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Cortical network architecture for context processing in primate brain.

Chao ZC, Nagasaka Y, Fujii N - Elife (2015)

Bottom Line: We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity.These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows.This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako-shi, Japan.

ABSTRACT
Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition.

No MeSH data available.


Causal outflow in individual subjects.Cortical areas with overall positive causal outflow (source areas) are indicated shown in red, and those with overall negative causal outflow (sink areas) are shown in blue. Results from individual subjects and the summarized results after brain map registration are shown for each latent network structure.DOI:http://dx.doi.org/10.7554/eLife.06121.020
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fig4s2: Causal outflow in individual subjects.Cortical areas with overall positive causal outflow (source areas) are indicated shown in red, and those with overall negative causal outflow (sink areas) are shown in blue. Results from individual subjects and the summarized results after brain map registration are shown for each latent network structure.DOI:http://dx.doi.org/10.7554/eLife.06121.020


Cortical network architecture for context processing in primate brain.

Chao ZC, Nagasaka Y, Fujii N - Elife (2015)

Causal outflow in individual subjects.Cortical areas with overall positive causal outflow (source areas) are indicated shown in red, and those with overall negative causal outflow (sink areas) are shown in blue. Results from individual subjects and the summarized results after brain map registration are shown for each latent network structure.DOI:http://dx.doi.org/10.7554/eLife.06121.020
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4584448&req=5

fig4s2: Causal outflow in individual subjects.Cortical areas with overall positive causal outflow (source areas) are indicated shown in red, and those with overall negative causal outflow (sink areas) are shown in blue. Results from individual subjects and the summarized results after brain map registration are shown for each latent network structure.DOI:http://dx.doi.org/10.7554/eLife.06121.020
Bottom Line: We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity.These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows.This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako-shi, Japan.

ABSTRACT
Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition.

No MeSH data available.