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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.


Related in: MedlinePlus

Context as a sequence of interactions between network structures.(A) Coordination between network structures (S1 to S5, circles), under Rn (top) or Rf (bottom) responses. In both response contingencies, context perception (S1) encoded contextual information (S3). However, when the response stimulus contained high emotional valence (Rf, bottom), response perception (S2) reactivates the contextual information (S4), resulting in top-down modulation feedback (S5) that shares the same context and response dependence as the gazing behavior (black arrow and rounded rectangles). Green, blue, and red arrows represent correlations in context dependence in Rn, context dependence in Rf, and in response dependence, respectively (see Figure 6A). (B) Temporal, spectral, and spatial profiles and overlap in defined network structures. Network structures can be characterized by frequency range (labeled on the left) and connectivity pattern (shown on the right). Their temporal activations are plotted over trial time, with a ‘sound-like’ presentation, where a higher volume represents stronger activation. Black vertical lines represent the events as indicated in Figure 2.DOI:http://dx.doi.org/10.7554/eLife.06121.026
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fig7: Context as a sequence of interactions between network structures.(A) Coordination between network structures (S1 to S5, circles), under Rn (top) or Rf (bottom) responses. In both response contingencies, context perception (S1) encoded contextual information (S3). However, when the response stimulus contained high emotional valence (Rf, bottom), response perception (S2) reactivates the contextual information (S4), resulting in top-down modulation feedback (S5) that shares the same context and response dependence as the gazing behavior (black arrow and rounded rectangles). Green, blue, and red arrows represent correlations in context dependence in Rn, context dependence in Rf, and in response dependence, respectively (see Figure 6A). (B) Temporal, spectral, and spatial profiles and overlap in defined network structures. Network structures can be characterized by frequency range (labeled on the left) and connectivity pattern (shown on the right). Their temporal activations are plotted over trial time, with a ‘sound-like’ presentation, where a higher volume represents stronger activation. Black vertical lines represent the events as indicated in Figure 2.DOI:http://dx.doi.org/10.7554/eLife.06121.026

Mentions: These results suggest a basic structural organization of large-scale communication within brain networks that coordinate context processing, and provide insight into how apparently seamless cognition is constructed from these network communication modules. In contrast to previous studies where brain modularity is defined as a ‘community’ of spatial connections (Bullmore and Sporns, 2009; Sporns, 2011), or coherent oscillations among neuronal populations in overlapping frequency bands (Siegel et al., 2012), our findings provide an even more general yet finer grained definition of modularity based on not only anatomical and spectral properties, but also temporal, functional, and directional connectivity data. The relationships among network properties in the functional, temporal, spectral, and anatomical domains revealed network structures whose activity coordinated with each other in a deterministic manner (Figure 7A), despite being highly overlapping in time, frequency, and space (Figure 7B). Such multiplexed, yet large-scale, neuronal network structures could represent a novel meta-structure organization for brain network communication. Further studies will be needed to show whether these structures are components of cognition.10.7554/eLife.06121.026Figure 7.Context as a sequence of interactions between network structures.


Cortical network architecture for context processing in primate brain.

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

Context as a sequence of interactions between network structures.(A) Coordination between network structures (S1 to S5, circles), under Rn (top) or Rf (bottom) responses. In both response contingencies, context perception (S1) encoded contextual information (S3). However, when the response stimulus contained high emotional valence (Rf, bottom), response perception (S2) reactivates the contextual information (S4), resulting in top-down modulation feedback (S5) that shares the same context and response dependence as the gazing behavior (black arrow and rounded rectangles). Green, blue, and red arrows represent correlations in context dependence in Rn, context dependence in Rf, and in response dependence, respectively (see Figure 6A). (B) Temporal, spectral, and spatial profiles and overlap in defined network structures. Network structures can be characterized by frequency range (labeled on the left) and connectivity pattern (shown on the right). Their temporal activations are plotted over trial time, with a ‘sound-like’ presentation, where a higher volume represents stronger activation. Black vertical lines represent the events as indicated in Figure 2.DOI:http://dx.doi.org/10.7554/eLife.06121.026
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Related In: Results  -  Collection

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fig7: Context as a sequence of interactions between network structures.(A) Coordination between network structures (S1 to S5, circles), under Rn (top) or Rf (bottom) responses. In both response contingencies, context perception (S1) encoded contextual information (S3). However, when the response stimulus contained high emotional valence (Rf, bottom), response perception (S2) reactivates the contextual information (S4), resulting in top-down modulation feedback (S5) that shares the same context and response dependence as the gazing behavior (black arrow and rounded rectangles). Green, blue, and red arrows represent correlations in context dependence in Rn, context dependence in Rf, and in response dependence, respectively (see Figure 6A). (B) Temporal, spectral, and spatial profiles and overlap in defined network structures. Network structures can be characterized by frequency range (labeled on the left) and connectivity pattern (shown on the right). Their temporal activations are plotted over trial time, with a ‘sound-like’ presentation, where a higher volume represents stronger activation. Black vertical lines represent the events as indicated in Figure 2.DOI:http://dx.doi.org/10.7554/eLife.06121.026
Mentions: These results suggest a basic structural organization of large-scale communication within brain networks that coordinate context processing, and provide insight into how apparently seamless cognition is constructed from these network communication modules. In contrast to previous studies where brain modularity is defined as a ‘community’ of spatial connections (Bullmore and Sporns, 2009; Sporns, 2011), or coherent oscillations among neuronal populations in overlapping frequency bands (Siegel et al., 2012), our findings provide an even more general yet finer grained definition of modularity based on not only anatomical and spectral properties, but also temporal, functional, and directional connectivity data. The relationships among network properties in the functional, temporal, spectral, and anatomical domains revealed network structures whose activity coordinated with each other in a deterministic manner (Figure 7A), despite being highly overlapping in time, frequency, and space (Figure 7B). Such multiplexed, yet large-scale, neuronal network structures could represent a novel meta-structure organization for brain network communication. Further studies will be needed to show whether these structures are components of cognition.10.7554/eLife.06121.026Figure 7.Context as a sequence of interactions between network structures.

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.


Related in: MedlinePlus