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Integrating animals into therapy is applied increasingly in patients in a minimally conscious state (MCS). This pilot study investigates the effect of animal presence on frontal brain activity in MCS patients compared to healthy subjects. O; 2; HB, HHb and tHb of two MCS patients and two healthy adults was measured in frontal cortex using functional near-infrared spectroscopy during three sessions with a live animal and three sessions with a mechanical toy animal present. Each session had five phases: (1) baseline, (2) watching animal, (3) passive contact, (4) active contact, (5) neutral. Data were descriptively analysed. All participants showed the largest hemodynamic response during direct contact with the live or toy animal compared to "baseline" and "watching." During active contact, three of the four participants showed a stronger response when stroking the live compared to the toy animal. All participants showed an inverted signal with higher HHb than O; 2; Hb concentrations while stroking the live or toy animal. Animal contact leads to a neurovascular reaction in both MCS patients and healthy subjects, indicating elevated neural activity in the frontal cortex. We conclude that while a toy animal can elicit attention processes, active contact to a living animal is combined with emotional processes.

Age-related declines in associative memory are ubiquitous, having been observed across a wide array of stimuli and experimental paradigms. Research further shows that such decreases in behavioral discriminability arise from increases in false memories for recombined lures. The current study examined the underlying neural basis of associative false memories by using representational similarity analyses to examine both age differences in the reactivation of encoded representations during retrieval and the neural overlap in the similarity of neural patterns underlying targets and related lures during retrieval. Behaviorally, we observed an age-related reduction in d’, which was shown to be driven by increased false alarms in the older adults. While we found no age difference in the relationship between patterns of neural activity underlying hits across memory phases (as measured by ERS), the similarity of neural patterns underlying targets and lures was affected by age. Specifically, while younger and older adults exhibited overall higher pattern similarity between hits and CRs compared to hits and FAs (as measured by RSA), this difference was reduced in older adults within occipital cortices. Additionally, greater Hit-FA representational similarity correlated with increases in associative FAs across occipital, frontal, and parietal cortices. Results suggest that while neural representations underlying targets may not differ across age, greater pattern similarity between the neural representation of targets and lures may reflect reduced distinctiveness of the information encoded in memory, such that old and new items are more difficult to discriminate, leading to more false alarms.

Aesthetic experiences have an influence on many aspects of life. Interest in the neural basis of aesthetic experiences has grown rapidly in the past decade, and fMRI studies have identified several brain systems supporting aesthetic experiences. Work on the rapid neuronal dynamics of aesthetic experience, however, is relatively scarce. This study adds to this field by investigating the experience of being aesthetically moved by means of ERP and time–frequency analysis. Participants' EEG was recorded while they viewed a diverse set of artworks and evaluated the extent to which these artworks moved them. Results show that being aesthetically moved is associated with a sustained increase in gamma activity over centroparietal regions. In addition, alpha power over right frontocentral regions was reduced in high- and low-moving images, compared to artworks given intermediate ratings. We interpret the gamma effect as an indication for sustained savoring processes for aesthetically moving artworks compared to aesthetically less-moving artworks. The alpha effect is interpreted as an indication of increased attention for aesthetically salient images. In contrast to previous works, we observed no significant effects in any of the established ERP components, but we did observe effects at latencies longer than 1 sec. We conclude that EEG time–frequency analysis provides useful information on the neuronal dynamics of aesthetic experience.

Minimally delayed (MD) saccades require inhibition of a prepotent response until a target is extinguished, and unlike the more extensively studied antisaccade task, do not require the additional cognitive component of vector inversion (i.e., 180° target spatial transposition). Here, participants completed separate blocks of MD and prepotent stimulus-driven saccades (i.e., respond at target onset) while cortical hemodynamics were measured via functional transcranial Doppler ultrasound. MD saccades produced longer and more variable reaction times (RT). In turn, MD and stimulus-driven saccade preparatory phase cortical hemodynamics increased and decreased, respectively, relative to baseline and the two conditions differed from one another throughout the preparatory phase. The longer RTs and increased cortical hemodynamics of MD saccades is taken to evince response complexity and the increased neural activity to accommodate response inhibition. To our knowledge, such findings provide the first work to examine the neural foundations of MD saccades.

Devices that can record or modulate neural activity are essential tools in clinical diagnostics and monitoring, basic research, and consumer electronics. Realizing stable functional interfaces between manmade electronics and biological tissues is a longstanding challenge that requires device and material innovations to meet stringent safety and longevity requirements and to improve functionality. Compared to conventional materials, nanocarbons and carbides offer a number of specific advantages for neuroelectronics that can enable advances in functionality and performance. Here, we review the latest emerging trends in neuroelectronic interfaces based on nanocarbons and carbides, with a specific emphasis on technologies developed for use in vivo. We highlight specific applications where the ability to tune fundamental material properties at the nanoscale enables interfaces that can safely and precisely interact with neural circuits at unprecedented spatial and temporal scales, ranging from single synapses to the whole human body.

Mindfulness-based interventions have been shown to impact a broad range of outcomes including enhanced attention, memory, and self-regulation. Previously, mindfulness training has been negatively correlated with brain activity across the default mode network nodes following mindfulness-based practice. Currently, little research has been done to understand the neural basis of differences in mindfulness levels in untrained individuals. In this study, we explored the relationship between the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) during the resting state and the level of dispositional mindfulness, which was measured by using the Five Facet Mindfulness Questionnaire (FFMQ). The results showed that the total scores on the FFMQ were negatively correlated with the spontaneous activation of left premotor cortex. This indicates that individuals with higher levels of dispositional mindfulness might require less effort to control their irrelevant motor responses.

Observation is a powerful way to learn efficient actions from others. However, the role of observers’ motor skill in assessing efficiency of others is unknown. Preschoolers are notoriously poor at performing multi-step actions like grasping the handle of a tool. Preschoolers (N = 22) and adults (N = 22) watched video-recorded actors perform efficient and inefficient tool use. Eye tracking showed that preschoolers and adults looked equally long at the videos, but adults looked longer than children at how actors grasped the tool. Deep learning analyses of participants’ eye gaze distinguished efficient from inefficient grasps for adults, but not for children. Moreover, only adults showed differential action-related pupil dilation and neural activity (suppressed oscillation power in the mu frequency) while observing efficient vs. inefficient grasps. Thus, children observe multi-step actions without “seeing” whether the initial step is efficient. Findings suggest that observer’s own motor efficiency determines whether they can perceive action efficiency in others.

Establishing consistent relationships between neural activity and behavior is a challenge in human cognitive neuroscience research. We addressed this issue using variable time constraints in an oddball frequency-sweep design for visual discrimination of complex images (face exemplars). Sixteen participants viewed sequences of ascending presentation durations, from 25 to 333 ms (40–3 Hz stimulation rate) while their electroencephalogram (EEG) was recorded. Throughout each sequence, the same unfamiliar face picture was repeated with variable size and luminance changes while different unfamiliar facial identities appeared every 1 s (1 Hz). A neural face individuation response, tagged at 1 Hz and its unique harmonics, emerged over the occipito-temporal cortex at 50 ms stimulus duration (25–100 ms across individuals), with an optimal response reached at 170 ms stimulus duration. In a subsequent experiment, identity changes appeared non-periodically within fixed-frequency sequences while the same participants performed an explicit face individuation task. The behavioral face individuation response also emerged at 50 ms presentation time, and behavioral accuracy correlated with individual participants’ neural response amplitude in a weighted middle stimulus duration range (50–125 ms). Moreover, the latency of the neural response peaking between 180 and 200 ms correlated strongly with individuals’ behavioral accuracy in this middle duration range, as measured independently. These observations point to the minimal (50 ms) and optimal (170 ms) stimulus durations for human face individuation and provide novel evidence that inter-individual differences in the magnitude and latency of early, high-level neural responses are predictive of behavioral differences in performance at this function.

Speech neuroprosthetics aim to provide a natural communication channel to individuals who are unable to speak due to physical or neurological impairments. Real-time synthesis of acoustic speech directly from measured neural activity could enable natural conversations and notably improve quality of life, particularly for individuals who have severely limited means of communication. Recent advances in decoding approaches have led to high quality reconstructions of acoustic speech from invasively measured neural activity. However, most prior research utilizes data collected during open-loop experiments of articulated speech, which might not directly translate to imagined speech processes. Here, we present an approach that synthesizes audible speech in real-time for both imagined and whispered speech conditions. Using a participant implanted with stereotactic depth electrodes, we were able to reliably generate audible speech in real-time. The decoding models rely predominately on frontal activity suggesting that speech processes have similar representations when vocalized, whispered, or imagined. While reconstructed audio is not yet intelligible, our real-time synthesis approach represents an essential step towards investigating how patients will learn to operate a closed-loop speech neuroprosthesis based on imagined speech., Miguel Angrick et al. develop an intracranial EEG-based method to decode imagined speech from a human patient and translate it into audible speech in real-time. This report presents an important proof of concept that acoustic output can be reconstructed on the basis of neural signals, and serves as a valuable step in the development of neuroprostheses to help nonverbal patients interact with their environment.

Congenital Zika Syndrome (CZS) is characterized by changes in cranial morphology associated with heterogeneous neurological manifestations and cognitive and behavioral impairments. In this syndrome, longitudinal neuroimaging could help clinicians to predict developmental trajectories of children and tailor treatment plans accordingly. However, regularly acquiring magnetic resonance imaging (MRI) has several shortcomings besides cost, particularly those associated with childrens' clinical presentation as sensitivity to environmental stimuli. The indirect monitoring of local neural activity by non-invasive functional near-infrared spectroscopy (fNIRS) technique can be a useful alternative for longitudinally accessing the brain function in children with CZS. In order to provide a common framework for advancing longitudinal neuroimaging assessment, we propose a principled guideline for fNIRS acquisition and analyses in children with neurodevelopmental disorders. Based on our experience on collecting fNIRS data in children with CZS we emphasize the methodological challenges, such as clinical characteristics of the sample, desensitization, movement artifacts and environment control, as well as suggestions for tackling such challenges. Finally, metrics based on fNIRS can be associated with established clinical metrics, thereby opening possibilities for exploring this tool as a long-term predictor when assessing the effectiveness of treatments aimed at children with severe neurodevelopmental disorders.

The moment of awakening from sleep reflects a profound transformation in neural activity and behavior. The thalamus is a key controller of arousal state, but whether its diverse nuclei exhibit coordinated or distinct activity at transitions in behavioral arousal state is not known. Using fast fMRI at ultra-high field (7 Tesla), we measured sub-second activity across thalamocortical networks and within nine thalamic nuclei to delineate these dynamics during spontaneous transitions in behavioral arousal state. We discovered a stereotyped sequence of activity across thalamic nuclei that preceded behavioral arousal after a period of inactivity, followed by widespread cortical deactivation. These thalamic dynamics were linked to whether participants remained awake or fell back asleep, with unified thalamic activation reflecting subsequent maintenance of awake behavior. These results provide an outline of the complex interactions across thalamocortical circuits that orchestrate arousal state transitions, and additionally, demonstrate that fast fMRI can resolve sub-second subcortical dynamics in the human brain.

Theta-burst transcranial magnetic stimulation (TBS) has become a standard non-invasive technique to induce offline changes in cortical excitability in human volunteers. Yet, TBS suffers from a high variability across subjects. A better knowledge about how TBS affects neural activity in vivo could uncover its mechanisms of action and ultimately allow its mainstream use in basic science and clinical applications. To address this issue, we applied continuous TBS (cTBS, 300 pulses) in awake behaving rhesus monkeys and quantified its after-effects on neuronal recordings and behavior. Guided by anatomical MRI, we recorded single-cell activity in parietal area PFG during passive fixation of real-world objects. Overall, we observed a pronounced, long-lasting and highly reproducible reduction in neuronal excitability after cTBS in individual parietal neurons, with some neurons exhibiting periods of hyperexcitability during the recovery phase. We applied the same stimulation protocol during visually-guided grasping of objects, and observed a significant grasping impairment. These results provide the first experimental evidence on the effects of cTBS on single neurons in awake behaving monkeys.

Attending toward fearful faces and other threatening stimuli increase the chance of survival. The dot-probe task is a commonly used measure of spatial attention. Event-related potentials (ERPs) have been found to be a reliable measure of attentional bias. The dot-probe literature suggests that posterior contralateral N170 amplitudes are more enhanced by fearful faces compared to ipsilateral amplitudes. However, ERP methods remove non-phase locked frequencies, which provides additional information about neural activity. Specifically, theta oscillations (5–7 Hz) have been linked to attentional processing. The purpose of this study was to examine the relationship between posterior contralateral theta oscillations and N170 amplitudes in the dot-probe task. A modified dot-probe task was used with fear and neutral facial expressions and EEG data was recorded from 33 electrodes. The ERP and time-frequency data were extracted from the P7 and P8 electrodes (left and right occipitotemporal regions). This study found enhanced N170 amplitude and theta oscillations in the electrodes posterior contralateral to the fearful face. Contralateral N170 amplitudes and theta oscillations were related such that greater N170 amplitudes were associated with greater theta oscillations. The results indicated that increased contralateral N170 and theta oscillations are related to each other and underlie attentional bias to fearful faces.

Purpose The planning and execution of motor behaviors require coordination of neurons that are established through synchronization of neural activity. Movements are typically preceded by event-related desynchronization (ERD) in the beta range (15–30 Hz) primarily localized in the motor cortex, while movement onset is associated with event-related synchronization (ERS). It is hypothesized that ERD is important for movement preparation and execution, and ERS serves to inhibit movement and update the motor plan. The primary objective of this study was to determine to what extent movement-related oscillatory brain patterns (ERD and ERS) during verbal and nonverbal tasks may be affected differentially by variations in task complexity. Method Seventeen right-handed adult participants (nine women, eight men; M age = 25.8 years, SD = 5.13) completed a sequential button press and verbal task. The final analyses included data for 15 participants for the nonverbal task and 13 for the verbal task. Both tasks consisted of two complexity levels: simple and complex sequences. Magnetoencephalography was used to record modulations in beta band brain oscillations during task performance. Results Both the verbal and button press tasks were characterized by significant premovement ERD and postmovement ERS. However, only simple sequences showed a distinct transient synchronization during the premovement phase of the task. Differences between the two tasks were reflected in both latency and peak amplitude of ERD and ERS, as well as in lateralization of oscillations. Conclusions Both verbal and nonverbal movements showed a significant desynchronization of beta oscillations during the movement preparation and holding phase and a resynchronization upon movement termination. Importantly, the premovement phase for simple but not complex tasks was characterized by a transient partial synchronization. In addition, the data revealed significant differences between the two tasks in terms of lateralization of oscillatory modulations. Our findings suggest that, while data from the general motor control research can inform our understanding of speech motor control, significant differences exist between the two motor systems that caution against overgeneralization of underlying neural control processes.

Attentional lapses occur commonly and are associated with mind wandering, where focus is turned to thoughts unrelated to ongoing tasks and environmental demands, or mind blanking, where the stream of consciousness itself comes to a halt. To understand the neural mechanisms underlying attentional lapses, we studied the behaviour, subjective experience and neural activity of healthy participants performing a task. Random interruptions prompted participants to indicate their mental states as task-focused, mind-wandering or mind-blanking. Using high-density electroencephalography, we report here that spatially and temporally localized slow waves, a pattern of neural activity characteristic of the transition toward sleep, accompany behavioural markers of lapses and preceded reports of mind wandering and mind blanking. The location of slow waves could distinguish between sluggish and impulsive behaviours, and between mind wandering and mind blanking. Our results suggest attentional lapses share a common physiological origin: the emergence of local sleep-like activity within the awake brain., Attentional lapses occur in many forms such as mind-wandering or mindblanking. Here the authors show different types of attentional lapse are accompanied by slow waves, neural activity that is characteristic of transitions into sleep.

Newly learned information undergoes a process of awake reactivation shortly after the learning offset and we recently demonstrated that this effect can be observed as early as area V1. However, reactivating all experiences can be wasteful and unnecessary, especially for familiar stimuli. Therefore, here we tested whether awake reactivation occurs differentially for new and familiar stimuli. Subjects completed a brief visual task on a stimulus that was either novel or highly familiar due to extensive prior training on it. Replicating our previous results, we found that awake reactivation occurred in V1 for the novel stimulus. On the other hand, brief exposure to the familiar stimulus led to ‘awake suppression’ such that neural activity patterns immediately after exposure to the familiar stimulus diverged from the patterns associated with that stimulus. Further, awake reactivation was observed selectively in V1, whereas awake suppression had similar strength across areas V1–V3. These results are consistent with the presence of a competition between local awake reactivation and top-down awake suppression, with suppression becoming dominant for familiar stimuli., Bang & Rahnev tested whether awake reactivation occurs differentially for new and familiar stimuli, given that reactivating all experiences can be wasteful. They expose participants to brief visual tasks in which the stimulus was either novel or familiar. They observed that whilst novel stimuli were associated with reactivation of cortical area V1, familiar stimuli led to ‘awake suppression’ in which neural activity diverged from patterns previously associated with that stimulus. The results support the existence of competition between local awake reactivation and top-down awake suppression, with suppression being dominant for familiar stimuli.

Electrical signals from the peripheral nervous system have the potential to provide the necessary motor, sensory or autonomic information for implementing closed-loop control of neuroprosthetic or neuromodulatory systems. However, developing methods to recover information encoded in these signals is a significant challenge. Our goal was to test the feasibility of measuring physiologically generated nerve action potentials that can be classified as sensory or motor signals. A tetrapolar recording nerve cuff electrode was used to measure vagal nerve (VN) activity in a rodent model of upper airway obstruction. The effect of upper airway occlusions on VN activity related to respiration (RnP) was calculated and compared for 4 different cases: (1) intact VN, (2) VN transection only proximal to recording electrode, (3) VN transection only distal to the recording electrode, and (4) transection of VN proximal and distal to electrode. We employed a Support Vector Machine (SVM) model with Gaussian Kernel to learn a model capable of classifying efferent and afferent waveforms obtained from the tetrapolar electrode. In vivo results showed that the RnP values decreased significantly during obstruction by 91.7% ± 3.1%, and 78.2% ± 3.4% for cases of intact VN or proximal transection, respectively. In contrast, there were no significant changes for cases of VN transection at the distal end or both ends of the electrode. The SVM model yielded an 85.8% accuracy in distinguishing motor and sensory signals. The feasibility of measuring low-noise directionally-sensitive neural activity using a tetrapolar nerve cuff electrode along with the use of an SVM classifier was shown. Future experimental work in chronic implant studies is needed to support clinical translatability.

Affective future thinking allows us to prepare for future outcomes, but we know little about neural representation of emotional future simulations. We used a multi-voxel pattern analysis to determine whether patterns of neural activity can reliably distinguish between positive and negative future simulations. Neural patterning in the anterior cingulate and ventromedial prefrontal cortices distinguished positive from negative future simulations, indicating that these regions code for the emotional valence of future events. These results support prior findings that anterior medial regions contain representations of emotions across various stimuli, and contribute to identifying potential rewarding outcomes of future events. More broadly, these results demonstrate that the phenomenological features of future thinking can be decoded using neural activity.

Humans perceive expected stimuli faster and more accurately. However, the mechanism behind the integration of expectations with sensory information during perception remains unclear. We investigated the hypothesis that such integration depends on “fusion”—the weighted averaging of different cues informative about stimulus identity. We first trained participants to map a range of tones onto faces spanning a male–female continuum via associative learning. These two features served as expectation and sensory cues to sex, respectively. We then tested specific predictions about the consequences of fusion by manipulating the congruence of these cues in psychophysical and fMRI experiments. Behavioral judgments and patterns of neural activity in auditory association regions revealed fusion of sensory and expectation cues, providing evidence for a precise computational account of how expectations influence perception.

The readiness potential (RP), a slow buildup of electrical potential recorded at the scalp using electroencephalography, has been associated with neural activity involved in movement preparation. It became famous thanks to Benjamin Libet (Brain 1983;106:623-642), who used the time difference between the RP and self-reported time of conscious intention to move to argue that we lack free will. The RP's informativeness about self-generated action and derivatively about free will has prompted continued research on this neural phenomenon. Here, we argue that recent advances in our understanding of the RP, including computational modeling of the phenomenon, call for a reassessment of its relevance for understanding volition and the philosophical problem of free will.

There is growing concern about a potential decline in empathy among medical students over time. Despite the importance of empathy toward patients in medicine, it remains unclear the nature of the changes in empathy among medical students. Thus, we systematically investigated affective and cognitive empathy for patients among medical students using neuroscientific approach. Nineteen medical students who completed their fifth-year medical curriculum and 23 age- and sex-matched nonmedical students participated in a functional magnetic resonance imaging study. Inside a brain scanner, all participants read empathy-eliciting scenarios while adopting either the patient or doctor perspective. Brain activation and self-reported ratings during the experience of empathy were obtained. Behavioral results indicated that all participants reported greater emotional negativity and empathic concern in association with the patient perspective condition than with the doctor perspective condition. Functional brain imaging results indicated that neural activity in the posterior superior temporal region implicated in goal-relevant attention reorienting was overall increased under the patient perspective than the doctor perspective condition. Relative to nonmedical students, medical students showed decreased activity in the temporoparietal region implicated in mentalizing under the patient perspective versus doctor perspective condition. Notably, this same region showed increased activity under the doctor versus patient condition in medical students relative to nonmedical students. This study is among the first to investigate the neural mechanisms of empathy among medical students and the current findings point to the cognitive empathy system as the locus of the primary brain differences associated with empathy toward patients.

Since our environment typically contains more information than can be processed at any one time due to the limited capacity of our visual system, we are bound to differentiate between relevant and irrelevant information. This process, termed attentional selection, is usually categorized into bottom-up and top-down processes. However, recent research suggests reward might also be an important factor in guiding attention. Monetary reward can bias attentional selection in favor of task-relevant targets and reduce the efficiency of visual search when a reward-associated, but task-irrelevant distractor is present. This study is the first to investigate reward-related target and distractor processing in an additional singleton task using neurophysiological measures and source space analysis. Based on previous studies, we hypothesized that source space analysis would find enhanced neural activity in regions of the value-based attention network, such as the visual cortex and the anterior cingulate. Additionally, we went further and explored the time courses of the underlying attentional mechanisms. Our neurophysiological results showed that rewarding distractors led to a stronger attentional capture. In line with this, we found that reward-associated distractors (compared with reward-associated targets) enhanced activation in frontal regions, indicating the involvement of top-down control processes. As hypothesized, source space analysis demonstrated that reward-related targets and reward-related distractors elicited activation in regions of the value-based attention network. However, these activations showed time-dependent differences, indicating that the neural mechanisms underlying reward biasing might be different for task-relevant and task-irrelevant stimuli. Supplementary Information The online version contains supplementary material available at 10.1007/s10548-021-00827-3.

Human and non-human animal behavior is highly malleable and adapts successfully to internal and external demands. Such behavioral success stands in striking contrast to the apparent instability in neural activity (i.e., variability) from which it arises. Here, we summon the considerable evidence across scales, species, and imaging modalities that neural variability represents a key, undervalued dimension for understanding brain-behavior relationships at inter- and intra-individual levels. We believe that only by incorporating a specific focus on variability will the neural foundation of behavior be comprehensively understood.

The use of scene context is a powerful way by which biological organisms guide and facilitate visual search. Although many studies have shown enhancements of target-related electroencephalographic activity (EEG) with synthetic cues, there have been fewer studies demonstrating such enhancements during search with scene context and objects in real world scenes. Here, observers covertly searched for a target in images of real scenes while we used EEG to measure the steady state visual evoked response to objects flickering at different frequencies. The target appeared in its typical contextual location or out of context while we controlled for low-level properties of the image including target saliency against the background and retinal eccentricity. A pattern classifier using EEG activity at the relevant modulated frequencies showed target detection accuracy increased when the target was in a contextually appropriate location. A control condition for which observers searched the same images for a different target orthogonal to the contextual manipulation, resulted in no effects of scene context on classifier performance, confirming that image properties cannot explain the contextual modulations of neural activity. Pattern classifier decisions for individual images was also related to the aggregated observer behavioral decisions for individual images. Together, these findings demonstrate target-related neural responses are modulated by scene context during visual search with real world scenes and can be related to behavioral search decisions.Significance StatementContextual relationships among objects are fundamental for humans to find objects in real world scenes. Although there is a larger literature understanding the brain mechanisms when a target appears at a location indicated by a synthetic cue such as an arrow or box, less is known about how the scene context modulates target-related neural activity. Here we show how neural activity predictive of the presence of a searched object in cluttered real scenes increases when the target object appears at a contextual location and diminishes when it appears at a place that is out of context. The results increase our understanding of how the brain processes real scenes and how context modulates object processing.

The existence of neural correlates of spatial attention is not limited to the reactive stage of stimulus processing: neural activities subtending spatial attention are deployed well ahead of stimulus onset. ERP evidence supporting this proactive (top-down) attentional control is based on trial-by-trial S1-S2 paradigms, where the onset of a directional cue (S1) indicates on which side attention must be directed to respond to an upcoming target stimulus (S2). Crucially, S1 onset trigger both attention and motor preparation, therefore, these paradigms are not ideal to demonstrate the effect of attention at preparatory stage of processing. To isolate top-down anticipatory attention, the present study used a sustained attention paradigm based on a steady cue that indicates the attended side constantly throughout an entire block of trials, without any onset of an attentional cue. The main result consists in the description of the attention effect on the visual negativity (vN) component, a growing neural activity starting before stimulus presentation in extrastriate visual areas. The vN was consistently lateralized in the hemisphere contralateral to the attended side, regardless of the hand to be used. At the opposite, the lateralized motor activity emerged long after, confirming that the hand-selection process followed the spatial attention orientation process. The present study confirms the anticipatory nature of the vN component and corroborate its role in terms of preparatory visuospatial attention.

The long-range temporal correlation (LRTC) in resting-state intrinsic brain activity is known to be associated with temporal behavioral patterns, including decision making based on internal criteria such as self-knowledge. However, the association between the neuronal LRTC and the subjective sense of identity remains to be explored; in other words, whether our subjective sense of consistent self across time relates to the temporal consistency of neural activity. The present study examined the relationship between the LRTC of resting-state scalp electroencephalography (EEG) and a subjective sense of identity measured by the Erikson Psychosocial Stage Inventory (EPSI). Consistent with our prediction based on previous studies of neuronal-behavioral relationships, the frontocentral alpha LRTC correlated negatively with identity confusion. Moreover, from the descriptive analyses, centroparietal beta LRTC showed negative correlations with identity confusion, and frontal theta LRTC showed positive relationships with identity synthesis. These results suggest that more temporal consistency (reversely, less random noise) in intrinsic brain activity is associated with less confused and better-synthesized identity. Our data provide further evidence that the LRTC of intrinsic brain activity might serve as a noise suppression mechanism at the psychological level.

Neural recording technologies increasingly enable simultaneous measurement of neural activity from multiple brain areas. To gain insight into distributed neural computations, a commensurate advance in experimental and analytical methods is necessary. We discuss two opportunities towards this end: the manipulation and modeling of neural population dynamics.

Early adverse experiences are believed to have a profound effect on inhibitory control and the underlying neural regions. In the current study, behavioral and event-related potential (ERP) data were collected during a go/no-go task from adolescents who were involved with the child welfare system due to child maltreatment (n = 129) and low-income, nonmaltreated adolescents (n = 102). The nonmaltreated adolescents were more accurate than the maltreated adolescents on the go/no-go task, particularly on the no-go trials. Paralleling the results with typically developing populations, the nonmaltreated adolescents displayed a more pronounced amplitude of the N2 during the no-go trials than during the go trials. However, the maltreated adolescents demonstrated a more pronounced amplitude of the N2 during the go trials than during the no-go trials. Furthermore, while the groups did not differ during the go trials, the nonmaltreated adolescents displayed a more negative amplitude of the N2 than the maltreated adolescents during no-go trials. In contrast, there was not a significant group difference in amplitude of the P3. Taken together, these results provide evidence that the early adverse experiences encountered by maltreated populations impact inhibitory control and the underlying neural activity in early adolescence.

Intraindividual variability in gait and cognitive performance is distinct from central-tendency measures and associated with clinical outcomes in aging. Knowledge concerning intraindividual variability in neural activity, however, has been relatively scarce, and no research to date has reported on such variability during active walking. The current study addressed this major gap in knowledge. Participants were community-residing older adults (n = 394; mean age = 76.29 ± 6.65 years; %female = 55). Functional near-infrared spectroscopy (fNIRS) was used to measure oxygenated hemoglobin (HbO2) in the prefrontal cortex under three experimental conditions: single-task-walk, single-task-alpha (cognitive task), and dual-task-walk, which required the participants to perform the two single tasks simultaneously. Intraindividual variability in neural activity was operationalized using the standard deviation of fNIRS-derived HbO2 observations assessed during a 30-s interval in each experimental condition. The increase in intraindividual variability in neural activity in the dual-task-walk condition compared to both single-task conditions was associated with the presence of cognitive impairments and being a male. Furthermore, measures of intraindividual variability in neural activity and gait performance were positively correlated only under the dual-task-walk condition. Intraindividual variability in the neural activity of gait may be a novel marker for age-related impairments in mobility and cognitive function. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Vassiliadis P, Derosiere G, Grandjean J, Duque J. Motor training strengthens corticospinal suppression during movement preparation. J Neurophysiol 124: 1656-1666, 2020. First published September 30, 2020; doi:10.1152/jn.00378.2020.-Training can improve motor skills and modify neural activity at rest and during movement execution. Learning-related modulations may also concern motor preparation but the neural correlates and the potential behavioral relevance of such adjustments remain unclear. In humans, preparatory processes have been largely investigated using transcranial magnetic stimulation (TMS) with several studies reporting decreased corticospinal excitability (CSE) relative to a baseline measure at rest; a phenomenon called preparatory suppression. Here, we investigated the effect of motor training on such preparatory suppression, in relation to resting CSE, in humans. We trained participants to initiate quick movements in an instructed-delay reaction time (RT) task and used TMS to investigate changes in CSE over the practice blocks. Training on the task speeded up RTs, with no repercussion on error rates. Training also increased resting CSE. Most interestingly, we found that CSE during action preparation did not mirror the training-related increase observed at rest. Rather, compared with the rising baseline, the degree of preparatory suppression strengthened with practice. This training-related change in preparatory suppression (but not the changes in baseline CSE) predicted RT gains: the subjects showing a greater strengthening of preparatory suppression were also those exhibiting larger gains in RTs. Finally, such a relationship between RTs and preparatory suppression was also evident at the single-trial level, though only in the nonselected effector: RTs were generally faster in trials where preparatory suppression was deeper. These findings suggest that training induces changes in motor preparatory processes that are linked to an enhanced ability to initiate fast movements., NEW & NOTEWORTHY Movement preparation involves a broad suppression in the excitability of the corticospinal pathway, a phenomenon called preparatory suppression. Here, we show that motor training strengthens preparatory suppression and that this strengthening is associated with faster reaction times. Our findings highlight a key role of preparatory suppression in training-driven behavioral improvements.

Reactivation refers to the phenomenon wherein patterns of neural activity expressed during perceptual experience are re-expressed at a later time, a putative neural marker of memory. Reactivation of perceptual content has been observed across many cortical areas and correlates with objective and subjective expressions of memory in humans. However, because reactivation emphasizes similarities between perceptual and memory-based representations, it obscures differences in how perceptual events and memories are represented. Here, we highlight recent evidence of systematic differences in how (and where) perceptual events and memories are represented in the brain. We argue that neural representations of memories are best thought of as spatially transformed versions of perceptual representations. We consider why spatial transformations occur and identify critical questions for future research.

Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait-related modulations of neural activity, we collected high-density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event-related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG-based brain-body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders. ispartof: HUMAN BRAIN MAPPING vol:43 issue:11 pages:3404-3415 ispartof: location:United States status: published

Value-based decision-making is often studied in a static context, where participants decide which option to select from those currently available. However, everyday life often involves an additional dimension: deciding when to select to maximise reward. Recent evidence suggests that agents track the latent reward of an option, updating changes in their latent reward estimate, to achieve appropriate selection timing (latent reward tracking). However, this strategy can be difficult to distinguish from one in which the optimal selection time is estimated in advance, allowing an agent to wait a pre-determined amount of time before selecting, without needing to monitor an option’s latent reward (distance-to-goal tracking). Here we show that these strategies can in principle be dissociated. Human brain activity was recorded using electroencephalography (EEG) while female and male participants performed a novel decision task. Participants were shown an option and decided when to select it, as its latent reward changed from trial-to-trial. While the latent reward was uncued, it could be estimated using cued information about the option’s starting value and value growth rate. We then used representational similarity analysis to assess whether EEG signals more closely resembled latent reward tracking or distance-to-goal tracking. This approach successfully dissociated the strategies in this task. Starting value and growth rate were translated into a distance-to-goal signal, far in advance of selecting the option. Latent reward could not be independently decoded. These results demonstrate the feasibility of using high temporal resolution neural recordings to identify internally computed decision variables in the human brain.Significance StatementReward-seeking behaviour involves acting at the right time. However, the external world does not always tell us when an action is most rewarding, necessitating internal representations that guide action timing. Specifying this internal neural representation is challenging because it might stem from a variety of strategies, many of which make similar predictions about brain activity. This study used a novel approach to test whether alternative strategies could be dissociated in principle. Using representational similarity analysis, we were able to distinguish between candidate internal representations for selection timing. This shows how pattern analysis methods can be used to measure latent decision information in non-invasive neural data.

Semantic processing impairments are present in a proportion of individuals with autism spectrum disorder (ASD). Despite the numerous imaging studies investigating this language domain in ASD, there is a lack of consensus regarding the brain structures showing abnormal pattern of activity. This meta-analysis aimed to identify neural activation patterns present during semantic processing in ASD. Findings reveal activation of areas associated with semantic processing and executive functions in ASD. However, the activation was less concise in comparison to controls and there was less activation in the right hemisphere and in areas associated with executive functions. This provides strong support for impaired semantic processing in ASD that is consistently associated with abnormal patterns of neural activity in the semantic network.

Rumination, repetitively thinking about the causes, consequences, and one's negative affect, has been considered as an important factor of depression. The intrusion of ruminative thoughts is not easily controlled, and it may be useful to visualize one's neural activity related to rumination and to use that information to facilitate one's self‐control. Real‐time fMRI neurofeedback (rtfMRI‐nf) enables one to see and regulate the fMRI signal from their own brain. This proof‐of concept study utilized connectivity‐based rtfMRI‐nf (cnf) to normalize brain functional connectivity (FC) associated with rumination. Healthy participants were instructed to brake or decrease FC between the precuneus and the right temporoparietal junction (rTPJ), associated with high levels of rumination, while engaging in a self‐referential task. The cnf group (n = 14) showed a linear decrease in the precuneus‐rTPJ FC across neurofeedback training (trend [112] = −0.180, 95% confidence interval [CI] −0.330 to −0.031, while the sham group (n = 14) showed a linear increase in the target FC (trend [112] = 0.151, 95% CI 0.017 to 0.299). Although the cnf group showed a greater reduction in state‐rumination compared to the sham group after neurofeedback training (p, Regions of interest (ROI) for the connectivity‐based rtfMRI‐nf and the neurofeedback algorithm. (a) ROIs for the connectivity‐based rtfMRI‐nf. (b) Neurofeedback algorithm and display. Red circles and arrows indicate the precuneus ROI and BOLD activities, and blue circles and arrows indicate the right temporoparietal junction (rTPJ) ROI and BOLD activities. The sidebars on the screen were updated every 2‐s with positive feedback (+1: light blue color) or no feedback (0: blank color).

OBJECTIVE Report pilot findings of neurobehavioral gains and network changes observed in persons with disordered consciousness (DoC) who received repetitive transcranial magnetic stimulation (rTMS) or amantadine (AMA), and then rTMS+AMA. PARTICIPANTS Four persons with DoC 1 to 15 years after traumatic brain injury (TBI). DESIGN Alternate treatment-order, within-subject, baseline-controlled trial. MAIN MEASURES For group and individual neurobehavioral analyses, predetermined thresholds, based on mixed linear-effects models and conditional minimally detectable change, were used to define meaningful neurobehavioral change for the Disorders of Consciousness Scale-25 (DOCS) total and Auditory-Language measures. Resting-state functional connectivity (rsFC) of the default mode and 6 other networks was examined. RESULTS Meaningful gains in DOCS total measures were observed for 75% of treatment segments and auditory-language gains were observed after rTMS, which doubled when rTMS preceded rTMS+AMA. Neurobehavioral changes were reflected in rsFC for language, salience, and sensorimotor networks. Between networks interactions were modulated, globally, after all treatments. CONCLUSIONS For persons with DoC 1 to 15 years after TBI, meaningful neurobehavioral gains were observed after provision of rTMS, AMA, and rTMS+AMA. Sequencing and combining of treatments to modulate broad-scale neural activity, via differing mechanisms, merits investigation in a future study powered to determine efficacy of this approach to enabling neurobehavioral recovery.

Amyotrophic lateral sclerosis (ALS) is a multi-system disease featured by movement disorder. Studies on ALS using static neuroimaging indexes demonstrated inconsistent results. However, recent work indicated that the intrinsic brain activity was time-varying, and the abnormal temporal dynamics of brain activity in ALS remains unknown. Resting-state functional magnetic resonance imaging data were first obtained from 54 patients with ALS and 54 healthy controls (HCs). Then the dynamic regional homogeneity (d-ReHo) was calculated and compared between the two groups. Correlation analyses between altered d-ReHo and clinical scores were further performed. Compared with HCs, ALS patients showed higher d-ReHo in the left lingual gyrus while lower d-ReHo in the left rectus gyrus and left parahippocampal gyrus. Moreover, the d-ReHo in the left lingual gyrus exhibited correlation with disease progression rate in ALS at a trend level. Our findings suggested that altered dynamics in intrinsic brain activity might be a potential biomarker for diagnosing of ALS.

Posttraumatic stress disorder (PTSD) is characterized by exaggerated salience of previously innocuous cues and associated with hyperactivity of salience-related brain regions. Recently, computational models have been deployed to operationalize salience more precisely regarding surprise-driven learning, leading to findings that such learning is altered in anxiety-related disorders. In the present study, a sample of 20 combat veterans completed a probabilistic learning task during fMRI scanning. We applied a computational model to generate a trial-by-trial surprise signal (i.e., unsigned prediction error or difference between the expected probability of an outcome and the actual observed outcome), which allowed us to examine the neural response to surprising events. We did not observe an association between PTSD symptoms and behavioral indices of learning in the task. Surprising errors were associated with increased activity in the left precuneus/inferior parietal lobule and right inferior parietal lobule, two parietal regions that are linked to salience processing. Additionally, PTSD symptom severity was positively associated with precuneus/inferior parietal lobule activation to surprising errors, r = .63, p = .004. Taken together, this pattern of results suggests that PTSD symptoms are specifically associated with an exaggerated response to surprising errors in salience-related regions of the brain. This altered pattern of neural activity could represent a target for intervention to improve PTSD symptoms.

Despite advances in understanding the consequences of age-related episodic memory decline for future simulation, much remains unknown regarding changes in the neural underpinnings of future thinking with age. We used a repetition suppression paradigm to explore age-related changes in the neural correlates of emotional future simulation. Younger and older adults simulated positive, negative, and neutral future events either two or five times. Reductions in neural activity for events simulated five versus two times (i.e., repetition suppression) identifies brain regions responsive to the specific emotion of simulated events. Critically, older adults showed greater repetition suppression than younger adults in the temporal pole for negative simulations, and the cuneus for positive simulations. These findings suggest that older adults distance themselves from negative future possibilities by thinking about them in a more semantic way, consistent with the view that older adults down-regulate negative affect and up-regulate positive affect. More broadly this study increases our understanding of the impact of aging on the neural underpinnings of episodic future simulation.

Healthy aging is associated with a multitude of structural changes in the brain. These physical age-related changes are accompanied by increased variability in neural activity of all kinds, and this increased variability, collectively referred to as “neural noise,” is argued to contribute to age-related cognitive decline. In this study, we examine the relationship between two particular types of neural noise in aging. We recorded scalp EEG from younger (20–30 years old) and older (60–70 years old) adults performing a spatial visual discrimination task. First, we used the 1/f-like exponent of the EEG power spectrum, a putative marker of neural noise, to assess baseline shifts toward a noisier state in aging. Next, we examined age-related decreases in the trial-by-trial consistency of visual stimulus processing. Finally, we examined to what extent these two age-related noise markers are related, hypothesizing that greater baseline noise would increase the variability of stimulus-evoked responses. We found that visual cortical baseline noise was higher in older adults, and the consistency of older adults' oscillatory alpha (8–12 Hz) phase responses to visual targets was also lower than that of younger adults. Crucially, older adults with the highest levels of baseline noise also had the least consistent alpha phase responses, whereas younger adults with more consistent phase responses achieved better behavioral performance. These results establish a link between tonic neural noise and stimulus-associated neural variability in aging. Moreover, they suggest that tonic age-related increases in baseline noise might diminish sensory processing and, as a result, subsequent cognitive performance.

Definitions of what constitutes the 'signal of interest' in neuroscience can be controversial, due in part to continuously evolving notions regarding the significance of spontaneous neural activity. This review highlights how the challenge of separating brain signal from noise has led to new conceptualizations of brain functional organization at both the micro- and macroscopic level. Recent debates in the functional neuroimaging community surrounding artifact removal processes have revived earlier discussions surrounding how to appropriately isolate and measure neuronal signals against a background of noise from various sources. Insights from electrophysiological studies and computational modeling can inform current theory and data analytic practices in human functional neuroimaging, given that signal and noise may be inextricably linked in the brain.

Nearly all brain functions involve routing neural activity among a distributed network of areas. Understanding this routing requires more than a description of inter-areal anatomical connectivity: it requires understanding what controls the flow of signals through inter-areal circuitry, and how this communication might be modulated to allow flexible behavior. Here we review proposals of how communication—particularly between visual cortical areas—is instantiated and modulated, highlighting recent work that offers new perspectives. We suggest transitioning from a focus on assessing changes in the strength of inter-areal interactions, as often seen in studies of inter-areal communication, to a broader consideration of how different signaling schemes might contribute to computation. To this end, we discuss a set of features that might be desirable for a communication scheme.

Past research has found that neural activity associated with feedback processing is enhanced by positive approach‐motivated states. However, no past work has examined how reward processing changes in the context of revenge. Using a novel aggression paradigm, we sought to explore the influence of approach‐motivated anger on neural responses to feedback indicating the opportunity to seek revenge against an offending opponent by examining the reward positivity (RewP), an event‐related potential indexing performance feedback. In Experiment 1, after receiving insulting feedback from an opponent, participants played a reaction time game with three trial types: revenge trials, aggravation trials, and no‐consequence trials. Results revealed that RewP amplitudes were larger to revenge trial win feedback than no‐consequence trial win feedback or revenge trial loss feedback. RewP amplitudes were larger to both aggravation trial win and loss feedback than on no‐consequence trials. Experiment 2 examined the influence of approach‐motivated anger during the acquisition of rewards on the RewP without the possibility of retribution from the offending individual. Participants played a reaction time game similar to Experiment 1, except instead of giving or receiving noise blasts, participants could win money from the insulter (revenge trials) or a neutral‐party (e.g., bank). Results indicated that revenge wins elicited larger RewP amplitudes than bank wins. These results suggest that anger enhances revenge‐related RewP amplitudes to obtaining revenge opportunities and further aggravation wins or losses. Anger appears to enhance the pleasurable feelings of revenge., Using a novel aggression paradigm, we sought to explore the influence of approach‐motivated anger on neural responses to feedback indicating the opportunity to seek revenge against an offending opponent by examining the reward positivity (RewP), an event‐related potential indexing performance feedback. Results indicated that, in participants who were angry, the RewP was largest during revenge trials, suggested that anger enhances revenge‐related RewP amplitudes to obtaining revenge opportunities and further aggravation wins or losses. Anger appears to enhance the pleasurable feelings of revenge.

Significance Exposure to misleading information can distort memory for past events (misinformation effect). Here, we show that providing individuals with a simple warning about the threat of misinformation significantly reduces the misinformation effect, regardless of whether warnings are provided proactively (before exposure to misinformation) or retroactively (after exposure to misinformation). In the brain, this protective effect of warning is associated with increased reactivation of sensory regions associated with the original event and decreased reactivation of sensory regions associated with the misleading information. These findings reveal that warnings can protect memory from misinformation by modulating reconstructive processes at the time of memory retrieval and have important practical implications for improving the accuracy of eyewitness testimony as well as everyday memory reports., Exposure to even subtle forms of misleading information can significantly alter memory for past events. Memory distortion due to misinformation has been linked to faulty reconstructive processes during memory retrieval and the reactivation of brain regions involved in the initial encoding of misleading details (cortical reinstatement). The current study investigated whether warning participants about the threat of misinformation can modulate cortical reinstatement during memory retrieval and reduce misinformation errors. Participants watched a silent video depicting a crime (original event) and were given an initial test of memory for the crime details. Then, participants listened to an auditory narrative describing the crime in which some original details were altered (misinformation). Importantly, participants who received a warning about the reliability of the auditory narrative either before or after exposure to misinformation demonstrated less susceptibility to misinformation on a final test of memory compared to unwarned participants. Warned and unwarned participants also demonstrated striking differences in neural activity during the final memory test. Compared to participants who did not receive a warning, participants who received a warning (regardless of its timing) demonstrated increased activity in visual regions associated with the original source of information as well as decreased activity in auditory regions associated with the misleading source of information. Stronger visual reactivation was associated with reduced susceptibility to misinformation, whereas stronger auditory reactivation was associated with increased susceptibility to misinformation. Together, these results suggest that a simple warning can modulate reconstructive processes during memory retrieval and reduce memory errors due to misinformation.

Transcranial alternating current stimulation (tACS) is a non-invasive method of brain stimulation that modulates oscillatory neural activity in the cortical area under the electrodes. Gamma (γ)-tACS applied over the primary motor cortex (M1) and cerebellar hemisphere is known to improve motor performance; however, it is not yet known whether it affects motor learning. Thus, here we investigated whether γ-tACS applied over the M1 and cerebellar hemisphere affects motor learning. This study involved 30 healthy subjects (14 females, 16 males) performing a visuomotor control task (eight trials) during an administration of either γ-tACS or a sham stimulation (15 subjects per condition) over their right M1 and left cerebellar hemisphere. Each subject performed five trials after 24 h. The motor learning efficiency, motor learning retention and re-motor learning efficiency in each condition were compared. The motor learning retention in the γ-tACS condition was significantly higher than that in the sham condition (p = 0.031). Thus, subjects who were administered γ-tACS maintained their motor performance the next day better than sham-stimulated subjects. There was no significant difference between the conditions in the motor learning efficiency and those in the re-motor learning efficiency. Our results demonstrate that γ-tACS administered over the M1 and cerebellar hemisphere during a motor learning task can enhance motor learning retention.

High-density electroencephalography (hdEEG) has been successfully used for large-scale investigations of neural activity in the healthy and diseased human brain. Because of their high computational demand, analyses of source-projected hdEEG data are typically performed offline. Here, we present a real-time noninvasive electrophysiology toolbox, RT-NET, which has been specifically developed for online reconstruction of neural activity using hdEEG. RT-NET relies on the Lab Streaming Layer for acquiring raw data from a large number of EEG amplifiers and for streaming the processed data to external applications. RT-NET estimates a spatial filter for artifact removal and source activity reconstruction using a calibration dataset. This spatial filter is then applied to the hdEEG data as they are acquired, thereby ensuring low latencies and computation times. Overall, our analyses show that RT-NET can estimate real-time neural activity with performance comparable to offline analysis methods. It may therefore enable the development of novel brain-computer interface applications such as source-based neurofeedback. ispartof: NEUROINFORMATICS vol:19 issue:2 pages:251-266 ispartof: location:United States status: published

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.

Facial expressions are important for intentional display of emotions in social interaction. For people with severe paralysis, the ability to display emotions intentionally can be impaired. Current brain-computer interfaces (BCIs) allow for linguistic communication but are cumbersome for expressing emotions. Here, we investigated the feasibility of a BCI to display emotions by decoding facial expressions. We used electrocorticographic recordings from the sensorimotor cortex of people with refractory epilepsy and classified five facial expressions, based on neural activity. The mean classification accuracy was 72%. This approach could be a promising avenue for development of BCI-based solutions for fast communication of emotions. ANN NEUROL 2020;88:631-636.