Mapping brain-behavior space relationships along the psychosis spectrum

Abstract

Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 PSD patients spanning several diagnoses, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results with current sample sizes. However, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and neural gene expression maps derived from the Allen Human Brain Atlas. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.

Classic Psychedelic Drugs: Update on Biological Mechanisms

“…Notably, a recent whole-brain model using the dynamical mean-field quantitative description of excitatory and inhibitory neuronal populations as well as the associated synaptic gain function suggests that the effect of LSD on global brain connectivity can be best explained by the regional distribution and density of 5-HT2A receptors located on cortical pyramidal neurons [174]. A similar approach employing a transcriptomics-informed large-scale cortical model, including the expression level of various serotonergic and dopaminergic genes also found that modulation of pyramidal cell gain by 5-HT2A receptor activation accurately captures the LSDinduced GBC changes [119,144,145]. In addition, fitting to GBC in individual subjects revealed that the model also captures patterns of individual differences in LSD response that predict different aspects of the psychedelic experience [144].…”

Using dimensionality-reduction techniques to understand the organization of psychotic symptoms in persistent psychotic illness and first episode psychosis

“…Our data-driven approaches suggest instead studying symptoms which are statistically rather than conceptually related. In fact, recent neuroimaging research has shown that PCA components of symptom scales were superior for identifying robust correlates of brain connectivity compared to traditional scale sub-scores 28 .…”

From Neurotransmitters to Networks: Transcending Organisational Hierarchies with Molecular-informed Functional Imaging

“…Ji and colleagues took an alternative approach and examined a heterogeneous cohort of patients with psychosisspectrum disorders (PSD) with the aim of mapping cognition and psychopathology to imaging data trans-nosologically (Ji et al, 2021). In their initial analyses, they found that the clinical measures could be distilled down to five key components using principal components analysis and that these demonstrated substantially stronger relationships to global brain connectivity (GCB; a measure of FC) than the conventional psychometric measures.…”