Neuromodulation of inhibitory control using phase-lagged transcranial alternating current stimulation.

BACKGROUND: Transcranial alternating current stimulation (tACS) is a prominent non-invasive brain stimulation method for modulating neural oscillations and enhancing human cognitive function. This study aimed to investigate the effects of individualized theta tACS delivered in-phase and out-of-phase between the dorsal anterior cingulate cortex (dACC) and left dorsolateral prefrontal cortex (lDLPFC) during inhibitory control performance. METHODS: The participants engaged in a Stroop task with phase-lagged theta tACS over individually optimized high-density electrode montages targeting the dACC and lDLPFC. We analyzed task performance, event-related potentials, and prestimulus electroencephalographic theta and alpha power. RESULTS: We observed significantly reduced reaction times following out-of-phase tACS, accompanied by reduced frontocentral N1 and N2 amplitudes, enhanced parieto-occipital P1 amplitudes, and pronounced frontocentral late sustained potentials. Out-of-phase stimulation also resulted in significantly higher prestimulus frontocentral theta and alpha activity. CONCLUSIONS: These findings suggest that out-of-phase theta tACS potently modulates top-down inhibitory control, supporting the feasibility of phase-lagged tACS to enhance inhibitory control performance.

Non-invasive electrical brain stimulation modulates human conscious perception of mental representation.

Mental representation is a key concept in cognitive science; nevertheless, its neural foundations remain elusive. We employed non-invasive electrical brain stimulation and functional magnetic resonance imaging to address this. During this process, participants perceived flickering red and green visual stimuli, discerning them either as distinct, non-fused colours or as a mentally generated, fused colour (orange). The application of transcranial alternating current stimulation to the medial prefrontal region (a key node of the default-mode network) suppressed haemodynamic activation in higher-order subthalamic and central executive networks associated with the perception of fused colours. This implies that higher-order thalamocortical and default-mode networks are crucial in humans' conscious perception of mental representation.

Out-of-phase transcranial alternating current stimulation modulates the neurodynamics of inhibitory control.

Transcranial alternating current stimulation (tACS) is an efficient neuromodulation technique that enhances cognitive function in a non-invasive manner. Using functional magnetic resonance imaging, we investigated whether tACS with different phase lags (0° and 180°) between the dorsal anterior cingulate and left dorsolateral prefrontal cortices modulated inhibitory control performance during the Stroop task. We found out-of-phase tACS mediated improvements in task performance, which was neurodynamically reflected as putamen, dorsolateral prefrontal, and primary motor cortical activation as well as prefrontal-based top-down functional connectivity. Our observations uncover the neurophysiological bases of tACS-phase-dependent neuromodulation and provide a feasible non-invasive approach to effectively modulate inhibitory control.

Electroencephalographic features of elderly patients during anesthesia induction with remimazolam: a sub-study of a randomized controlled trial.

BACKGROUND: Although remimazolam is used as a general anesthetic in elderly patients due to its hemodynamic stability, the electroencephalogram (EEG) characteristics of remimazolam are not well-known. The purpose of this study was to identify the EEG features of remimazolam-induced unconsciousness in elderly patients and compare them with propofol. METHODS: Remimazolam (n=26) or propofol (n=26) were randomly administered for anesthesia induction in surgical patients. The hypnotic agent was blinded only to the patients. During the induction of anesthesia, remimazolam was administered at a rate of 6 mg/kg/h, and propofol was administered at a target effect-site concentration of 3.5 µg/ml. The EEG signals from 8 channels (Fp1,Fp2,Fz,F3,F4,Pz,P3,P4, referenced to A2, using the 10-20 system) were acquired during the induction of anesthesia and in the postoperative care unit. Power spectrum analysis was performed, and directed functional connectivity between frontal and parietal regions was evaluated using normalized symbolic transfer entropy. Functional connectivity in unconscious processes induced by remimazolam or propofol was compared with baseline. To compare each power of frequency over time of the two hypnotic agents, a permutation test with t statistic was conducted. RESULTS: Compared to the baseline in the alpha band, the feedback connectivity decreased by an average of 46% and 43%, respectively, after the loss of consciousness induced by remimazolam and propofol (95% CI for the mean difference:-0.073 to -0.044 for remimazolam, P<0.001,-0.068 to -0.042 for propofol,P<0.001). Asymmetry in the feedback and feedforward connectivity in the alpha band was suppressed after the loss of consciousness induced by remimazolam and propofol. There were no significant differences in the power of each frequency over time between the two hypnotic agents (minimum q-value=0.4235). CONCLUSIONS: Both regimens showed a greater decrease in feedback connectivity compared to a decrease in feedforward connectivity after loss of consciousness, leading to a disruption of asymmetry between the frontoparietal connectivity.

Resting-state electroencephalographic characteristics related to mild cognitive impairments.

Alzheimer's disease (AD) causes a rapid deterioration in cognitive and physical functions, including problem-solving, memory, language, and daily activities. Mild cognitive impairment (MCI) is considered a risk factor for AD, and early diagnosis and treatment of MCI may help slow the progression of AD. Electroencephalography (EEG) analysis has become an increasingly popular tool for developing biomarkers for MCI and AD diagnosis. Compared with healthy elderly, patients with AD showed very clear differences in EEG patterns, but it is inconclusive for MCI. This study aimed to investigate the resting-state EEG features of individuals with MCI (n = 12) and cognitively healthy controls (HC) (n = 13) with their eyes closed. EEG data were analyzed using spectral power, complexity, functional connectivity, and graph analysis. The results revealed no significant difference in EEG spectral power between the HC and MCI groups. However, we observed significant changes in brain complexity and networks in individuals with MCI compared with HC. Patients with MCI exhibited lower complexity in the middle temporal lobe, lower global efficiency in theta and alpha bands, higher local efficiency in the beta band, lower nodal efficiency in the frontal theta band, and less small-world network topology compared to the HC group. These observed differences may be related to underlying neuropathological alterations associated with MCI progression. The findings highlight the potential of network analysis as a promising tool for the diagnosis of MCI.

Deep learning-based electroencephalic diagnosis of tinnitus symptom.

Tinnitus is a neuropathological phenomenon caused by the recognition of external sound that does not actually exist. Existing diagnostic methods for tinnitus are rather subjective and complicated medical examination procedures. The present study aimed to diagnose tinnitus using deep learning analysis of electroencephalographic (EEG) signals while patients performed auditory cognitive tasks. We found that, during an active oddball task, patients with tinnitus could be identified with an area under the curve of 0.886 through a deep learning model (EEGNet) using EEG signals. Furthermore, using broadband (0.5 to 50 Hz) EEG signals, an analysis of the EEGNet convolutional kernel feature maps revealed that alpha activity might play a crucial role in identifying patients with tinnitus. A subsequent time-frequency analysis of the EEG signals indicated that the tinnitus group had significantly reduced pre-stimulus alpha activity compared with the healthy group. These differences were observed in both the active and passive oddball tasks. Only the target stimuli during the active oddball task yielded significantly higher evoked theta activity in the healthy group compared with the tinnitus group. Our findings suggest that task-relevant EEG features can be considered as a neural signature of tinnitus symptoms and support the feasibility of EEG-based deep-learning approach for the diagnosis of tinnitus.

The thalamocortical inhibitory network controls human conscious perception.

Although conscious perception is a fundamental cognitive function, its neural correlates remain unclear. It remains debatable whether thalamocortical interactions play a decisive role in conscious perception. To clarify this, we used functional magnetic resonance imaging (fMRI) where flickering red and green visual cues could be perceived either as a non-fused colour or fused colour. Here we show significantly differentiated fMRI neurodynamics only in higher-order thalamocortical regions, compared with first-order thalamocortical regions. Anticorrelated neurodynamic behaviours were observed between the visual stream network and default-mode network. Its dynamic causal modelling consistently provided compelling evidence for the involvement of higher-order thalamocortical iterative integration during conscious perception of fused colour, while inhibitory control was revealed during the non-fusion condition. Taken together with our recent magnetoencephalography study, our fMRI findings corroborate a thalamocortical inhibitory model for consciousness, where both thalamic inhibitory regulation and integrative signal iterations across higher-order thalamocortical regions are essential for conscious perception.

Neurodynamic correlates for the cross-frequency coupled transcranial alternating current stimulation during working memory performance.

Transcranial current stimulation is a neuromodulation technique used to modulate brain oscillations and, in turn, to enhance human cognitive function in a non-invasive manner. This study investigated whether cross-frequency coupled transcranial alternating current stimulation (CFC-tACS) improved working memory performance. Participants in both the tACS-treated and sham groups were instructed to perform a modified Sternberg task, where a combination of letters and digits was presented. Theta-phase/high-gamma-amplitude CFC-tACS was administered over electrode F3 and its four surrounding return electrodes (Fp1, Fz, F7, and C3) for 20 min. To identify neurophysiological correlates for the tACS-mediated enhancement of working memory performance, we analyzed EEG alpha and theta power, cross-frequency coupling, functional connectivity, and nodal efficiency during the retention period of the working memory task. We observed significantly reduced reaction times in the tACS-treated group, with suppressed treatment-mediated differences in frontal alpha power and unidirectional Fz-delta-phase to Oz-high-gamma-amplitude modulation during the second half of the retention period when network analyses revealed tACS-mediated fronto-occipital dissociative neurodynamics between alpha suppression and delta/theta enhancement. These findings indicate that tACS modulated top-down control and functional connectivity across the fronto-occipital regions, resulting in improved working memory performance. Our observations are indicative of the feasibility of enhancing cognitive performance by the CFC-formed tACS.

Deep-Learning-Based Automatic Selection of Fewest Channels for Brain-Machine Interfaces.

Due to the development of convenient brain-machine interfaces (BMIs), the automatic selection of a minimum channel (electrode) set has attracted increasing interest because the decrease in the number of channels increases the efficiency of BMIs. This study proposes a deep-learning-based technique to automatically search for the minimum number of channels applicable to general BMI paradigms using a compact convolutional neural network for electroencephalography (EEG)-based BMIs. For verification, three types of BMI paradigms are assessed: 1) the typical P300 auditory oddball; 2) the new top-down steady-state visually evoked potential; and 3) the endogenous motor imagery. We observe that the optimized minimal EEG-channel sets are automatically selected in all three cases. Their decoding accuracies using the minimal channels are statistically equivalent to (or even higher than) those based on all channels. The brain areas of the selected channel set are neurophysiologically interpretable for all of these cognitive task paradigms. This study shows that the minimal EEG channel set can be automatically selected, irrespective of the types of BMI paradigms or EEG input features using a deep-learning approach, which also contributes to their portability.

Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex.

The prefrontal cortex (PFC) plays a pivotal role in goal-directed cognition, yet its representational code remains an open problem with decoding techniques ineffective in disentangling task-relevant variables from PFC. Here we applied regularized linear discriminant analysis to human scalp EEG data and were able to distinguish a mental-rotation task versus a color-perception task with 87% decoding accuracy. Dorsal and ventral areas in lateral PFC provided the dominant features dissociating the two tasks. Our findings show that EEG can reliably decode two independent task states from PFC and emphasize the PFC dorsal/ventral functional specificity in processing the where rotation task versus the what color task.

Rich-club in the brain's macrostructure: Insights from graph theoretical analysis.

The brain is a complex network. Growing evidence supports the critical roles of a set of brain regions within the brain network, known as the brain's cores or hubs. These regions require high energy cost but possess highly efficient neural information transfer in the brain's network and are termed the rich-club. The rich-club of the brain network is essential as it directly regulates functional integration across multiple segregated regions and helps to optimize cognitive processes. Here, we review the recent advances in rich-club organization to address the fundamental roles of the rich-club in the brain and discuss how these core brain regions affect brain development and disorders. We describe the concepts of the rich-club behind network construction in the brain using graph theoretical analysis. We also highlight novel insights based on animal studies related to the rich-club and illustrate how human studies using neuroimaging techniques for brain development and psychiatric/neurological disorders may be relevant to the rich-club phenomenon in the brain network.

Thalamocortical inhibitory dynamics support conscious perception.

Whether thalamocortical interactions play a decisive role in conscious perception remains an open question. We presented rapid red/green color flickering stimuli, which induced the mental perception of either an illusory orange color or non-fused red and green colors. Using magnetoencephalography, we observed 6-Hz thalamic activity associated with thalamocortical inhibitory coupling only during the conscious perception of the illusory orange color. This sustained thalamic disinhibition was temporally coupled with higher visual cortical activation during the conscious perception of the orange color, providing neurophysiological evidence of the role of thalamocortical synchronization in conscious awareness of mental representation. Bayesian model comparison consistently supported the thalamocortical model in conscious perception. Taken together, experimental and theoretical evidence established the thalamocortical inhibitory network as a gateway to conscious mental representations.

New Cognitive Neurotechnology Facilitates Studies of Cortical-Subcortical Interactions.

Most of the studies employing neuroimaging have focused on cortical and subcortical signals individually to obtain neurophysiological signatures of cognitive functions. However, understanding the dynamic communication between the cortex and subcortical structures is essential for unraveling the neural correlates of cognition. In this quest, magnetoencephalography (MEG) and electroencephalography (EEG) are the methods of choice because they are noninvasive electrophysiological recording techniques with high temporal resolution. Sophisticated MEG/EEG source estimation techniques and network analysis methods, developed recently, can provide a more comprehensive understanding of the neurophysiological mechanisms of fundamental cognitive processes. Used together with noninvasive modulation of cortical-subcortical communication, these approaches may open up new possibilities for expanding the repertoire of noninvasive cognitive neurotechnology.

The absence of resting-state high-gamma cross-frequency coupling in patients with tinnitus.

Tinnitus is a psychoacoustic phantom perception of currently unknown neuropathology. Despite a growing number of post-stimulus tinnitus studies, uncertainty still exists regarding the neural signature of tinnitus in the resting-state brain. In the present study, we used high-gamma cross-frequency coupling and a Granger causality analysis to evaluate resting-state electroencephalographic (EEG) data in healthy participants and patients with tinnitus. Patients with tinnitus lacked robust frontal delta-phase/central high-gamma-amplitude coupling that was otherwise clearly observed in healthy participants. Since low-frequency phase and high-frequency amplitude coupling reflects inter-regional communication during cognitive processing, and given the absence of frontal modulation in patients with tinnitus, we hypothesized that tinnitus might be related to impaired prefrontal top-down inhibitory control. A Granger causality analysis consistently showed abnormally pronounced functional connectivity of low-frequency activity in patients with tinnitus, possibly reflecting a deficiency in large-scale communication during the resting state. Moreover, different causal neurodynamics were characterized across two subgroups of patients with tinnitus; the T1 group (with higher P300 amplitudes) showed abnormal frontal-to-auditory cortical information flow, whereas the T2 group (with lower P300 amplitudes) exhibited abnormal auditory-to-frontal cortical information control. This dissociation in resting-state low-frequency causal connectivity is consistent with recent post-stimulus observations. Taken together, our findings suggest that maladaptive neuroplasticity or abnormal reorganization occurs in the auditory default mode network of patients with tinnitus. Additionally, our data highlight the utility of resting-state EEG for the quantitative diagnosis of tinnitus symptoms and the further characterization of tinnitus subtypes.

Harnessing Prefrontal Cognitive Signals for Brain-Machine Interfaces.

Brain-machine interfaces (BMIs) enable humans to interact with devices by modulating their brain signals. Despite impressive technological advancements, several obstacles remain. The most commonly used BMI control signals are derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of human intentions. Therefore, additional sources of brain activity for controlling BMIs need to be explored. In particular, higher-order cognitive brain signals, specifically those encoding goal-directed intentions, are natural candidates for enlarging the repertoire of BMI control signals and making them more efficient and intuitive. Thus, here, we identify the prefrontal brain area as a key target region for future BMIs, given its involvement in higher-order, goal-oriented cognitive processes.

Top-down and bottom-up neurodynamic evidence in patients with tinnitus.

Although a peripheral auditory (bottom-up) deficit is an essential prerequisite for the generation of tinnitus, central cognitive (top-down) impairment has also been shown to be an inherent neuropathological mechanism. Using an auditory oddball paradigm (for top-down analyses) and a passive listening paradigm (for bottom-up analyses) while recording electroencephalograms (EEGs), we investigated whether top-down or bottom-up components were more critical in the neuropathology of tinnitus, independent of peripheral hearing loss. We observed significantly reduced P300 amplitudes (reflecting fundamental cognitive processes such as attention) and evoked theta power (reflecting top-down regulation in memory systems) for target stimuli at the tinnitus frequency of patients with tinnitus but without hearing loss. The contingent negative variation (reflecting top-down expectation of a subsequent event prior to stimulation) and N100 (reflecting auditory bottom-up selective attention) were different between the healthy and patient groups. Interestingly, when tinnitus patients were divided into two subgroups based on their P300 amplitudes, their P170 and N200 components, and annoyance and distress indices to their tinnitus sound were different. EEG theta-band power and its Granger causal neurodynamic results consistently support a double dissociation of these two groups in both top-down and bottom-up tasks. Directed cortical connectivity corroborates that the tinnitus network involves the anterior cingulate and the parahippocampal areas, where higher-order top-down control is generated. Together, our observations provide neurophysiological and neurodynamic evidence revealing a differential engagement of top-down impairment along with deficits in bottom-up processing in patients with tinnitus but without hearing loss.

Decoding of top-down cognitive processing for SSVEP-controlled BMI.

We present a fast and accurate non-invasive brain-machine interface (BMI) based on demodulating steady-state visual evoked potentials (SSVEPs) in electroencephalography (EEG). Our study reports an SSVEP-BMI that, for the first time, decodes primarily based on top-down and not bottom-up visual information processing. The experimental setup presents a grid-shaped flickering line array that the participants observe while intentionally attending to a subset of flickering lines representing the shape of a letter. While the flickering pixels stimulate the participant's visual cortex uniformly with equal probability, the participant's intention groups the strokes and thus perceives a 'letter Gestalt'. We observed decoding accuracy of 35.81% (up to 65.83%) with a regularized linear discriminant analysis; on average 2.05-fold, and up to 3.77-fold greater than chance levels in multi-class classification. Compared to the EEG signals, an electrooculogram (EOG) did not significantly contribute to decoding accuracies. Further analysis reveals that the top-down SSVEP paradigm shows the most focalised activation pattern around occipital visual areas; Granger causality analysis consistently revealed prefrontal top-down control over early visual processing. Taken together, the present paradigm provides the first neurophysiological evidence for the top-down SSVEP BMI paradigm, which potentially enables multi-class intentional control of EEG-BMIs without using gaze-shifting.

Porohyperelastic anatomical models for hydrocephalus and idiopathic intracranial hypertension.

OBJECT: Brain deformation can be seen in hydrocephalus and idiopathic intracranial hypertension (IIH) via medical images. The phenomenology of local effects, brain shift, and raised intracranial pressure and herniation are textbook concepts. However, there are still uncertainties regarding the specific processes that occur when brain tissue is subject to the mechanical stress of different temporal and spatial profiles of the 2 neurological disorders. Moreover, recent studies suggest that IIH and hydrocephalus may be diseases with opposite pathogenesis. Nevertheless, the similarities and differences between the 2 subjects have not been thoroughly investigated. METHODS: An anatomical porohyperelastic finite element model was used to assess the brain tissue responses associated with hydrocephalus and IIH. The same set of boundary conditions, with the exception of brain loading for development of the transmantle pressure gradient, was applied for the 2 models. The distribution of stress and strain during tissue distortion is described by the mechanical parameters. RESULTS: The results of both the hydrocephalus and IIH models correlated with pathological characteristics. For the hydrocephalus model, periventricular edema was associated with the presence of positive volumetric strain and void ratio in the lateral ventricle horns. By contrast, the IIH model revealed edema across the cerebral mantle, including the centrum semiovale, with a positive void ratio and volumetric strain. CONCLUSIONS: The model simulates all the clinical features in correlation with the MR images obtained in patients with hydrocephalus and IIH, thus providing support for the role of the transmantle pressure gradient and capillary CSF absorption in CSF-related brain deformation. The finite element methods can be used for a better understanding of the pathophysiological mechanisms of neurological disorders associated with parenchymal volumetric fluctuation.

Blue light aids in coping with the post-lunch dip: an EEG study.

The 'post-lunch dip' is a commonly experienced period of drowsiness in the afternoon hours. If this inevitable period can be disrupted by an environmental cue, the result will be enhanced workplace performance. Because blue light is known to be a critical cue for entraining biological rhythms, we investigated whether blue light illumination can be a practical strategy for coping with the post-lunch dip. Twenty healthy participants underwent a continuous performance test, during which the electroencephalogram (EEG) was recorded under four different illumination conditions: dark ( < 0.3 lx), 33% blue-enriched light, 66% blue-enriched light and white polychromatic light. As a result, exposure to blue-enriched light during the post-lunch dip period significantly reduced the EEG alpha activity, and increased task performance. Since desynchronisation of alpha activity reflects enhancement of vigilance, our findings imply that blue light might disrupt the post-lunch dip. Subsequent exploration of illumination parameters will be beneficial for possible chronobiological and ergonomic applications.

Neurophysiologic correlates of sonication treatment in patients with essential tremor.

Transcranial magnetic resonance imaging-guided high-intensity focused ultrasound (MRgHIFU) is gaining attention as a potent substitute for surgical intervention in the treatment of neurologic disorders. To discern the neurophysiologic correlates of its therapeutic effects, we applied MRgHIFU to an intractable neurologic disorder, essential tremor, while measuring magnetoencephalogram mu rhythms from the motor cortex. Focused ultrasound sonication destroyed tissues by focusing a high-energy beam on the ventralis intermedius nucleus of the thalamus. The post-treatment effectiveness was also evaluated using the clinical rating scale for tremors. Thalamic MRgHIFU had substantial therapeutic effects on patients, based on MRgHIFU-mediated improvements in movement control and significant changes in brain mu rhythms. Ultrasonic thalamotomy may reduce hyper-excitable activity in the motor cortex, resulting in normalized behavioral activity after sonication treatment. Thus, non-invasive and spatially accurate MRgHIFU technology can serve as a potent therapeutic tool with broad clinical applications.