Tactile spatial attention enhances gamma-band activity in somatosensory cortex and reduces low-frequency activity in parieto-occipital areas

Passive mapping of hand motor cortex across altered states of consciousness

OBJECTIVE

To evaluate the ability of median nerve stimulation (MNS)-induced high gamma band (HGB) activity in mapping the hand motor cortex at different states of consciousness.

METHODS

Five patients undergoing awake craniotomy were recruited. MNS-induced electrocorticographic signals were recorded from awake to anesthetic states, with the loss of consciousness (LOC) session divided into three stages (LOC1, LOC2, and LOC3) based on conscious level. HGB signals were analyzed to localize hand motor cortex. Linear models were applied to analyze HGB dynamics during LOC.

RESULTS

The sensitivity of hand motor cortex mapping based on HGB average envelope at short-latency period was 100%, 96.67%±3.33%, 83.47%±8.19%, and 82.22%±11.44% for the awake, LOC1, LOC2 and LOC3 stages. The sensitivity for HGB average envelope at long-latency period was 92.67%±4.52%, 90.85%±4.13%, 72.27%±17.07%, and 40.53%±12.82% across the same stages. The sensitivity based on HGB average power at short-latency period decreased from 100% in awake stage to 72.83%±12.95%, 48.11%±15.95%, and 21.12%±5.70% across LOC stages. The sensitivity for HGB average power at long-latency period dropped from 92.67%±4.52% in awake stage to 70.94%±10.79%, 58.37%±17.49%, and 25.71%±14.95% in the subsequent LOC stages. The slope coefficient of the simple linear model for long-latency average envelope was significantly smaller than that for short-latency. In the linear mixed effects model, the Condition × Sliding Window estimate coefficient was -0.794.

CONCLUSION

In awake state, HGB average envelope and average power both effectively localized hand motor cortex. With declining consciousness, the mapping ability of average power significantly deteriorated, while the mapping ability of short-latency average envelope remained relatively stable.

Distinct age-related alterations in alpha-beta neural oscillatory activity during verbal working memory encoding in children and adolescents

Emerging imaging studies of working memory (WM) have identified significant WM-related oscillatory events that are unique to each phase of working memory (e.g. encoding, maintenance). Although many previous imaging studies have shown age-related changes within the frontoparietal network when performing a WM task, understanding of the age-related changes in the oscillatory dynamics underlying each phase of WM during development and their relationships to other cognitive function is still in its infancy. To this end, we enrolled a group of 74 typically-developing youths aged 7-15 years to perform a letter-based Sternberg WM task during magnetoencephalography. Trial-wise data were transformed into the time-frequency domain, and significant oscillatory responses during the encoding and maintenance phases of the task were independently imaged using beamforming. Our results revealed widespread age-related power differences in alpha-beta oscillatory activity during encoding throughout left frontal, parietal, temporal, occipital and cerebellar regions. By contrast, age-related differences in maintenance-related activity were limited to a small area in the superior temporal gyrus and parieto-occipital regions. Follow-up exploratory factor analysis of age-related encoding alpha-beta activity revealed two distinct factors, and these factors were each found to significantly mediate age-related improvements in both verbal and non-verbal cognitive ability. Additionally, late maintenance alpha activity was related to reaction time on the task. Taken together, our results indicate that the neural dynamics in the alpha and beta bands are uniquely sensitive to age-related changes throughout this developmental period and are related to both task performance and other aspects of cognitive development. KEY POINTS: Understanding of the age-related changes in neural oscillatory dynamics serving verbal working memory function is in its infancy. This study identified the age-related neural alterations during each phase of working memory processing in youths. Developmental differences during working memory processing were primarily isolated to alpha-beta activity during the encoding phase. Alpha-beta activity during encoding significantly mediated age-related improvements in both verbal and non-verbal ability. This study establishes new brain-behaviour relationships linking working memory function to other aspects of cognitive development.

Spatial attention modulates time perception on the human torso

Time perception is a fundamental aspect of human life, and is influenced and regulated by cognitive and sensory processes. For instance, spatial attention is found to modulate temporal judgments when resources are allocated to a specific stimulus location in vision and audition. However, it is unclear to what extent the attentional effects observed in vision and audition can be generalized to the tactile modality. Here, we study the effects of attentional cues on the time perception of tactile stimuli presented on the human torso. Across four experiments, we examined (1) the impact of visual versus tactile spatial cues, (2) the modulation of time perception by dynamic versus static tactile cues, (3) the role of spatial congruency between cue and target locations (front vs. back of the torso), and (4) the influence of cue-target intervals. Participants performed temporal bisection tasks, judging whether the vibrations following the cues were closer to short or long anchor durations. Tactile cues expanded the perceived duration of subsequent stimuli, with dynamic cues having a greater effect than static ones. While no congruency effects were observed for left and right torso locations, front-back congruency enhanced time expansion. The attentional effect peaked at a 100-ms cue-target interval. We conclude that the time-expanding effects of spatial attention extend to tactile stimuli on the human torso given that time expansion follows principles known from spatial attention.

A neuroadaptive interface shows intentional control alters the experience of time

A reliable experience of time is critical for perception and action in the present, for accurately remembering our past, and for successfully planning a future. Theories of time perception commonly assume a central mechanism keeps time by providing a relatively independent, internal clock. Recent work, however, shows imaginary self-movements alter subjective time, suggesting a critical role for action in temporal cognition. To test the hypothesis that time perception derives from the relationship between action and perception, we designed a neuroadaptive interface operating on imaginary movement to visualize movement through virtual reality. EEG activity was classified online as reflecting accelerating movement or static imagery, which was then used in providing feedback for adapting the velocity of optical flow presented in a star field to enable neuroadaptive control. Two cybernetic experiments were conducted to determine how neuroadaptivity in the relation between action and perception affected temporal perception in the verbal time estimation task. In particularly, we contrasted neuroadaptive feedback (e.g. imagined running > visual acceleration) with non-adaptive (imagined standing > visual acceleration) and pseudoadaptive (sham) feedback conditions. Movement imagery biased estimated duration while intentional control increased judgements of the passage of time. We conclude that perception and imaginary action co-determine temporal cognition. Furthermore, the relationship between perception and action-our evaluation of perceived movement as intentionally produced-alters the subjective experience of time. Finally, we discuss the potential for our novel, neuroadaptive methodology as an investigative tool for temporal disturbances observed in psychopathology.

Effect of Different Frequencies of Transcutaneous Electrical Acupoint Stimulation (TEAS) on EEG Source Localization in Healthy Volunteers: A Semi-Randomized, Placebo-Controlled, Crossover Study

Background/Objectives: Transcutaneous electrical acupoint stimulation (TEAS), also known as transcutaneous electroacupuncture stimulation, delivers electrical pulses to the skin over acupuncture points ("acupoints") via surface electrodes. Electroencephalography (EEG) is an important tool for assessing the changes in the central nervous system (CNS) that may result from applying different TEAS frequencies peripherally-i.e., acting via the peripheral nervous system (PNS)-and determining how these influence cerebral activity and neural plasticity. Methods: A total of 48 healthy volunteers were allocated in a semi-randomized crossover study to receive four different TEAS frequencies: 2.5 pulses per second (pps); 10 pps; 80 pps; and sham (160 pps at a low, clinically ineffective amplitude). TEAS was applied for 20 min to each hand at the acupuncture point Hegu (LI4). The EEG was recorded during an initial 5 min baseline recording, then during TEAS application, and after stimulation for a further 15 min, separated into three periods of 5 min (initial, intermediate, and final) in order to assess post-stimulation changes. Source localization analysis was conducted for the traditional five EEG frequency bands: delta (0.1-3.9 Hz), theta (4-7.9 Hz), alpha (8-13 Hz), beta (14-30 Hz), and gamma (30.1-45 Hz). Results: Within-group source localization analyses of EEG data showed that during the initial 5 min post-stimulation, theta oscillations in the 2.5 pps TEAS group increased over the parahippocampal gyrus (t = 4.42, p < 0.01). The 10 pps TEAS group exhibited decreased alpha rhythms over the inferior parietal gyrus (t = -4.20, p < 0.05), whereas the sham (160 pps) TEAS group showed decreased delta rhythms over the postcentral gyrus (t = -3.97, p < 0.05). During the intermediate 5 min post-stimulation, the increased theta activity over the left parahippocampal gyrus (BA27) remained in the 2.5 pps TEAS group (t = 3.97, p < 0.05). However, diminished alpha rhythms were observed in the 10 pps TEAS group over the postcentral gyrus (t = -4.20, p < 0.01), as well as in the delta rhythms in the sham (160 pps) TEAS group in the same area (t = -4.35, p < 0.01). In the final 5 min post-stimulation, reduced alpha rhythms were exhibited over the insula in the 10 pps TEAS group (t = -4.07, p < 0.05). Interaction effects of condition by group demonstrate decreased alpha rhythms in the 10 pps TEAS group over the supramarginal gyrus during the initial 5 min post-stimulation (t = -4.31, p < 0.05), and decreased delta rhythms over the insula in the sham TEAS group during the final 5 min post-stimulation (t = -4.42, p < 0.01). Conclusions: This study revealed that low TEAS frequencies of 2.5 pps and 10 pps modulate theta and alpha oscillations over the brain areas related to emotional and attentional processes driven by external stimuli, as well as neural synchronization of delta rhythms in the sham group in brain areas related to stimulus expectation at baseline. It is hoped that these findings will stimulate further research in order to evaluate such TEAS modulation effects in clinical patients.

Large-scale interactions in predictive processing: oscillatory versus transient dynamics

How do the two main types of neural dynamics, aperiodic transients and oscillations, contribute to the interactions between feedforward (FF) and feedback (FB) pathways in sensory inference and predictive processing? We discuss three theoretical perspectives. First, we critically evaluate the theory that gamma and alpha/beta rhythms play a role in classic hierarchical predictive coding (HPC) by mediating FF and FB communication, respectively. Second, we outline an alternative functional model in which rapid sensory inference is mediated by aperiodic transients, whereas oscillations contribute to the stabilization of neural representations over time and plasticity processes. Third, we propose that the strong dependence of oscillations on predictability can be explained based on a biologically plausible alternative to classic HPC, namely dendritic HPC.

Involvement of muscarinic acetylcholine receptor-mediated cholinergic neurotransmission in TMS-EEG responses

The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a valuable tool for investigating brain functions in health and disease. However, the detailed neural mechanisms underlying TMS-EEG responses, including TMS-evoked EEG potentials (TEPs) and TMS-induced EEG oscillations (TIOs), remain largely unknown. Combining TMS-EEG with pharmacological interventions provides a unique opportunity to elucidate the roles of specific receptor-mediated neurotransmissions in these responses. Here, we investigated the involvement of muscarinic acetylcholine receptor (mAChR)-mediated cholinergic neurotransmission in TMS-EEG responses by evaluating the effects of mAChR antagonists on TEPs and TIOs in twenty-four healthy participants using a randomized, placebo-controlled crossover design. TEPs and TIOs were measured before and after administering a single oral dose of scopolamine (a non-selective mAChR antagonist), biperiden (an M1 mAChR antagonist), or placebo, with TMS targeting the left medial prefrontal cortex (mPFC), angular gyrus (AG), and supplementary motor area (SMA). The results indicated that mAChR-mediated cholinergic neurotransmission played a role in TEPs, but not TIOs, in a target-specific manner. Specifically, scopolamine significantly increased the amplitude of a local TEP component between approximately 40 and 63 ms post-stimulus when TMS was applied to the SMA, but not the mPFC or AG. Biperiden produced a similar but less pronounced effect. Importantly, the effects of these mAChR antagonists on TEPs were independent of those on sensory-evoked EEG potentials caused by TMS-associated sensory stimulation. These findings expand our understanding of TMS-EEG physiology, providing insights for its application in physiological and clinical research.

The Brain Waves During Reaching Tasks in People with Subacute Low Back Pain: A Cross-Sectional Study

Subacute low back pain (sLBP) is a critical transitional phase between acute and chronic stages and is key in determining the progression to chronic pain. While persistent pain has been linked to changes in brain activity, studies have focused mainly on acute and chronic phases, leaving neural changes during the subacute phase-especially during movement-under-researched. This cross-sectional study aimed to investigate changes in brain activity and the impact of pain intensity in individuals with sLBP during rest and reaching movements. Using a 28-electrode EEG, we measured motor-related brain waves, including theta, alpha, beta, and gamma oscillations. Transitioning from rest to movement phases resulted in significant reductions (> 80%) in mean power across all frequency bands, indicating dynamic brain activation in response to movement. Furthermore, pain intensity was significantly correlated with brain wave activity. During rest, pain intensity was positively correlated with alpha oscillation activity in the central brain area (r = 0.40, p < 0.05). In contrast, during movement, pain intensity was negatively correlated with changes in brain activity (r = -0.36 to -0.40, p < 0.05). These findings suggest that pain influences brain activity differently during rest and movement, underscoring the impact of pain levels on neural networks related to the sensorimotor system in sLBP and highlighting the importance of understanding neural changes during this critical transitional phase.

Interactions of transcranial magnetic stimulation with brain oscillations: a narrative review

Brain responses to transcranial magnetic stimulation (TMS) can be recorded with electroencephalography (EEG) and comprise TMS-evoked potentials and TMS-induced oscillations. Repetitive TMS may entrain endogenous brain oscillations. In turn, ongoing brain oscillations prior to the TMS pulse can influence the effects of the TMS pulse. These intricate TMS-EEG and EEG-TMS interactions are increasingly attracting the interest of researchers and clinicians. This review surveys the literature of TMS and its interactions with brain oscillations as measured by EEG in health and disease.

Neurophysiological principles underlying predictive coding during dynamic perception-action integration

A major concept in cognitive neuroscience is that brains are "prediction machines". Yet, conceptual frameworks on how perception and action become integrated still lack the concept of predictability and it is unclear how neural processes may implement predictive coding during dynamic perception-action integration. We show that distinct neurophysiological mechanisms of nonlinearly directed connectivities in the theta and alpha band between cortical structures underlie these processes. During the integration of perception and motor codes, especially theta band activity in the insular cortex and temporo-hippocampal structures is modulated by the predictability of upcoming information. Here, the insular cortex seems to guide processes. Conversely, the retrieval of such integrated perception-action codes during actions heavily relies on alpha band activity. Here, directed top-down influence of alpha band activity from inferior frontal structures on insular and temporo-hippocampal structures is key. This suggests that these top-down effects reflect attentional shielding of retrieval processes operating in the same neuroanatomical structures previously involved in the integration of perceptual and motor codes. Through neurophysiology, the present study connects predictive coding mechanisms with frameworks specifying the dynamic integration of perception and action.

Firing rate models for gamma oscillations in I-I and E-I networks

Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional Wilson-Cowan-like models, even when extended to include an explicit dynamic synaptic activation variable, are found unable to capture some dynamics such as Interneuronal Network Gamma oscillations (ING). Use of an explicit delay is helpful in simulations at the expense of complicating mathematical analysis. We resolve this issue by introducing a dynamic variable, u, that acts as an effective delay in the negative feedback loop between firing rate (r) and synaptic gating of inhibition (s). In effect, u endows synaptic activation with second order dynamics. With linear stability analysis, numerical branch-tracking and simulations, we show that our r-u-s rate model captures some key qualitative features of spiking network models for ING. We also propose an alternative formulation, a v-u-s model, in which mean membrane potential v satisfies an averaged current-balance equation. Furthermore, we extend the framework to E-I networks. With our six-variable v-u-s model, we demonstrate in firing rate models the transition from Pyramidal-Interneuronal Network Gamma (PING) to ING by increasing the external drive to the inhibitory population without adjusting synaptic weights. Having PING and ING available in a single network, without invoking synaptic blockers, is plausible and natural for explaining the emergence and transition of two different types of gamma oscillations.

Neuro-Muscular Responses Adaptation to Dynamic Changes in Grip Strength

Precise control of strength is of significant importance in upper limb functional rehabilitation. Understanding the neuro-muscular response in strength regulation can help optimize the rehabilitation prescriptions and facilitate the relative training process for recovery control. This study aimed to investigate the inherent characteristics of neural-muscular activity during dynamic hand strength adjustment. Four dynamic grip force tracking modes were set by manipulating different magnitude and speed of force variations, and thirteen healthy young individuals took participation in the experiment. Electroencephalography were recorded in the contralateral sensorimotor cortex area, as well as the electromyography from the first dorsal interosseous muscle were collected synchronously. The metrics of the Event-related desynchronization, the electromyography stability index, and the force variation, were used to represent the corresponding cortical neural responses, muscle contraction activities, and the level of strength regulation, respectively; and further neuro-muscular coupling between the sensorimotor cortex and the first dorsal interosseous muscle was investigated by transfer entropy analysis. The results indicated a strong relationship that the increase of force regulation demand would result in a force variation increase as well as a stability reduction in muscle motor unit output. Meanwhile, the intensity of neural response increased in both the α and β frequency bands. As the force regulation demand increased, the strength of bidirectional transfer entropy showed a clear shift from β to the γ frequency band, which facilitate rapid integration of dynamic strength compensation to adapt to motor task changes.

Sensitivity to and Control of Distraction: Distractor-Entrained Oscillation and Frontoparietal EEG Gamma Synchronization

While recent advancements have been made towards a better understanding of the involvement of the prefrontal cortex (PFC) in the context of cognitive control, the exact mechanism is still not fully understood. Successful behavior requires the correct detection of goal-relevant cues and resisting irrelevant distractions. Frontal parietal networks have been implicated as important for maintaining cognitive control in the face of distraction. The present study investigated the role of gamma-band power in distraction resistance and frontoparietal networks, as its increase is linked to cholinergic activity. We examined changes in gamma activity and their relationship to frontoparietal top-down modulation for distractor challenges and to bottom-up distractor processing. Healthy young adults were tested using a modified version of the distractor condition sustained attention task (dSAT) while wearing an EEG. The modified distractor was designed so that oscillatory activities could be entrained to it, and the strength of entrainment was used to assess the degree of distraction. Increased top-down control during the distractor challenge increased gamma power in the left parietal regions rather than the right prefrontal regions predicted from rodent studies. Specifically, left parietal gamma power increased in response to distraction where the amount of this increase was negatively correlated with the neural activity reflecting bottom-up distractor processing in the visual area. Variability in gamma power in right prefrontal regions was associated with increased response time variability during distraction. This may suggest that the right prefrontal region may contribute to the signaling needed for top-down control rather than its implementation.

Tracking the neurodevelopmental trajectory of beta band oscillations with optically pumped magnetometer-based magnetoencephalography

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - optically pumped magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Cingulate microstimulation induces negative decision-making via reduced top-down influence on primate fronto-cingulo-striatal network

The dorsolateral prefrontal cortex (dlPFC) is crucial for regulation of emotion that is known to aid prevention of depression. The broader fronto-cingulo-striatal (FCS) network, including cognitive dlPFC and limbic cingulo-striatal regions, has been associated with a negative evaluation bias often seen in depression. The mechanism by which dlPFC regulates the limbic system remains largely unclear. Here we have successfully induced a negative bias in decision-making in female primates performing a conflict decision-making task, by directly microstimulating the subgenual cingulate cortex while simultaneously recording FCS local field potentials (LFPs). The artificially induced negative bias in decision-making was associated with a significant decrease in functional connectivity from cognitive to limbic FCS regions, represented by a reduction in Granger causality in beta-range LFPs from the dlPFC to the other regions. The loss of top-down directional influence from cognitive to limbic regions, we suggest, could underlie negative biases in decision-making as observed in depressive states.

Learning spiking neuronal networks with artificial neural networks: neural oscillations

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations. Specifically, we develop a class of artificial neural networks to provide faithful surrogates to the high-dimensional, nonlinear oscillatory dynamics produced by a spiking neuronal network model. Furthermore, when the training data set is enlarged within a range of parameter choices, the artificial neural networks become generalizable to these parameters, covering cases in distinctly different dynamical regimes. In all, our work opens a new avenue for modeling complex neuronal network dynamics with artificial neural networks.

Comparison of Immediate Neuromodulatory Effects between Focal Vibratory and Electrical Sensory Stimulations after Stroke

Focal vibratory stimulation (FVS) and neuromuscular electrical stimulation (NMES) are promising technologies for sensory rehabilitation after stroke. However, the differences between these techniques in immediate neuromodulatory effects on the poststroke cortex are not yet fully understood. In this research, cortical responses in persons with chronic stroke (n = 15) and unimpaired controls (n = 15) were measured by whole-brain electroencephalography (EEG) when FVS and NMES at different intensities were applied transcutaneously to the forearm muscles. Both FVS and sensory-level NMES induced alpha and beta oscillations in the sensorimotor cortex after stroke, significantly exceeding baseline levels (p < 0.05). These oscillations exhibited bilateral sensory deficiency, early adaptation, and contralesional compensation compared to the control group. FVS resulted in a significantly faster P300 response (p < 0.05) and higher theta oscillation (p < 0.05) compared to NMES. The beta desynchronization over the contralesional frontal-parietal area remained during NMES (p > 0.05), but it was significantly weakened during FVS (p < 0.05) after stroke. The results indicated that both FVS and NMES effectively activated the sensorimotor cortex after stroke. However, FVS was particularly effective in eliciting transient involuntary attention, while NMES primarily fostered the cortical responses of the targeted muscles in the contralesional motor cortex.

Alpha oscillations reflect similar mapping mechanisms for localizing touch on hands and tools

It has been suggested that our brain re-uses body-based computations to localize touch on tools, but the neural implementation of this process remains unclear. Neural oscillations in the alpha and beta frequency bands are known to map touch on the body in external and skin-centered coordinates, respectively. Here, we pinpointed the role of these oscillations during tool-extended sensing by delivering tactile stimuli to either participants' hands or the tips of hand-held rods. To disentangle brain responses related to each coordinate system, we had participants' hands/tool tips crossed or uncrossed at their body midline. We found that midline crossing modulated alpha (but not beta) band activity similarly for hands and tools, also involving a similar network of cortical regions. Our findings strongly suggest that the brain uses similar oscillatory mechanisms for mapping touch on the body and tools, supporting the idea that body-based neural processes are repurposed for tool use.

EEG-based neurophysiological indices for expert psychomotor performance - a review

A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).

Semantic associations restore neural encoding mechanisms

Lapses in attention can negatively impact later memory of an experience. Attention and encoding resources are thought to decline as more experiences are encountered in succession, accounting for the primacy effect in which memory is better for items encountered early compared to late in a study list. However, accessing prior knowledge during study can facilitate subsequent memory, suggesting a potential avenue to counteract this decline. Here, we investigated the extent to which semantic associations-shared meaning between experiences-can counteract declines in encoding resources. Our hypothesis is that semantic associations restore neural encoding mechanisms, which in turn improves memory. We recorded scalp electroencephalography (EEG) while male and female human participants performed a delayed free recall task. Half of the items from late in each study list were semantically associated with an item presented earlier in the list. We find that semantic associations improve memory specifically for late list items and selectively modulate the neural signals engaged during the study of late list items. Relative to other recalled items, late list items that are subsequently semantically clustered-recalled consecutively with their semantic associate-elicit increased high-frequency activity and decreased low-frequency activity, a hallmark of successful encoding. Our findings demonstrate that semantic associations restore neural encoding mechanisms and improve later memory. More broadly, these findings suggest that prior knowledge modulates the orientation of attention to influence encoding mechanisms.

High-Frequency Local Field Potential Oscillations for Pigeons in Effective Turning

Flexible turning behavior endows Homing Pigeons (Columba livia domestica) with high adaptability and intelligence in long-distance flight, foraging, hazard avoidance, and social interactions. The present study recorded the activity pattern of their local field potential (LFP) oscillations and explored the relationship between different bands of oscillations and turning behaviors in the formatio reticularis medialis mesencephali (FRM). The results showed that the C (13-60 Hz) and D (61-130 Hz) bands derived from FRM nuclei oscillated significantly in active turning, while the D and E (131-200 Hz) bands oscillated significantly in passive turning. Additionally, compared with lower-frequency stimulation (40 Hz and 60 Hz), 80 Hz stimulation can effectively activate the turning function of FRM nuclei. Electrical stimulation elicited stronger oscillations of neural activity, which strengthened the pigeons' turning locomotion willingness, showing an enhanced neural activation effect. These findings suggest that different band oscillations play different roles in the turning behavior; in particular, higher-frequency oscillations (D and E bands) enhance the turning behavior. These findings will help us decode the complex relationship between bird brains and behaviors and are expected to facilitate the development of neuromodulation techniques for animal robotics.

The temporal effect of uncertain context on the perceptual processing of painful and non-painful stimulation

Uncertainty has been demonstrated to influence the perception of noxious stimuli, but little is known about the effects of prolonged uncertain contexts on the perception of painful and non-painful stimuli. To address this knowledge gap, the present study utilized a cue-based NPU-threat task, where uncertain and certain trials were separated into distinct blocks. The objective was to investigate the impact of uncertain contexts on the temporal dynamics of electroencephalogram (EEG) activity during the processing of painful and non-painful stimuli. The results revealed that the influence of uncertain contexts on neural responses extends beyond painful trials and is also evident in non-painful trials. In uncertain contexts, it has been observed that painful stimuli elicit larger P2 amplitudes and late beta band (13-30 Hz) event-related desynchronization (ERD) around 500-700 ms. However, in certain contexts, painful stimuli evoke stronger late gamma band (50-70 Hz) event-related synchronization (ERS) around 600-700 ms. For non-painful trials, in uncertain contexts, significantly higher amplitudes of the late positive potential (LPP) component and delta-theta band (2-7 Hz) ERS were observed compared to certain non-painful stimuli. These findings demonstrate that uncertain contexts exert a significant impact on the processing of both painful and non-painful stimuli, and this influence is mediated by distinct neural mechanisms.

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

Pinprick-induced gamma-band oscillations are not a useful electrophysiological marker of pinprick hypersensitivity in humans

OBJECTIVE

This study aimed to investigate scalp gamma-band oscillations (GBOs) induced by mechanical stimuli activating skin nociceptors before and after the induction of mechanical hypersensitivity using high-frequency electrical stimulation (HFS) of the skin.

METHODS

In twenty healthy volunteers, we recorded the electroencephalogram during robot-controlled mechanical pinprick stimulation (512 mN) applied at the right ventral forearm before and after HFS.

RESULTS

HFS induced a significant increase in mechanical pinprick sensitivity, but this increased pinprick sensitivity was, at the group level, not accompanied by a significant increase in GBOs. Visual inspection of the individual data revealed that possible GBOs were present in eight out of twenty participants (40%) and the frequency of these GBOs varied substantially across participants.

CONCLUSIONS

Based on the low number of participants showing GBOs we question the (clinical) utility of mechanically-induced GBOs as an electrophysiological marker of pinprick hypersensitivity in humans.

SIGNIFICANCE

Mechanical pinprick-induced scalp GBOs are not useful for evaluating mechanical pinprick hypersensitivity in humans.

Measurable fields-to-spike causality and its dependence on cortical layer and area

Distinct dynamics in different cortical layers are apparent in neuronal and local field potential (LFP) patterns, yet their associations in the context of laminar processing have been sparingly analyzed. Here, we study the laminar organization of spike-field causal flow within and across visual (V4) and frontal areas (PFC) of monkeys performing a visual task. Using an event-based quantification of LFPs and a directed information estimator, we found area and frequency specificity in the laminar organization of spike-field causal connectivity. Gamma bursts (40-80 Hz) in the superficial layers of V4 largely drove intralaminar spiking. These gamma influences also fed forward up the cortical hierarchy to modulate laminar spiking in PFC. In PFC, the direction of intralaminar information flow was from spikes → fields where these influences dually controlled top-down and bottom-up processing. Our results, enabled by innovative methodologies, emphasize the complexities of spike-field causal interactions amongst multiple brain areas and behavior.

Early musical training benefits to non-musical cognitive ability associated with the Gestalt principles

Musical training has been evidenced to facilitate music perception, which refers to the consistencies, boundaries, and segmentations in pieces of music that are associated with the Gestalt principles. The current study aims to test whether musical training is beneficial to non-musical cognitive ability with Gestalt principles. Three groups of Chinese participants (with early, late, and no musical training) were compared in terms of their performances on the Motor-Free Visual Perception Test (MVPT). The results show that the participants with early musical training had significantly better performance in the Gestalt-like Visual Closure subtest than those with late and no musical training, but no significances in other Gestalt-unlike subtests was identified (Visual Memory, Visual Discrimination, Spatial Relationship, Figure Ground in MVPT). This study suggests the benefit of early musical training on non-musical cognitive ability with Gestalt principles.

Individual/Peak Gamma Frequency: What Do We Know?

In recent years, the concept of individualized measures of electroencephalographic (EEG) activity has emerged. Gamma-band activity plays an important role in many sensory and cognitive processes. Thus, peak frequency in the gamma range has received considerable attention. However, peak or individual gamma frequency (IGF) is rarely used as a primary measure of interest; consequently, little is known about its nature and functional significance. With this review, we attempt to comprehensively overview available information on the functional properties of peak gamma frequency, addressing its relationship with certain processes and/or modulation by various factors. Here, we show that IGFs seem to be related to various endogenous and exogenous factors. Broad functional aspects that are related to IGF might point to the differences in underlying mechanisms. Therefore, research utilizing different types of stimulation for IGF estimation and covering several functional aspects in the same population is required. Moreover, IGFs span a wide range of frequencies (30-100 Hz). This could be partly due to the variability of methods used to extract the measures of IGF. In order to overcome this issue, further studies aiming at the optimization of IGF extraction would be greatly beneficial.

Neurophysiological correlates of tactile width discrimination in humans

Introduction

Tactile information processing requires the integration of sensory, motor, and cognitive information. Width discrimination has been extensively studied in rodents, but not in humans.

Methods

Here, we describe Electroencephalography (EEG) signals in humans performing a tactile width discrimination task. The first goal of this study was to describe changes in neural activity occurring during the discrimination and the response periods. The second goal was to relate specific changes in neural activity to the performance in the task.

Results

Comparison of changes in power between two different periods of the task, corresponding to the discrimination of the tactile stimulus and the motor response, revealed the engagement of an asymmetrical network associated with fronto-temporo-parieto-occipital electrodes and across multiple frequency bands. Analysis of ratios of higher [Ratio 1: (0.5-20 Hz)/(0.5-45 Hz)] or lower frequencies [Ratio 2: (0.5-4.5 Hz)/(0.5-9 Hz)], during the discrimination period revealed that activity recorded from frontal-parietal electrodes was correlated to tactile width discrimination performance between-subjects, independently of task difficulty. Meanwhile, the dynamics in parieto-occipital electrodes were correlated to the changes in performance within-subjects (i.e., between the first and the second blocks) independently of task difficulty. In addition, analysis of information transfer, using Granger causality, further demonstrated that improvements in performance between blocks were characterized by an overall reduction in information transfer to the ipsilateral parietal electrode (P4) and an increase in information transfer to the contralateral parietal electrode (P3).

Discussion

The main finding of this study is that fronto-parietal electrodes encoded between-subjects' performances while parieto-occipital electrodes encoded within-subjects' performances, supporting the notion that tactile width discrimination processing is associated with a complex asymmetrical network involving fronto-parieto-occipital electrodes.

Dynamic peripheral nerve stimulation can produce cortical activation similar to punctate mechanical stimuli

During contact, phasic and tonic responses provide feedback that is used for task performance and perceptual processes. These disparate temporal dynamics are carried in peripheral nerves, and produce overlapping signals in cortex. Using longitudinal intrafascicular electrodes inserted into the median nerve of a nonhuman primate, we delivered composite stimulation consisting of onset and release bursts to capture rapidly adapting responses and sustained stochastic stimulation to capture the ongoing response of slowly adapting receptors. To measure the stimulation's effectiveness in producing natural responses, we monitored the local field potential in somatosensory cortex. We compared the cortical responses to peripheral nerve stimulation and vibrotactile/punctate stimulation of the fingertip, with particular focus on gamma band (30-65 Hz) responses. We found that vibrotactile stimulation produces consistently phase locked gamma throughout the duration of the stimulation. By contrast, punctate stimulation responses were phase locked at the onset and release of stimulation, but activity maintained through the stimulation was not phase locked. Using these responses as guideposts for assessing the response to the peripheral nerve stimulation, we found that constant frequency stimulation produced continual phase locking, whereas composite stimulation produced gamma enhancement throughout the stimulus, phase locked only at the onset and release of the stimulus. We describe this response as an "Appropriate Response in the gamma band" (ARγ), a trend seen in other sensory systems. Our demonstration is the first shown for intracortical somatosensory local field potentials. We argue that this stimulation paradigm produces a more biomimetic response in somatosensory cortex and is more likely to produce naturalistic sensations for readily usable neuroprosthetic feedback.

Neuronal Correlates of Task Irrelevant Distractions Enhance the Detection of Attention Deficit/Hyperactivity Disorder

Early diagnosis and treatment can reduce the symptoms of Attention Deficit/Hyperactivity Disorder (ADHD) in children, but medical diagnosis is usually delayed. Hence, it is important to increase the efficiency of early diagnosis. Previous studies used behavioral and neuronal data during GO/NOGO task to help detect ADHD and the accuracy differed considerably from 53% to 92%, depending on the employed methods and the number of electroencephalogram (EEG) channels. It remains unclear whether data from a few EEG channels can still lead to a good accuracy of detecting ADHD. Here, we hypothesize that introducing distractions into a VR-based GO/NOGO task can augment the detection of ADHD using 6-channel EEG because children with ADHD are easily distracted. Forty-nine ADHD children and 32 typically developing children were recruited. We use a clinically applicable system with EEG to record data. Statistical analysis and machine learning methods were employed to analyze the data. The behavioral results revealed significant differences in task performance when there are distractions. The presence of distractions leads to EEG changes in both groups, indicating immaturity in inhibitory control. Importantly, the distractions additionally enhanced the between-group differences in NOGO $\alpha $ and $\gamma $ power, reflecting insufficient inhibition in different neural networks for distraction suppression in the ADHD group. Machine learning methods further confirmed that distractions enhance the detection of ADHD with an accuracy of 85.45%. In conclusion, this system can assist in fast screenings for ADHD and the findings of neuronal correlates of distractions can help design therapeutic strategies.

Functional changes in brain oscillations in dementia: a review

A growing body of evidence indicates that several characteristics of electroencephalography (EEG) and magnetoencephalography (MEG) play a functional role in cognition and could be linked to the progression of cognitive decline in some neurological diseases such as dementia. The present paper reviews previous studies investigating changes in brain oscillations associated to the most common types of dementia, namely Alzheimer's disease (AD), frontotemporal degeneration (FTD), and vascular dementia (VaD), with the aim of identifying pathology-specific patterns of alterations and supporting differential diagnosis in clinical practice. The included studies analysed changes in frequency power, functional connectivity, and event-related potentials, as well as the relationship between electrophysiological changes and cognitive deficits. Current evidence suggests that an increase in slow wave activity (i.e., theta and delta) as well as a general reduction in the power of faster frequency bands (i.e., alpha and beta) characterizes AD, VaD, and FTD. Additionally, compared to healthy controls, AD exhibits alteration in latencies and amplitudes of the most common event related potentials. In the reviewed studies, these changes generally correlate with performances in many cognitive tests. In conclusion, particularly in AD, neurophysiological changes can be reliable early markers of dementia.

Parkinsonian daytime sleep-wake classification using deep brain stimulation lead recordings

Excessive daytime sleepiness is a recognized non-motor symptom that adversely impacts the quality of life of people with Parkinson's disease (PD), yet effective treatment options remain limited. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for PD motor signs. Reliable daytime sleep-wake classification using local field potentials (LFPs) recorded from DBS leads implanted in STN can inform the development of closed-loop DBS approaches for prompt detection and disruption of sleep-related neural oscillations. We performed STN DBS lead recordings in three nonhuman primates rendered parkinsonian by administrating neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Reference sleep-wake states were determined on a second-by-second basis by video monitoring of eyes (eyes-open, wake and eyes-closed, sleep). The spectral power in delta (1-4 Hz), theta (4-8 Hz), low-beta (8-20 Hz), high-beta (20-35 Hz), gamma (35-90 Hz), and high-frequency (200-400 Hz) bands were extracted from each wake and sleep epochs for training (70% data) and testing (30% data) a support vector machines classifier for each subject independently. The spectral features yielded reasonable daytime sleep-wake classification (sensitivity: 90.68 ± 1.28; specificity: 88.16 ± 1.08; accuracy: 89.42 ± 0.68; positive predictive value; 88.70 ± 0.89, n = 3). Our findings support the plausibility of monitoring daytime sleep-wake states using DBS lead recordings. These results could have future clinical implications in informing the development of closed-loop DBS approaches for automatic detection and disruption of sleep-related neural oscillations in people with PD to promote wakefulness.

Long-latency gamma modulation after median nerve stimulation delineates the central sulcus and contrasts the states of consciousness

OBJECTIVE

To evaluate the functional use of sub-band modulations in somatosensory evoked potentials (SSEPs) to discriminate between the primary somatosensory (S1) and motor (M1) areas and contrast the states of consciousness.

METHODS

During routine intraoperative cortical mapping, SSEPs were recorded with electrocorticography (ECoG) grids from the sensorimotor cortex of eight patients in the anesthetized and awake states. We conducted a time-frequency analysis on the SSEP trace to extract the spectral modulations in each state and visualize their spatial topography.

RESULTS

We observed late gamma modulation (60-250 Hz) in all subjects approximately 50 ms after stimulation onset, extending up to 250 ms in each state. The late gamma activity enhancement was predominant in S1 in the awake state, where it discriminated S1 from M1 at a higher accuracy (92 %) than in the anesthetized state (accuracy = 70 %).

CONCLUSIONS

These results showed that sensorimotor mapping does not need to rely on only SSEP phase reversal. The long latency gamma modulation can serve as a biomarker for primary sensorimotor localization and monitor the level of consciousness in neurosurgical practice.

SIGNIFICANCE

While the intraoperative assessment of SSEP phase reversal with ECoG is widely employed to delineate the central sulcus, the median nerve stimulation-induced spatio-spectral patterns can distinctly localize it and distinguish between conscious states.

Altered Odor-Evoked Electrophysiological Responses in the Anterior Piriform Cortex of Conscious APP/PS1 Mice

Background: Olfactory decline is an indicator of early-stage Alzheimer’s disease (AD). Although the anterior piriform cortex (aPC) is an important brain area involved in processing olfactory input, little is known about how its neuronal activity is affected in early-stage AD. Objective: To elucidate whether odor-induced electrophysiological responses are altered in the aPC of 3-5-month-old APP/PS1 mice. Methods: Using head-fixed multi-channel recording techniques in APP/PS1 AD mouse model to uncover potential aberrance of the aPC neuronal firing and local field potential (LFP) in response to vanillin. Results: We show that the firing rate of aPC neurons evoked by vanillin is significantly reduced in conscious APP/PS1 mice. LFP analysis demonstrates reduced low- and high-gamma (γ low, γ high) oscillations during both the baseline and odor stimulation periods in APP/PS1 mice. Moreover, according to spike-field coherence (SFC) analysis, APP/PS1 mice show decreased coherence between odor-evoked spikes and γ low rhythms, while the coherence with γ high rhythms and the ΔSFC of the oscillations is unaffected. Furthermore, APP/PS1 mice show reduced phase-locking strength in the baseline period, such that there is no difference between baseline and odor-stimulation conditions. This contrasts markedly with wild type mice, where phase-locking strength decreases on stimulation. Conclusion: The abnormalities in both the neuronal and oscillatory activities of the aPC may serve as electrophysiological indicators of underlying olfactory decline in early AD.

Cortical beta burst dynamics are altered in Parkinson's disease but normalized by deep brain stimulation

Exaggerated subthalamic beta oscillatory activity and increased beta range cortico-subthalamic synchrony have crystallized as the electrophysiological hallmarks of Parkinson's disease. Beta oscillatory activity is not tonic but occurs in 'bursts' of transient amplitude increases. In Parkinson's disease, the characteristics of these bursts are altered especially in the basal ganglia. However, beta oscillatory dynamics at the cortical level and how they compare with healthy brain activity is less well studied. We used magnetoencephalography (MEG) to study sensorimotor cortical beta bursting and its modulation by subthalamic deep brain stimulation in Parkinson's disease patients and age-matched healthy controls. We show that the changes in beta bursting amplitude and duration typical of Parkinson's disease can also be observed in the sensorimotor cortex, and that they are modulated by chronic subthalamic deep brain stimulation, which, in turn, is reflected in improved motor function at the behavioural level. In addition to the changes in individual beta bursts, their timing relative to each other was altered in patients compared to controls: bursts were more clustered in untreated Parkinson's disease, occurring in 'bursts of bursts', and re-burst probability was higher for longer compared to shorter bursts. During active deep brain stimulation, the beta bursting in patients resembled healthy controls' data. In summary, both individual bursts' characteristics and burst patterning are affected in Parkinson's disease, and subthalamic deep brain stimulation normalizes some of these changes to resemble healthy controls' beta bursting activity, suggesting a non-invasive biomarker for patient and treatment follow-up.

Cues to body-related distortions and hallucinations? Spontaneous sensations correlate with EEG oscillatory activity recorded at rest in the somatosensory cortices

Body awareness may arise in the total absence of sensory input, as suggested by the spontaneous occurrence of normal and pathological (i.e., hallucinatory) bodily sensations. These phenomena may arise due to back-projections from higher-order cortical areas to the primary (SI) and secondary (SII) somatosensory cortices, and would appear to be reflected in cortical oscillatory activity in both SI and SII. Here, we set to investigate the relationship of SI and SII in SPS. Healthy participants underwent an EEG recording session at rest, and then completed an experiment on the perception of spontaneous sensations occurring on the hands. Cortical oscillatory activity was extracted from specified ROIs in the somatosensory cortices. The findings showed that (i) SPS perceived in the fingers correlated positively with alpha-band oscillations recorded in SI, and that (ii) SPS perceived in the palm correlated positively with gamma-band oscillations and negatively with beta-band oscillations recorded in SII. Apart from supporting the idea that the somatosensory cortices are involved in bodily awareness even in the absence of sensory input, these findings also suggest that default oscillatory activity in the somatosensory cortices reflects individual differences in bodily awareness. The results are interpreted in terms of neural and cognitive processes that may give rise to bodily awareness and modulate it, and their importance in understanding body perception distortions and bodily delusions and hallucinations is discussed.

The rubber hand illusion is accompanied by a distributed reduction of alpha and beta power in the EEG

Previous studies have reported correlates of bodily self-illusions such as the rubber hand in signatures of rhythmic brain activity. However, individual studies focused on specific variations of the rubber hand paradigm, used different experimental setups to induce this, or used different control conditions to isolate the neurophysiological signatures related to the illusory state, leaving the specificity of the reported illusion-signatures unclear. We here quantified correlates of the rubber hand illusion in EEG-derived oscillatory brain activity and asked two questions: which of the observed correlates are robust to the precise nature of the control conditions used as contrast for the illusory state, and whether such correlates emerge directly around the subjective illusion onset. To address these questions, we relied on two experimental configurations to induce the illusion, on different non-illusion conditions to isolate neurophysiological signatures of the illusory state, and we implemented an analysis directly focusing on the immediate moment of the illusion onset. Our results reveal a widespread suppression of alpha and beta-band activity associated with the illusory state in general, whereby the reduction of beta power prevailed around the immediate illusion onset. These results confirm previous reports of a suppression of alpha and beta rhythms during body illusions, but also highlight the difficulties to directly pinpoint the precise neurophysiological correlates of the illusory state.

The perceived duration of expected events depends on how the expectation is formed

Repeated events can seem shortened. It has been suggested that this results from an inverse relationship between predictability and perceived duration, with more predictable events seeming shorter. Some evidence disputes this generalisation, as there are cases where this relationship has been nullified, or even reversed. This study sought to combine different factors that encourage expectation into a single paradigm, to directly compare their effects. We find that when people are asked to declare a prediction (i.e., to predict which colour sequence will ensue), guess-confirming events can seem relatively protracted. This augmented a positive time-order error, with the first of two sequential presentations already seeming protracted. We did not observe a contraction of perceived duration for more probable or for repeated events. Overall, our results are inconsistent with a simple mapping between predictability and perceived duration. Whether the perceived duration of an expected event will seem relatively contracted or expanded seems to be contingent on the causal origin of expectation.

Sensitivity of the S1 neuronal calcium network to insulin and Bay-K 8644 in vivo: Relationship to gait, motivation, and aging processes

Neuronal hippocampal Ca²⁺ dysregulation is a critical component of cognitive decline in brain aging and Alzheimer's disease and is suggested to impact communication and excitability through the activation of a larger after hyperpolarization. However, few studies have tested for the presence of Ca²⁺ dysregulation in vivo, how it manifests, and whether it impacts network function across hundreds of neurons. Here, we tested for neuronal Ca²⁺ network dysregulation in vivo in the primary somatosensory cortex (S1) of anesthetized young and aged male Fisher 344 rats using single‐cell resolution techniques. Because S1 is involved in sensory discrimination and proprioception, we tested for alterations in ambulatory performance in the aged animal and investigated two potential pathways underlying these central aging‐ and Ca²⁺‐dependent changes. Compared to young, aged animals displayed increased overall activity and connectivity of the network as well as decreased ambulatory speed. In aged animals, intranasal insulin (INI) increased network synchronicity and ambulatory speed. Importantly, in young animals, delivery of the L‐type voltage‐gated Ca²⁺ channel modifier Bay‐K 8644 altered network properties, replicating some of the changes seen in the older animal. These results suggest that hippocampal Ca²⁺ dysregulation may be generalizable to other areas, such as S1, and might engage modalities that are associated with locomotor stability and motivation to ambulate. Further, given the safety profile of INI in the clinic and the evidence presented here showing that this central dysregulation is sensitive to insulin, we suggest that these processes can be targeted to potentially increase motivation and coordination while also reducing fall frequency with age.

Evaluation of Post-Stroke Impairment in Fine Tactile Sensation by Electroencephalography (EEG)-Based Machine Learning

Electroencephalography (EEG)-based measurements of fine tactile sensation produce large amounts of data, with high costs for manual evaluation. In this study, an EEG-based machine-learning (ML) model with support vector machine (SVM) was established to automatically evaluate post-stroke impairments in fine tactile sensation. Stroke survivors (n = 12, stroke group) and unimpaired participants (n = 15, control group) received stimulations with cotton, nylon, and wool fabrics to the different upper limbs of a stroke participant and the dominant side of the control. The average and maximal values of relative spectral power (RSP) of EEG in the stimulations were used as the inputs to the SVM-ML model, which was first optimized for classification accuracies for different limb sides through hyperparameter selection (γ, C) in radial basis function (RBF) kernel and cross-validation during cotton stimulation. Model generalization was investigated by comparing accuracies during stimulations with different fabrics to different limbs. The highest accuracies were achieved with (γ = 21, C = 23) for the RBF kernel (76.8%) and six-fold cross-validation (75.4%), respectively, in the gamma band for cotton stimulation; these were selected as optimal parameters for the SVM-ML model. In model generalization, significant differences in the post-stroke fabric stimulation accuracies were shifted to higher (beta/gamma) bands. The EEG-based SVM-ML model generated results similar to manual evaluation of cortical responses to fabric stimulations; this may aid automatic assessments of post-stroke fine tactile sensations.

Human visual gamma for color stimuli

Strong gamma-band oscillations in primate early visual cortex can be induced by homogeneous color surfaces (Peter et al., 2019; Shirhatti and Ray, 2018). Compared to other hues, particularly strong gamma oscillations have been reported for red stimuli. However, precortical color processing and the resultant strength of input to V1 have often not been fully controlled for. Therefore, stronger responses to red might be due to differences in V1 input strength. We presented stimuli that had equal luminance and cone contrast levels in a color coordinate system based on responses of the lateral geniculate nucleus, the main input source for area V1. With these stimuli, we recorded magnetoencephalography in 30 human participants. We found gamma oscillations in early visual cortex which, contrary to previous reports, did not differ between red and green stimuli of equal L-M cone contrast. Notably, blue stimuli with contrast exclusively on the S-cone axis induced very weak gamma responses, as well as smaller event-related fields and poorer change-detection performance. The strength of human color gamma responses for stimuli on the L-M axis could be well explained by L-M cone contrast and did not show a clear red bias when L-M cone contrast was properly equalized.

Associations between Heart Rate Variability and Brain Activity during a Working Memory Task: A Preliminary Electroencephalogram Study on Depression and Anxiety Disorder

Heart rate variability (HRV) has been suggested to reflect executive function and related neural activity. Executive dysfunction has been suggested to play an important role in the pathophysiology of emotional disorders. The purpose of this study was to investigate whether HRV showed a significant correlation with electroencephalogram (EEG) during a working memory performance in patients with depressive or anxiety disorder. A retrospective analysis was conducted with data from 61 patients with depressive disorder (43 women and 18 men) and 59 patients with anxiety disorder (35 women and 24 men). HRV was measured in the resting state, and EEG was recorded in the resting state and during the execution of a working memory task. It was performed in patients with depressive and anxiety disorder, and the paired sample t-test between resting state and task performance, as well as the partial correlation analysis between HRV and EEG, was conducted. Both depressed and anxious patients showed weaker beta relative power during the working memory task compared to the rest period. The resting-state EEG did not correlate with HRV parameters in both groups. In depressed patients, HRV showed a positive correlation with delta power during the task and a negative correlation with beta relative power during the task. In patients with anxiety disorder, HRV showed a significant positive correlation with theta power of the right frontal region during the task. Our results suggest that HRV would be related to executive-function-related neural activity in patients with depressive or anxiety disorder. Future studies with more subjects, including healthy controls, are needed to verify the correlation between HRV and EEG and to come up with a more comprehensive picture of neurobiological changes in emotional disorders.

Reproducibility of Rolandic beta rhythm modulation in MEG and EEG

The Rolandic beta rhythm, at ∼20 Hz, is generated in the somatosensory and motor cortices and is modulated by motor activity and sensory stimuli, causing a short lasting suppression that is followed by a rebound of the beta rhythm. The rebound reflects inhibitory changes in the primary sensorimotor (SMI) cortex, and thus it has been used as a biomarker to follow the recovery of patients with acute stroke. The longitudinal stability of beta rhythm modulation is a prerequisite for its use in long-term follow-ups. We quantified the reproducibility of beta rhythm modulation in healthy subjects in a 1-year-longitudinal study both for MEG and EEG at T₀, 1 month (T_1-month, n = 8) and 1 year (T_1-year, n = 19). The beta rhythm (13–25 Hz) was modulated by fixed tactile and proprioceptive stimulations of the index fingers. The relative peak strengths of beta suppression and rebound did not differ significantly between the sessions, and intersession reproducibility was good or excellent according to intraclass correlation-coefficient values (0.70–0.96) both in MEG and EEG. Our results indicate that the beta rhythm modulation to tactile and proprioceptive stimulation is well reproducible within 1 year. These results support the use of beta modulation as a biomarker in long-term follow-up studies, e.g., to quantify the functional state of the SMI cortex during rehabilitation and drug interventions in various neurological impairments.

NEW & NOTEWORTHY The present study demonstrates that beta rhythm modulation is highly reproducible in a group of healthy subjects within a year. Hence, it can be reliably used as a biomarker in longitudinal follow-up studies in different neurological patient groups to reflect changes in the functional state of the sensorimotor cortex.

Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

High-gamma mirror activity patterns in the human brain during reach-to-grasp movement observation, retention, and execution-An MEG study

While the existence of a human mirror neuron system is evident, the involved brain areas and their exact functional roles remain under scientific debate. A number of functionally different mirror neuron types, neurons that selectively respond to specific grasp phases and types for example, have been reported with single cell recordings in monkeys. In humans, spatially limited, intracranially recorded electrophysiological signals in the high-gamma (HG) range have been used to investigate the human mirror system, as they are associated with spiking activity in single neurons. Our goal here is to complement previous intracranial HG studies by using magnetoencephalography to record HG activity simultaneously from the whole head. Participants performed a natural reach-to-grasp movement observation and delayed imitation task with different everyday objects and grasp types. This allowed us to characterize the spatial organization of cortical areas that show HG-activation modulation during movement observation (mirroring), retention (mnemonic mirroring), and execution (motor control). Our results show mirroring related HG modulation patterns over bilateral occipito-parietal as well as sensorimotor areas. In addition, we found mnemonic mirroring related HG modulation over contra-lateral fronto-temporal areas. These results provide a foundation for further human mirror system research as well as possible target areas for brain-computer interface and neurorehabilitation approaches.

Modulating Gamma Oscillations Promotes Brain Connectivity to Improve Cognitive Impairment

Dementia causes a substantial global economic burden, but effective treatment is lacking. Recently, studies have revealed that gamma-band waves of electrical brain activity, particularly 40 Hz oscillations, are closely associated with high-order cognitive functions and can activate microglia to clear amyloid-β deposition. Here, we found that compared with sham stimulation, applying 40-Hz high-frequency repetitive transcranial magnetic stimulation (rTMS) over the bilateral angular gyrus in patients with probable Alzheimer's disease (AD; n = 37) resulted in up to 8 weeks of significantly improved cognitive function. Power spectral density analysis of the resting-state electroencephalography (EEG) demonstrated that 40-Hz rTMS modulated gamma-band oscillations in the left posterior temporoparietal region. Further testing with magnetic resonance imaging and TMS-EEG revealed the following: 40-Hz rTMS 1) prevented gray matter volume loss, 2) enhanced local functional integration within bilateral angular gyrus, as well as global functional integration in bilateral angular gyrus and the left middle frontal gyrus, 3) strengthened information flow from the left posterior temporoparietal region to the frontal areas and strengthened the dynamic connectivity between anterior and posterior brain regions. These findings demonstrate that modulating gamma-band oscillations effectively improves cognitive function in patients with probable AD by promoting local, long-range, and dynamic connectivity within the brain.

Precision control for a flexible body representation

Adaptive body representation requires the continuous integration of multisensory inputs within a flexible 'body model' in the brain. The present review evaluates the idea that this flexibility is augmented by the contextual modulation of sensory processing 'top-down'; which can be described as precision control within predictive coding formulations of Bayesian inference. Specifically, I focus on the proposal that an attenuation of proprioception may facilitate the integration of conflicting visual and proprioceptive bodily cues. Firstly, I review empirical work suggesting that the processing of visual vs proprioceptive body position information can be contextualised 'top-down'; for instance, by adopting specific attentional task sets. Building up on this, I review research showing a similar contextualisation of visual vs proprioceptive information processing in the rubber hand illusion and in visuomotor adaptation. Together, the reviewed literature suggests that proprioception, despite its indisputable importance for body perception and action control, can be attenuated top-down (through precision control) to facilitate the contextual adaptation of the brain's body model to novel visual feedback.

Neural shifts in alpha rhythm's dual functioning during empathy

INTRODUCTION

Alpha oscillations are unique in their capacity to relay neuronal information through a dual-process named "gating by inhibition": rhythmic enhancement inhibits task-irrelevant regions while rhythmic suppression engages task-relevant regions in the brain. A social-cognitive process that operates by relying on the suppression of the alpha rhythm in the primary somatosensory cortex (S1) is the ability to generate empathy. This phenomenon has been evidenced in dozens of electrophysiological studies targeting adult human subjects. Yet, recent studies on the neurodevelopment of empathy indicate that in younger age, empathy does not involve alpha suppression in S1 but only enhancement. More interestingly, right before adulthood, this rhythm is still enhanced, but in a remarkable shift, a pattern of suppression emerges. In this registered magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) study, we will capture frequency-decomposed neural activity particularly at the alpha range and its corresponding hemodynamic response and target subjects at around 20 years old as a unique time-window in development that allows investigating in parallel both low-alpha suppression and high-alpha enhancement. We aim to address two questions: (a) Does alpha power suppression in the S1 region during empathy correspond to BOLD increase in this region? (b) What is the functional role of alpha power enhancement during empathy development (BOLD signal increase or decrease)? Addressing these questions will particularly advance knowledge on the process of empathy in the brain, and the way in which it is underpinned by alpha oscillations. Moreover, examining these experimental outcomes can potentially lay the ground for future studies that would further examine the role of alpha oscillations in empathy during the course of development.

METHODS

Brain data of forty healthy individuals close to 20 years old will be recorded in two consecutive MEG and fMRI sessions while subjects observing physical pain versus neutral stimuli. Besides, each participant's subjective experiences wll be measred by questionnaires, interviews and rating of the stimuli.

Can the causal role of brain oscillations be studied through rhythmic brain stimulation?

Many studies have investigated the causal relevance of brain oscillations using rhythmic stimulation, either through direct-brain or sensory stimulation. Yet, how intrinsic rhythms interact with the externally generated rhythm is largely unknown. We presented a flickered (60 Hz) visual grating or its correspondent unflickered stimulus in a psychophysical change detection task during simultaneous magnetoencephalography recordings to humans to test the effect of visual entrainment on induced gamma oscillations. Notably, we generally observed the coexistence of the broadband induced gamma rhythm with the entrained flicker rhythm (reliably measured in each participant), with the peak frequency of the induced response remaining unaltered in approximately half of participants—relatively independently of their native frequency. However, flicker increased broadband induced gamma power, and this was stronger in participants with a native frequency closer to the flicker frequency (resonance) and led to strong phase entrainment. Presence of flicker did not change behavior itself but profoundly altered brain behavior correlates across the sample: While broadband induced gamma oscillations correlated with reaction times for unflickered stimuli (as known previously), for the flicker, the amplitude of the entrained flicker rhythm (but no more the induced oscillation) correlated with reaction times. This, however, strongly depended on whether a participant's peak frequency shifted to the entrained rhythm. Our results suggests that rhythmic brain stimulation leads to a coexistence of two partially independent oscillations with heterogeneous effects across participants on the downstream relevance of these rhythms for behavior. This may explain the inconsistency of findings related to external entrainment of brain oscillations and poses further questions toward causal manipulations of brain oscillations in general.