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• W2904617901 startingPage "e1006893" @default.
• W2904617901 abstract "Neural activity exhibits a vast range of timescales that can be several fold larger than the membrane time constant of individual neurons. Two types of mechanisms have been proposed to explain this conundrum. One possibility is that large timescales are generated by a network mechanism based on positive feedback, but this hypothesis requires fine-tuning of the synaptic connections. A second possibility is that large timescales in the neural dynamics are inherited from large timescales of underlying biophysical processes, two prominent candidates being adaptive ionic currents and synaptic transmission. How the timescales of these processes influence the timescale of the network dynamics has however not been fully explored. To address this question, we analyze large networks of randomly connected excitatory and inhibitory units with additional degrees of freedom that correspond to adaptation or synaptic filtering. We determine the fixed points of the systems, their stability to perturbations and the corresponding dynamical timescales. Furthermore, we apply dynamical mean field theory to study the temporal statistics of the activity in the fluctuating regime, and examine how the adaptation and synaptic timescales transfer from individual units to the whole population. Our overarching finding is that synaptic filtering and adaptation in single neurons have very different effects at the network level. Unexpectedly, the macroscopic network dynamics do not inherit the large timescale present in adaptive currents. In contrast, the timescales of network activity increase proportionally to the time constant of the synaptic filter. Altogether, our study demonstrates that the timescales of different biophysical processes have different effects on the network level, so that the slow processes within individual neurons do not necessarily induce slow activity in large recurrent neural networks." @default.
• W2904617901 created "2018-12-22" @default.
• W2904617901 creator A5028433393 @default.
• W2904617901 creator A5058457117 @default.
• W2904617901 date "2019-03-21" @default.
• W2904617901 modified "2023-10-16" @default.
• W2904617901 title "Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks" @default.
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• W2904617901 doi "https://doi.org/10.1371/journal.pcbi.1006893" @default.
• W2904617901 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6445477" @default.
• W2904617901 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30897092" @default.
• W2904617901 hasPublicationYear "2019" @default.
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