AUTHOR=Bhatt Dhruval , Kopchick John , Abel Clifford , Thomas Patricia , Rajan Usha , Khatib Dalal , Zajac-Benitez Caroline , Haddad Luay , Amirsadri Alireza , Stanley Jeffrey A. , Diwadkar Vaibhav A. 

TITLE=Monotonicity in graph theoretic summaries of fMRI data acquired during human learning

JOURNAL=Frontiers in Human Neuroscience

VOLUME=Volume 19 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2025.1595331

DOI=10.3389/fnhum.2025.1595331

ISSN=1662-5161

ABSTRACT=IntroductionBehavioral performance during associative learning typically improves monotonically; performance on each successive iteration of the task is no worse (and typically better) than on the previous one. It is unclear whether connectomic measures of brain function (from fMRI data acquired during learning) also increase monotonically. We used a well-established associative learning paradigm to test for the possible co-observance of monotonicity in behavior and connectomics.MethodsfMRI data were summarized using two distinct connectomic (i.e., graph theoretic) measures: (a) Betweenness Centrality (of nodes) and (b) Average Shortest Path Length (i.e., a measure of network efficiency) across the graph. To broaden our study’s breath, in addition to healthy controls (n = 39), we extended the analyses to data collected in schizophrenia patients (n = 49). Past studies show that although patients show deficits in learning (lower learning capacity), behavior does typically display monotonicity.ResultsWe observed robust evidence for monotonic changes in behavior at the group level, and in most participants regardless of group. Evidence for monotonic changes in graph theoretic summaries of the co-acquired fMRI data was less widespread and was in general, more evident in group level summaries (regardless of group).DiscussionThis modest co-observance of monotonicity in behavior and fMRI-based connectomics re-emphasizes what has long been suspected: the relationship between overt measures of behavioral competence and the co-acquired imaging signals is complex. This may be because psychological events (whether in the healthy brain, or in clinical populations like schizophrenia) emerge not from local activity in circumscribed brain regions, but rather from widely distributed activity across the brain. While well-defined mathematical concepts like monotonicity can anchor attempts to co-observe properties of change in overt behavior, and underlying brain signals, we suggest that the search for such relationships will remain a challenge.