Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks
Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable in the brain. The analysis is performed by combining extens...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-12-01
|
| Series: | Frontiers in Systems Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnsys.2021.752261/full |
| _version_ | 1818404093954097152 |
|---|---|
| author | Hongjie Bi Hongjie Bi Matteo di Volo Alessandro Torcini Alessandro Torcini |
| author_facet | Hongjie Bi Hongjie Bi Matteo di Volo Alessandro Torcini Alessandro Torcini |
| author_sort | Hongjie Bi |
| collection | DOAJ |
| description | Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable in the brain. The analysis is performed by combining extensive simulations of sparse E-I networks composed of N spiking neurons with analytical investigations of low dimensional neural mass models. The bifurcation diagrams, derived for the neural mass model, allow us to classify the possible asynchronous and coherent behaviors emerging in balanced E-I networks with structural heterogeneity for any finite in-degree K. Analytic mean-field (MF) results show that both supra and sub-threshold balanced asynchronous regimes are observable in our system in the limit N >> K >> 1. Due to the heterogeneity, the asynchronous states are characterized at the microscopic level by the splitting of the neurons in to three groups: silent, fluctuation, and mean driven. These features are consistent with experimental observations reported for heterogeneous neural circuits. The coherent rhythms observed in our system can range from periodic and quasi-periodic collective oscillations (COs) to coherent chaos. These rhythms are characterized by regular or irregular temporal fluctuations joined to spatial coherence somehow similar to coherent fluctuations observed in the cortex over multiple spatial scales. The COs can emerge due to two different mechanisms. A first mechanism analogous to the pyramidal-interneuron gamma (PING), usually invoked for the emergence of γ-oscillations. The second mechanism is intimately related to the presence of current fluctuations, which sustain COs characterized by an essentially simultaneous bursting of the two populations. We observe period-doubling cascades involving the PING-like COs finally leading to the appearance of coherent chaos. Fluctuation driven COs are usually observable in our system as quasi-periodic collective motions characterized by two incommensurate frequencies. However, for sufficiently strong current fluctuations these collective rhythms can lock. This represents a novel mechanism of frequency locking in neural populations promoted by intrinsic fluctuations. COs are observable for any finite in-degree K, however, their existence in the limit N >> K >> 1 appears as uncertain. |
| first_indexed | 2024-12-14T08:34:41Z |
| format | Article |
| id | doaj.art-f2418c6bb0794890947caab199cf5d70 |
| institution | Directory Open Access Journal |
| issn | 1662-5137 |
| language | English |
| last_indexed | 2024-12-14T08:34:41Z |
| publishDate | 2021-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Systems Neuroscience |
| spelling | doaj.art-f2418c6bb0794890947caab199cf5d702022-12-21T23:09:27ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372021-12-011510.3389/fnsys.2021.752261752261Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking NetworksHongjie Bi0Hongjie Bi1Matteo di Volo2Alessandro Torcini3Alessandro Torcini4CY Cergy Paris Université, Laboratoire de Physique Théorique et Modélisation, CNRS, UMR 8089, Cergy-Pontoise, FranceNeural Coding and Brain Computing Unit, Okinawa Institute of Science and Technology, Okinawa, JapanCY Cergy Paris Université, Laboratoire de Physique Théorique et Modélisation, CNRS, UMR 8089, Cergy-Pontoise, FranceCY Cergy Paris Université, Laboratoire de Physique Théorique et Modélisation, CNRS, UMR 8089, Cergy-Pontoise, FranceCNR-Consiglio Nazionale delle Ricerche, Istituto dei Sistemi Complessi, Sesto Fiorentino, ItalyDynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable in the brain. The analysis is performed by combining extensive simulations of sparse E-I networks composed of N spiking neurons with analytical investigations of low dimensional neural mass models. The bifurcation diagrams, derived for the neural mass model, allow us to classify the possible asynchronous and coherent behaviors emerging in balanced E-I networks with structural heterogeneity for any finite in-degree K. Analytic mean-field (MF) results show that both supra and sub-threshold balanced asynchronous regimes are observable in our system in the limit N >> K >> 1. Due to the heterogeneity, the asynchronous states are characterized at the microscopic level by the splitting of the neurons in to three groups: silent, fluctuation, and mean driven. These features are consistent with experimental observations reported for heterogeneous neural circuits. The coherent rhythms observed in our system can range from periodic and quasi-periodic collective oscillations (COs) to coherent chaos. These rhythms are characterized by regular or irregular temporal fluctuations joined to spatial coherence somehow similar to coherent fluctuations observed in the cortex over multiple spatial scales. The COs can emerge due to two different mechanisms. A first mechanism analogous to the pyramidal-interneuron gamma (PING), usually invoked for the emergence of γ-oscillations. The second mechanism is intimately related to the presence of current fluctuations, which sustain COs characterized by an essentially simultaneous bursting of the two populations. We observe period-doubling cascades involving the PING-like COs finally leading to the appearance of coherent chaos. Fluctuation driven COs are usually observable in our system as quasi-periodic collective motions characterized by two incommensurate frequencies. However, for sufficiently strong current fluctuations these collective rhythms can lock. This represents a novel mechanism of frequency locking in neural populations promoted by intrinsic fluctuations. COs are observable for any finite in-degree K, however, their existence in the limit N >> K >> 1 appears as uncertain.https://www.frontiersin.org/articles/10.3389/fnsys.2021.752261/fullbalanced spiking neural populationssparse inhibitory-excitatory networksasynchronous dynamicscollective oscillationsneural mass modelquadratic integrate and fire neuron |
| spellingShingle | Hongjie Bi Hongjie Bi Matteo di Volo Alessandro Torcini Alessandro Torcini Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks Frontiers in Systems Neuroscience balanced spiking neural populations sparse inhibitory-excitatory networks asynchronous dynamics collective oscillations neural mass model quadratic integrate and fire neuron |
| title | Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks |
| title_full | Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks |
| title_fullStr | Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks |
| title_full_unstemmed | Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks |
| title_short | Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks |
| title_sort | asynchronous and coherent dynamics in balanced excitatory inhibitory spiking networks |
| topic | balanced spiking neural populations sparse inhibitory-excitatory networks asynchronous dynamics collective oscillations neural mass model quadratic integrate and fire neuron |
| url | https://www.frontiersin.org/articles/10.3389/fnsys.2021.752261/full |
| work_keys_str_mv | AT hongjiebi asynchronousandcoherentdynamicsinbalancedexcitatoryinhibitoryspikingnetworks AT hongjiebi asynchronousandcoherentdynamicsinbalancedexcitatoryinhibitoryspikingnetworks AT matteodivolo asynchronousandcoherentdynamicsinbalancedexcitatoryinhibitoryspikingnetworks AT alessandrotorcini asynchronousandcoherentdynamicsinbalancedexcitatoryinhibitoryspikingnetworks AT alessandrotorcini asynchronousandcoherentdynamicsinbalancedexcitatoryinhibitoryspikingnetworks |