Isaac Z. Pope

Growing evidence indicates that macroscopic cortical activity is dominated by propagating waves of excitation. However, many computational models of such wave dynamics assume that the cortex is a spatially homogeneous medium, ignoring the rich regional variations in cellular, molecular, and physiological properties that are known to shape how brain activity evolves through both space and time. Here, we develop a general framework grounded in neural field theory to model how regional heterogeneities in diverse cortical properties shape spatiotemporal brain activity evolving on cortical surface meshes. This enables high resolution, vertex-level simulations without requiring predefined parcellations. The model requires only a standard mesh model of the cortical manifold and a spatial heterogeneity map, providing a biologically grounded and computationally efficient framework that can be generalised to human and non-human species. Using multiple cellular, molecular, and physiological maps in humans—and analogous maps in macaques and marmosets—we show that our model can consistently recapitulate known relationships between regional heterogeneities and variations in cortical wave speed. In particular, we find that models parameterised by heterogeneities in intracortical myelin and excitation-inhibition balance yield the largest performance improvements relative to spatially homogeneous models. Our results identify a key role for regional variations in myelin, receptor, and genetic architecture in shaping the spatial patterning of macroscale cortex-wide activity that is conserved across primate species with diverse cortical geometries.

Background Clinical outcomesfollowing a first episode of psychosis (FEP) are highly heterogeneous between patients. The identification of prognostic biomarkers would greatly facilitate personalized treatments. Psychosis patients often display brain-wide disruptions of inter-regional functional coupling (FC), with some being linked to symptom severity and remission. FC may thus hold prognostic potential for people experiencing psychosis. Methods Ninety antipsychotic-naïve FEP patients (51% female, 15-25 years) were randomized to receive either antipsychotic or placebo tablets for 6 months alongside psychosocial interventions. A subset of these patients also completed functional magnetic resonance imaging (55 with usable data at baseline and 37 at 3 months), which was used to evaluate whether baseline FC, or 3-month change in FC, could predict 6- and 12-month changes in symptoms and functioning, quantified using the Brief Psychiatric Rating Scale and the Social and Occupational Functioning Assessment Scale, respectively. We considered three different cross-validated prediction algorithms: (i) connectome-based predictive modelling; (ii) kernel ridge regression; and (iii) multilayer meta-matching. Results All algorithms showed poor performance in predicting patients’ 6- and 12-month changes in symptoms and functioning (all r_mean < 0.3), and no model achieved significance via permutation testing (all p > 0.05). Conclusions Our findings suggest that brain-wide measures of FC may not be suitable for predicting extended clinical outcomes over a 6- to 12-month period in FEP patients.