Biology subjects

Iwama, S.

Publications and source records attributed to Iwama, S..

4 recordsLinked to original sources

bioRxiv2024

Enhanced human sensorimotor integration via self-modulation of the somatosensory activity

Kinesthetic motor imagery, the mental rehearsal of movement and its associated sensations1,2, activates somatosensory and motor cortices3,4. Motor imagery improves performance in neurorehabilitation5, sports6, and instrument play7. However, the mechanism that enhances performance through repetitive motor imagery remains unclear. Here, we combined individually tailored motor imagery training combined with closed-loop neurofeedback training, neurophysiology, and behavioral assessment to characterize how the training can modulate the somatosensory system and improve performance. The closed-loop training using real-time feedback of human electroencephalogram (EEG) signals enhanced participants self-modulation ability of intrinsic neural oscillations in the primary somatosensory cortex (S1) within 30 minutes. Further, the short-term reorganization in S1 was corroborated by the post-training reactivity enhancement revealed by changes in somatosensory evoked potential (SEP) amplitude of early component originating from S18. Meanwhile those derived from peripheral sensory fibers were maintained, suggesting that the closed-loop training manipulated cortical activities. Behavioral evaluation demonstrated improved performance during keyboard touch-typing indexed by resolved the speed-accuracy trade-off9. Collectively, our results provide evidence that mentally rehearsed movement during kinesthetic motor imagery induces functional reorganization of S1 activities that can contribute to performance improvement.

neuroscience↗

bioRxiv2023

An Alzheimer's disease-associated common regulatory variant in PTK2B has causal effects on microglial function

Genome-wide association studies (GWAS) are revealing an ever-growing number of genetic associations with disease, but identifying and functionally validating the causal variants underlying these associations is very challenging and has only been done for a vanishingly small number of variants. Here we validate a single nucleotide polymorphism (SNP) associated with an increased risk of Alzheimers disease (AD) in an intronic enhancer of the PTK2B gene, by engineering it into human induced pluripotent stem cells (hiPSCs). Upon differentiation to macrophages and microglia, this variant shows effects on chromatin accessibility of the enhancer and increased binding of the transcription factor CEBPB but only subtle effects on PTK2B or CLU expression. Nevertheless, this variant results in global changes to the transcriptome and phenotype of these cells. Expression of interferon gamma responsive genes including chemokine transcripts and their protein products are altered, and chemotaxis of the resulting microglial cells is affected. This variant thus causes disease-relevant transcriptomic and phenotypic changes, and we propose that it acts by altering microglia reactivity, consistent with the role of these cells in progression of AD.

neuroscience↗

bioRxiv2022

Two common issues in synchronized multimodal recordings with EEG: Jitter and Latency

Multimodal recording using electroencephalogram (EEG) and other biological signals (e.g., electromyograms, eye movement, pupil information, or limb kinematics) is ubiquitous in human neuroscience research. However, the precise time alignment of data from heterogeneous sources is limited due to variable recording parameters of commercially available research devices and experimental setups. Here, we introduced the versatility of a Lab Streaming Layer (LSL)-based application for multimodal recordings of high-density EEG and other devices such as eye trackers or hand kinematics. To introduce the benefit of recording multiple devices in a time-synchronized manner, we discuss two common issues in measuring multimodal data: jitter and latency. The LSL-based system can be used for research on precise time-alignment of datasets, such as detecting stimulus-induced transient neural responses and testing hypotheses well-formulated in time by leveraging the millisecond time resolution of the system.

neuroscience↗

bioRxiv2021

De novo brain-computer interfacing deforms manifold of populational neural activity patterns in human cerebral cortex

Human brains are capable of modulating innate activities to adapt to novel environmental stimuli; for sensorimotor cortices (SM1) this means acquisition of a rich repertoire of motor behaviors. We investigated the adaptability of human SM1 motor control by analyzing net neural population activity during the learning of brain-computer interface (BCI) operations. We found systematic interactions between the neural manifold of cortical population activities and BCI classifiers; the neural manifold was stretched by rescaling motor-related features of electroencephalograms with model-based fixed classifiers, but not with adaptive classifiers that were constantly recalibrated to user activity. Moreover, operation of a BCI based on a de novo classifier with a fixed decision boundary based on biologically unnatural features, deformed the neural manifold to be orthogonal to the boundary. These principles of neural adaptation at a macroscopic level may underlie the ability of humans to learn wide-ranging behavioral repertoires and adapt to novel environments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/450263v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@12a66c3org.highwire.dtl.DTLVardef@c090e8org.highwire.dtl.DTLVardef@698f87org.highwire.dtl.DTLVardef@4e135c_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗