Peter A. Robinson

Geometric constraints on the architecture of mammalian cortical connectomes

This paper develops a geometric model of cortical connectomes that outperforms existing approaches in reproducing topological and topographical properties across multiple species.

Cortical geometry constrains the unimodal anchors of sensory integration

The paper tests if cortical geometry encodes sensory function by modeling multisensory integration from geometric eigenmodes, finding they align with sensory domains but require additional modes for full hierarchy.

Geometry-Constrained Coupling Drives Critical Dynamics Across Neural Manifolds

This paper introduces a framework for geometry-constrained coupling between neural manifolds, showing how inter-manifold interactions reorganize dynamics and produce critical transitions in brain activity.

Personalized stimulation therapies for disorders of consciousness: A computational approach to inducing healthy-like brain activity based on neural field theory

This paper introduces a computational method to generate personalized brain stimulation signals for disorders of consciousness, showing in silico that it can induce healthy-like EEG power spectra.

Geometric influences on the regional organization of the mammalian brain

This paper develops a geometrically constrained framework to map brain regions across species and shows geometry influences regional organization through patterning molecules.

Generation of surrogate brain maps preserving spatial autocorrelation through random rotation of geometric eigenmodes

This paper introduces eigenstrapping, a method to generate surrogate brain maps that preserve spatial autocorrelation while breaking map correlations, improving false positive control in brain map analysis.

Reply to: Eigenmodes of the brain: revisiting connectomics and geometry

The paper responds to criticisms of a previous study showing that geometric eigenmodes of the human cortex better reconstruct fMRI activity maps than connectome-derived eigenmodes.

Reply to: Commentary on Pang et al. (2023) Nature

The paper addresses concerns about eigenmode reconstructions in a previous study, demonstrating how specificity is achieved through appropriate benchmarks.

Effects of Parcellation and Threshold on Brain Connectivity Measures

This paper shows that brain connectivity measures depend on parcellation and thresholding, and can be modeled using a distance-based physical connectivity model.