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Do neural oscillations modulate information processing in the brain? From routing states to computing modes| old_uid | 15924 |
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| title | Do neural oscillations modulate information processing in the brain? From routing states to computing modes |
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| start_date | 2018/05/17 |
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| schedule | 14h-15h |
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| online | no |
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| details | GNT External Seminar series |
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| summary | Perception, cognition and behavior rely on flexible communication
between microcircuits in distinct cortical regions.
The mechanisms underlying rapid information rerouting between such
microcircuits are still unknown. It has been proposed based on growing
experimental evidence that changing patterns of coherence between
local gamma rhythms support flexible information rerouting. The
stochastic and transient nature of gamma oscillations in vivo,
however, is hard to reconcile with such a function, as other
experiments have shown in a seemingly contradictory way. Here we show
through a computational modelling approach that models of cortical
circuits near the onset of oscillatory synchrony are well able to
selectively route input signals despite the short duration of gamma
bursts and the irregularity of neuronal firing. In canonical multiarea
circuits, we find that gamma bursts spontaneously arise with matched
timing and frequency and that they organize information flow by
large-scale routing states. Specific self-organized routing states can
be induced by minor modulations of background activity.
Moving then to the analysis of electrophysiological recordings in
anaesthetized and sleeping rats, we investigate whether changing
oscillatory states may have an impact on ongoing information
processing, beyond information routing. We are able to identify a
multiplicity of internal "computing modes", characterized by the
flexible recruitment of alternative hub neurons, specialised in
distinct elementary information processing functions (storage and
transfer).
We then characterize the discrete transitions spontaneously occurring
between these modes. We find
that switching between oscillatory states largely constrains which
computing modes can be observed (theta-vs slow-oscillation specific
modes). Furthermore, switching transitions assemble into sequences
whose complexity is quantitatively and consistently measured to be
larger during theta than slow oscillation epochs. Thus, changes of the
oscillatory mode impact on both the "dictionary" within which
computing modes are sampled and the "grammar" generating transitions
between these modes. |
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| responsibles | Kushnir |
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