Biology subjects

Hosomi, K.

Publications and source records attributed to Hosomi, K..

4 recordsLinked to original sources

bioRxiv2025

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

Research on biomarkers for predicting psychiatric disorders from resting-state functional connectivity (FC) is advancing. While the focus has primarily been on the discriminative performance of biomarkers by machine learning, identification of abnormal FCs in psychiatric disorders has often been treated as a secondary goal. However, it is crucial to investigate the effect size and robustness of the selected FCs because they can be used as potential targets of neurofeedback training or transcranial magnetic stimulation therapy. Here, we incorporated approximately 5,000 runs of resting-state functional magnetic resonance imaging from six datasets, including individuals with three different psychiatric disorders (major depressive disorder [MDD], schizophrenia [SCZ], and autism spectrum disorder [ASD]). We demonstrated that an unsupervised feature-computation-based feature selection method can robustly extract FCs related to psychiatric disorders compared to other conventional supervised feature selection methods. We found that our proposed method robustly extracted FCs with larger effect sizes from the validation dataset compared to different types of feature selection methods based on supervised learning for MDD (Cohens d = 0.40 vs. 0.25), SCZ (0.37 vs. 0.28), and ASD (0.17 vs. 0.16). We found 78, 69, and 81 essential FCs for MDD, SCZ, and ASD, respectively, and these FCs were mainly thalamic and motor network FCs. The current study showed that the unsupervised feature-computation-based feature selection method robustly identified abnormal FCs in psychiatric disorders consistently across datasets. The discovery of such robust FCs will contribute to understanding neural mechanisms as abnormal brain signatures in psychiatric disorders. Furthermore, this finding can aid in developing precise therapeutic interventions, such as neurofeedback training or transcranial magnetic stimulation therapy.

neuroscience↗

bioRxiv2025

Transcranial electrical stimulation for memory enhancement: A systematic review and meta-analysis

BackgroundNon-invasive brain stimulation techniques have received increasing interest for their potential to enhance memory function, a fundamental cognitive aspect of daily life. MethodsThis systematic review and meta-analysis investigated the efficacy of transcranial electrical stimulation (tES) in enhancing memory function in healthy adults, following the pre-registered strategy at PROSPERO (CRD42022353630). ResultsA total of 66 articles (119 trials, 3,786 participants) focusing on transcranial direct current stimulation and transcranial alternating current stimulation were identified. Meta-analysis revealed a significant overall effect of tES on memory function compared with sham stimulation (standardized mean difference [95% confidence interval] = 0.19 [0.12-0.27]), with anodal transcranial direct current stimulation showing the most consistent enhancement. In particular, stimulation of the frontal regions effectively improved working and declarative memories. While the effects remained significant within hours post-stimulation, they diminished after one day or longer. Regarding adverse events, tingling and itching sensations on the scalp occurred more frequently in the active group than in the sham group, but no severe adverse events were reported. Challenges, including publication bias, heterogeneity, and bias toward specific aspects of memory were noted, emphasizing the need for improved experimental rigor and diversification of memory tasks. ConclusionThese findings highlight the potential of tES as a safe and effective tool for memory enhancement while emphasizing areas for future research to develop its applications.

neuroscience↗

bioRxiv2025

Cerebellum involvement in visuo-vestibular interaction for the perception of gravitational direction: a repetitive transcranial magnetic stimulation study

Accurate perception of the direction of gravity relies on the integration of multisensory information, particularly from the visual and vestibular systems, within the brain. Although a recent study of patients with cerebellar degeneration suggested a cerebellar role in visuo-vestibular interaction in the perception of gravitational direction, direct evidence remains limited. To address this gap, we conducted two experiments with 42 healthy participants to evaluate the impact of repetitive 1-Hz transcranial magnetic stimulation (rTMS) over the posterior cerebellum on visual dependency, quantified by the subjective visual vertical bias induced by rotating optokinetic stimulation (OKS). Electric field simulations in high-resolution head models were used to ensure focal stimulation of the cerebellum at the group level. The results demonstrated that repetitive transcranial magnetic stimulation (rTMS) applied to the cerebellar vermis significantly attenuated the OKS-induced shift in visual vertical (SVV) bias. This effect was not observed when stimulation was applied to the early visual cortex (V1-2) or the cerebellar hemisphere. Also, the vermis rTMS had no effect on the judgement precision in the absence of visual motion cues, suggesting that the rTMS may reduce visual weight in visuo-vestibular processing by increasing visual motion noise rather than affecting vestibular function. These findings suggest a direct involvement of the cerebellar vermis in the visuo-vestibular interaction underlying the perception of gravitational direction, providing new insights into cerebellar contributions in human spatial orientation. Significance StatementThe cerebellum has been implicated in multisensory integration for spatial orientation, but its direct role in visuo-vestibular interactions remains limited. Using 1-Hz rTMS, we demonstrated that stimulation of the cerebellar vermis significantly reduced visual dependency in the perception of gravitational direction, as measured by the subjective visual vertical bias induced by rotating optokinetic stimulation. This effect was absent when adjacent areas, such as early visual cortex and the cerebellar hemisphere, were stimulated. These results suggest that the cerebellar vermis is directly involved in visuo-vestibular interaction, providing new insights into the cerebellar contribution to spatial orientation in humans.

neuroscience↗

bioRxiv2024

Computational Mechanisms of Neuroimaging Biomarkers Uncovered by Multicenter Resting-State fMRI Connectivity Variation Profile

Resting-state functional connectivity (rsFC) is increasingly used to develop biomarkers for psychiatric disorders. Despite progress, development of the reliable and practical FC biomarker remains an unmet goal, particularly one that is clinically predictive at the individual level with generalizability, robustness, and accuracy. In this study, we propose a new approach to profile each connectivity from diverse perspective, encompassing not only disorder-related differences but also disorder-unrelated variations attributed to individual difference, within-subject across-runs, imaging protocol, and scanner factors. By leveraging over 1500 runs of 10-minute resting-state data from 84 traveling-subjects across 29 sites and 900 participants of the case-control study with three psychiatric disorders, the disorder-related and disorder-unrelated FC variations were estimated for each individual FC. Using the FC profile information, we evaluated the effects of the disorder-related and disorder-unrelated variations on the output of the multi-connectivity biomarker trained with ensemble sparse classifiers and generalizable to the multicenter data. Our analysis revealed hierarchical variations in individual functional connectivity, ranging from within-subject across-run variations, individual differences, disease effects, inter-scanner discrepancies, and protocol differences, which were drastically inverted by the sparse machine-learning algorithm. We found this inversion mainly attributed to suppression of both individual difference and within-subject across-runs variations relative to the disorder-related difference by weighted-averaging of the selected FCs and ensemble computing. This comprehensive approach will provide an analytical tool to delineate future directions for developing reliable individual-level biomarkers.

neuroscience↗