Clusters Of Brain Regions Research Articles

Longitudinal reduction in brain volume in patients with schizophrenia and its association with cognitive function.

Establishing a brain biomarker for schizophrenia is strongly desirable not only to support diagnosis by psychiatrists but also to help track the progressive changes in the brain over the course of the illness. A brain morphological signature of schizophrenia was reported in a recent study and is defined by clusters of brain regions with reduced volume in schizophrenia patients compared to healthy individuals. This signature was proven to be effective at differentiating patients with schizophrenia from healthy individuals, suggesting that it is a good candidate brain biomarker of schizophrenia. However, the longitudinal characteristics of this signature have remained unclear. In this study, we examined whether these changes occurred over time and whether they were associated with clinical outcomes. We found a significant change in the brain morphological signature in schizophrenia patients with more brain volume loss than the natural, age-related reduction in healthy individuals, suggesting that this change can capture a progressive morphological change in the brain. We further found a significant association between changes in the brain morphological signature and changes in the full-scale intelligence quotient (IQ). The patients with IQ improvement showed preserved brain morphological signatures, whereas the patients without IQ improvement showed progressive changes in the brain morphological signature, suggesting a link between potential recovery of intellectual abilities and the speed of brain pathology progression. We conclude that the brain morphological signature is a brain biomarker that can be used to evaluate progressive changes in the brain that are associated with cognitive impairment due to schizophrenia.

Transcutaneous auricular vagus nerve stimulation can modulate fronto-parietal brain networks.

Recent studies have shown that transcutaneous vagal nerve stimulation (tVNS) holds promise as a treatment for neurological or psychiatric disease through the ability to modulate neural activity in some brain regions without an invasive procedure. The objective of this study was to identify the neural correlates underlying the effects of tVNS. Twenty right-handed healthy subjects with normal hearing participated in this study. An auricle-applied tVNS device (Soricle, Neurive Co., Ltd., Gyeongsangnam-do, Republic of Korea) was used to administer tVNS stimulation. A session consisted of 14 blocks, including 7 blocks of tVNS stimulation or sham stimulation and 7 blocks of rest, and lasted approximately 7 min (1 block = 30 s). Functional magnetic resonance imaging (fMRI) was performed during the stimulation. No activated regions were observed in the fMRI scans following both sham stimulation and tVNS after the first session. After the second session, tVNS activated two clusters of brain regions in the right frontal gyrus. A comparison of the activated regions after the second session of each stimulation revealed that the fMRI following tVNS exhibited four surviving clusters. Additionally, four clusters were activated in the overall stimulated area during both the first and second sessions. When comparing the fMRI results after each type of stimulation, the fMRI following tVNS showed four surviving clusters compared to the fMRI after sham stimulation. tVNS could stimulate some brain regions, including the fronto-parietal network. Stimulating these regions for treating neurological or psychiatric disease might require applying tVNS for at least 3.5 min.

Dysregulation of Long Intergenic Non-Coding RNA Expression in the Schizophrenia Brain.

Transcriptomic studies of the brains of schizophrenia (SZ) patients have produced abundant but largely inconsistent findings about the disorders pathophysiology. These inconsistencies might stem not only from the heterogeneous nature of the disorder, but also from the unbalanced focus on particular cortical regions and protein-coding genes. Compared to protein-coding transcripts, long intergenic non-coding RNA (lincRNA) display substantially greater brain region and disease response specificity, positioning them as prospective indicators of SZ-associated alterations. Further, a growing understanding of the systemic character of the disorder calls for a more systematic screening involving multiple diverse brain regions. We aimed to identify and interpret alterations of the lincRNA expression profiles in SZ by examining the transcriptomes of 35 brain regions. We measured the transcriptome of 35 brain regions dissected from eight adult brain specimens, four SZ patients, and four healthy controls, using high-throughput RNA sequencing. Analysis of these data yielded 861 annotated human lincRNAs passing the detection threshold. Of the 861 detected lincRNA, 135 showed significant region-dependent expression alterations in SZ (two-way ANOVA, BH-adjusted p 0.05) and 37 additionally showed significant differential expression between HC and SZ individuals in at least one region (post hoc Tukey test, p 0.05). For these 37 differentially expressed lincRNAs (DELs), 88% of the differences occurred in a cluster of brain regions containing axon-rich brain regions and cerebellum. Functional annotation of the DEL targets further revealed stark enrichment in neurons and synaptic transmission terms and pathways. Our study highlights the utility of a systematic brain transcriptome analysis relying on the expression profiles measured across multiple brain regions and singles out white matter regions as a prospective target for further SZ research.

A naturalistic approach to studying temporal processing during music performance

In recent years, the push to embrace naturalistic stimuli over artificial designs has enriched what we know about the neural underpinnings of human attention, memory, and communication in real life. Previous work using natural stories scrambled (at the word, sentence, and paragraph level) has revealed a hierarchy of brain regions that organize natural acoustic input at these different timescales. While this approach has advanced our understanding of language processing, many fewer studies to date have explored the neural underpinnings of music perception, let alone music production, in naturalistic settings. In our novel paradigm, we asked expert pianists to play musical pieces, scrambled at different timescales (measure, phrase, section) on a non-ferromagnetic piano keyboard inside the fMRI scanner. This dataset provides unprecedented access to expert musicians’ brains starting from their first exposure to a novel piece and continuing over the course of learning to play it. We found distinct patterns of tuning to musical timescales across several clusters of brain regions (e.g., sensory/motor, parietal, and frontal/memory). We also found that musical predictability impacts functional connectivity between auditory, motor, and higher-order regions during performance. Finally, we applied several machine learning analyses to understand how the brain dynamically represents acoustic and musical features.

A Single Intraperitoneal Injection of Endotoxin Changes Glial Cells in Rats as Revealed by Positron Emission Tomography Using [11C]PK11195.

Intracranial administration of lipopolysaccharide (LPS) is known to elicit a rapid innate immune response, activate glial cells in the brain, and induce depression-like behavior. However, no study has focused on the changes in glial cells induced by intraperitoneal injection of LPS in vivo. Ten adult male Fischer F344 rats underwent [11C]PK11195 PET before and 2days after intraperitoneal injection of LPS to evaluate the changes in glial cells. The difference in standardized uptake values (SUV) of [11C]PK11195 between before and after injection was determined. There was a cluster of brain regions that showed significant reductions in SUV. This cluster included the bilateral striata and bilateral frontal regions, especially the somatosensory areas. Changes in activity of glial cells induced by the intraperitoneal injection of LPS were detected in vivo by [11C]PK11195 PET. Intraperitoneal injection of LPS is known to induce depression, and further studies with [11C]PK11195 PET would clarify the relationships between neuroinflammation and depression.

A receptor-based analysis of local ecosystems in the human brain

BackgroundAs a complex system, the brain is a self-organizing entity that depends on local interactions among cells. Its regions (anatomically defined nuclei and areas) can be conceptualized as cellular ecosystems, but the similarity of their functional profiles is poorly understood. The study used the Allen Human Brain Atlas to classify 169 brain regions into hierarchically-organized environments based on their expression of 100 G protein-coupled neurotransmitter receptors, with no a priori reference to the regions’ positions in the brain’s anatomy or function. The analysis was based on hierarchical clustering, and multiscale bootstrap resampling was used to estimate the reliability of detected clusters.ResultsThe study presents the first unbiased, hierarchical tree of functional environments in the human brain. The similarity of brain regions was strongly influenced by their anatomical proximity, even when they belonged to different functional systems. Generally, spatial vicinity trumped long-range projections or network connectivity. The main cluster of brain regions excluded the dentate gyrus of the hippocampus. The nuclei of the amygdala formed a cluster irrespective of their striatal or pallial origin. In its receptor profile, the hypothalamus was more closely associated with the midbrain than with the thalamus. The cerebellar cortical areas formed a tight and exclusive cluster. Most of the neocortical areas (with the exception of some occipital areas) clustered in a large, statistically well supported group that included no other brain regions.ConclusionsThis study adds a new dimension to the established classifications of brain divisions. In a single framework, they are reconsidered at multiple scales—from individual nuclei and areas to their groups to the entire brain. The analysis provides support for predictive models of brain self-organization and adaptation.

Frequency based mutual information measures between clusters of brain regions in functional magnetic resonance imaging

Mutual information tools have been recently applied to quantify the connectivity between brain regions in functional magnetic resonance imaging (fMRI). Here we develop measures of mutual information between clusters of brain regions in the frequency domain. The properties and limitations of the method are exemplified through a single resting state fMRI dataset, and with a comparison involving frontostriatal connections in schizophrenic patients and healthy controls.