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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.


Examples of eye movement.Examples of eye position during CmRf scenario under C+ condition from Subject 2. Sampled eye positions (circles) in the three periods (Waiting, Context, and Response) are shown, where the corresponding timings are indicated by the colorbar. Snapshots of the videos during the corresponding periods are also shown.DOI:http://dx.doi.org/10.7554/eLife.06121.012
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fig2s1: Examples of eye movement.Examples of eye position during CmRf scenario under C+ condition from Subject 2. Sampled eye positions (circles) in the three periods (Waiting, Context, and Response) are shown, where the corresponding timings are indicated by the colorbar. Snapshots of the videos during the corresponding periods are also shown.DOI:http://dx.doi.org/10.7554/eLife.06121.012

Mentions: During the task, subjects freely moved their eyes to observe the video interactions. We monitored eye movements to examine these spontaneous behavioral reactions and the associated zones in the video. We divided the trials into two conditions based on whether the context stimulus was visually perceived: C+ where the subject was looking at the screen during the Context period, and C− where the subject was either closing its eyes or looking outside of the screen. Example eye movements are shown in Figure 2—figure supplement 1.


Cortical network architecture for context processing in primate brain.

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

Examples of eye movement.Examples of eye position during CmRf scenario under C+ condition from Subject 2. Sampled eye positions (circles) in the three periods (Waiting, Context, and Response) are shown, where the corresponding timings are indicated by the colorbar. Snapshots of the videos during the corresponding periods are also shown.DOI:http://dx.doi.org/10.7554/eLife.06121.012
© Copyright Policy
Related In: Results  -  Collection

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

fig2s1: Examples of eye movement.Examples of eye position during CmRf scenario under C+ condition from Subject 2. Sampled eye positions (circles) in the three periods (Waiting, Context, and Response) are shown, where the corresponding timings are indicated by the colorbar. Snapshots of the videos during the corresponding periods are also shown.DOI:http://dx.doi.org/10.7554/eLife.06121.012
Mentions: During the task, subjects freely moved their eyes to observe the video interactions. We monitored eye movements to examine these spontaneous behavioral reactions and the associated zones in the video. We divided the trials into two conditions based on whether the context stimulus was visually perceived: C+ where the subject was looking at the screen during the Context period, and C− where the subject was either closing its eyes or looking outside of the screen. Example eye movements are shown in Figure 2—figure supplement 1.

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.