Neural processes for intentional control of perceptual switching: a magnetoencephalography study

Efficient communication dynamics on macro-connectome, and the propagation speed

Global communication dynamics in the brain can be captured using fMRI, MEG, or electrocorticography (ECoG), and the global slow dynamics often represent anatomical constraints. Complementary single-/multi-unit recordings have described local fast temporal dynamics. However, global fast temporal dynamics remain incompletely understood with considering of anatomical constraints. Therefore, we compared temporal aspects of cross-area propagations of single-unit recordings and ECoG, and investigated their anatomical bases. First, we demonstrated how both evoked and spontaneous ECoGs can accurately predict latencies of single-unit recordings. Next, we estimated the propagation velocity (1.0–1.5 m/s) from brain-wide data and found that it was fairly stable among different conscious levels. We also found that the shortest paths in anatomical topology strongly predicted the latencies. Finally, we demonstrated that Communicability, a novel graph-theoretic measure, is able to quantify that more than 90% of paths should use shortest paths and the remaining are non-shortest walks. These results revealed that macro-connectome is efficiently wired for detailed communication dynamics in the brain.

Functional Clusters, Hubs, and Communities in the Cortical Microconnectome

Although relationships between networks of different scales have been observed in macroscopic brain studies, relationships between structures of different scales in networks of neurons are unknown. To address this, we recorded from up to 500 neurons simultaneously from slice cultures of rodent somatosensory cortex. We then measured directed effective networks with transfer entropy, previously validated in simulated cortical networks. These effective networks enabled us to evaluate distinctive nonrandom structures of connectivity at 2 different scales. We have 4 main findings. First, at the scale of 3-6 neurons (clusters), we found that high numbers of connections occurred significantly more often than expected by chance. Second, the distribution of the number of connections per neuron (degree distribution) had a long tail, indicating that the network contained distinctively high-degree neurons, or hubs. Third, at the scale of tens to hundreds of neurons, we typically found 2-3 significantly large communities. Finally, we demonstrated that communities were relatively more robust than clusters against shuffling of connections. We conclude the microconnectome of the cortex has specific organization at different scales, as revealed by differences in robustness. We suggest that this information will help us to understand how the microconnectome is robust against damage.

Global mapping of the whole-brain network underlining binocular rivalry

We investigated how the structure of the brain network relates to the stability of perceptual alternation in binocular rivalry. Historically, binocular rivalry has provided important new insights to our understandings in neuroscience. Although various relationships between the local regions of the human brain structure and perceptual switching phenomena have been shown in previous researches, the global organization of the human brain structural network relating to this phenomenon has not yet been addressed. To approach this issue, we reconstructed fiber-tract bundles using diffusion tensor imaging and then evaluated the correlations between the speeds of perceptual alternation and fractional anisotropy (FA) values in each fiber-tract bundle integrating among 84 brain regions. The resulting comparison revealed that the distribution of the global organization of the structural brain network showed positive or negative correlations between the speeds of perceptual alternation and the FA values. First, the connections between the subcortical regions stably were negatively correlated. Second, the connections between the cortical regions mainly showed positive correlations. Third, almost all other cortical connections that showed negative correlations were located in one central cluster of the subcortical connections. This contrast between the contribution of the cortical regions to destabilization and the contribution of the subcortical regions to stabilization of perceptual alternation provides important information as to how the global architecture of the brain structural network supports the phenomenon of binocular rivalry.

Predictive Context Influences Perceptual Selection during Binocular Rivalry

Prediction may be a fundamental principle of sensory processing: it has been proposed that the brain continuously generates predictions about forthcoming sensory information. However, little is known about how prediction contributes to the selection of a conscious percept from among competing alternatives. Here, we used binocular rivalry to investigate the effects of prediction on perceptual selection. In binocular rivalry, incompatible images presented to the two eyes result in a perceptual alternation between the images, even though the visual stimuli remain constant. If predictive signals influence the competition between neural representations of rivalrous images, this influence should generate a bias in perceptual selection that depends on predictive context. To manipulate predictive context, we developed a novel binocular rivalry paradigm in which rivalrous test images were immediately preceded by a sequence of context images presented identically to the two eyes. One of the test images was consistent with the preceding image sequence (it was the expected next image in the series), and the other was inconsistent (non-predicted). We found that human observers were more likely to perceive the consistent image at the onset of rivalry, suggesting that predictive context biased selection in favor of the predicted percept. This prediction effect was distinct from the effects of adaptation to stimuli presented before the binocular rivalry test. In addition, perceptual reports were speeded for predicted percepts relative to non-predicted percepts. These results suggest that predictive signals related to visual stimulus history exist at neural sites that can bias conscious perception during binocular rivalry. Our paradigm provides a new way to study how prior information and incoming sensory information combine to generate visual percepts.