Biology subjects

Imamizu, H.

Publications and source records attributed to Imamizu, H..

At least 19 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.

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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.

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bioRxiv2025

Effects of stimulus modality and response type on oddball stimulus discrimination using polarity-considered EEG microstate labeling

ObjectiveBrain-computer interfaces (BCIs) require effective feature extraction and dimensionality reduction from multidimensional brain signals. Electroencephalogram (EEG) microstate analysis offers a fast and noise-resistant approach by classifying the states of brain signals into spatial distribution patterns (templates). Each EEG segment was assigned the template with the highest spatial correlation, reducing the information to a one-dimensional representation. However, prior BCI studies have often ignored the polarity of spatial distributions in these templates. Incorporating polarity during labeling may enhance classification performance. This study investigated the effectiveness of polarity-considered microstate labeling for classifying infrequent stimuli in an auditory-visual oddball task with implications for BCI applications. MethodEEG recordings were analyzed using polarity-considered microstate labeling to classify infrequent stimuli. This study examined the effects of stimulus modality (auditory or visual), modality conditions (unimodal: stimulus and response in the same modality; cross-modal: stimulus and response in different modalities), and response type (key-press task vs. mental counting task) on classification accuracy. Machine learning models were used for classification, including support vector machine, random forest, logistic regression, XGBoost, CatBoost and K-means methods. ResultsPolarity-considered labeling outperformed the non-polarity approach, especially in decision-tree-based models (20.1% improvement in the key-press task and 22.2% improvement in the mental counting task). A significant interaction was observed between stimulus modality and response type, with the highest accuracy achieved when the infrequent stimuli in the key-press task involved cross-modal visual information. ConclusionThe findings suggest that polarity-considered microstate labeling enhances EEG-based classification. This approach has potential applications in BCI, such as in P300 spellers using cross-modal auditory-visual stimuli.

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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.

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bioRxiv2025

Whole-brain EEG dynamics depending on the stimulus modality and task requirements in oddball tasks

Electroencephalography (EEG) microstates constitute temporal map configurations that reflect the whole brain electrical state. The dynamics of EEG microstates may serve as an effective discretization method for capturing spatiotemporally continuous neural dynamics with high temporal resolution. In this study, we employed polarity-sensitive microstate analysis to investigate whole-brain state transitions during audiovisual oddball tasks. Moreover, we examined how sensory modality and its coupling, types of response to target stimuli, and the physical presence or absence of target stimuli affected EEG dynamics. The results demonstrated that the abovementioned factors affected both behavioral indices and the event-related potential (ERP) components, particularly the P300. Importantly, when considering the topographical polarity of map configuration, transitions to microstate E-, which originates within 300 to 600 ms after stimulus onset and coincides with the typical latency of the P300 component potentially reflect attentional and conscious processes that are associated with the P300. These novel insights into the dynamic transitions of whole brain states during cognitive processes complement the results of traditional ERP analyses.

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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

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bioRxiv2024

Human sensorimotor cortex reactivates recent visuomotor experience during awake rest

Previous studies have suggested that awake rest after training is helpful in improving motor performance and memory consolidation in visuomotor learning. Re-emergence of task-related activation patterns during awake rest has been reported, which play a role in memory consolidation or perceptual learning. This study aimed to test whether such reactivation occurs after visuomotor learning in the primary sensorimotor cortex. During fMRI scanning, 42 normal participants learned visuomotor tracking, while a rotational perturbation was introduced between a cursor position and a joystick angle. This visuomotor learning block was interleaved with the control block, during which the participants passively viewed a replay of previously performed cursor movements of their own. Half of the participants used their right hand, and the other half used their left hand to control the joystick. The resting-state scans were measured before and after the visuomotor learning sessions. A multivariate pattern classifier was trained to classify task and control blocks and then tested with resting scans before and after learning. Results revealed a significant increase in the number of volumes classified as the task in the post-learning rest compared with the pre-learning, indicating a re-emergence of task-related activities. Representational similarity analysis also showed a more similar pattern of activity with the task during the post-learning rest period. Furthermore, this effect is specific to the primary sensorimotor cortex contralateral to the hand used and significantly correlated with motor improvement after rest. Our finding revealed the reactivation of task-related patterns in the primary sensorimotor cortex for offline visuomotor learning. Significance StatementPrevious research suggests that awake rest after learning promotes memory consolidation, which is subserved by the re-emergence of task-specific activity patterns. We aimed to determine whether such reactivation occurs in the primary sensorimotor cortex following visuomotor learning for offline memory consolidation. Our results showed a significant increase in task-classified brain volumes during the post-learning rest period compared to the pre-learning period, indicating a re-emergence of task-related activity. Furthermore, this effect was specific to the primary sensorimotor cortex contralateral to the hand used for the task and significantly correlated with the motor performance following the rest period. These findings provide evidence for the reactivation of task-related patterns during offline visuomotor learning, which may underlie memory consolidation processes.

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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.

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bioRxiv2024

Topographical polarity reveals continuous EEG microstate transitions and electric field direction in healthy aging

EEG microstate sequences, representing whole-brain spatial potential distribution patterns of the EEG, offer valuable insights for capturing spatiotemporally continuous and fluctuating neural dynamics with high temporal resolution through appropriate discretization. Recent studies suggest that EEG microstate transitions are gradual and continuous phenomena, contrary to the classical view of binary transitions. This study aimed to update conventional microstate analysis to reflect continuous EEG dynamics and examine differences in age-related electrophysiological state transitions. We considered the relative positions of EEG microstates on the neural manifold and their topographical polarity. Transition probability results showed fewer transitions on the microstate D-C-E axis in older adults. In contrast, transitions among microstates A, D, and B increased in the older group and were mainly observed within polarity. Furthermore, the 100 microstate transitions, which are variations of the shortest transitions between 10 microstates, could be reduced to 8 principal components based on the co-occurrence of each transition, including hubs C and E, planar transitions through msA/B and D, and unidirectional transition components. Several transition components were potentially significant predictors of age group. These features were nearly replicated in independent data, indicating their robustness in characterizing age-related electrophysiological spatiotemporal dynamics.

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bioRxiv2024

Comprehensive evaluation of pipelines for diagnostic biomarkers of major depressive disorder using multi-site resting-state fMRI datasets

The objective diagnostic and stratification biomarkers developed with resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for mental disorders. Unfortunately, there are currently no widely accepted biomarkers, partially due to the large variety of analysis pipelines for developing them. In this study we comprehensively evaluated analysis pipelines using a large-scale, multi-site fMRI dataset for major depressive disorder (MDD) (1162 participants from eight imaging sites). We explored the combinations of options in four subprocesses of analysis pipelines: six types of brain parcellation, four types of estimations of functional connectivity (FC), three types of site difference harmonization, and five types of machine learning methods. 360 different MDD diagnostic biomarkers were constructed using the SRPBS dataset acquired with unified protocols (713 participants from four imaging sites) as a discovery dataset and evaluated with datasets from other projects acquired with heterogeneous protocols (449 participants from four imaging sites) for independent validation. To identify the optimal options regardless of the discovery dataset, we repeated the same procedure after swapping the roles of the two datasets. We found pipelines that included Glassers parcellation, tangent-covariance, no harmonization, and non-sparse machine learning methods tended to result in high classification performance. The diagnosis results of the top 10 biomarkers showed high similarity, and weight similarity was also observed between eight of the biomarkers, except two that used both data-driven parcellation and FC computation. We applied the top 10 pipelines to the datasets of other mental disorders (autism spectral disorder: ASD and schizophrenia: SCZ) and eight of the ten biomarkers showed sufficient classification performances for both disorders, except two pipelines that included Pearson correlation, ComBat harmonization and random forest classifier combination. HighlightsO_LIWe evaluated the analysis pipelines of rsFC biomarker development. C_LIO_LIFour subprocesses in them were investigated with two multi-site datasets. C_LIO_LIGlassers parcellation, tangent covariance, and non-sparse methods were preferred. C_LIO_LIThe weight patterns of eight of the top 10 biomarkers showed high commonality. C_LIO_LIEight of the top 10 pipelines were successful for developing SCZ/ASD biomarkers. C_LI

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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.

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bioRxiv2023

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P<0.05, family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

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bioRxiv2023

Time-dependent neural arbitration between cue associative and episodic fear memories

After traumatic events, simple cue-threat associative memories strengthen while episodic memories become fragmented. However, how the brain prioritizes cue associations over episodic coding of traumatic events remains unclear. Here, we developed a new episodic threat conditioning paradigm in which participants concurrently form two memory representations: cue associations and episodic cue sequence. We discovered that these two distinct memories compete for physiological fear expression, reorganizing overnight from an overgeneralized cue-based to a precise sequence-based expression. With multivariate fMRI, we track inter-area communication of the memory representations and demonstrate that a shift from hippocampal-dominant to prefrontal-dominant control of the fear regulatory circuit governs this memory maturation. Critically, this overnight reorganization is altered in individuals with heightened trait anxiety. Together, these findings suggest the brain prioritizes generalizable associative memories under recent traumatic stress, but resorts to selective episodic memories 24 hrs later. Time-dependent memory competition provides a unifying account for memory dysfunctions in posttraumatic stress disorders.

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bioRxiv2022

Fear in action: Fear conditioning and alleviation through body movements

Acquisition of fear memories enhances survival especially when the memories guide defensive movements to minimize harm. Accordingly, fear memories and body movements have tight relationships in animals: Fear memory acquisition results in adapting reactive defense movements, while training active defense movements to avoid threat reduces fear memory. However, evidence in humans is scarce because their movements are typically marginalized in experiments. Here, we tracked participants whole-body motions while they underwent fear conditioning in a virtual 3D space. First, representational similarity analysis of body motions revealed that participants obtained distinct spatiotemporal movement patterns through fear conditioning. Second, subsequent training to actively avoid threats with naturalistic defensive actions led to a long-term (24 hrs) reduction of physiological and embodied conditioned responses, while extinction or vicarious training only transiently reduced the responses followed by their spontaneous return. Together, our results highlight the intrinsic role of body movements in human fear memory functions, suggesting the potential for improving fear memory interventions through embodiment.

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bioRxiv2021

Neural basis for adaptive motor behavior during car driving

Car driving is supported by motor skills trained through continuous daily practice. One of the skills unique to expert drivers is the ability to detect abrupt changes in the driving environment and then quickly adapt their operation mode to the changes. Previous functional neuroimaging studies on motor control investigated the mechanisms underlying behaviors adaptive to changes in control properties of simple experimental devices such as a computer mouse or a joystick. The switching of multiple internal models mainly engages adaptive behaviors and underlies the interplay between the cerebellum and frontoparietal network (FPN) regions as the neural process. However, it remains unclear whether the neural mechanisms identified through an experimental paradigm using such simple devices also underlie practical driving behaviors. In the current study, we measure functional magnetic resonance imaging (fMRI) activities while participants control a realistic driving simulator inside the MRI scanner. Here, the accelerator sensitivity of a virtual car is abruptly changed, requiring participants to respond to this change as quickly as possible. We first compare brain activities before and after the sensitivity change. As a result, sensorimotor areas, including the left cerebellum, increase their activities after the sensitivity change. Moreover, after the change, activity significantly increases in the inferior parietal lobe and dorsolateral prefrontal cortex, parts of the FPN regions. By contrast, the posterior cingulate cortex, a part of the default mode network, deactivates after the sensitivity change. Our results suggest that the neural bases found in previous experiments using the simpler devices can serve as the foundation of adaptive car driving. At the same time, this study also highlights the unique contribution of non-motor-related regions to addressing the high cognitive demands of driving.

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bioRxiv2020

My voice therefore I spoke: sense of agency over speech enhanced in hearing self-voice

The subjective experience of causing an action is known as the sense of agency. Dysfunction in the sense of agency has been suggested as a cause of auditory hallucinations (AHs), an important diagnostic criterion for schizophrenia. However, agency over speech has not been extensively characterized in previous empirical studies. Here, we examine both implicit and explicit measures of the sense of agency and reveal bottom-up and top-down components that constitute self-agency during speech. The first is action-outcome causality, which is perceived based on a low-level sensorimotor process when hearing their own voice following their speech. The second component is self-voice identity, which is embedded in the acoustic quality of voice and dominantly influences agency over speech at the cognitive judgment level. Our findings provide profound insight into the sense of agency over speech and present an informative perspective for understanding aberrant experience in AHs.

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bioRxiv2020

Common brain networks between major depressive disorder and symptoms of depression that are validated for independent cohorts

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable major depressive disorder (MDD) brain network markers which would distinguish patients from healthy controls (a classifier) or would predict symptom severity (a prediction model) based on resting state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD brain network markers. The classifier achieved 70% generalization accuracy, and the prediction model moderately well predicted symptom severity for an independent validation dataset with 449 participants from 4 different imaging sites. Finally, we found common 2 functional connections between those related to MDD diagnosis and those related to depression symptoms. The successful generalization to the perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

neuroscience↗

bioRxiv2019

The self as a generative, teleological, and subjective prior: Mutually-modulated temporal agency

How can we certify our existence? Recent theoretical studies have suggested that, in the brain, the effect inversely infers the possibility of the existence of the self as the cause. While this Bayesian view of the sense of agency is widely accepted, empirical evidence in support of this theory is still lacking. The current study examined outcome-modulated agency in terms of time perception in seven experiments, with a total of 90 participants. It was hypothesized that perceptual generation, not termination, should subjectively infer the existence of the self, even though both include the same stimuli and are driven by the same teleological action. Results suggest support for the hypothesis (Experiments 1 and 2). Participants judged stronger self-agency, detected less delay, or felt shorter duration for auditory generation, compared with termination, which was driven by the same volitional key-press. Furthermore, the main experiment, Experiment 3, focused on temporal probability distributions both for action and outcome (e.g., standard deviations or relative entropy), and concluded that the observed contrast in onset/offset agency indicates a mutual or bidirectional relationship between cause and effect only during agentive action, characterized by active (i.e., teleological) generation. Finally, the concurrent theoretical models for volitional action-modulated time perception are discussed on the basis of the suggested triplet (generativity, teleology, and subjectivity) dimensions of agency.\n\nExtended abstractThe sense of agency refers to the subjective experience of generating ones own actions (Gallagher, 2000). Within the past decade, research on this subject has increased, as increased understanding of human agency could be a window into knowing how we are aware of ourselves, and possibly allowing for a better understanding of mental illnesses, like schizophrenia. However, \"free will,\" \"self-consciousness,\" and/or \"volition\" are concepts that are always difficult to empirically investigate (Frith & Haggard, 2018). Researchers do not know exactly what occurs in our sensorium during \"agentive action.\" However, three conceptions could represent genuine dimensions of agency: generativity, teleology, and subjectivity (Haggard, 2019).\n\nRecent theoretical studies have suggested that, in the brain, the effect inversely infers the possibility of the existence of the self as the cause. This Bayesian view of the sense of agency may provide an explanation for classical statements, such as \"ego cogito, ergo sum (I think, therefore I am),\" \"cogito cogito, ergo cogito sum (I think that I think, therefore I think that I am),\" \"I move, therefore I am,\" or \"I predict, therefore I am.\" (e.g., Corlett, 2017). All of these theoretical claims implicitly refer to the Bayesian \"inverse\" probability or inference (e.g., \"thought as action\"), where the effect (perception) retrospectively postdicts the cause (action), as well as the action predicting the following perception (Figure 1, including generativity, teleology, and subjectivity as triplet dimensions of agency). This bidirectional temporal relationship between action and perception can be empirically examined in terms of the \"certification of the self\" or self as prior.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC=\"FIGDIR/small/519934_fig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@e2d70dorg.highwire.dtl.DTLVardef@94b9d0org.highwire.dtl.DTLVardef@330b16org.highwire.dtl.DTLVardef@11d00a4_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO The theoretical hypothesis of cross-dependency between action and sensation in time.\n\nNote: Bayesian subjective probability ignores the order between cause and effect (i.e., the physical temporal arrow), even if we make a distinction between the two (prediction vs. postdiction). Furthermore, the posterior distributions (as a result of dissolving the pre/postdiction error) for action-timing and sensation-timing are mutually-tugged since both share the same prior (i.e., the self must be the immediate active generator, as the current study suggests). Icon made by Freepik from www.flaticon.com.\n\nC_FIG\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC=\"FIGDIR/small/519934_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@1151ce4org.highwire.dtl.DTLVardef@11bc371org.highwire.dtl.DTLVardef@1bc6393org.highwire.dtl.DTLVardef@12d48c8_HPS_FORMAT_FIGEXP M_FIG C_FIG\n\nThe current study examined effect-modulated agency in terms of time perception in seven experiments, conducted with a total of 90 participants. We hypothesized that perceptual generation, not termination, should inversely infer the self in action, even though both include the same stimuli, and are driven by the same action. Results support this hypothesis (Experiments 1 and 2). Participants judged stronger self-agency, detected less delay, or felt shorter duration for auditory generation, compared to termination, in instances driven by a key-press of his/her own volition, but may have also had different \"priors\" (i.e., self or other, as a categorical causal structure selection or model weighting). Furthermore, the main experiment, Experiment 3, focused on probability distributions both for action and outcome on the same temporal axis (e.g., standard deviations or relative entropy), and concluded that this contrast in onset/offset agency indicates the mutual or bidirectional relationship between cause and effect only during agentive action, characterized by the active generation (Figure 2). In summary, results indicate that the self is learned as a prior to being an independent agent that can immediately cause actions to occur within the environment merely through ones own volition. This interpretation is highly congruent with the literal meaning of the sense of agency and also with the theory of the triplet dimensions of agency.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC=\"FIGDIR/small/519934_fig2.gif\" ALT=\"Figure 2\">\nView larger version (30K):\norg.highwire.dtl.DTLVardef@57f98org.highwire.dtl.DTLVardef@fbf3f7org.highwire.dtl.DTLVardef@14e0bcborg.highwire.dtl.DTLVardef@e86727_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Summarized results across Experiments 1(A,B,C) and 2(A,B,C).\n\nNote: Asterisks represent the significant differences only between onset and offset conditions. Dashed arches represent the main effect of on/offset condition. Error bars represents {+/-} 1 SE. ** p < .01, * p < .05, {dagger} p < .10, see Table S2 for full ANOVA results.\n\nC_FIG\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC=\"FIGDIR/small/519934_ufig2.gif\" ALT=\"Figure 2\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@1cc466corg.highwire.dtl.DTLVardef@2375feorg.highwire.dtl.DTLVardef@17a4edorg.highwire.dtl.DTLVardef@4ceba8_HPS_FORMAT_FIGEXP M_FIG C_FIG\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@39d38org.highwire.dtl.DTLVardef@146d3d9org.highwire.dtl.DTLVardef@fe5678org.highwire.dtl.DTLVardef@1df0ffaorg.highwire.dtl.DTLVardef@19205d1_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable S2.C_FLOATNO O_TABLECAPTIONThe means and SDs of reports in each condition in Experiment 3.\n\nC_TABLECAPTION C_TBL We believe that the current study successfully observed the previously invisible relationship between action and perception in favor of advanced analysis, based on information theory, computational neuroscience (Figure 3), and theoretical discussions.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR/small/519934_fig3.gif\" ALT=\"Figure 3\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@1bc1dc5org.highwire.dtl.DTLVardef@146975borg.highwire.dtl.DTLVardef@17aed8forg.highwire.dtl.DTLVardef@1825b88_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 3.C_FLOATNO The motor, tone, and intentional binding effect in Experiment 3.\n\nNote: Dashed arches represent the main effects of factors. Error bars represents {+/-} 1 SE. ** p < .01, * p < .05, {dagger} p < .10, see Table S2 for full ANOVA results.\n\nC_FIG\n\nThis manuscript has not been published or presented elsewhere in part or in entirety. There are no conflicts of interest to declare.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC=\"FIGDIR/small/519934_ufig3.gif\" ALT=\"Figure 3\">\nView larger version (34K):\norg.highwire.dtl.DTLVardef@1477b04org.highwire.dtl.DTLVardef@1dd4b72org.highwire.dtl.DTLVardef@18438aforg.highwire.dtl.DTLVardef@1a57f7a_HPS_FORMAT_FIGEXP M_FIG C_FIG ReferencesO_BIBINTEXTCorlettP. PredictI, Therefore I Am: Perturbed Predictive Coding Under Ketamine and in Schizophrenia. O_TITLEBiological PsychiatryC_TITLE, O_VOLUMENR81C_VOLUMENR, O_FIRSTPAGE465C_FIRSTPAGE-466 (O_DATE2017C_DATE).C_BIBINTEXT\n\nO_BIBINTEXTFrithC. D., HaggardP. Volition and the Brain - Revisiting a Classic Experimental Study. O_TITLETrends NeurosciC_TITLE. O_VOLUMENR41C_VOLUMENR, O_FIRSTPAGE405C_FIRSTPAGE-407 (O_DATE2018C_DATE).C_BIBINTEXT\n\nO_BIBINTEXTGallagherS. Philosophical conceptions of the self: implications for cognitive science. O_TITLETrends Cogn. Sci.C_TITLE O_VOLUMENR4C_VOLUMENR, O_FIRSTPAGE14C_FIRSTPAGE-21 (O_DATE2000C_DATE).C_BIBINTEXT\n\nO_BIBINTEXTHaggardP. The Neurocognitive Bases of Human Volition. O_TITLEAnnu Rev Psychol. (in press)C_TITLEC_BIBINTEXT

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