Biology subjects

Hiromitsu, K.

Publications and source records attributed to Hiromitsu, K..

4 recordsLinked to original sources

bioRxiv2026

Characterizing load-dependent changes in whole-brain activity patterns during an extended N-back task

Working memory (WM) is a core cognitive function that supports goal-directed behavior by temporarily maintaining and manipulating information. One of the most widely used paradigms for investigating WM function is the N-back task, and numerous neuroimaging studies have examined load-dependent neural responses using a variety of analytical approaches. However, most previous studies have focused on low-to-moderate load ranges (primarily 0-3-back), and it remains unclear how whole-brain activity patterns reconfigure across a broader range of WM demands, including conditions approaching capacity limits. In the present study, we investigated behavioral performance and whole-brain activity patterns across an extended N-back task ranging from 0-back to 7-back. Behavioral analyses revealed that discrimination sensitivity (d') decreased nonlinearly with increasing WM load, whereas reaction time (RT) exhibited an inverted-U pattern, peaking at intermediate load conditions. To characterize load-dependent whole-brain activity patterns, we computed relative activation maps by subtracting the participant-wise mean activation map across all conditions from each condition-specific activation map. Spatial similarity analyses with the Yeo 7-network templates revealed that low-load conditions showed relatively high similarity to default mode network (DMN)-related patterns. Similarity to the dorsal attention network (DAN) and frontoparietal network (FPN) was maximal at intermediate load levels, indicating load-dependent changes in network similarity profiles. High-load conditions were characterized by partial re-emergence of DMN-related patterns, accompanied by reduced DAN/FPN similarity. In addition, semantic similarity analysis using Neurosynth-derived semantic maps revealed relatively high similarity to default mode-related and self-referential representations under low-load conditions. Intermediate-load conditions showed strong correspondence with working memory- and executive control-related representations, whereas high-load conditions exhibited increased similarity to salience-, aversive/interoceptive-, and inhibitory-control-related representations. Together, these findings suggest that increasing WM load is associated not merely with stronger activation, but with changes in whole-brain activity patterns accompanied by nonlinear changes in network similarity profiles across levels of cognitive demand. Furthermore, the relative activation map-based whole-brain pattern analysis used in this study may provide a useful approach for evaluating changes in whole-brain state representations associated with cognitive load.

neuroscience↗

bioRxiv2026

Behavioural and neural signatures across diverse cognitive demands in a multimodal electroencephalography-functional magnetic resonance imaging design

Efficient multimodal designs that capture differences across cognitive domains and variations in cognitive demand remain limited. In this study, we tested a compact framework with 58 healthy participants who completed multimodal electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) sessions. The framework comprised two complementary batteries: the HCP-aligned multitask paradigm (HCP-mini), which integrates eight HCP-aligned cognitive tasks and rest within a single run, and an extended N-back task ranging from 0-back to 7-back. Designed to support broad cross-domain coverage and matched multimodal assessment, the two batteries captured the expected group-level behavioural structure across modalities. Behavioural performance exceeded chance levels or aligned with findings from previous studies in both EEG and fMRI. Descriptive intraclass correlation coefficient (ICC) analyses showed numerically higher within-modality run-to-run values than between-modality values. At the neural level, HCP-mini fMRI activation patterns closely recapitulated the canonical large-scale task organisation of the original HCP dataset, with corresponding task pairs showing the strongest spatial similarity. Together, these findings demonstrate a compact and efficient framework for multimodal characterisation of cognition across domains and graded cognitive demands.

neuroscience↗

bioRxiv2024

Immediate Modulation of the Blood Oxygenation Level-Dependent Signals by Dual-Site Transcranial Alternating Current Stimulation Propagates Across the Whole Brain

Transcranial alternating current stimulation (tACS) is assumed to target specific brain regions and modulate their activity. Recent discussions of tACS propose that, entraining the phase of brain activity to the stimulation current, stimulation effects extend globally across the whole brain based on phase differences. However, immediate online spatiotemporal propagation of resting-state blood oxygenation level-dependent (BOLD) signals within the brain due to multi-region stimulation remains unclear. The objectives of the present study were three-fold: 1) to elucidate the immediate online effect of tACS on BOLD signal, 2) to examine the extent of the influence on the brain when applying tACS, and 3) to explore whether variations in the phase difference between two brain regions result in differential effects on the stimulated areas and the whole brain. Through two experiments involving high-definition tACS with simultaneous measurements using a functional magnetic resonance imaging (fMRI), we revealed that the immediate online stimulation effects not only altered BOLD signals in the stimulated regions but also propagated across the whole brain in specific spatiotemporal patterns (functional networks). Stimulation effects were observed specifically in regions rich in neural fibres, including the grey and white matter, with no effect in regions containing cerebrospinal fluid. The timing of the signal value peaks depended on the stimulated region and functional networks, with a notable trend observed. Thus, tACS with a specific phase difference in two anatomically connected brain regions can immediately modulate online neural dynamics at both local and global scales. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/610912v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@124d6e1org.highwire.dtl.DTLVardef@1976b16org.highwire.dtl.DTLVardef@1f78294org.highwire.dtl.DTLVardef@9df1b7_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Spatio-temporal "global" neurodynamics in both continuous and discrete pictures for human brains

The neural manifold in state space represents the mass neural dynamics of a biological system. A challenging modern approach treats the brain as a whole in terms of the interaction between the agent and the world. Therefore, we need to develop a method for this global neural workspace. The current study aimed to visualize spontaneous neural trajectories regardless of their measuring modalities (electroencephalography [EEG], functional magnetic resonance imaging [fMRI], and magnetoencephalography [MEG]). First, we examined the possible visualization of EEG manifolds. These results suggest that a spherical surface can be clearly observed within the spatial similarity space where canonical microstates are on-manifold. Once valid (e.g., differentiable) and useful (e.g., low-dimensional) manifolds are obtained, the nature of the sphere, such as shape and size, becomes a possible target of interest. Because these should be practically useful, we suggest advantages of the EEG manifold (essentially continuous) or the state transition matrix (coarse-grained discrete). Finally, because our basic procedure is modality-independent, MEG and fMRI manifolds were also compared. These results strongly suggest the need to update our understanding of neural mass representations to include robust "global" dynamics.

neuroscience↗