo. Due to the limitations of available experimental techniques, investigating synaptic plasticity at the micro-circuit level relies on simulation-based approaches. Although modeling studies provide valuable insights, they are usually limited in scale and generality. To overcome these limitations, we extended a previously published and validated large-scale cortical network model with a recently developed calcium-based model of functional plasticity between excitatory cells. We calibrated the network to mimic anin vivostate characterized by low synaptic release probability and low-rate asynchronous firing, and exposed it to ten different stimuli. We found that synaptic plasticity sparsely and specifically strengthened synapses forming spatial clusters on postsynaptic dendrites and those between populations of co-firing neurons, also known as cell assemblies: among 312 million synapses, only 5% experienced noticeable plasticity and cross-assembly synapses underwent three times more changes than average. Furthermore, as occasional large-amplitude potentiation was counteracted by more frequent synaptic depression, the network remained stable without explicitly modeling homeostatic plasticity. When comparing the network’s responses to the different stimuli before and after plasticity, we found that it became more stimulus-specific after plasticity, manifesting in prolonged activity after selected stimuli and more unique groups of neurons responding exclusively to a single pattern. Taken together, we present the first stable simulation of Hebbian plasticity without homeostatic terms at this level of detail and analyze the rules determining the sparse changes.

show abstract

Section: Increased Stimulus-specificity Characterize the Network Afte...supporting

confidence: 81%

Section: Determination Of Consensus Assembliesmentioning

confidence: 79%

Section: More Frequent Plastic Changes Within and Across Cell Assembliesmentioning

confidence: 99%

Section: Cell Assembly Detectionmentioning

confidence: 99%

Section: Cell Assembly Detectionmentioning

confidence: 99%

See 3 more Smart Citations

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Ecker,

Egas Santander,

Abdellah

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part I: Anatomy

Reimann

Bolaños-Puchet

Courcol

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The function of the neocortex is fundamentally determined by its repeating microcircuit motif, but also by its rich, hierarchical, interregional structure with a highly specific laminar architecture. The last decade has seen the emergence of extensive new data sets on anatomy and connectivity at the whole brain scale, providing promising new directions for studies of cortical function that take into account the inseparability of whole-brain and microcircuit architectures. Here, we present a data-driven computational model of the anatomy of non-barrel primary somatosensory cortex of juvenile rat, which integrates whole-brain scale data while providing cellular and subcellular specificity. This multiscale integration was achieved by building the morphologically detailed model of cortical circuitry embedded within a volumetric, digital brain atlas. The model consists of 4.2 million morphologically detailed neurons belonging to 60 different morphological types, placed in the nonbarrel subregions of the Paxinos and Watson atlas. They are connected by 13.2 billion synapses determined by axo-dendritic overlap, comprising local connectivity and long-range connectivity defined by topographic mappings between subregions and laminar axonal projection profiles, both parameterized by whole brain data sets. Additionally, we incorporated core- and matrix-type thalamocortical projection systems, associated with sensory and higher-order extrinsic inputs, respectively. An analysis of the modeled synaptic connectivity revealed a highly nonrandom topology with substantial structural differences but also synergy between local and long-range connectivity. Long-range connections featured a more divergent structure with a comparatively small group of neurons serving as hubs to distribute excitation to far away locations. Taken together with analyses at different spatial granularities, these results support the notion that local and interregional connectivity exist on a spectrum of scales, rather than as separate and distinct networks, as is commonly assumed. Finally, we predicted how the emergence of primary sensory cortical maps is constrained by the anatomy of thalamo-cortical projections. A subvolume of the model comprising 211,712 neurons in the front limb, jaw, and dysgranular zone has been made freely and openly available to the community.

show abstract

Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part II: Physiology and Experimentation

Isbister,

Ecker,

Pokorny

et al. 2023

Preprint

View full text Add to dashboard Cite

In recent years, large-scale computational models of the cortex have emerged as a powerful way to study the multi-scale mechanisms of neural processing. However, due to computational costs and difficulty of parameterization, detailed biophysical reconstructions have so far been restricted to small volumes of tissue, where the study of macro- and meso-scale interactions that are central to cortical function is not possible. We describe here, and in a companion paper, an approach to address the scaling challenges and provide a model of multiple interacting cortical regions at a subcellular level of detail. The model consists of 4.2 million morphologically detailed neurons in 8 sub-regions and connected with 13.2 billion synapses through local and long-range connectivity. Its anatomical aspects are described in the companion paper; here, we introduce physiological models of neuronal activity and synaptic transmission that integrate a large number of literature sources and were built using previously published algorithms. Biological neuronal diversity was captured in 208 morpho-electrical neuron types, five types of synaptic short-term dynamics, and pathway-specificity of synaptic parameters. A representation of synaptic input from cortical regions not present in the model was added and efficiently calibrated to reference firing rates. The model exhibits a spectrum of dynamical states differing in the degree to which they are internally versus externally driven. We characterized which parts of the spectrum are compatible with available experimental data on layer-specific delays and amplitudes of responses to simple stimuli, and found anin vivo-like regime at the edge of a transition from asynchronous to synchronous spontaneous activity. We developed a rich set of simulation tools to recreate a diverse set of laboratory experimentsin silico, providing further validation and demonstrating the utility of the model in a variety of paradigms. Finally, we found that the large spatial scale of the model, that incorporates multiple cortical regions, led to the emergence of multiple independent computational units interacting through long-range synaptic pathways. The model provides a framework for the continued integration of experimental findings, for challenging hypotheses and making testable predictions, and provides a foundation for further simulation-based studies of cortical processing and learning.

show abstract

Cortical cell assemblies and their underlying connectivity: anin silicostudy

Cited by 4 publications

References 75 publications

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part I: Anatomy

Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part II: Physiology and Experimentation

Contact Info

Product

Resources

About