Cortical dynamics during naturalistic sensory stimulations: experiments and models.
Abstract
We report the results of our experimental and theoretical investigations of the neural
response dynamics in primary visual cortex (V1) during naturalistic visual stimulation.
We recorded Local Field Potentials (LFPs) and spiking activity from V1 of anaesthetized
macaques during binocular presentation of Hollywood color movies. We analyzed these
recordings with information theoretic methods, and found that visual information was
encoded mainly by two bands of LFP responses: the network fluctuations measured by
the phase and power of low-frequency (less than 12 Hz) LFPs; and fast gamma-range
(50-100 Hz) oscillations. Both the power and phase of low frequency LFPs carried information
largely complementary to that carried by spikes, whereas gamma range oscillations
carried information largely redundant to that of spikes. To interpret these results
within a quantitative theoretical framework, we then simulated a sparsely connected
recurrent network of excitatory and inhibitory neurons receiving slowly varying naturalistic
inputs, and we determined how the LFPs generated by the network encoded information
about the inputs. We found that this simulated recurrent network reproduced well the
experimentally observed dependency of LFP information upon frequency. This network
encoded the overall strength of the input into the power of gamma-range oscillations
generated by inhibitory-excitatory neural interactions, and encoded slow variations
in the input by entraining the network LFP at the corresponding frequency. This dynamical
behavior accounted quantitatively for the independent information carried by high
and low frequency LFPs, and for the experimentally observed cross-frequency coupling
between phase of slow LFPs and the power of gamma LFPs. We also present new results
showing that the model's dynamics also accounted for the extra visual information
that the low-frequency LFP phase of spike firing carries beyond that carried by spike
rates. Overall, our results suggest biological mechanisms by which cortex can multiplex
information about naturalistic sensory environments.
Type
Journal articleSubject
Visual CortexNeurons
Animals
Macaca
Electroencephalography
Photic Stimulation
Visual Perception
Evoked Potentials, Visual
Action Potentials
Models, Neurological
Brain Waves
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https://hdl.handle.net/10161/23363Published Version (Please cite this version)
10.1016/j.jphysparis.2011.07.014Publication Info
Mazzoni, Alberto; Brunel, Nicolas; Cavallari, Stefano; Logothetis, Nikos K; & Panzeri,
Stefano (2011). Cortical dynamics during naturalistic sensory stimulations: experiments and models.
Journal of physiology, Paris, 105(1-3). pp. 2-15. 10.1016/j.jphysparis.2011.07.014. Retrieved from https://hdl.handle.net/10161/23363.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Nicolas Brunel
Professor of Neurobiology
We use theoretical models of brain systems to investigate how they process and learn
information from their inputs. Our current work focuses on the mechanisms of learning
and memory, from the synapse to the network level, in collaboration with various experimental
groups. Using methods fromstatistical physics, we have shown recently that the synapticconnectivity
of a network that maximizes storage capacity reproducestwo key experimentally observed
features: low connection proba

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