Mapping the structure-function relationship along macroscale gradients in the human brain.

Functional coactivation between human brain regions is partly explained by white matter connections; however, how the structure-function relationship varies by function remains unclear. Here, we reference large data repositories to compute maps of structure-function correspondence across hundreds of specific functions and brain regions. We use natural language processing to accurately predict structure-function correspondence for specific functions and to identify macroscale gradients across the brain that correlate with structure-function correspondence as well as cortical thickness.

Pathogenic variants in autism gene cause hydrocephalus and disrupt neuronal connectivity by impairing ciliary microtubule dynamics.

Enlargement of the cerebrospinal fluid (CSF)-filled brain ventricles (cerebral ventriculomegaly), the cardinal feature of congenital hydrocephalus (CH), is increasingly recognized among patients with autism spectrum disorders (ASD). a member of Katanin family microtubule-severing ATPases, is a known ASD risk gene, but its roles in human brain development remain unclear. Here, we show that nonsense truncation of () in mice results in classic ciliopathy phenotypes, including impaired spermatogenesis and cerebral ventriculomegaly.

Low-calorie diet-induced weight loss is associated with altered brain connectivity and food desire in obesity.

Objective: The main objective of this study is to better understand the effects of diet-induced weight loss on brain connectivity in response to changes in glucose levels in individuals with obesity.

Methods: A total of 25 individuals with obesity, among whom 9 had a diagnosis of type 2 diabetes, underwent functional magnetic resonance imaging (fMRI) scans before and after an 8-week low-calorie diet. We used a two-step hypereuglycemia clamp approach to mimic the changes in glucose levels observed in the postprandial period in combination with task-mediated fMRI intrinsic connectivity distribution (ICD) analysis.

Multimodal identification of the mouse brain using simultaneous Ca imaging and fMRI.

Individual differences in neuroimaging are of interest to clinical and cognitive neuroscientists based on their potential for guiding the personalized treatment of various heterogeneous neurological conditions and diseases. Despite many advantages, the workhorse in this arena, BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI) suffers from low spatiotemporal resolution and specificity as well as a propensity for noise and spurious signal corruption. To better understand individual differences in BOLD-fMRI data, we can use animal models where fMRI, alongside complementary but more invasive contrasts, can be accessed.