Multiple sensitivity profiles to diversity and transition structure in non-stationary
input.
Abstract:
Recent formalizations suggest that the human brain codes for the degree of order in the
environment and utilizes this knowledge to optimize perception and performance in the
immediate future. However, the neural bases of how the brain spontaneously codes for order are
poorly understood. It has been shown that activity in lateral temporal cortex and the
hippocampus is linearly correlated with the order of short visual series under tasks requiring
attention to the input and when series order is invariant over time. Here, we examined if
sensitivity to order is manifested in both linear and non-linear BOLD response profiles,
quantified the degree to which order-sensitive regions operate as a functional network, and
evaluated these questions using a paradigm in which performance of the ongoing task could be
completed without any attention to the stimulus whose order was manipulated. Participants
listened to a 10-minute sequence of tones characterized by non-stationary order, and fMRI
identified cortical regions sensitive to time-varying statistical features of this input. Activity in
perisylvian regions was negatively correlated with input diversity, quantified via Shannon’s
Entropy. Activity in ventral premotor, lateral temporal, and insular regions was correlated
linearly, parabolically, or via a step-function with the strength of transition constraints in the
series, quantified via Markov Entropy. Granger-Causality analysis revealed that order-sensitive
regions form a functional network, with regions showing non-linear responses to order
associated with more afferent connectivity than those showing linear responses. These findings
identify networks that spontaneously code and respond to diverse aspects of order via multiple
response profiles, and that play a central role in generating and gating predictive neural activity.