Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness.

Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.

Mapping the Unconscious Brain: Insights From Advanced Neuroimaging.

SUMMARY: Recent advances in neuroimaging have been a preeminent factor in the scientific effort to unravel mechanisms of conscious awareness and the pathophysiology of disorders of consciousness. In the first part of this review, we selectively discuss operational models of consciousness, the biophysical signal that is measured using different imaging modalities, and knowledge on disorders of consciousness that has been gleaned with each neuroimaging modality. Techniques considered include diffusion-weighted imaging, diffusion tensor imaging, different types of nuclear medicine imaging, functional MRI, magnetoencephalography, and the combined transcranial magnetic stimulation-electroencephalography approach. In the second part of this article, we provide an overview of how advanced neuroimaging can be leveraged to support neurological prognostication, the use of machine learning to process high-dimensional imaging data, potential applications in clinical practice, and future directions.

Perfusion Imaging Predicts Favorable Outcomes after Basilar Artery Thrombectomy.

OBJECTIVE: Perfusion imaging identifies anterior circulation stroke patients who respond favorably to endovascular thrombectomy (ET), but its role in basilar artery occlusion (BAO) is unknown. We hypothesized that BAO patients with limited regions of severe hypoperfusion (time to reach maximum concentration in seconds [Tmax] > 10) would have a favorable response to ET compared to patients with more extensive regions involved. METHODS: We performed a multicenter retrospective cohort study of BAO patients with perfusion imaging prior to ET. We prespecified a Critical Area Perfusion Score (CAPS; 0-6 points), which quantified severe hypoperfusion (Tmax > 10) in cerebellum (1 point/hemisphere), pons (2 points), and midbrain and/or thalamus (2 points). Patients were dichotomized into favorable (CAPS ≤ 3) and unfavorable (CAPS > 3) groups. The primary outcome was a favorable functional outcome 90 days after ET (modified Rankin Scale = 0-3). RESULTS: One hundred three patients were included. CAPS ≤ 3 patients (87%) had a lower median National Institutes of Health Stroke Scale score (NIHSS; 12.5, interquartile range [IQR] = 7-22) compared to CAPS > 3 patients (13%; 23, IQR = 19-36; p = 0.01). Reperfusion was achieved in 84% of all patients, with no difference between CAPS groups (p = 0.42). Sixty-four percent of reperfused CAPS ≤ 3 patients had a favorable outcome compared to 8% of nonreperfused CAPS ≤ 3 patients (odds ratio [OR] = 21.0, 95% confidence interval [CI] = 2.6-170; p < 0.001). No CAPS > 3 patients had a favorable outcome, regardless of reperfusion. In a multivariate regression analysis, CAPS ≤ 3 was a robust independent predictor of favorable outcome after adjustment for reperfusion, age, and pre-ET NIHSS (OR = 39.25, 95% CI = 1.34->999, p = 0.04). INTERPRETATION: BAO patients with limited regions of severe hypoperfusion had a favorable response to reperfusion following ET. However, patients with more extensive regions of hypoperfusion in critical brain regions did not benefit from endovascular reperfusion. ANN NEUROL 2022;91:23-32.

Central neurogenetic signatures of the visuomotor integration system.

Visuomotor impairments characterize numerous neurological disorders and neurogenetic syndromes, such as autism spectrum disorder (ASD) and Dravet, Fragile X, Prader-Willi, Turner, and Williams syndromes. Despite recent advances in systems neuroscience, the biological basis underlying visuomotor functional impairments associated with these clinical conditions is poorly understood. In this study, we used neuroimaging connectomic approaches to map the visuomotor integration (VMI) system in the human brain and investigated the topology approximation of the VMI network to the Allen Human Brain Atlas, a whole-brain transcriptome-wide atlas of cortical genetic expression. We found the genetic expression of four genes-TBR1, SCN1A, MAGEL2, and CACNB4-to be prominently associated with visuomotor integrators in the human cortex. TBR1 gene transcripts, an ASD gene whose expression is related to neural development of the cortex and the hippocampus, showed a central spatial allocation within the VMI system. Our findings delineate gene expression traits underlying the VMI system in the human cortex, where specific genes, such as TBR1, are likely to play a central role in its neuronal organization, as well as on specific phenotypes of neurogenetic syndromes.

Quantifying the Effects of 16p11.2 Copy Number Variants on Brain Structure: A Multisite Genetic-First Study.

BACKGROUND: 16p11.2 breakpoint 4 to 5 copy number variants (CNVs) increase the risk for developing autism spectrum disorder, schizophrenia, and language and cognitive impairment. In this multisite study, we aimed to quantify the effect of 16p11.2 CNVs on brain structure. METHODS: Using voxel- and surface-based brain morphometric methods, we analyzed structural magnetic resonance imaging collected at seven sites from 78 individuals with a deletion, 71 individuals with a duplication, and 212 individuals without a CNV. RESULTS: Beyond the 16p11.2-related mirror effect on global brain morphometry, we observe regional mirror differences in the insula (deletion > control > duplication). Other regions are preferentially affected by either the deletion or the duplication: the calcarine cortex and transverse temporal gyrus (deletion > control; Cohen's d > 1), the superior and middle temporal gyri (deletion < control; Cohen's d < -1), and the caudate and hippocampus (control > duplication; -0.5 > Cohen's d > -1). Measures of cognition, language, and social responsiveness and the presence of psychiatric diagnoses do not influence these results. CONCLUSIONS: The global and regional effects on brain morphometry due to 16p11.2 CNVs generalize across site, computational method, age, and sex. Effect sizes on neuroimaging and cognitive traits are comparable. Findings partially overlap with results of meta-analyses performed across psychiatric disorders. However, the lack of correlation between morphometric and clinical measures suggests that CNV-associated brain changes contribute to clinical manifestations but require additional factors for the development of the disorder. These findings highlight the power of genetic risk factors as a complement to studying groups defined by behavioral criteria.

Opposing brain differences in 16p11.2 deletion and duplication carriers.

Deletions and duplications of the recurrent ~600 kb chromosomal BP4-BP5 region of 16p11.2 are associated with a broad variety of neurodevelopmental outcomes including autism spectrum disorder. A clue to the pathogenesis of the copy number variant (CNV)'s effect on the brain is that the deletion is associated with a head size increase, whereas the duplication is associated with a decrease. Here we analyzed brain structure in a clinically ascertained group of human deletion (N = 25) and duplication (N = 17) carriers from the Simons Variation in Individuals Project compared with age-matched controls (N = 29 and 33, respectively). Multiple brain measures showed increased size in deletion carriers and reduced size in duplication carriers. The effects spanned global measures of intracranial volume, brain size, compartmental measures of gray matter and white matter, subcortical structures, and the cerebellum. Quantitatively, the largest effect was on the thalamus, but the collective results suggest a pervasive rather than a selective effect on the brain. Detailed analysis of cortical gray matter revealed that cortical surface area displays a strong dose-dependent effect of CNV (deletion > control > duplication), whereas average cortical thickness is less affected. These results suggest that the CNV may exert its opposing influences through mechanisms that influence early stages of embryonic brain development.