Biology subjects

Okimura, T.

Publications and source records attributed to Okimura, T..

4 recordsLinked to original sources

bioRxiv2026

Reduced EEG Complexity and Its Association with Social Communication in Adults with Autism Spectrum Disorder: A Multiscale Entropy Study

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 ({tau} = 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.

neuroscience↗

bioRxiv2026

Preserved Intrinsic Neural Timescale Organization with Hierarchical Variation in Autism Spectrum Disorder

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 participants 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. HighlightsO_LIAcross 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. C_LIO_LIAt 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. C_LIO_LIGlobal 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. C_LIO_LIAfter 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. C_LI

neuroscience↗

bioRxiv2025

Iron deposition and functional connectivity alterations in the right substantia nigra of adult males with autism

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 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.

neuroscience↗

bioRxiv2020

Computational Psychiatry Research Map (CPSYMAP): a New Database for Visualizing Research Papers

The field of computational psychiatry is growing in prominence along with the recent advances in computational neuroscience, machine learning, and the cumulative scientific evidence of psychiatric disorders. Computational approaches provide an understanding of disorders using psychological and neuroscience terms and help to determine treatment protocols based on high-dimensional data. However, the multidisciplinary nature of this field seems to limit the development of computational psychiatry studies. Computational psychiatry combines knowledge from neuroscience, psychiatry, and computation; thus, there is an emerging need for a platform to integrate and coordinate these perspectives. In this study, we developed a new database for visualizing research papers as a two-dimensional "map" called the Computational Psychiatry Research Map (CPSYMAP). This map shows the distribution of papers along neuroscientific, psychiatric, and computational dimensions to enable anyone to find niche research and deepen their understanding of the field.

neuroscience↗