Dynamical consequences of regional heterogeneity in the brain’s transcriptional landscape

Brain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles or MRI-derived estimates of myeloarchitecture. We further show that regional transcriptional heterogeneity is essential for yielding both ignition-like dynamics, which are thought to support conscious processing, and a wide variance of regional-activity time scales, which supports a broad dynamical range. We thus identify a key role for E:I heterogeneity in generating complex neuronal dynamics and demonstrate the viability of using transcriptomic data to constrain models of large-scale brain function

Clinically feasible brain morphometric similarity network construction approaches with restricted magnetic resonance imaging acquisitions

Morphometric similarity networks (MSNs) estimate organization of the cortex as a biologically meaningful set of similarities between anatomical features at the macro-and microstructural level, derived from multiple structural MRI (sMRI) sequences. These networks are clinically relevant, predicting 40% variance in IQ. However, the sequences required (T1w, T2w, DWI) to produce these networks are longer acquisitions, less feasible in some populations. Thus, estimating MSNs using features from T1w sMRI is attractive to clinical and developmental neuroscience. We studied whether reduced-feature approaches approximate the original MSN model as a potential tool to investigate brain structure. In a large, homogenous dataset of healthy young adults (from the Human Connectome Project, HCP), we extended previous investigations of reduced-feature MSNs by comparing not only T1w-derived networks, but also additional MSNs generated with fewer MR sequences, to their full acquisition counterparts. We produce MSNs that are highly similar at the edge level to those generated with multimodal imaging; however, the nodal topology of the networks differed. These networks had limited predictive validity of generalized cognitive ability. Overall, when multimodal imaging is not available or appropriate, T1w-restricted MSN construction is feasible, provides an appropriate estimate of the MSN, and could be a useful approach to examine outcomes in future studies

Adolescent self-control predicts midlife hallucinatory experiences:40-year follow-up of a national birth cohort

Associations between self-control in adolescence and adult mental health are unclear in the general population; to our knowledge, no study has investigated self-control in relation to psychotic-like symptoms

Interactive computation and visualization of structural connectomes in real-time

Structural networks contain high dimensional data that raise huge computational and visualization problems, especially when attempting to characterise them using graph theory. As a result, it can be non-intuitive to grasp the contribution of each edge within a graph, both at a local and global scale. Here, we introduce a new platform that enables tractography-based networks to be explored in a highly interactive real-time fashion. The framework allows one to interactively tune graph-related parameters on the fly, as opposed to conventional visualization softwares that rely on pre-computed connectivity matrices. From a neurosurgical perspective, the method also provides enhanced understanding regarding the potential removal of a specific node or transection of an edge from the network, allowing surgeons and clinicians to discern the value of each node

Temporal perception deficits in schizophrenia: integration is the problem, not deployment of attentions

Patients with schizophrenia are known to have impairments in sensory processing. In order to understand the specific temporal perception deficits of schizophrenia, we investigated and determined to what extent impairments in temporal integration can be dissociated from attention deployment using Attentional Blink (AB). Our findings showed that there was no evident deficit in the deployment of attention in patients with schizophrenia. However, patients showed an increased temporal integration deficit within a hundred-millisecond timescale. The degree of such integration dysfunction was correlated with the clinical manifestations of schizophrenia. There was no difference between individuals with/without schizotypal personality disorder in temporal integration. Differently from previous studies using the AB, we did not find a significant impairment in deployment of attention in schizophrenia. Instead, we used both theoretical and empirical approaches to show that previous findings (using the suppression ratio to correct for the baseline difference) produced a systematic exaggeration of the attention deficits. Instead, we modulated the perceptual difficulty of the task to bring the baseline levels of target detection between the groups into closer alignment. We found that the integration dysfunction rather than deployment of attention is clinically relevant, and thus should be an additional focus of research in schizophrenia

Changes in the Frontotemporal Cortex and Cognitive Correlates in First-Episode Psychosis

Background: Loss of cortical volume in frontotemporal regions has been reported in patients with schizophrenia and their relatives. Cortical area and thickness are determined by different genetic processes, and measuring these parameters separately may clarify disturbances in corticogenesis relevant to schizophrenia. Our study also explored clinical and cognitive correlates of these parameters.Methods: Thirty-seven patients with first-episode psychosis (34 schizophrenia, 3 schizoaffective disorder) and 38 healthy control subjects matched for age and sex took part in the study. Imaging was performed on an magnetic resonance imaging 1.5-T scanner. Area and thickness of the frontotemporal cortex were measured using a surface-based morphometry method (Freesurfer). All subjects underwent neuropsychologic testing that included measures of premorbid and current IQ, working and verbal memory, and executive function.Results: Reductions in cortical area, more marked in the temporal cortex, were present in patients. Overall frontotemporal cortical thickness did not differ between groups, although regional thinning of the right superior temporal region was observed in patients. There was a significant association of both premorbid IQ and IQ at disease onset with area, but not thickness, of the frontotemporal cortex, and working memory span was associated with area of the frontal cortex. These associations remained significant when only patients with schizophrenia were considered.Conclusions: Our results suggest an early disruption of corticogenesis in schizophrenia, although the effect of subsequent environmental factors cannot be excluded. In addition, cortical abnormalities are subject to regional variations and differ from those present in neurodegenerative diseases

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development

Personalized brain stimulation of memory networks

Available online 13 September 2022Background: The finding that transcranial magnetic stimulation (TMS) can enhance memory performance via stimulation of parietal sites within the Cortical-Hippocampal Network counts as one of the most exciting findings in this field in the past decade. However, the first independent effort aiming to fully replicate this finding found no discernible influence of TMS on memory performance. Objective: We examined whether this might relate to interindividual spatial variation in brain connectivity architecture, and the capacity of personalisation methodologies to overcome the noise inherent across independent scanners and cohorts. Methods: We implemented recently detailed personalisation methodology to retrospectively compute individual-specific parietal targets and then examined relation to TMS outcomes. Results: Closer proximity between actual and novel fMRI-personalized targets associated with greater improvement in memory performance. Conclusion: These findings demonstrate the potential importance of aligning brain stimulation targets according to individual-specific differences in brain connectivity, and extend upon recent findings in prefrontal cortex.Robin F.H. Cash, Joshua Hendrikse, Kavisha B Fernando, Sarah Thompson, Chao Suo, Alex Fornito, Murat Yücel, Nigel C. Rogasch, Andrew Zalesky, James P. Coxo

Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders

The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks