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 Substudy of a Randomized Controlled Trial.

BACKGROUND: Although remimazolam is used as a general anesthetic in elderly patients due to its hemodynamic stability, the electroencephalogram characteristics of remimazolam are not well known. The purpose of this study was to identify the electroencephalographic 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-1 · h-1, and propofol was administered at a target effect-site concentration of 3.5 µg/ml. The electroencephalogram signals from eight channels (Fp1, Fp2, Fz, F3, F4, Pz, P3, and P4, referenced to A2, using the 10 to 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 averages 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] and -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.

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.

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.

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.

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.

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.

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.

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 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.

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.

Focused ultrasound modulates region-specific brain activity.

We demonstrated the in vivo feasibility of using focused ultrasound (FUS) to transiently modulate (through either stimulation or suppression) the function of regional brain tissue in rabbits. FUS was delivered in a train of pulses at low acoustic energy, far below the cavitation threshold, to the animal's somatomotor and visual areas, as guided by anatomical and functional information from magnetic resonance imaging (MRI). The temporary alterations in the brain function affected by the sonication were characterized by both electrophysiological recordings and functional brain mapping achieved through the use of functional MRI (fMRI). The modulatory effects were bimodal, whereby the brain activity could either be stimulated or selectively suppressed. Histological analysis of the excised brain tissue after the sonication demonstrated that the FUS did not elicit any tissue damages. Unlike transcranial magnetic stimulation, FUS can be applied to deep structures in the brain with greater spatial precision. Transient modulation of brain function using image-guided and anatomically-targeted FUS would enable the investigation of functional connectivity between brain regions and will eventually lead to a better understanding of localized brain functions. It is anticipated that the use of this technology will have an impact on brain research and may offer novel therapeutic interventions in various neurological conditions and psychiatric disorders.

Focused ultrasound-mediated suppression of chemically-induced acute epileptic EEG activity.

BACKGROUND: Epilepsy is a common neurological disorder, which is attributed to uncontrollable abnormal hyper-excitability of neurons. We investigated the feasibility of using low-intensity, pulsed radiation of focused ultrasound (FUS) to non-invasively suppress epileptic activity in an animal model (rat), which was induced by the intraperitonial injection of pentylenetetrazol (PTZ). RESULTS: After the onset of induced seizures, FUS was transcranially administered to the brain twice for three minutes each while undergoing electroencephalographic (EEG) monitoring. An air-backed, spherical segment ultrasound transducer (diameter: 6 cm; radius-of-curvature: 7 cm) operating at a fundamental frequency of 690 KHz was used to deliver a train of 0.5 msec-long pulses of sonication at a repetitive rate of 100 Hz to the thalamic areas of the brain. The acoustic intensity (130 mW/cm2) used in the experiment was sufficiently within the range of safety guidelines for the clinical ultrasound imaging. The occurrence of epileptic EEG bursts from epilepsy-induced rats significantly decreased after sonication when it was compared to the pre-sonication epileptic state. The PTZ-induced control group that did not receive any sonication showed a sustained number of epileptic EEG signal bursts. The animals that underwent sonication also showed less severe epileptic behavior, as assessed by the Racine score. Histological analysis confirmed that the sonication did not cause any damage to the brain tissue. CONCLUSIONS: These results revealed that low-intensity, pulsed FUS sonication suppressed the number of epileptic signal bursts using acute epilepsy model in animal. Due to its non-invasiveness and spatial selectivity, FUS may offer new perspectives for a possible non-invasive treatment of epilepsy.

EEG oscillations reflect visual short-term memory processes for the change detection in human faces.

People often fail to notice a large change in the visual scene when the change occurs during a brief interruption of the viewing. Since the change is well above perceptual threshold in continuous viewing, the failure (termed change blindness) has been attributed to abnormal visual short-term memory (VSTM). However, it is still unclear where the abnormality lies among the phases in VSTM, namely, encoding, maintenance, and retrieval-comparison. EEG oscillations, especially the gamma activity, have been suggested as neural signatures of VSTM, but have not been examined in the context of change blindness. Thus, we asked in the present study whether change detection or failure is correlated with EEG oscillatory activities and, if so, whether the timing and the spatial distribution of the oscillations could pin-point the abnormal phase of VSTM in change blindness. While on EEG recording, subjects watched morphed pictures of human faces in trials which consisted of a 200-ms initial image display, a 500-ms blank period, and a 200-ms comparison image display. The two images were either the same or clearly different above threshold. Trials with different images were classified as hit or missed, based on subjects' responses, and EEG data were compared between the two types of trials. Enhanced gamma activity was observed in the right temporal-parietal region during all periods in the hit trials compared to the missed ones. Frontal theta activity was increased during initial image encoding, whereas beta activity was decreased during maintenance and retrieval-comparison in the hit trials. These results point to weak encoding of initial images as the culprit for a later failure in change detection, while abnormal processing in subsequent phases of VSTM may result from the weak encoding and also contribute to change blindness.

Task-related modulation of anterior theta and posterior alpha EEG reflects top-down preparation.

BACKGROUND: Prestimulus EEG alpha activity in humans has been considered to reflect ongoing top-down preparation for the performance of subsequent tasks. Since theta oscillations may be related to poststimulus top-down processing, we investigated whether prestimulus EEG theta activity also reflects top-down cognitive preparation for a stimulus. RESULTS: We recorded EEG data from 15 healthy controls performing a color and shape discrimination task, and used the wavelet transformation to investigate the time course and power of oscillatory activity in the signals. We observed a relationship between both anterior theta and posterior alpha power in the prestimulus period and the type of subsequent task. CONCLUSIONS: Since task-differences were reflected in both theta and alpha activities prior to stimulus onset, both prestimulus theta (particularly around the anterior region) and prestimulus alpha (particularly around the posterior region) activities may reflect prestimulus top-down preparation for the performance of subsequent tasks.

A thalamic reticular networking model of consciousness.

[BACKGROUND]: It is reasonable to consider the thalamus a primary candidate for the location of consciousness, given that the thalamus has been referred to as the gateway of nearly all sensory inputs to the corresponding cortical areas. Interestingly, in an early stage of brain development, communicative innervations between the dorsal thalamus and telencephalon must pass through the ventral thalamus, the major derivative of which is the thalamic reticular nucleus (TRN). The TRN occupies a striking control position in the brain, sending inhibitory axons back to the thalamus, roughly to the same region where they receive afferents. [HYPOTHESES]: The present study hypothesizes that the TRN plays a pivotal role in dynamic attention by controlling thalamocortical synchronization. The TRN is thus viewed as a functional networking filter to regulate conscious perception, which is possibly embedded in thalamocortical networks. Based on the anatomical structures and connections, modality-specific sectors of the TRN and the thalamus appear to be responsible for modality-specific perceptual representation. Furthermore, the coarsely overlapped topographic maps of the TRN appear to be associated with cross-modal or unitary conscious awareness. Throughout the latticework structure of the TRN, conscious perception could be accomplished and elaborated through accumulating intercommunicative processing across the first-order input signal and the higher-order signals from its functionally associated cortices. As the higher-order relay signals run cumulatively through the relevant thalamocortical loops, conscious awareness becomes more refined and sophisticated. [CONCLUSIONS]: I propose that the thalamocortical integrative communication across first- and higher-order information circuits and repeated feedback looping may account for our conscious awareness. This TRN-modulation hypothesis for conscious awareness provides a comprehensive rationale regarding previously reported psychological phenomena and neurological symptoms such as blindsight, neglect, the priming effect, the threshold/duration problem, and TRN-impairment resembling coma. This hypothesis can be tested by neurosurgical investigations of thalamocortical loops via the TRN, while simultaneously evaluating the degree to which conscious perception depends on the severity of impairment in a TRN-modulated network.

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.

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.

Prestimulus EEG alpha activity reflects temporal expectancy.

Since prestimulus EEG alpha activity has recently been considered to convey prestimulus top-down processing, we investigated whether prestimulus alpha activity reflects temporal expectancy of upcoming stimulation even under the non-classical contingent negative variation (CNV) paradigm. EEG was recorded from 16 subjects performing a color and a shape discrimination task manipulated with constant and variable inter-stimulus interval (ISI) conditions. The power of oscillatory activity was investigated by convolving the EEG signals with Morlet wavelets. The constant ISI condition yielded significantly shorter reaction times than the variable ISI condition, indicating more efficient preparation for upcoming stimuli during the constant ISI. We found significantly higher prestimulus alpha activity in the constant ISI condition than in the variable ISI condition, but no significant CNV even in the constant ISI condition. Such a reflection of temporal expectancy in the prestimulus alpha activity corroborates that the prestimulus top-down mental state for preparing upcoming task-performance is considerably reflected in the prestimulus ongoing alpha activity.