Biology subjects

Osu, R.

Publications and source records attributed to Osu, R..

4 recordsLinked to original sources

bioRxiv2022

Brain Activity During Constraint Relaxation in the Insight Problem-Solving Process: An fNIRS Study

People solve insight problems that they encounter daily with a sudden sense of aha! to reach a solution. Chunk decomposition, which decomposes the factors of the problem, and constraint relaxation, which manipulates filters to organize the information necessary to solve the problem, are important in insight problem-solving. Although there have been many studies on brain activity during chunk decomposition, few have examined brain activity during constraint relaxation. Particularly, no study has observed the changes over time due to constraint relaxation during insight problem-solving. This study used a slot machine task as an insight problem to measure brain activity using functional Near-Infrared Spectroscopy (fNIRS), and eye movements to estimate constraint relaxation. The results showed that the right dorsolateral prefrontal cortex (DLPFC) and right superior temporal gyrus (STG) were activated over time in participants in whom constraint relaxation was induced. The right inferior temporal gyrus (ITG) of participants who were able to solve the insight problem after constraint relaxation was also activated. The analysis of brain activity during constraint relaxation in insight problem-solving may be useful for advancing research on the aha! phenomenon and creativity.

neuroscience↗

bioRxiv2021

The Relationship between Stability of Interpersonal Coordination and Inter-Brain EEG Synchronization during Anti-phase Tapping

Inter-brain synchronization is enhanced when individuals perform rhythmic interpersonal coordination tasks, such as playing instruments in music ensembles. Experimentally, synchronization has been shown to correlate with the performance of joint tapping tasks. However, it is unclear whether inter-brain synchronization is related to the stability of interpersonal coordination represented as the standard deviation of relative phase (SDRP). In this study, we simultaneously recorded electroencephalograms of two paired individuals during anti-phase tapping in three speed conditions: slow (reference inter-tap interval [ITI]: 0.5 s), fast (reference ITI: 0.25 s), and free (preferred ITI). We calculated the inter-brain synchronization within six regions of interest: frontal, central, left/right temporal, parietal, and occipital regions. We found that synchronization of the central-temporal regions was positively correlated with SDRP in the theta and alpha bands, while synchronization of the frontal-frontal and frontal-central was positively correlated with SDRP in the beta band. These results demonstrate that inter-brain synchronization occurs only when task requirements are high, and that it increases with the instability of the coordination. This may be explained by the stronger mutual prediction required in unstable coordination than that in stable coordination, which increases inter-brain synchronization.

neuroscience↗

bioRxiv2021

Identifying Brain Regions Related to Word Prediction During Listening to Japanese Speech by Combining a LSTM Language Model and MEG

Recently, a neuroscientific approach has revealed that humans understand language while subconsciously predicting the next word from the preceding context. Most studies on human word prediction have investigated the correlations between brain activity while reading or listening to sentences on functional magnetic resonance imaging (fMRI) and the predictive difficulty of each word in a sentence calculated by the N-gram language model. However, because of its low temporal resolution, fMRI is not optimal for identifying the changes in brain activity that accompany language comprehension. In addition, the N-gram language model is a simple computational structure that does not account for the structure of the human brain. Furthermore, it is necessary for humans to retain information prior to the N-1 word in order to form a contextual understanding of a presented story. Therefore, in the present study, we measured brain activity using magnetoencephalography (MEG), which has a higher temporal resolution than fMRI, and calculated the prediction difficulty of words using a long short-term memory language model (LSTMLM), which is based on a neural network inspired by the structure of the human brain and has longer information retention than the N-gram language model. We then identified the brain regions involved in language prediction during Japanese-language speech listening using encoding and decoding analyses. In addition to surprisal-related regions revealed in previous studies, such as the superior temporal gyrus, fusiform gyrus, and temporal pole, we also found relationships between surprisal and brain activity in other regions, including the insula, superior temporal sulcus, and middle temporal gyrus, which are believed to be involved in longer-term, sentence-level cognitive processing.

neuroscience↗

bioRxiv2020

Hierarchical motor adaptations negotiate failures during force field learning

Humans have the amazing ability to learn the dynamics of the body and environment to develop motor skills. Traditional motor studies using arm reaching paradigms have viewed this ability as the process of internal model adaptation. However, the behaviors have not been fully explored in the case when reaches fail to attain the intended target. Here we examined human reaching under two force fields types; one that induces failures (i.e., target errors), and the other that does not. Our results show the presence of a distinct failure-driven adaptation process that enables quick task success after failures, and before completion of internal model adaptation, but that can result in persistent changes to the undisturbed trajectory. These behaviors can be explained by considering a hierarchical interaction between internal model adaptation and the failure-driven adaptation of reach direction. Our findings suggest that movement failure is negotiated using hierarchical motor adaptations by humans.

neuroscience↗