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Ray, K. L.

Publications and source records attributed to Ray, K. L..

3 recordsLinked to original sources

Human white matter tracts aligned with canonical functional brain networks

White matter tracts form the structural backbone of large-scale brain networks, yet their relation to functional organization remains poorly defined. Although major pathways are well characterized anatomically, their relationship to distributed cognitive systems has not been systematically established. Here, we constructed a population-level white matter tract termination atlas and projected tract endpoints onto the cortical surface to characterize their spatial organization. We integrated this atlas with large-scale meta-analytic decoding to derive functional profiles for individual tracts. Functional decoding revealed that white matter tracts exhibited distinct and biologically interpretable cognitive signatures. Hierarchical clustering of these profiles further showed that tracts organize into coherent ensembles defined by shared functional associations. These tract ensembles recapitulated canonical intrinsic brain networks across multiple cortical atlases, including a notable ensemble that demonstrated alignment with the default mode, salience, and frontoparietal control networks, corresponding to the core architecture of the triple-network model of cognitive control. This finding identified a candidate structural backbone linking distributed functional systems implicated across neuropsychiatric conditions. Together, these results demonstrate that white matter architecture is organized according to large-scale functional principles and establish a tract-to-network framework for linking structural connectivity to cognition.

neuroscience↗

Meta-analytic decoding of the cortical gradient of functional connectivity

Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.

neuroscience↗

Meta-analytic connectivity modelling of deception-related brain regions

Brain-based deception research began only two decades ago and has since included a wide variety of contexts and response modalities for deception paradigms. Investigations of this sort serve to better our neuroscientific and legal knowledge of the ways in which individuals deceive others. To this end, we conducted activation likelihood estimation (ALE) and meta-analytic connectivity modelling (MACM) using BrainMap software to examine 45 task-based fMRI brain activation studies on deception. An activation likelihood estimation comparing activations during deceptive versus honest behavior revealed 7 significant peak activation clusters (bilateral insula, left superior frontal gyrus, bilateral supramarginal gyrus, and bilateral medial frontal gyrus). Meta-analytic connectivity modelling revealed an interconnected network amongst the 7 regions comprising both unidirectional and bidirectional connections. Together with subsequent behavioral and paradigm decoding, these findings implicate the supramarginal gyrus as a key component for the sociocognitive process of deception.

neuroscience↗