Ryu-Ichiro Hashimoto

Background: Brain functions emerge from temporally organized neural dynamics, and an appropriate level of neural complexity may support flexible information processing. Electroencephalographic (EEG) studies using multiscale entropy (MSE), which quantifies signal complexity across multiple temporal scales, have reported reduced MSE at longer scales in individuals with autism spectrum disorder (ASD). However, most evidence comes from studies of infant and child samples, leaving adult data scarce, and the associations between reduced MSE, clinical symptoms, and social information processing are insufficiently understood. Methods: We recorded and analyzed EEG data from adults with ASD (n = 47) and typically developing (TD) controls (n = 40) during eyes-closed rest and two movie viewing conditions: Inscapes, comprising dynamically changing abstract visual patterns, and Partly Cloudy, an emotionally engaging animated social narrative. Group and condition effects were assessed using cluster-based permutation tests, and associations between MSE and Social Affect (SA) scores from the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), as well as group differences in event-related MSE changes, were examined using linear mixed-effects models. Results: Across conditions, adults with ASD showed lower MSE at longer scales (τ = 16–30), corresponding to effective sampling rates of 12.50–6.67 Hz in the coarse-grained time series, than TD adults. Longer-scale MSE within the ASD−TD difference cluster was negatively associated with ADOS-2 SA scores across diagnostic groups. The difference in event-related MSE change between Social and Non-Social conditions, comparing empathic-pain and mentalizing events in Partly Cloudy with temporally matched non-social windows in Inscapes, was smaller in ASD participants than in TD participants. No significant difference between Social and Non-Social windows was observed among ASD participants, whereas TD participants showed significantly greater MSE change during Social than Non-Social windows. Limitations: This study used a modest sample without an independent replication cohort, and the short event windows limited the precision of the MSE estimation. Conclusions: Reduced longer-scale MSE extends to adults with ASD and is associated with higher ADOS-2 SA scores across diagnostic groups. Event-related findings further suggest attenuated differentiation of longer-scale MSE between socially relevant and matched non-social windows in ASD.

Intrinsic neural timescales (INTs) index the temporal decay of neural activity and form a cortical hierarchy from fast sensorimotor to slow transmodal regions. Altered INTs have been reported in autism spectrum disorder (ASD), but it remains unclear whether the hierarchical organization is preserved and how individual variability along this hierarchy relates to sensory traits. Using resting-state fMRI from 182 participants (67 ASD, 115 typically developed controls (TDC)), we estimated INT at each cortical vertex from the autocorrelation half-life and averaged these values across four five-minute runs per participant. Vertex-wise INTs were then averaged within predefined cortical parcels and large-scale functional networks for subsequent analyses. The cortical INT hierarchy was preserved in ASD, showing comparable sensorimotor-to-transmodal hierarchy in both groups. However, regions operating at longer timescales showed prolonged INTs in ASD, and such tendency increased systematically along the hierarchy. No vertex, parcel, or network survived correction of multiple comparisons, indicating that observed alterations followed a distributed hierarchical trend rather than a focal pattern. To disentangle group-level differences from inter-individual variability, we next modeled each participant’s parcel-wise INT profile relative to a TDC-derived group-averaged template. At the individual level, decomposition of INT profiles revealed that global shifts and hierarchical scaling primarily reflected demographic variation (plimarily sex) rather than diagnostic group membership. After accounting for these components, residual deviations from theTDC-derived cortical INT hierarchy showed a modest association with sensory traits characterized by reduced sensory registration. Together, these findings indicate that while the large-scale hierarchical organization of cortical temporal dynamics is largely preserved in ASD, individual-specific deviations from this hierarchy may contribute to variability in sensory experience beyond group-level differences. Highlights: Across both autism spectrum disorder (ASD) and typically developed controls (TDC), intrinsic neural timescales (INTs) followed the established sensory cortical hierarchy and showed a negative association with cortical microstructural markers (myelin content and neurite density index), with no group difference in hierarchical slope. At the whole-brain level, the hierarchical organization of INTs was preserved across ASD and TDC, although regions operating at longer timescales exhibited relatively greater extension in ASD. Global shifts and hierarchical scaling, describing individual positioning within the INT-based cortical hierarchy, were more strongly associated with demographic variation (primarily sex) than with diagnosis. After accounting for these global and hierarchical components, residual deviations from the INT-based cortical hierarchy were modestly associated with sensory traits characterized by reduced sensory registration.

To advance the application of functional near-infrared spectroscopy (fNIRS) in brain-computer interface (BCI) technology, we investigated cortical activation patterns associated with auditory selective attention. Using a dichotic listening paradigm, participants were presented with simultaneous music and reading sounds to the left or right ear. During fNIRS recordings, they were instructed to selectively attend to the sound attribute (music vs. reading) or the spatial location (left vs. right ear). Cortical activity differences related to attentional targets were analyzed using a two-way analysis of variance (ANOVA), with sound attribute and spatial information as factors. Our results revealed a significant main effect of the sound attribute factor across multiple measurement channels. Notably, the right parietal region exhibited consistently greater activation when attention was directed toward music compared to reading sounds. Conversely, bilateral dorsolateral prefrontal cortex (DLPFC) channels showed higher activation when participants attended to reading sounds than to music. These findings indicate that cortical activation patterns are modulated by auditory attentional states based on sound attributes. Furthermore, preliminary classification analyses achieved an accuracy of 73.7% in discriminating attentional targets (music vs. reading sounds), demonstrating the feasibility of fNIRS-based BCI applications.

Background Large-scale, multi-site brain magnetic resonance imaging (MRI) studies have revealed neuroanatomical alterations in various psychiatric disorders. However, site-specific differences—such as sampling and measurement biases—and the non-linear nature of brain features can limit individual-level investigations. These constraints underscore the need for a meta-analytic approach to accurately capture and compare brain structural changes across different psychiatric conditions. Methods Structural MRI data were collected from 1736 healthy controls and 1371 participants with clinical conditions, including major depressive disorder, schizophrenia, bipolar disorder, first-episode psychosis, ultra-high risk for psychosis, and autism spectrum disorder. A harmonization procedure was applied to reduce measurement bias across sites. Subsequently, deviations from normative trajectories—modeled on healthy controls—were estimated to diminish non-disease-related variations while preserving disease-specific patterns of brain changes. Results Significant reductions in cortical thickness, surface area, and subcortical volumes were observed in most clinical groups. The effect sizes exceeded those reported in previous meta-analyses, indicating enhanced sensitivity in detecting subtle neuroanatomical alterations. Furthermore, distinct profiles of brain alterations emerged across the examined psychiatric disorders and conditions, highlighting the heterogeneous nature of structural changes. Conclusion This study provides important insights into the neuroanatomical underpinnings of psychiatric disorders. By leveraging harmonized datasets and robust statistical methods, we demonstrate improved detection of structural alterations across psychiatric disorders, underscoring the value of multi-site collaborations and advanced analytic techniques for elucidating the complex neurobiology of psychiatric conditions.

The substantia nigra (SN) is a midbrain nucleus implicated not only in motor control and reward processing but also in higher-order cognitive functions. Iron homeostasis in this region is essential for neurotransmitter synthesis, especially for dopamine, and thus, iron dysregulation may contribute to the symptomatology of autism spectrum disorder (ASD). However, iron deposition and functional circuits of the SN in the autistic brain remain underexplored. This study investigated iron deposition and functional connectivity (FC) of the SN in 53 adult males with ASD and 99 typically developing controls using quantitative susceptibility mapping and resting-state fMRI. Compared to controls, the ASD group exhibited higher magnetic susceptibility in the right SN, suggesting elevated iron deposition. Within the ASD group, higher iron deposition was associated with more severe socio-communicative deficits and reduced sensory-seeking behavior. Seed-based FC analyses further revealed that the ASD group exhibited stronger FC between the right SN and bilateral visual cortices and reduced FC with the right superior frontal gyrus. These results highlight the critical role of the SN in the autistic brain and indicate that altered iron homeostasis in the SN may contribute to disruptions in the dopaminergic system that underlie the core symptoms of ASD.

Autobiographic remembering often involves types of constructive processes for psychological experiences and hypothetical scenarios of past events. Previous psychological research revealed a range of phenomenological and functional characteristics associated with recalls of episodes with high autobiographical significance. However, neural bases of such psychological characteristics and their association with memory construction processes remain unclear. In this functional magnetic resonance imaging study, we collected autobiographical episodes from 28 young adults and their extensive metrics of phenomenological and functional characteristics related to autobiographical significance. We then sought to identify neural correlates of the psychological characteristics by measuring brain activity while participants recalled specified episodes as accurately as possible or in counterfactual simulation. Multiple-regression analysis using latent factors of psychological characteristics revealed that a factor representing autobiographical significance was associated with activation in the posterior medial memory system, including the angular cortex, precuneus, and posterior cingulate cortex, during counterfactual simulation. Furthermore, representation similarity analysis using patterns of factor scores revealed significant clusters in the posterior medial system and parts of cerebellar parcels, mainly during counterfactual simulation. These findings indicate that multidimensional psychological characteristics of episodes with autobiographical significance are associated with hypothetical constructive processes in the cortical posterior medial system and cerebellum.

Autism spectrum disorder (ASD) is a lifelong condition with elusive biological mechanisms. The complexity of factors, including inter-site and developmental differences, hinders the development of a generalizable neuroimaging classifier for ASD. Here, we developed a classifier for ASD using a large-scale, multisite resting-state fMRI dataset of 730 Japanese adults, aiming to capture neural signatures that reflect pathophysiology at the functional network level, neurotransmitters, and clinical symptoms of the autistic brain. Our adult ASD classifier was successfully generalized to adults in the United States, Belgium, and Japan. The classifier further demonstrated its successful transportability to children and adolescents. The classifier contained 141 functional connections (FCs) that were important for discriminating individuals with ASD from typically developing controls. These FCs and their terminal brain regions were associated with difficulties in social interaction and dopamine and serotonin, respectively. Finally, we mapped attention-deficit/hyperactivity disorder (ADHD), schizophrenia (SCZ), and major depressive disorder (MDD) onto the biological axis defined by the ASD classifier. ADHD and SCZ, but not MDD, were located proximate to ASD on the biological dimensions. Our results revealed functional signatures of the ASD brain, grounded in molecular characteristics and clinical symptoms, achieving generalizability and transportability applicable to the evaluation of the biological continuity of related diseases.

The human auditory system includes discrete cortical patches and selective regions for processing voice information, including emotional prosody. Although behavioral evidence indicates individuals with autism spectrum disorder (ASD) have difficulties in recognizing emotional prosody, it remains understudied whether and how localized voice patches (VPs) and other voice-sensitive regions are functionally altered in processing prosody. This fMRI study investigated neural responses to prosodic voices in 25 adult males with ASD and 33 controls using voices of anger, sadness, and happiness with varying degrees of emotion. We used a functional region-of-interest analysis with an independent voice localizer to identify multiple VPs from combined ASD and control data. We observed a general response reduction to prosodic voices in specific VPs of left posterior temporal VP (TVP) and right middle TVP. Reduced cortical responses in right middle TVP were consistently correlated with the severity of autistic symptoms for all examined emotional prosodies. Moreover, representation similarity analysis revealed the reduced effect of emotional intensity in multivoxel activation patterns in left anterior superior temporal cortex only for sad prosody. These results indicate reduced response magnitudes to voice prosodies in specific TVPs and altered emotion intensity-dependent multivoxel activation patterns in adult ASDs, potentially underlying their socio-communicative difficulties.