Biology subjects

Tamaki, M.

Publications and source records attributed to Tamaki, M..

12 recordsLinked to original sources

bioRxiv2026

Memory transfer unfolds through rapid shifts in memory stability states during sleep in humans

Sleep benefits learning and memory. Fundamental questions remain regarding whether and how sleep transfers memories for adaptive behavior in humans. We demonstrate that declarative to procedural memory transfer occurs through rapid network reorganization and memory stability shifts in human participants. Following local processing in motor circuit during slow wave-spindle coupling in nonrapid eye movement (NREM) sleep, multiregional communication during phasic rapid-eye movement (REM) sleep enables transfer. By leveraging a newly developed time-resolved simultaneous ultrahigh-field magnetic resonance spectroscopy and polysomnography, we further reveal that memory state becomes instantaneously unstable during slow wave-spindle coupling then enters a hyperstable state during phasic-REM sleep. Thus, sleep bridges memory systems, utilizing increased instability in NREM sleep, and transferring memory through hyperstabilization in REM sleep for knowledge integration.

neuroscience↗

bioRxiv2025

Does wearable neurofeedback training improve memory aptitudes in healthy adults?--A systematic review and meta-analysis

Neurofeedback training (NFT) provides individuals with real-time feedback on their brain activity, enabling voluntary modulation. Interest in NFT for memory enhancement has surpassed the cumulative evidence in healthy adults, especially for modalities feasible outside of laboratory settings. To address this gap, this systematic review and meta-analysis focused on electroencephalography (EEG) and functional near- infrared spectroscopy (fNIRS), both of which are portable and widely accessible. Randomized controlled trials published between January 1990 and September 2022 were retrieved from PubMed, Scopus, Web of Science, and APA PsycInfo. Of the 44 eligible studies, 24 reported sufficient data for inclusion in the meta-analysis. Using a random-effects model, we found that NFT produced a small-to-moderate improvement in memory performance (standardized mean difference = 0.28; 95% confidence interval = 0.065-0.48; t(11.9) = 2.86; p = 0.014), with moderate heterogeneity. No publication bias was detected. Subgroup meta-analyses revealed significant effects in younger adults, for EEG-based protocols, and in tasks assessing verbal and short-term memory tasks. Meta-regression identified a positive association between daily session duration and effect size, with sessions longer than 30 minutes more likely to produce positive effects. As effects also varied by targeted brain regions and EEG frequency bands used for neurofeedback, protocol differences likely contributed to the observed variability in outcomes. Long- term follow-up is warranted to determine the persistence of NFT effects.

neuroscience↗

bioRxiv2025

Luteal-phase resistance training enhances nocturnal heat dissipation and delta power during sleep

Study ObjectivesThis study examined the effects of resistance training on sleep architecture, physiological heat dissipation, and {delta} power in young adult women during the follicular and luteal phases of the menstrual cycle. MethodsNine healthy young women participated in a four-condition crossover protocol comprising (1) follicular phase non-exercise, (2) follicular phase exercise, (3) luteal phase non-exercise, and (4) luteal phase exercise. The exercise condition consisted of 30 minutes of resistance training at 70% of one-repetition maximum performed during the day. During each night, electroencephalography, body temperature, and core body temperature were measured in the home environment. The distal-proximal body temperature gradient (DPG), which is a validated indicator of heat dissipation, was calculated ResultsResistance training enhanced heat dissipation, as reflected by increased DPG values, and increased the proportion of stage N3 sleep during both menstrual cycle phases, with more pronounced effects during the luteal phase. Sleep from bedtime to wake time was divided into four equal segments. Under the luteal phase with exercise, the appearance of stage N3, {delta} power, and the DPG were elevated in the mid-to-late segments of sleep. ConclusionsThese findings suggest that daytime resistance training promotes nocturnal deep sleep and facilitates thermoregulatory heat loss, as indicated by an increased DPG, particularly during the luteal phase when thermoregulation is less stable than the follicular phase. This training may represent a practical intervention to improve sleep quality and physiological recovery in women across different phases of the menstrual cycle. STATEMENT OF SIGNIFICANCEWomen often experience sleep disturbances during the luteal phase of the menstrual cycle, but the physiological mechanisms and effective interventions remain unclear. This study shows that daytime resistance training enhances nighttime heat dissipation and increases slow-wave sleep during this phase. These findings suggest that exercise is a practical approach to alleviate menstrual cycle-related sleep issues. By clarifying how exercise interacts with thermoregulation and sleep across the cycle, this work contributes to understanding female-specific sleep physiology and supports the development of non-pharmacological strategies to improve womens sleep health in women. Future research should examine the long-term effects of daytime resistance training and compare different exercise modalities across diverse populations.

neuroscience↗

bioRxiv2025

Concurrent multimodal measurement of excitation and inhibition shows that EEG-based estimates are linked to the ratio of glutamate to GABA

Neural excitation/inhibition (E/I) ratio is dynamically regulated on multiple timescales. Adaptive changes in E/I ratio can support healthy development, learning, and cognition, while disordered E/I ratio has been implicated in neurodevelopmental disorders, neurodegenerative disorders, and states of impaired vigilance. There has been growing interest in inferring E/I ratio from efficient and noninvasive measurements such as electroencephalography (EEG), and several algorithms have been proposed to estimate E/I ratio from EEG. Despite promising results, there has been a lack of validation studies testing the underlying neurochemical changes leading to increased or decreased EEG-based E/I ratio. Here, using concurrent EEG and magnetic resonance spectroscopy (MRS) for over an hour, we assessed which algorithm of EEG-based E/I ratio best matched with MRS-based E/I ratio in humans of both sexes. The MRS-based E/I ratio was obtained by the ratio of glutamate concentration to GABA concentration. We applied 10 candidate indices of EEG-based E/I ratio using four approaches in several spontaneous frequency bands. Uniquely, we quantified the associations between the EEG-based E/I ratio and MRS-based E/I ratio separately for between-subjects and within-subjects variations. We found that each EEG-based E/I algorithm showed reliable and positive associations with MRS-based E/I, and especially EEG-based E/I ratio in alpha band with a criticality theory based approach showed the best association to the MRS-based E/I ratio. While these associations were evident for between-subjects comparisons, they were quite weak for within-subjects comparisons. These results suggest that EEG-based E/I algorithms are likely to reflect, at least in part, relative concentrations of glutamate and GABA.

neuroscience↗

bioRxiv2024

Human deep sleep facilitates faster cerebrospinal fluid dynamics linked to brain oscillations for sleep homeostasis and memory

How sleep maintains our healthy brain function has remained one of the biggest mysteries in neuroscience, medical settings, and daily lives. While cerebrospinal fluid (CSF) during sleep have been implicated in metabolic waste reduction in animals, how CSF dynamics are driven in the healthy human brain during deep sleep remains elusive. A myriad of research has shown that crucial cognitive processing manifests in slow wave and rapid-eye movement (REM) sleep, suggesting that a key to maintaining brain functions lies in deep sleep. By leveraging a simultaneous sparse-fMRI and polysomnography method, we demonstrate that deep sleep-specific faster CSF dynamics are associated with spontaneous brain oscillations in healthy young human participants. Slow waves and sleep spindles during slow-wave sleep and rapid eye movements and sawtooth waves during rapid eye movement (REM) sleep are tightly linked to low-amplitude faster CSF fluctuations. In contrast, slow waves during light sleep and arousals produced large but slower CSF signal changes. Furthermore, CSF signals are significantly faster in frequency during deep than light sleep. These brain oscillations during light and deep sleep recruited essentially different brain networks, with deep sleep involving memory and homeostatic circuits. Thus, human deep sleep has a unique way of enabling faster CSF dynamics that are distinctive from arousal mechanisms. Significance StatementSleep is indispensable to our life, but its functions remain a significant mystery in the field of neuroscience. One of the most enigmatic issues in sleep is whether and how sleep regulates the CSF. The present study demonstrates deep sleep-specific faster CSF dynamics time locked to sleep brain oscillations in healthy young human participants. Slow waves and sleep spindles during slow-wave sleep and rapid eye movements and sawtooth waves during REM sleep are tightly linked to CSF fluctuations, contributing to faster CSF signals. Our results consistently demonstrate that human deep sleep has a unique way of enabling faster CSF dynamics that are distinctive from arousal mechanisms.

neuroscience↗

bioRxiv2024

First-night effect reduces the beneficial effects of sleep on visual plasticity and modifies the underlying neurochemical processes

Individuals experience difficulty falling asleep in a new environment, termed the first night effect (FNE). However, the impact of the FNE on sleep-induced brain plasticity remains unclear. Here, using a within-subject design, we found that the FNE significantly reduces visual plasticity during sleep in young adults. Sleep-onset latency (SOL), an indicator of the FNE, was significantly longer during the first sleep session than the second session, confirming the FNE. We assessed performance gains in visual perceptual learning after sleep and increases in the excitatory-to-inhibitory neurotransmitter (E/I) ratio in early visual areas during sleep using magnetic resonance spectroscopy and polysomnography. These parameters were significantly smaller in sleep with the FNE than in sleep without the FNE; however, these parameters were not correlated with SOL. These results suggest that while the neural mechanisms of the FNE and brain plasticity are independent, sleep disturbances temporarily block the neurochemical process fundamental for brain plasticity.

neuroscience↗

bioRxiv2020

Visual perceptual learning of a primitive feature in human V1/V2 as a result of unconscious processing, revealed by Decoded fMRI Neurofeedback (DecNef)

While numerous studies have shown that visual perceptual learning (VPL) occurs as a result of exposure to a visual feature in a task-irrelevant manner, the underlying neural mechanism is poorly understood. In a previous psychophysical study, subjects were repeatedly exposed to a task-irrelevant global motion display that induced the perception of not only the local motions but also a global motion moving in the direction of the spatiotemporal average of the local motion vectors. As a result, subjects enhanced their sensitivity only to the local moving directions, suggesting that early visual areas (V1/V2) that process local motions are involved in task-irrelevant VPL. However, this hypothesis has never been examined by directly examining the involvement of early visual areas (V1/V2). Here, we employed a decoded neurofeedback technique (DecNef) using functional magnetic resonance imaging. During the DecNef training, subjects were trained to induce the activity patterns in V1/V2 that were similar to those evoked by the actual presentation of the global motion display. The DecNef training was conducted with neither the actual presentation of the display nor the subjects awareness of the purpose of the experiment. As a result, subjects increased the sensitivity to the local motion directions but not specifically to the global motion direction. The training effect was strictly confined to V1/V2. Moreover, subjects reported that they neither perceived nor imagined any motion during the DecNef training. These results together suggest that that V1/V2 are sufficient for exposure-based task-irrelevant VPL to occur unconsciously. Significance StatementWhile numerous studies have shown that visual perceptual learning (VPL) occurs as a result of exposure to a visual feature in a task-irrelevant manner, the underlying neural mechanism is poorly understood. Previous psychophysical experiments suggest that early visual areas (V1/V2) are involved in task-irrelevant VPL. However, this hypothesis has never been examined by directly examining the involvement of early visual areas (V1/V2). Here, using decoded fMRI neurofeedback, the activity patterns similar to those evoked by the presentation of a complex motion display were repeatedly induced only in early visual areas. The training sensitized only the local motion directions and not the global motion direction, suggesting that V1/V2 are involved in task-irrelevant VPL.

neuroscience↗

bioRxiv2020

Sleep-dependent offline performance gain in visual perceptual learning is consistent with a learning-dependent model

Are the sleep-dependent offline performance gains of visual perceptual learning (VPL) consistent with a use-dependent or learning-dependent model? Here, we found that a use-dependent model is inconsistent with the offline performance gains in VPL. In two training conditions with matched visual usages, one generated VPL (learning condition), while the other did not (interference condition). The use-dependent model predicts that slow-wave activity (SWA) during posttraining NREM sleep in the trained region increases in both conditions, in correlation with offline performance gains. However, compared with those in the interference condition, sigma activity, not SWA, during NREM sleep and theta activity during REM sleep, source-localized to the trained early visual areas, increased in the learning condition. Sigma activity correlated with offline performance gain. These significant differences in spontaneous activity between the conditions suggest that there is a learning-dependent process during posttraining sleep for the offline performance gains in VPL.

neuroscience↗

bioRxiv2019

Opponent neurochemical and functional processing in NREM and REM sleep in visual learning

Sleep is beneficial for learning. However, whether NREM or REM sleep facilitates learning, whether the learning facilitation results from plasticity increases or stabilization and whether the facilitation results from learning-specific processing are all controversial. Here, after training on a visual task we measured the excitatory and inhibitory neurochemical (E/I) balance, an index of plasticity in human visual areas, for the first time, while subjects slept. Off-line performance gains of presleep learning were associated with the E/I balance increase during NREM sleep, which also occurred without presleep training. In contrast, increased stabilization was associated with decreased E/I balance during REM sleep only after presleep training. These indicate that the above-mentioned issues are not matters of controversy but reflect opposite neurochemical processing for different roles in learning during different sleep stages: NREM sleep increases plasticity leading to performance gains independently of learning, while REM sleep decreases plasticity to stabilize learning in a learning-specific manner.

neuroscience↗

bioRxiv2019

Reward does not facilitate visual perceptual learning until sleep occurs

A growing body of evidence indicates that visual perceptual learning (VPL) is enhanced by reward provided during training. Another line of studies has shown that sleep following training also plays a role in facilitating VPL, an effect known as the offline performance gain of VPL. However, whether the effects of reward and sleep interact on VPL remains unclear. Here, we show that reward interacts with sleep to facilitate offline performance gains of VPL. First, we demonstrated a significantly larger offline performance gain over a 12-h interval including sleep in a reward group than that in a No-reward group. However, the offline performance gains over the 12-h interval without sleep were not significantly different with or without reward during training, indicating a crucial interaction between reward and sleep in VPL. Next, we tested whether neural activations during posttraining sleep were modulated after reward was provided during training. Reward provided during training enhanced REM sleep time, increased oscillatory activities for reward processing in the prefrontal region during REM sleep, and inhibited neural activation in the untrained region in early visual areas in NREM and REM sleep. The offline performance gains were significantly correlated with oscillatory activities of visual processing during NREM sleep and reward processing during REM sleep in the reward group but not in the No-reward group. These results suggest that reward provided during training becomes effective during sleep, with excited reward processing sending inhibitory signals to suppress noise in visual processing, resulting in larger offline performance gains over sleep.\n\nSignificance statementIndependent lines of research have shown that visual perceptual learning (VPL) is improved by reward or sleep. Here, we show that reward provided during training increased offline performance gains of VPL over sleep. Moreover, during posttraining sleep, reward was associated with longer REM sleep, increased activity in reward processing in the prefrontal region during REM sleep, and decreased activity in the untrained region of early visual areas during NREM and REM sleep. Offline performance gains were correlated with modulated oscillatory activity in reward processing during REM sleep and visual processing during NREM sleep. These results suggest that reward provided during training becomes effective on VPL through the interaction between reward and visual processing during sleep after training.

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bioRxiv2019

Night watch during REM sleep for the first-night effect

We experience disturbed sleep in a new place, and this effect is known as the first-night effect (FNE) in sleep research. We previously demonstrated that the FNE was associated with a protective night-watch system during NREM sleep in one hemisphere, which is shown as interhemispheric asymmetry in sleep depth in the default-mode network (DMN), and interhemispheric asymmetry in increased vigilance to monitor external stimuli. The present study investigated whether rapid eye movement (REM) sleep exhibited a form similar to a night-watch system during NREM sleep. First, we tested whether theta activity, which is an index of the depth of REM sleep, showed interhemispheric asymmetry in association with the FNE, by source-localizing to the DMN. However, interhemispheric asymmetry in theta activity during REM sleep was not found in association with the FNE. Next, we tested whether vigilance, as measured by evoked brain responses to deviant sounds, was increased in one hemisphere and showed interhemispheric asymmetry in association with the FNE during REM sleep. Because vigilance is different between the phasic period where rapid eye movements occur and the tonic period where rapid eye movements do not occur during REM sleep, REM sleep was split into phasic and tonic periods for measurements of evoked brain responses. While the evoked brain responses are generally small during the phasic period without the FNE, we found that the evoked brain response was significantly augmented by the FNE during the phasic period. In contrast, the evoked brain response during the tonic period did not differ by the presence of the FNE. Interhemispheric asymmetry in brain responses was not found during the phasic or tonic periods. These results suggest that a night-watch system for the FNE appears as interhemispheric asymmetry in sleep depth and vigilance during NREM sleep, but it appears as increased vigilance in both hemispheres during the phasic period, when vigilance to external stimuli is generally reduced without the FNE, during REM sleep. Therefore, a night-watch system associated with the FNE may be subserved by different neural mechanisms during NREM and REM sleep.

neuroscience↗

bioRxiv2018

Trained-feature specific offline learning in an orientation detection task

It has been suggested that sleep provides additional enhancement of visual perceptual learning (VPL) acquired before sleep, termed offline performance gains. A majority of the studies that found offline performance gains of VPL used discrimination tasks including the texture discrimination task (TDT). This makes it questionable whether offline performance gains on VPL are generalized to other visual tasks. The present study examined whether a Gabor orientation detection task, which is a standard task in VPL, shows offline performance gains. In Experiment 1, we investigated whether sleep leads to offline performance gains on the task. Subjects were trained with the Gabor orientation detection task, and re-tested it after a 12-hr interval that included either nightly sleep or only wakefulness. We found that performance on the task improved to a significantly greater degree after the interval that included sleep and wakefulness than the interval including wakefulness alone. In addition, offline performance gains were specific to the trained orientation. In Experiment 2, we tested whether offline performance gains occur by a nap. Also, we tested whether spontaneous sigma activity in early visual areas during non-rapid eye movement (NREM) sleep, previously implicated in offline performance gains of TDT, was associated with offline performance gains of the task. A different group of subjects had a nap with polysomnography. The subjects were trained with the task before the nap and re-tested after the nap. The performance of the task improved significantly after the nap only on the trained orientation. Sigma activity in the trained region of early visual areas during NREM sleep was significantly larger than in the untrained region, in correlation with offline performance gains. These aspects were also found with VPL of TDT. The results of the present study demonstrate that offline performance gains are not specific to a discrimination task such as TDT, and can be generalized to other forms of VPL tasks, along with trained-feature specificity. Moreover, the present results also suggest that sigma activity in the trained region of early visual areas plays an important role in offline performance gains of VPL of detection as well as discrimination tasks.

neuroscience↗