Transcriptomics-informed large-scale cortical model captures topography of pharmacological neuroimaging effects of LSD

Abstract

Psychoactive drugs can transiently perturb brain physiology while preserving brain structure. The role of physiological state in shaping neural function can therefore be investigated through neuroimaging of pharmacologically-induced effects. This paradigm has revealed that neural and experiential effects of lysergic acid diethylamide (LSD) are attributable to its agonist activity at the serotonin-2A receptor. Here, we integrate brainwide transcriptomics with biophysically-based large-scale circuit modeling to simulate acute neuromodulatory effects of LSD on human cortical dynamics. Our model captures the topographic effects of LSD-induced changes in cortical BOLD functional connectivity. These findings suggest that serotonin-2A-mediated modulation of pyramidal cell gain is the circuit mechanism through which LSD alters cortical functional topography. Individual-subject fitting reveals that the model captures patterns of individual neural differences in drug response that predict altered states of consciousness. This work establishes a framework for linking molecular-level manipulations to salient changes in brain function, with implications for precision medicine.

Classic Psychedelic Drugs: Update on Biological Mechanisms

“…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]. Thus, it appears that the integration of bio-physical modeling and empirical neuroimaging data provides a promising framework to further unravel circuit mechanisms through which psychedelics alter cortical functional topography.…”

“…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].…”

Prefrontal contributions to the stability and variability of thought and conscious experience

“…The REBUS model proposes a unifying account of how serotonergic psychedelic compounds affect conscious experience [32]. Serotonergic psychedelics are a specific class of psychoactive compounds including but not limited to lysergic acid diethylamide (LSD), psilocybin, and dimethyltryptamine (DMT), that principally act upon cortical serotonin 2A receptors [54][55][56][57][58][59][60][61][62][63][64] to achieve their profound psychological effects [32,65,66] and therapeutic potential [67][68][69][70][71][72]. Moving forward, we use the term psychedelics to refer to these serotonergic psychedelics.…”

Mapping Pharmacologically-induced Functional Reorganisation onto the Brain’s Neurotransmitter Landscape

“…Such hypotheses may be tested experimentally, but also in silico: whole-brain computational modelling is becoming increasingly prominent as a tool to investigate the causal mechanisms that drive brain activity and organisation in healthy and pathological conditions [171][172][173][174] Crucially, the more biologically-inspired models (e.g. dynamic mean-field) can also be enriched with further information, such as regional myelination 153 , or the regional distribution of specific receptors and ion channels obtained from PET or transcriptomics [70][71][72]175,176 , to reflect neurotransmitter influences. This approach may complement experimental manipulations, making it possible to systematically evaluate the causal effects of combinations of different neuromodulators on the brain's functional connectivity.…”