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Hanakawa, T.

Publications and source records attributed to Hanakawa, T..

13 recordsLinked to original sources

Serial dependence in haptic perception during active manual exploration.

Serial dependence, whereby current perception is systematically biased toward the most recent sensory experience, has been demonstrated across multiple sensory modalities. However, whether serial dependence occurs during active haptic perception remains unknown. Moreover, because haptic perception of object geometry depends on hand movements for sensory acquisition (i.e., active touch), it remains unclear whether serial dependence, if any, originates from perceptual processing, movement, or both. Here, we investigated whether active haptic perception exhibits attractive serial dependence using a newly developed haptic device that let participants explore virtual slopes of different heights. Participants reported perceived slope heights, and we recorded their kinematics. Perceptual judgments were systematically attracted toward the most recently experienced slope, demonstrating serial dependence during active haptic perception. By contrast, none of the kinematic parameters exhibited corresponding serial dependence. These findings show that serial dependence extends to the somatosensory perceptual domain and suggest that the observed perceptual bias was not mediated by systematic changes in hand movements.

neuroscience↗

Subsecond whole-brain neural dynamics identified by hidden Markov modeling reflect value-based decision making in humans

Value-based decision making emerges from coordinated neural dynamics across distributed brain networks. Recent studies using noninvasive whole-brain measurements in humans have highlighted the importance of neural activity in the 2-10 Hz frequency band for value-based decision making. Using magnetoencephalography and hidden Markov model (HMM) analysis, we examined whether and how whole-brain neural dynamics in this frequency band, evolving on a timescale of a few hundred milliseconds, reflect value-based decision processes. Thirty-five healthy adults (females and males) made binary choices between risky and sure options. Trial-wise subjective values were estimated using behavioral economic modeling based on prospect theory. We found that HMM-derived trial-by-trial whole-brain neural dynamics (defined by 2-10 Hz amplitude envelopes in distributed brain regions and their interregional coupling) were associated with the subjective values of choice options in a manner distinct from simple perceptual- or motor-evoked activity. Notably, these trial-by-trial whole-brain dynamics covaried with the difference in subjective values between the chosen and unchosen options when the neural data were time-locked to participants responses, but not when time-locked to option onset. These findings revealed a crucial link between subsecond whole-brain neural dynamics and trial-by-trial decision variables, providing insights into how value-based decision processes unfold over time in the human brain.

neuroscience↗

Tegmental atrophy in isolated REM sleep behaviour disorder: Ex vivo-informed in vivo imaging

Isolated rapid eye movement (REM) sleep behaviour disorder (iRBD) is an early-stage synucleinopathy characterized by brainstem pathology. In rodents, the pontine tegmentum contains an REM sleep centre, the sublaterodorsal nucleus (SLD), which expresses corticotropin-releasing hormone binding protein (CRHBP). While the involvement of brainstem pathophysiology is thus implicated in iRBD, its solid evidence remains scarce in humans due to the difficulty in identifying small brainstem nuclei with conventional MRI technology alone. Here, we aimed to detect tegmental atrophy in iRBD with voxel-based morphometry (VBM) analysis combined with a novel human brainstem atlas. Structural MRIs from 98 patients with iRBD and 114 controls were analysed to investigate grey matter volume (GMV) using VBM. Our unique approach involved detailed assessments of the VBM results, guided by a high-resolution MRI-based atlas of the human brainstem. This brainstem atlas was founded on ex vivo MRI of 10 postmortem human specimens. We validated it with CRHBP immunostaining, which aided in identifying putative REM sleep-regulating nuclei in humans. We applied this brainstem atlas to identify atrophy in specific brainstem regions in iRBD and correlate their volumes with clinical measures, including autonomic functions. VBM revealed a focal cluster of grey matter atrophy in the dorsal pontine tegmentum of iRBD patients, including the laterodorsal tegmental nucleus, ventral part (LDTgV) and the pedunculopontine tegmental nucleus (PTg). Our atlas-based analysis confirmed the LDTgV as the site of most conspicuous atrophy, revealing a significant volume reduction in iRBD patients compared to controls with a moderate effect size (Cohens d = 0.46, Bonferroni-corrected p = 0.019). Furthermore, greater atrophy in the LDTgV and the PTg was associated with more severe autonomic dysfunction as measured by Scales for Outcomes in Parkinsons Disease-Autonomic dysfunction (SCOPA-AUT) scores (partial r = -0.237, p = 0.019 and partial r = -0.236, p = 0.019, respectively). Histological analysis confirmed that the LDTgV is selectively enriched with CRHBP-positive neurons, a putative marker for REM sleep-on neurons. We provided novel evidence for the involvement of LDTgV, the putative human homolog of the murine SLD, in iRBD. The present findings advance our understanding of the neuroanatomical basis of iRBD and will contribute to the development of early biomarkers for -synucleinopathies.

neuroscience↗

Effects of Postmortem Intervals on Quantitative MRI in Unfixed and Fixed Swine Brain: Implications for Ex Vivo MRI Applications

PurposeThe postmortem interval (PMI) alters tissue properties that shape quantitative MRI (qMRI) signals. We systematically investigated the effects of PMI on relaxation times, depending on tissue characteristics, in both unfixed and fixed pig brains. MethodsTwelve pig brains (n = 12) were scanned in both unfixed and fixed states at three PMI windows ({approx}12, 24, 48 h). Quantitative T1, T2, and T2* maps were acquired with identical protocols at controlled room temperature ([~]24 {degrees}C). We assessed the PMI effects on relaxation times in the gray matter (GM) and the white matter (WM) at both group and sample levels, while fixation-induced effects and inter-sample variability were evaluated using pairwise rank correlation and coefficient of variation (CV) visualization. ResultsIn unfixed tissues, T1 significantly differed among PMI groups in GM (p = 0.0141) and WM (p = 0.0315) in the early window ([≤] 24 h). In the same window, PMI-T1 correlations were observed in both GM (r = 0.921, p = 0.007) and WM (r = 0.876, p = 0.013). T2 showed no group differences but exhibited an inverse correlation with PMI in WM (r = -0.849, p = 0.015). No significant PMI-T2* relationships were detected (all p > 0.05). At later PMI (20-50 h), PMI-qMRI correlations diminished. Fixation processes altered all qMRI parameters. Notably, the PMI effects on T1 in the unfixed brains were preserved even after fixation at an ordinal level, although fixation introduced substantial inter-sample variability. ConclusionsPMI exerts the most robust effects on T1. Fixation has a significant impact on qMRI values, mitigating the apparent PMI effect and increasing the inter-sample variability. However, it is still possible to retrieve the PMI effects from fixed brain at the level of rank order, providing practical guidance for further ex vivo qMRI studies on PMI.

bioengineering↗

Neural Underpinnings of Olfactory Dysfunction across Parkinson's and Alzheimer's Spectra

Olfactory dysfunction is a frequent yet understudied feature of neurodegenerative spectrum disorders, including Alzheimers disease (AD) and Parkinsons disease (PD). To disentangle the neural substrates of hyposmia across disease spectra, we examined 222 participants from the Parkinsons and Alzheimers disease Dimensional Neuroimaging Initiative cohort. Participants were classified according to the presence of cognitive disturbance, movement disorder, or both. Olfactory testing disclosed that cognitive disturbance and movement disorder were independently associated with hyposmia, and having both cognitive disturbance and movement disorder was associated with severe hyposmia. Whole-brain voxel-based morphometry revealed that hyposmia was associated with atrophy in the medial temporal lobe (MTL) in individuals with cognitive disturbance, whereas an artificial intelligence-based segmentation model identified olfactory bulb atrophy in those with movement disorder. Regression analysis and structural equation modeling further confirmed that the MTL and olfactory bulb volume contributed to olfactory performance through distinct processes. Individuals with cognitive disturbance and movement disorder had atrophy in both the MTL and olfactory bulb ("double hit"). We identified dual processes underlying hyposmia in the AD and PD spectra: a process linking MTL degeneration to cognitive disturbance and a process linking olfactory bulb degeneration to movement disorder. Our transdiagnostic approach enhances strategy in identifying specific neural correlates underlying hyposmia, lending support to the development of biomarkers for early intervention in AD and PD.

neuroscience↗

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↗

Establishment of a second-generation transgenic marmoset model of polyglutamine disease recapitulating neurological symptoms and pathology

Neurodegenerative diseases, including polyglutamine diseases, remain a major clinical challenge, partly because of limited animal models that recapitulate human disease. Here, we describe a second-generation transgenic marmoset model of spinocerebellar ataxia 3 (SCA3), a polyglutamine disease, which stably expresses expanded CAG repeats in ATXN3. All five offspring of the founder marmoset harbored the transgene with reduced transgene integration sites and without repeat instability or genetic mosaicism, offering improved construct validity. Three of the five marmosets developed progressive motor impairments that segregated into two distinct phenotypes: early onset with rapid progression and late onset with mild progression, accompanied by corresponding patterns in body weight gain and grip strength. Pathological analysis revealed cerebellar Purkinje cell loss, spinal cord neurodegeneration, and widespread intranuclear inclusions. The severity of motor phenotypes correlated with transgene expression levels in disease-relevant brain regions, including the cerebellum, spinal cord, and striatum. By overcoming the common translational limitations of rodent systems, our second-generation model offers a powerful platform for investigating disease mechanisms and testing potential therapeutic interventions. Our results advance the utility of transgenic marmosets as clinically relevant models of neurodegenerative diseases. Summary StatementSecond-generation transgenic marmoset models of spinocerebellar ataxia 3 replicated the progressive motor deficits and neuropathology of the founder marmoset, providing a powerful platform for studying disease mechanisms and developing therapies.

neuroscience↗

Dynamic and topological properties of large-scale brain networks in rapid eye movement behavior disorder

IntroductionThere is a lack of research in the existing literature when it comes to analyzing the dynamics of resting-state functional magnetic resonance imaging to understand the underlying mechanisms of isolated rapid eye movement sleep behavior disorder (iRBD). This study aims to contribute to our understanding of abnormalities in brain network dynamics in iRBD and their association with alpha-synucleinopathy. Additionally, I employed graph theoretical metrics to obtain a topological insight into the brain network of iRBD. MethodsResting-state fMRI data from 55 iRBD patients and 97 healthy controls (HCs) were utilized. A sliding window approach, functional connectivity analysis, and graph theory analysis were applied to the data. I calculated the mean, standard deviation, skewness, and kurtosis of the time series for both dynamic functional connectivity (dFC) and four graph metrics (clustering coefficient, global efficiency, assortativity coefficients, and eigenvector centrality). Subsequently, I compared the those metrices between iRBDs and HCs. Relationships between clinical scales and abnormal dFC were assessed using a general linear model. ResultsiRBD patients exhibited abnormal mean dFC, particularly in the default mode network, sensorimotor network, basal ganglia network, and cerebellum. Kurtosis of dFC revealed abnormalities between the middle temporal gyrus and cerebellum. Group differences were also observed in the mean eigenvector centrality of the precentral gyrus and thalamus. ConclusionThe mean of dFC identified impairments putatively in movement functions and various compensatory mechanisms. Moreover, mean eigenvector centrality revealed topological changes in motor-related network in iRBDs. The use of kurtosis as a potential index for extracting dynamic information may provide additional insights into pathophysiology in iRBDs.

neuroscience↗

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↗

Don't think, feel: basal ganglia-cortical connectivity underlies self-regulation of brain oscillations in humans

Brain-computer interfaces (BCIs) provide an artificial link by which the brain can directly interact with the environment. To achieve fine BCI control, participants must modulate the patterns of the cortical oscillations generated from the motor and somatosensory cortices. However, it remains unclear how humans regulate cortical oscillations, the controllability of which substantially varies across individuals. Here, we performed simultaneous electroencephalography (to assess BCI control) and functional magnetic resonance imaging (to measure brain activity) in healthy participants. Self-regulation of cortical oscillations induced activity in the basal ganglia-cortical network (BgCN) and the neurofeedback control network (NfCN). Successful self-regulation correlated with striatal activity in the BgCN, through which patterns of cortical oscillations were likely modulated. Moreover, BgCN and NfCN connectivity correlated with strong and weak self-regulation, respectively. The findings indicate that the BgCN is important for self-regulation, the understanding of which should help advance BCI technology.

neuroscience↗

Brain/MINDS Beyond Human Brain MRI Study: Multi-Site Harmonization for Brain Disorders Throughout the Lifespan

Psychiatric and neurological disorders are afflictions of the brain that can affect individuals throughout their lifespan. Many brain magnetic resonance imaging (MRI) studies have been conducted; however, imaging-based biomarkers are not yet well established for diagnostic and therapeutic use. This article describes an outline of the planned study, the Brain/MINDS Beyond human brain MRI project (FY2018 [~] FY2023), which aims to establish clinically-relevant imaging biomarkers with multi-site harmonization by collecting data from healthy traveling subjects (TS) at 13 research sites. Collection of data in psychiatric and neurological disorders across the lifespan is also scheduled at 13 sites, whereas designing measurement procedures, developing and analyzing neuroimaging protocols, and databasing are done at three research sites. The Harmonization protocol (HARP) was established for five high-quality 3T scanners to obtain multimodal brain images including T1 and T2-weighted, resting state and task functional and diffusion-weighted MRI. Data are preprocessed and analyzed using approaches developed by the Human Connectome Project. Preliminary results in 30 TS demonstrated cortical thickness, myelin, functional connectivity measures are comparable across 5 scanners, providing high reproducibility and sensitivity to subject-specific connectome. A total of 75 TS, as well as patients with various psychiatric and neurological disorders, are scheduled to participate in the project, allowing a mixed model statistical harmonization. The HARP protocols are publicly available online, and all the imaging, demographic and clinical information, harmonizing database will also be made available by 2024. To the best of our knowledge, this is the first project to implement a rigorous, prospective harmonization protocol with multi-site TS data. It explores intractable brain disorders across the lifespan and may help to identify the disease-specific pathophysiology and imaging biomarkers for clinical practice.

neuroscience↗

Frequency- and area-specific entrainment of intrinsic cortical oscillations by repetitive transcranial magnetic stimulation

Neural oscillations are ubiquitous throughout the cortex, but the frequency of oscillations differs from area to area. To elucidate the mechanistic architectures establishing various rhythmic activities, we tested whether spontaneous neural oscillations in different cortical modules can be entrained by direct perturbation with distinct frequencies of transcranial magnetic stimulation (TMS). While recording the electroencephalogram (EEG), we applied single-pulse TMS (sTMS) and repetitive TMS (rTMS) at 5, 11, and 23 Hz to motor or visual cortex. To assess entrainment, defined as phase locking of intrinsic oscillations to periodic external force , we examined local and global modulation of the phase-locking factor (PLF). sTMS triggered transient phase locking in a wide frequency band with distinct PLF peaks at 21 Hz in the motor cortex and 8 Hz in the visual cortex. With TMS pulse trains of 11 Hz over visual cortex and 23 Hz over motor cortex, phase locking was progressively enhanced at the stimulation frequency and lasted for a few cycles after the stimulation terminated. Moreover, such local entrainment propagated to other cortical regions, suggesting that rTMS entrained intrinsic neural oscillations locally and globally via network nodes. Because the entrainment was frequency-specific for each target site, these frequencies may correspond to the natural frequency of each cortical module and of the global networks. rTMS enables direct manipulation of the brain and is thus useful for investigating the causal roles of synchronous neural oscillations and synchrony in brain functions, and for the treatment of clinical symptoms associated with impaired oscillations and synchrony.\n\nSignificance StatementWe provide the first evidence for area- and frequency-specific entrainment by frequency-tuned repetitive transcranial magnetic stimulation (rTMS), and the propagation of this entrainment to other areas. Our results indicate that rTMS at the natural frequency of each cortical system is particularly effective for entraining oscillatory phase. Moreover, local entrainment led to global entrainment in functionally coupled areas. The ability to control brain rhythms in the intact human brain is highly beneficial for studying the causal roles of rhythmic activity in brain function. Moreover, this modulatory technique has the potential to treat patients with impaired rhythmic networks in disorders such as schizophrenia and stroke.

neuroscience↗

Phase-amplitude coupling of neural oscillations can be effectively probed with concurrent TMS-EEG

Despite the widespread use of transcranial magnetic stimulation (TMS), knowledge of its neurophysiological mode of action is still incomplete. Recently, TMS has been proposed to synchronise neural oscillators, and to thereby increase the detectability of corresponding oscillations at the population level. As oscillations in the human brain are known to interact within nested hierarchies via phase-amplitude coupling, TMS might also be able to increase the macroscopic detectability of such coupling. In a concurrent TMS-electroencephalography study, we therefore examined the techniques influence on theta-gamma, alpha-gamma and beta-gamma phase-amplitude coupling by delivering single-pulse TMS (sTMS) and repetitive TMS (rTMS) over the left motor cortex and right visual cortex of healthy participants. The rTMS pulse trains were of 5 Hz, 11 Hz and 23 Hz for the three coupling variations, respectively. Relative to sham stimulation, all conditions showed transient but significant increases in phase-amplitude coupling at the stimulation site. In addition, we observed enhanced coupling over various other cortical sites, with a more extensive propagation during rTMS than during sTMS. By indicating that scalp-recorded phase-amplitude coupling can be effectively probed with TMS, these findings open the door to the techniques application in manipulative dissections of such coupling during human cognition and behaviour in healthy and pathological conditions.

neuroscience↗