Transient suppression of broadband gamma power in the default-mode network is correlated with task complexity and subject performance

On the neural networks of self and other bias and their role in emergent social interactions

Extensive research has documented the brain networks that play an integral role in bias, or the alteration and filtration of information processing in a manner that fundamentally favors an individual. The roots of bias, whether self- or other-oriented, are a complex constellation of neural and psychological processes that start at the most fundamental levels of sensory processing. From the millisecond information is received in the brain it is filtered at various levels and through various brain networks in relation to extant intrinsic activity to provide individuals with a perception of reality that complements and satisfies the conscious perceptions they have for themselves and the cultures in which they were reared. The products of these interactions, in turn, are dynamically altered by the introduction of others, be they friends or strangers who are similar or different in socially meaningful ways. While much is known about the various ways that basic biases alter specific aspects of neural function to support various forms of bias, the breadth and scope of the phenomenon remains entirely unclear. The purpose of this review is to examine the brain networks that shape (i.e., bias) the self-concept and how interactions with similar (ingroup) compared to dissimilar (outgroup) others alter these network (and subsequent interpersonal) interactions in fundamental ways. Throughout, focus is placed on an emerging understanding of the brain as a complex system, which suggests that many of these network interactions likely occur on a non-linear scale that blurs the lines between network hierarchies.

Human local field potentials in motor and non-motor brain areas encode upcoming movement direction

Limb movement direction can be inferred from local field potentials in motor cortex during movement execution. Yet, it remains unclear to what extent intended hand movements can be predicted from brain activity recorded during movement planning. Here, we set out to probe the directional-tuning of oscillatory features during motor planning and execution, using a machine learning framework on multi-site local field potentials (LFPs) in humans. We recorded intracranial EEG data from implanted epilepsy patients as they performed a four-direction delayed center-out motor task. Fronto-parietal LFP low-frequency power predicted hand-movement direction during planning while execution was largely mediated by higher frequency power and low-frequency phase in motor areas. By contrast, Phase-Amplitude Coupling showed uniform modulations across directions. Finally, multivariate classification led to an increase in overall decoding accuracy (>80%). The novel insights revealed here extend our understanding of the role of neural oscillations in encoding motor plans.

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

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

Default mode network spatio-temporal electrophysiological signature and causal role in creativity

The default mode network (DMN) is a widely distributed, intrinsic brain network thought to play a crucial role in internally-directed cognition. It subserves self-referential thinking, recollection of the past, mind wandering, and creativity. Knowledge about the electrophysiology underlying DMN activity is scarce, due to the difficulty to simultaneously record from multiple distant cortical areas with commonly-used techniques. The present study employs stereo-electroencephalography depth electrodes in 13 human patients undergoing monitoring for epilepsy, obtaining high spatiotemporal resolution neural recordings across multiple canonical DMN regions. Our results offer a rare insight into the temporal evolution and spatial origin of theta (4-8Hz) and gamma signals (30-70Hz) during two DMN-associated higher cognitive functions: mind-wandering and alternate uses. During the performance of these tasks, DMN activity is defined by a specific pattern of decreased theta coupled with increased gamma power. Critically, creativity and mind wandering engage the DMN with different dynamics: creativity recruits the DMN strongly during the covert search of ideas, while mind wandering displays the strongest modulation of DMN during the later recall of the train of thoughts. Theta band power modulations, predominantly occurring during mind wandering, do not show a predominant spatial origin within the DMN. In contrast, gamma power effects were similar for mind wandering and creativity and more strongly associated to lateral temporal nodes. Interfering with DMN activity through direct cortical stimulation within several DMN nodes caused a decrease in creativity, specifically reducing the originality of the alternate uses, without affecting creative fluency or mind wandering. These results suggest that DMN activity is flexibly modulated as a function of specific cognitive processes and supports its causal role in creative thinking. Our findings shed light on the neural constructs supporting creative cognition and provide causal evidence for the role of DMN in the generation of original connections among concepts.

Fate of the second task in dual-task interference is associated with sensory system interactions with default-mode network

Psychological refractory period (PRP) effect refers to the delay in responding to the second of two tasks occurring in rapid succession. While all the major models of PRP highlight the importance of the frontoparietal control network (FPCN) in prioritizing the neural processing of the first task, the fate of the second task remains poorly understood. Here, we provide novel neural evidence on how the functional connectivity between sensory systems and the default-mode network (DMN) suspends the neural processing of the second task to ensure the efficient completion of the first task in dual-task situation. In a cross-modal PRP paradigm, a visual task could either precede or follow an auditory task. The DMN was generally deactivated during task performance and selectively coupled with the sensory system underlying the second task subjected to the PRP effect. Specifically, the DMN showed neural coupling with the auditory system when the auditory task came after the visual task, and with the visual system vice versa. More critically, the strength of the DMN-Sensory coupling correlated negatively with the size of the PRP effect: the stronger the coupling, the shorter the PRP. Therefore, rather than being detrimental to the dual-task performance, temporary suspension of the second task, via the DMN-Sensory coupling, surprisingly guaranteed the efficient completion of the first task by reducing the interference from the second task. Accordingly, the entry and processing of the second stimuli in the central executive system were speeded up as well.

Comparative analysis of multifaceted neural effects associated with varying endogenous cognitive load

Contemporary neuroscience has firmly established that mental state variation concurs with changes in neural dynamic activity in a complex way that a one-to-one mapping cannot describe. To explore the scenario of the multifaceted changes in neural dynamics associated with simple mental state variation, we took cognitive load - a common cognitive manipulation in psychology - as a venue to characterize how multiple neural dynamic features are simultaneously altered by the manipulation and how their sensitivity differs. Electroencephalogram was collected from 152 participants performing stimulus-free tasks with different demands. The results show that task demand alters wide-ranging neural dynamic features, including band-specific oscillations across broad frequency bands, scale-free dynamics, and cross-frequency phase-amplitude coupling. The scale-free dynamics outperformed others in indexing cognitive load variation. This study demonstrates a complex relationship between cognitive dynamics and neural dynamics, which points to a necessity to integrate multifaceted neural dynamic features when studying mind-brain relationship in the future.

Dynamic cortical and tractography atlases of proactive and reactive alpha and high-gamma activities

Alpha waves-posterior dominant rhythms at 8-12 Hz reactive to eye opening and closure-are among the most fundamental EEG findings in clinical practice and research since Hans Berger first documented them in the early 20th century. Yet, the exact network dynamics of alpha waves in regard to eye movements remains unknown. High-gamma activity at 70-110 Hz is also reactive to eye movements and a summary measure of local cortical activation supporting sensorimotor or cognitive function. We aimed to build the first-ever brain atlases directly visualizing the network dynamics of eye movement-related alpha and high-gamma modulations, at cortical and white matter levels. We studied 28 patients (age: 5-20 years) who underwent intracranial EEG and electro-oculography recordings. We measured alpha and high-gamma modulations at 2167 electrode sites outside the seizure onset zone, interictal spike-generating areas and MRI-visible structural lesions. Dynamic tractography animated white matter streamlines modulated significantly and simultaneously beyond chance, on a millisecond scale. Before eye-closure onset, significant alpha augmentation occurred at the occipital and frontal cortices. After eye-closure onset, alpha-based functional connectivity was strengthened, while high gamma-based connectivity was weakened extensively in both intra-hemispheric and inter-hemispheric pathways involving the central visual areas. The inferior fronto-occipital fasciculus supported the strengthened alpha co-augmentation-based functional connectivity between occipital and frontal lobe regions, whereas the posterior corpus callosum supported the inter-hemispheric functional connectivity between the occipital lobes. After eye-opening offset, significant high-gamma augmentation and alpha attenuation occurred at occipital, fusiform and inferior parietal cortices. High gamma co-augmentation-based functional connectivity was strengthened, whereas alpha-based connectivity was weakened in the posterior inter-hemispheric and intra-hemispheric white matter pathways involving central and peripheral visual areas. Our results do not support the notion that eye closure-related alpha augmentation uniformly reflects feedforward or feedback rhythms propagating from lower to higher order visual cortex, or vice versa. Rather, proactive and reactive alpha waves involve extensive, distinct white matter networks that include the frontal lobe cortices, along with low- and high-order visual areas. High-gamma co-attenuation coupled to alpha co-augmentation in shared brain circuitry after eye closure supports the notion of an idling role for alpha waves during eye closure. These normative dynamic tractography atlases may improve understanding of the significance of EEG alpha waves in assessing the functional integrity of brain networks in clinical practice; they also may help elucidate the effects of eye movements on task-related brain network measures observed in cognitive neuroscience research.

A tripartite view of the posterior cingulate cortex

The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.

Brain Mechanisms of Conscious Awareness: Detect, Pulse, Switch, and Wave

Consciousness is a fascinating field of neuroscience research where questions often outnumber the answers. We advocate an open and optimistic approach where converging mechanisms in neuroscience may eventually provide a satisfactory understanding of consciousness. We first review several characteristics of conscious neural activity, including the involvement of dedicated systems for content and levels of consciousness, the distinction and overlap of mechanisms contributing to conscious states and conscious awareness of transient events, nonlinear transitions and involvement of large-scale networks, and finally the temporal nexus where conscious awareness of discrete events occurs when mechanisms of attention and memory meet. These considerations and recent new experimental findings lead us to propose an inclusive hypothesis involving four phases initiated shortly after an external sensory stimulus: (1) Detect-primary and higher cortical and subcortical circuits detect the stimulus and select it for conscious perception. (2) Pulse-a transient and massive neuromodulatory surge in subcortical-cortical arousal and salience networks amplifies signals enabling conscious perception to proceed. (3) Switch-networks that may interfere with conscious processing are switched off. (4) Wave-sequential processing through hierarchical lower to higher cortical regions produces a fully formed percept, encoded in frontoparietal working memory and medial temporal episodic memory systems for subsequent report of experience. The framework hypothesized here is intended to be nonexclusive and encourages the addition of other mechanisms with further progress. Ultimately, just as many mechanisms in biology together distinguish living from nonliving things, many mechanisms in neuroscience synergistically may separate conscious from nonconscious neural activity.

Dopamine Improves Low Gamma Activities in the Dorsal Striatum of Haloperidol-induced Motor Impairment Mice

BACKGROUND/AIM

The dorsal striatum is a brain area integrating information for movement output. The local field potentials (LFPs) reflect the neuronal activity that can be used for monitoring brain activities and controlling movement.

MATERIALS AND METHODS

Rhythmic low gamma power activity (30.1-45 Hz) in the dorsal striatum was monitored according to voluntary motor movement in rotarod and bar tests in 0.5 mg/kg haloperidol-induced mice.

RESULTS

Haloperidol can effectively induce movement impairment indicated by decreased low gamma LFP with the lessened rotarod test's latency fall, and the enhanced bar test's descending latency. L-DOPA was used for the induction of a dopamine-dependent signal. The results showed that 25 mg/kg of L-DOPA could reverse the effect of haloperidol by enhancing low gamma oscillation concomitantly with the improvement in behavioral movement as fast as 60 min after administration, suggesting that dopamine signaling increases low gamma frequency of LFP in correlation with the improved mice movement. This work supports quantitative LFP assessment as a monitoring tool to track drug action on the nervous system.

CONCLUSION

In animal models of motor impairment, oral dopaminergic treatment can be effective in restoring motor dysfunction by stimulating low gamma power activity in the dorsal striatum.

The structure of anticorrelated networks in the human brain

During the performance of a specific task--or at rest--, the activity of different brain regions shares statistical dependencies that reflect functional connections. While these relationships have been studied intensely for positively correlated networks, considerably less attention has been paid to negatively correlated networks, a. k.a. anticorrelated networks (ACNs). Although the most celebrated of all ACNs is the default mode network (DMN), and has even been extensively studied in health and disease, for systematically all ACNs other than DMN, there is no comprehensive study yet. Here, we have addressed this issue by making use of three neuroimaging data sets: one of N = 192 healthy young adults to fully describe ACN, another of N = 40 subjects to compare ACN between two groups of young and old participants, and another of N = 1,000 subjects from the Human Connectome Project to evaluate the association between ACN and cognitive scores. We first provide a comprehensive description of the anatomical composition of all ACNs, each of which participated in distinct resting-state networks (RSNs). In terms of participation ranking, from highest to the lowest, the major anticorrelated brain areas are the precuneus, the anterior supramarginal gyrus and the central opercular cortex. Next, by evaluating a more detailed structure of ACN, we show it is possible to find significant differences in ACN between specific conditions, in particular, by comparing groups of young and old participants. Our main finding is that of increased anticorrelation for cerebellar interactions in older subjects. Finally, in the voxel-level association study with cognitive scores, we show that ACN has multiple clusters of significance, clusters that are different from those obtained from positive correlated networks, indicating a functional cognitive meaning of ACN. Overall, our results give special relevance to ACN and suggest their use to disentangle unknown alterations in certain conditions, as could occur in early-onset neurodegenerative diseases or in some psychiatric conditions.

Functional network antagonism and consciousness

Spontaneous brain activity changes across states of consciousness. A particular consciousness-mediated configuration is the anticorrelations between the default mode network and other brain regions. What this antagonistic organization implies about consciousness to date remains inconclusive. In this Perspective Article, we propose that anticorrelations are the physiological expression of the concept of segregation, namely the brain's capacity to show selectivity in the way areas will be functionally connected. We postulate that this effect is mediated by the process of neural inhibition, by regulating global and local inhibitory activity. While recognizing that this effect can also result from other mechanisms, neural inhibition helps the understanding of how network metastability is affected after disrupting local and global neural balance. In combination with relevant theories of consciousness, we suggest that anticorrelations are a physiological prior that can work as a marker of preserved consciousness. We predict that if the brain is not in a state to host anticorrelations, then most likely the individual does not entertain subjective experience. We believe that this link between anticorrelations and the underlying physiology will help not only to comprehend how consciousness happens, but also conceptualize effective interventions for treating consciousness disorders in which anticorrelations seem particularly affected.

Distinct population and single-neuron selectivity for executive and episodic processing in human dorsal posterior cingulate

Posterior cingulate cortex (PCC) is an enigmatic region implicated in psychiatric and neurological disease, yet its role in cognition remains unclear. Human studies link PCC to episodic memory and default mode network (DMN), while findings from the non-human primate emphasize executive processes more associated with the cognitive control network (CCN) in humans. We hypothesized this difference reflects an important functional division between dorsal (executive) and ventral (episodic) PCC. To test this, we utilized human intracranial recordings of population and single unit activity targeting dorsal PCC during an alternated executive/episodic processing task. Dorsal PCC population responses were significantly enhanced for executive, compared to episodic, task conditions, consistent with the CCN. Single unit recordings, however, revealed four distinct functional types with unique executive (CCN) or episodic (DMN) response profiles. Our findings provide critical electrophysiological data from human PCC, bridging incongruent views within and across species, furthering our understanding of PCC function.

Temporal stability of the hemodynamic response function across the majority of human cerebral cortex

The hemodynamic response function (HRF) measured with functional magnetic resonance imaging is generated by vascular and metabolic responses evoked by brief (<4 s) stimuli. It is known that the human HRF varies across cortex, between subjects, with stimulus paradigms, and even between different measurements in the same cortical location. However, our results demonstrate that strong HRFs are remarkably repeatable across sessions separated by time intervals up to 3 months. In this study, a multisensory stimulus was used to activate and measure the HRF across the majority of cortex (>70%, with lesser reliability observed in some areas of prefrontal cortex). HRFs were measured with high spatial resolution (2‐mm voxels) in central gray matter to minimize variations caused by partial‐volume effects. HRF amplitudes and temporal dynamics were highly repeatable across four sessions in 20 subjects. Positive and negative HRFs were consistently observed across sessions and subjects. Negative HRFs were generally weaker and, thus, more variable than positive HRFs. Statistical measurements showed that across‐session variability is highly correlated to the variability across events within a session; these measurements also indicated a normal distribution of variability across cortex. The overall repeatability of the HRFs over long time scales generally supports the long‐term use of event‐related functional magnetic resonance imaging protocols.

Excessive/Aberrant and Maladaptive Synaptic Plasticity: A Hypothesis for the Pathogenesis of Alzheimer’s Disease

The amyloid hypothesis for the pathogenesis of Alzheimer’s disease (AD) is widely accepted. Last year, the US Food and Drug Administration considered amyloid-β peptide (Aβ) as a surrogate biomarker and approved an anti-Aβ antibody, aducanumab, although its effectiveness in slowing the progression of AD is still uncertain. This approval has caused a great deal of controversy. Opinions are divided about whether there is enough evidence to definitely consider Aβ as a causative substance of AD. To develop this discussion constructively and to discover the most suitable therapeutic interventions in the end, an alternative persuasive hypothesis needs to emerge to better explain the facts. In this paper, I propose a hypothesis that excessive/aberrant and maladaptive synaptic plasticity is the pathophysiological basis for AD.

Subcortical control of the default mode network: Role of the basal forebrain and implications for neuropsychiatric disorders

The precise interplay between large-scale functional neural systems throughout the brain is essential for performance of cognitive processes. In this review we focus on the default mode network (DMN), one such functional network that is active during periods of quiet wakefulness and believed to be involved in introspection and planning. Abnormalities in DMN functional connectivity and activation appear across many neuropsychiatric disorders, including schizophrenia. Recent evidence suggests subcortical regions including the basal forebrain are functionally and structurally important for regulation of DMN activity. Within the basal forebrain, subregions like the ventral pallidum may influence DMN activity and the nucleus basalis of Meynert can inhibit switching between brain networks. Interactions between DMN and other functional networks including the medial frontoparietal network (default), lateral frontoparietal network (control), midcingulo-insular network (salience), and dorsal frontoparietal network (attention) are also discussed in the context of neuropsychiatric disorders. Several subtypes of basal forebrain neurons have been identified including basal forebrain parvalbumin-containing or somatostatin-containing neurons which can regulate cortical gamma band oscillations and DMN-like behaviors, and basal forebrain cholinergic neurons which might gate access to sensory information during reinforcement learning. In this review, we explore this evidence, discuss the clinical implications on neuropsychiatric disorders, and compare neuroanatomy in the human vs rodent DMN. Finally, we address technological advancements which could help provide a more complete understanding of modulation of DMN function and describe newly identified BF therapeutic targets that could potentially help restore DMN-associated functional deficits in patients with a variety of neuropsychiatric disorders.

Involvement of the default mode network under varying levels of cognitive effort

Everyday cognitive functioning is characterized by constant alternations between different modes of information processing, driven by constant fluctuations in environmental demands. At the neural level, this is realized through corresponding dynamic shifts in functional activation and network connectivity. A distinction is often made between resting and task processing and between task-negative and task-positive functional networks. The Default Mode Network (DMN) is classically considered as a resting state (i.e. task-negative) network, upregulated in the absence of cognitive demands. In contrast, task-positive networks have been labelled the Extrinsic Mode Network (EMN). We investigated changes in brain activation and functional network connectivity in an experimental situation of repeated alterations between levels of cognitive effort, following a block-design. Using fMRI and a classic Stroop paradigm, participants switched back and forth between periods of no effort (resting), low effort (word reading, i.e. automatic processing based on learned internal representations and rules) and high effort (color naming, i.e. cognitively controlled perceptual processing of specific features of external stimuli). Results showed an expected EMN-activation for task versus resting contrasts, and DMN-activation for rest versus task contrasts. The DMN was in addition more strongly activated during periods of low effort contrasted with high effort, suggesting a gradual up- and down-regulation of the DMN network, depending on the level of demand and the type of processing required. The often reported “anti-correlation” between DMN and EMN was strongest during periods of low effort, indicating intermittent contributions of both networks. Taken together, these results challenge the traditional view of the DMN as solely a task-negative network. Instead, both the EMN and DMN may contribute to low-effort cognitive processing. In contrast, periods of resting and high effort are dominated by the DMN and EMN, respectively.

Electrophysiological foundations of the human default-mode network revealed by intracranial-EEG recordings during resting-state and cognition

Investigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during resting-state and its modulation during a cognitive task involving episodic memory formation. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz), while DMN interactions with other brain networks was higher in the beta (12-30 Hz) and gamma (30-80 Hz) bands. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during both verbal memory encoding and recall. Compared to resting-state, slow-wave intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify frequency specific neurophysiological signatures of the DMN which allow it to maintain stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the electrophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.

Neural Connectivity Underlying Reward and Emotion-Related Processing: Evidence From a Large-Scale Network Analysis

Neuroimaging techniques have advanced our knowledge about neurobiological mechanisms of reward and emotion processing. It remains unclear whether reward and emotion-related processing share the same neural connection topology and how intrinsic brain functional connectivity organization changes to support emotion- and reward-related prioritized effects in decision-making. The present study addressed these challenges using a large-scale neural network analysis approach. We applied this approach to two independent functional magnetic resonance imaging datasets, where participants performed a reward value or emotion associative matching task with tight control over experimental conditions. The results revealed that interaction between the Default Mode Network, Frontoparietal, Dorsal Attention, and Salience networks engaged distinct topological structures to support the effects of reward, positive and negative emotion processing. Detailed insights into the properties of these connections are important for understanding in detail how the brain responds in the presence of emotion and reward related stimuli. We discuss the linking of reward- and emotion-related processing to emotional regulation, an important aspect of regulation of human behavior in relation to mental health.

Weak Task Synchronization of Default Mode Network in Task Based Paradigms

The brains Default mode network (DMN) is generally characterized by brain areas that gets deactivated upon the presentation of a wide variety of externally focused, attention demanding tasks. These areas also exhibit significant intra-DMN functional connectivity and significant negative functional connectivity with other brain areas, especially with attention networks, in both resting state and task conditions. Therefore, the DMN has been hypothesized to be involved in internally directed cognitive activities such as autobiographical recall of the past, future planning and mind wandering. Recent research has discovered the role of bottom-up attention in modulating the behaviour of DMN. We hypothesize that the de-engagement of the DMN regions upon the presentation of an externally-focused attention-demanding stimulus may not be strictly stimulus locked and may exhibit significant trial-to-trial as well as subject-to-subject variability. Due to the involvement of frontoparietal control network in modulating the anticorrelations between DMN and dorsal attention network (DAN), we expect the DMN regions to have lower inter-trial and inter-subject synchronization in their fMRI BOLD responses as compared to the bottom-up early-sensory task-positive regions. To test this hypothesis, we designed new statistical methods called Inter Trial Temporal Synchronization Analysis (IT-TSA) and Inter Subject TSA (IS-TSA) to analyse variability across trials and subjects respectively. We analysed four publicly available datasets (total 223 subjects) across seven tasks related to different cognitive modalities and found out that there is significantly low stimulus-locked synchronization across trials and subjects in the DMN regions as compared to early sensory task positive regions. Our study challenges the understanding of DMN as a strictly task-negative region and supports the recent findings that DMN acts as an active component associated with intrinsic processing which deactivates differentially and non-linearly across trials and subjects in the presence of extrinsic processes.

Neural dynamics of mindfulness meditation and hypnosis explored with intracranial EEG: A feasibility study

PURPOSE

Intracranial electroencephalography (iEEG) offers a unique window on brain dynamics with excellent temporal and spatial resolution and is less prone to recording artefacts than surface EEG. This study used a within-subject design to explore the feasibility to compare iEEG data during mind wandering, mindfulness meditation and hypnosis.

RESULTS

Three patients who had iEEG for clinical monitoring and who were new to mindfulness meditation and hypnosis were able to enter these states. We found non-specific and wide-spread amplitude modulations. Data-driven connectivity analysis revealed widespread connectivity patterns that were common across the three conditions. These were predominant in the low frequencies (delta, theta and alpha) and characterised by positively correlated activity. Connectivity patterns that were unique to the three conditions predominated in the gamma band, one third of the correlations in these patterns were negative.

CONCLUSIONS

This study is the first to support the feasibility of a direct comparison of the neural correlates of mindfulness meditation and hypnosis using iEEG. These modulations may reflect the complex interplay between different known brain networks, and warrant further functional investigations in particular in the gamma band.

Early cortical signals in visual stimulus detection

During visual conscious perception, the earliest responses linked to signal detection are little known. The current study aims to reveal the cortical neural activity changes in the earliest stages of conscious perception using recordings from intracranial electrodes. Epilepsy patients (N=158) were recruited from a multi-center collaboration and completed a visual word recall task. Broadband gamma activity (40-115Hz) was extracted with a band-pass filter and gamma power was calculated across subjects on a common brain surface. Our results show early gamma power increases within 0-50ms after stimulus onset in bilateral visual processing cortex, right frontal cortex (frontal eye fields, ventral medial/frontopolar, orbital frontal) and bilateral medial temporal cortex regardless of whether the word was later recalled. At the same early times, decreases were seen in the left rostral middle frontal gyrus. At later times after stimulus onset, gamma power changes developed in multiple cortical regions. These included sustained changes in visual and other association cortical networks, and transient decreases in the default mode network most prominently at 300-650ms. In agreement with prior work in this verbal memory task, we also saw greater increases in visual and medial temporal regions as well as prominent later (> 300ms) increases in left hemisphere language areas for recalled versus not recalled stimuli. These results suggest an early signal detection network in the frontal, medial temporal, and visual cortex is engaged at the earliest stages of conscious visual perception.

How the brain negotiates divergent executive processing demands: Evidence of network reorganization in fleeting brain states

During performance in everyday contexts, multiple networks draw from shared executive resources to maintain attention, regulate arousal, and solve problems. At times, requirements for attention and self-regulation appear to be in competition. How does the brain attempt to resolve conflicts arising from such divergent processing demands? Here we demonstrate that the brain is capable of managing multiple processes via rapidly cycling between functional brain states over time, as it is typically regarded. Treating the brain as a complex system, comprising relationships within and between functional networks, we implemented Hidden Markov Modeling (HMM) on electroencephalographic (EEG) data to identify nonlinear brain states in both intra and internetwork synchrony that produced better performance for women subjects who were tasked with solving difficult problems under autobiographically-relevant, evaluative stress. Prior work often found that emotion-regulation and default-mode network (ERN and DMN) activity conflicted with the frontoparietal network's (FPN) ability to facilitate executive functioning necessary for problem solving. Contrastingly, we discovered that fleeting, nonlinear states dominated by FPN and ERN internetwork synchrony supported optimum performance generally, while during stress, states dominated by ERN and DMN intranetwork synchrony were more important for performance. These results imply that the brain may be capable of resolving competing processes through networks' cooperative dynamics. Further, data suggests a novel role for DMN as a mechanism for integrating external threats with internal, self-referent processing during evaluative stress within the observed population.

Altered sense of self during seizures in the posteromedial cortex

In this manuscript, we report a rare case of a patient with localized seizures originating from the right anterior and dorsal posteromedial cortex (PMC). We mapped the electrophysiological and neuroimaging connectivity of the ictal onset site and replicated seizure auras by stimulating the homotopical PMC site in the left hemisphere. Our findings provide a causal link between PMC and the sense of self and provide unique clues about the pathophysiology of self-dissociation in neuropsychiatric conditions.

The posteromedial cortex (PMC) is known to be a core node of the default mode network. Given its anatomical location and blood supply pattern, the effects of targeted disruption of this part of the brain are largely unknown. Here, we report a rare case of a patient (S19_137) with confirmed seizures originating within the PMC. Intracranial recordings confirmed the onset of seizures in the right dorsal posterior cingulate cortex, adjacent to the marginal sulcus, likely corresponding to Brodmann area 31. Upon the onset of seizures, the patient reported a reproducible sense of self-dissociation—a condition he described as a distorted awareness of the position of his body in space and feeling as if he had temporarily become an outside observer to his own thoughts, his “me” having become a separate entity that was listening to different parts of his brain speak to each other. Importantly, 50-Hz electrical stimulation of the seizure zone and a homotopical region within the contralateral PMC induced a subjectively similar state, reproducibly. We supplement our clinical findings with the definition of the patient’s network anatomy at sites of interest using cortico-cortical–evoked potentials, experimental and resting-state electrophysiological connectivity, and individual-level functional imaging. This rare case of patient S19_137 highlights the potential causal importance of the PMC for integrating self-referential information and provides clues for future mechanistic studies of self-dissociation in neuropsychiatric populations.

Dissociations between glucose metabolism and blood oxygenation in the human default mode network revealed by simultaneous PET-fMRI

A consistent finding from functional MRI (fMRI) of externally focused cognitive control is negative signal change in the brain’s default mode network (DMN), but it is unknown whether this reflects an increase of synaptic activity during rest periods or active suppression during task. Using hybrid PET-MRI, we show that task-positive fMRI responses align with increasing glucose metabolism during cognitive control, but task-negative fMRI responses in DMN are not accompanied by corresponding decreases in metabolism. The results are incompatible with an interpretation of task-negative fMRI signal in DMN as a relative metabolic increase during a resting baseline condition. The present results open up avenues for understanding abnormal fMRI activity patterns in DMN in aging and psychiatric disease.

The finding of reduced functional MRI (fMRI) activity in the default mode network (DMN) during externally focused cognitive control has been highly influential to our understanding of human brain function. However, these negative fMRI responses, measured as relative decreases in the blood-oxygenation-level–dependent (BOLD) response between rest and task, have also prompted major questions of interpretation. Using hybrid functional positron emission tomography (PET)-MRI, this study shows that task-positive and -negative BOLD responses do not reflect antagonistic patterns of synaptic metabolism. Task-positive BOLD responses in attention and control networks were accompanied by concomitant increases in glucose metabolism during cognitive control, but metabolism in widespread DMN remained high during rest and task despite negative BOLD responses. Dissociations between glucose metabolism and the BOLD response specific to the DMN reveal functional heterogeneity in this network and demonstrate that negative BOLD responses during cognitive control should not be interpreted to reflect relative increases in metabolic activity during rest. Rather, neurovascular coupling underlying BOLD response patterns during rest and task in DMN appears fundamentally different from BOLD responses in other association networks during cognitive control.

Neuromodulation for Cognitive Disorders: In Search of Lazarus?

Alzheimer's disease (AD) and other forms of dementia can have a large impact on patients, their families, and for the society as a whole. Current medical treatments have not shown enough potential in treating or altering the course of the disease. Deep brain stimulation (DBS) has shown great neuromodulatory potential in Parkinson's disease, and there is a growing body of evidence for justifying its use in cognitive disorders. At the same time there is mounting interest at less invasive and alternative modes of neuromodulation for the treatment of AD. This manuscript is a brief review of the infrastructure of memory, the current understanding of the pathophysiology of AD, and the body of preclinical and clinical evidence for noninvasive and invasive neuromodulation modalities for the treatment of cognitive disorders and AD in particular.

Dynamic Configuration of Coactive Micropatterns in the Default Mode Network During Wakefulness and Sleep

Background: The default mode network (DMN) is a prominent intrinsic network that is observable in many mammalian brains. However, a few studies have investigated the temporal dynamics of this network based on direct physiological recordings. Methods: Herein, we addressed this issue by characterizing the dynamics of local field potentials from the rat DMN during wakefulness and sleep with an exploratory analysis. We constructed a novel coactive micropattern (CAMP) algorithm to evaluate the configurations of rat DMN dynamics, and further revealed the relationship between DMN dynamics with different wakefulness and alertness levels. Results: From the gamma activity (40-80 Hz) in the DMN across wakefulness and sleep, three spatially stable CAMPs were detected: a common low-activity level micropattern (cDMN), an anterior high-activity level micropattern (aDMN), and a posterior high-activity level micropattern (pDMN). A dynamic balance across CAMPs emerged during wakefulness and was disrupted in sleep stages. In the slow-wave sleep (SWS) stage, cDMN became the primary activity pattern, whereas aDMN and pDMN were the major activity patterns in the rapid eye movement sleep stage. In addition, further investigation revealed phasic relationships between CAMPs and the up-down states of the slow DMN activity in the SWS stage. Conclusion: Our study revealed that the dynamic configurations of CAMPs were highly associated with different stages of wakefulness, and provided a potential three-state model to describe the DMN dynamics for wakefulness and alertness. Impact statement In the current study, a novel coactive micropattern (CAMP) method was developed to elucidate fast default mode network (DMN) dynamics during wakefulness and sleep. Our findings demonstrated that the dynamic configurations of DMN activity are specific to different wakefulness stages and provided a three-state DMN CAMP model to depict wakefulness levels, thus revealing a potentially new neurophysiological representation of alertness levels. This work could elucidate the DMN dynamics underlying different stages of wakefulness and have important implications for the theoretical understanding of the neural mechanism of wakefulness and alertness.

Parsing Neurodynamic Information Streams to Estimate the Frequency, Magnitude and Duration of Team Uncertainty

Neurodynamic organizations are information-based abstractions, expressed in bits, of the structure of long duration EEG amplitude levels. Neurodynamic information (NI, the variable of neurodynamic organization) is thought to continually accumulate as EEG amplitudes cycle through periods of persistent activation and deactivation in response to the activities and uncertainties of teamwork. Here we show that (1) Neurodynamic information levels were a better predictor of uncertainty and novice and expert behaviors than were the EEG power levels from which NI was derived. (2) Spatial and temporal parsing of team NI from experienced submarine navigation and healthcare teams showed that it was composed of discrete peaks with durations up to 20–60 s, and identified the involvement of activated delta waves when precise motor control was needed. (3) The relationship between NI and EEG power was complex varying by brain regions, EEG frequencies, and global vs. local brain interactions. The presence of an organizational system of information that parallels the amplitude of EEG rhythms is important as it provides a greatly reduced data dimension while retaining the essential system features, i.e., linkages to higher scale behaviors that span temporal and spatial scales of teamwork. In this way the combinatorial explosion of EEG rhythmic variables at micro levels become compressed into an intermediate system of information and organization which links to macro-scale team and team member behaviors. These studies provide an avenue for understanding how complex organizations arise from the dynamics of underlying micro-scale variables. The study also has practical implications for how micro-scale variables might be better represented, both conceptually and in terms of parsimony, for training machines to recognize human behaviors that span scales of teams.

Deep Brain Stimulation in Alzheimer's Disease: Targeting the Nucleus Basalis of Meynert

Alzheimer's disease (AD) is becoming a prevalent disease in the elderly population. Past decades have witnessed the development of drug therapies with varying targets. However, all drugs with a single molecular target fail to reverse or ameliorate AD progression, which ultimately results in cortical and subcortical network dysregulation. Deep brain stimulation (DBS) has been proven effective for the treatment of Parkinson's disease, essential tremor, and other neurological diseases. As such, DBS has also been gradually acknowledged as a potential therapy for AD. The current review focuses on DBS of the nucleus basalis of Meynert (NBM). As a critical component of the cerebral cholinergic system and the Papez circuit in the basal ganglia, the NBM plays an indispensable role in the subcortical regulation of memory, attention, and arousal state, which makes the NBM a promising target for modulation of neural network dysfunction and AD treatment. We summarized the intricate projection relations and functionality of the NBM, current approaches for stereotactic localization and evaluation of the NBM, and the therapeutic effects of NBM-DBS both in patients and animal models. Furthermore, the current shortcomings of NBM-DBS, such as variations in cortical blood flow, increased temperature in the target area, and stimulation-related neural damage, were presented.

Decoding the neural dynamics of free choice in humans

How do we choose a particular action among equally valid alternatives? Nonhuman primate findings have shown that decision-making implicates modulations in unit firing rates and local field potentials (LFPs) across frontal and parietal cortices. Yet the electrophysiological brain mechanisms that underlie free choice in humans remain ill defined. Here, we address this question using rare intracerebral electroencephalography (EEG) recordings in surgical epilepsy patients performing a delayed oculomotor decision task. We find that the temporal dynamics of high-gamma (HG, 60-140 Hz) neural activity in distinct frontal and parietal brain areas robustly discriminate free choice from instructed saccade planning at the level of single trials. Classification analysis was applied to the LFP signals to isolate decision-related activity from sensory and motor planning processes. Compared with instructed saccades, free-choice trials exhibited delayed and longer-lasting HG activity during the delay period. The temporal dynamics of the decision-specific sustained HG activity indexed the unfolding of a deliberation process, rather than memory maintenance. Taken together, these findings provide the first direct electrophysiological evidence in humans for the role of sustained high-frequency neural activation in frontoparietal cortex in mediating the intrinsically driven process of freely choosing among competing behavioral alternatives.

Optogenetic Stimulation of Basal Forebrain Parvalbumin Neurons Activates the Default Mode Network and Associated Behaviors

Activation of the basal forebrain (BF) has been associated with increased attention, arousal, and a heightened cortical representation of the external world. In addition, BF has been implicated in the regulation of the default mode network (DMN) and associated behaviors. Here, we provide causal evidence for a role of BF in DMN regulation, highlighting a prominent role of parvalbumin (PV) GABAergic neurons. The optogenetic activation of BF PV neurons reliably drives animals toward DMN-like behaviors, with no effect on memory encoding. In contrast, BF electrical stimulation enhances memory performance and increases DMN-like behaviors. BF stimulation has a correlated impact on peptide regulation in the BF and ACC, enhancing peptides linked to grooming behavior and memory functions, supporting a crucial role of the BF in DMN regulation. We suggest that in addition to enhancing attentional functions, the BF harbors a network encompassing PV GABAergic neurons that promotes self-directed behaviors associated with the DMN.

Rhythmic neural activity is comodulated with short-term gait modifications during first-time use of a dummy prosthesis: a pilot study

Background

After transfemoral amputation, many hours of practice are needed to re-learn walking with a prosthesis. The long adaptation process that consolidates a novel gait pattern seems to depend on cerebellar function for reinforcement of specific gait modifications, but the precise, step-by-step gait modifications (e.g., foot placement) most likely rely on top-down commands from the brainstem and cerebral cortex. The aim of this study was to identify, in able-bodied individuals, the specific modulations of cortical rhythms that accompany short-term gait modifications during first-time use of a dummy prosthesis.

Methods

Fourteen naïve participants walked on a treadmill without (one block, 4 min) and with a dummy prosthesis (three blocks, 3 × 4 min), while ground reaction forces and 32-channel EEG were recorded. Gait cycle duration, stance phase duration, step width, maximal ground reaction force and, ground reaction force trace over time were measured to identify gait modifications. Independent component analysis of EEG data isolated brain-related activity from distinct anatomical sources. The source-level data were segmented into gait cycles and analyzed in the time–frequency domain to reveal relative enhancement or suppression of intrinsic cortical oscillations. Differences between walking conditions were evaluated with one-way ANOVA and post-hoc testing (α = 0.05).

Results

Immediate modifications occurred in the gait parameters when participants were introduced to the dummy prosthesis. Except for gait cycle duration, these modifications remained throughout the duration of the experimental session. Power modulations of the theta, mu, beta, and gamma rhythms, of sources presumably from the fronto-central and the parietal cortices, were found across the experimental session. Significant power modulations of the theta, beta, and gamma rhythms within the gait cycle were predominately found around the heel strike of both feet and the swing phase of the right (prosthetic) leg.

Conclusions

The modulations of cortical activity could be related to whole-body coordination, including the swing phase and placing of the prosthesis, and the bodyweight transfer between legs and arms. Reduced power modulation of the gamma rhythm within the experimental session may indicate initial motor memories being formed. Better understanding of the sensorimotor processes behind gait modifications may inform the development of neurofeedback strategies to assist gait rehabilitation.

Cholinergic Modulation of the Default Mode Like Network in Rats

The discovery of the default mode network (DMN), a large-scale brain network that is suppressed during attention-demanding tasks, had major impact in neuroscience. This network exhibits an antagonistic relationship with attention-related networks. A better understanding of the processes underlying modulation of DMN is imperative, as this network is compromised in several neurological diseases. Cholinergic neuromodulation is one of the major regulatory networks for attention, and studies suggest a role in regulation of the DMN. In this study, we unilaterally activated the right basal forebrain cholinergic neurons and observed decreased right intra-hemispheric and interhemispheric FC in the default mode like network (DMLN). Our findings provide critical insights into the interplay between cholinergic neuromodulation and DMLN, demonstrate that differential effects can be exerted between the two hemispheres by unilateral stimulation, and open windows for further studies involving directed modulations of DMN in treatments for diseases demonstrating compromised DMN activity.

Active Forgetting: Adaptation of Memory by Prefrontal Control

Over the past century, psychologists have discussed whether forgetting might arise from active mechanisms that promote memory loss to achieve various functions, such as minimizing errors, facilitating learning, or regulating one's emotional state. The past decade has witnessed a great expansion in knowledge about the brain mechanisms underlying active forgetting in its varying forms. A core discovery concerns the role of the prefrontal cortex in exerting top-down control over mnemonic activity in the hippocampus and other brain structures, often via inhibitory control. New findings reveal that such processes not only induce forgetting of specific memories but also can suppress the operation of mnemonic processes more broadly, triggering windows of anterograde and retrograde amnesia in healthy people. Recent work extends active forgetting to nonhuman animals, presaging the development of a multilevel mechanistic account that spans the cognitive, systems, network, and even cellular levels. This work reveals how organisms adapt their memories to their cognitive and emotional goals and has implications for understanding vulnerability to psychiatric disorders.

The functional networks of a novel environment: Neural activity mapping in awake unrestrained rats using positron emission tomography

INTRODUCTION

Novel environment stimulation is thought to have an important role in cognitive development and has been shown to encourage exploratory behavior in rats. However, psychopathology or perceived danger or stress can impede this exploratory drive. The balance between brain circuits controlling the exploratory drive elicited by a novel environment, and the avoidance response to stressors, is not well understood.

METHODS

Using positron emission tomography (PET) and the glucose analog [¹⁸ F]fluorodeoxyglucose (18F-FDG), we assessed awake brain glucose metabolism (BGluM) in rats while in a novel environment (cage of an unfamiliar male rat) and non-novel environment (the animal's home cage).

RESULTS

Exposure to the novel environment increased BGluM in regions associated with vision (visual cortex), motor function and motivated behavior (striatum and motor cortex), and anxiety (stria terminalis), and decreased BGluM in regions associated with auditory processing (auditory cortex, insular cortex, inferior colliculus), locomotor activity (globus pallidus, striatum, motor cortex, ventral thalamic nucleus), spatial navigation (retrosplenial cortex), and working memory (hippocampus, cingulate cortex, prelimbic cortex, orbitofrontal cortex).

CONCLUSION

These results suggest that the novel cage is a stressful environment that inhibits activity in brain regions associated with exploratory behavior. Patterns of inhibition in the novel cage also support the proposed rat default mode network, indicating that animals are more cognitively engaged in this environment. Additionally, these data support the unique capability of combining FDG-PET with psychopharmacology experiments to examine novelty seeking and brain activation in the context of decision making, risk taking, and cognitive function more generally, along with response to environmental or stress challenges.

Pitfalls in Scalp High-Frequency Oscillation Detection From Long-Term EEG Monitoring

Aims: Intracranially recorded high-frequency oscillations (>80 Hz) are considered a candidate epilepsy biomarker. Recent studies claimed their detectability on the scalp surface. We aimed to investigate the applicability of high-frequency oscillation analysis to routine surface EEG obtained at an epilepsy monitoring unit. Methods: We retrospectively analyzed surface EEGs of 18 patients with focal epilepsy and six controls, recorded during sleep under maximal medication withdrawal. As a proof of principle, the occurrence of motor task-related events during wakefulness was analyzed in a subsample of six patients with seizure- or syncope-related motor symptoms. Ripples (80-250 Hz) and fast ripples (>250 Hz) were identified by semi-automatic detection. Using semi-parametric statistics, differences in spontaneous and task-related occurrence rates were examined within subjects and between diagnostic groups considering the factors diagnosis, brain region, ripple type, and task condition. Results: We detected high-frequency oscillations in 17 out of 18 patients and in four out of six controls. Results did not show statistically significant differences in the mean rates of event occurrences, neither regarding the laterality of the epileptic focus, nor with respect to active and inactive task conditions, or the moving hand laterality. Significant differences in general spontaneous incidence [WTS(1) = 9.594; p = 0.005] that indicated higher rates of fast ripples compared to ripples, notably in patients with epilepsy compared to the control group, may be explained by variations in data quality. Conclusion: The current analysis methods are prone to biases. A common agreement on a standard operating procedure is needed to ensure reliable and economic detection of high-frequency oscillations.

Identifying task-relevant spectral signatures of perceptual categorization in the human cortex

Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks’ selectivity for categorical information processing is still unknown. In this work we train Random Forest classification models to decode eight perceptual categories from broad spectrum of human intracranial signals (4–150 Hz, 100 subjects) obtained during a visual perception task. We then analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding and gain the insights into which parts of the recorded activity are actually characteristic of the visual categorization process in the human brain. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low (4–50 Hz) and high (50–150 Hz) frequency bands. By focusing on task-relevant neural activity and separating it into dissociated anatomical and spectrotemporal groups we uncover spectral signatures that characterize neural mechanisms of visual category perception in human brain that have not yet been reported in the literature.

Reactivation of Motor-Related Gamma Activity in Human NREM Sleep

Models of memory consolidation posit a central role for reactivation of brain activity patterns during sleep, especially in non-Rapid Eye Movement (NREM) sleep. While such "replay" of recent waking experiences has been well-demonstrated in rodents, electrophysiological evidence of reactivation in human sleep is still largely lacking. In this intracranial study in patients with epilepsy (N = 9) we explored the spontaneous electroencephalographic reactivation during sleep of spatial patterns of brain activity evoked by motor learning. We first extracted the gamma-band (60-140 Hz) patterns underlying finger movements during a tapping task and underlying no-movement during a short rest period just prior to the task, and trained a binary classifier to discriminate between motor movements vs. rest. We then used the trained model on NREM sleep data immediately after the task and on NREM sleep during a control sleep period preceding the task. Compared with the control sleep period, we found, at the subject level, an increase in the detection rate of motor-related patterns during sleep following the task, but without association with performance changes. These data provide electrophysiological support for the reoccurrence in NREM sleep of the neural activity related to previous waking experience, i.e. that a basic tenet of the reactivation theory does occur in human sleep.

Relationship between direct cortical stimulation and induced high-frequency activity for language mapping during SEEG recording

OBJECTIVE

The authors assessed the clinical relevance of preoperative task-induced high-frequency activity (HFA) for language mapping in patients with refractory epilepsy during stereoelectroencephalography recording. Although HFA evaluation was described as a putative biomarker of cognition, its clinical relevance for mapping language networks was assessed predominantly by studies using electrocorticography (ECOG).

METHODS

Forty-two patients with epilepsy who underwent intracranial electrode implantation during both task-induced HFA and direct cortical stimulation (DCS) language mapping were evaluated. The spatial and functional relevance of each method in terms of specificity and sensitivity were evaluated.

RESULTS

The results showed that the two methods were able to map classic language regions, and a large and bilateral language network was obtained with induced HFA. At a regional level, differences were observed between methods for parietal and temporal lobes: HFA recruited a larger number of cortical parietal sites, while DCS involved more cortical temporal sites. Importantly, the results showed that HFA predicts language interference induced by DCS with high specificity (92.4%; negative predictive value 95.9%) and very low sensitivity (8.9%; positive predictive value 4.8%).

CONCLUSIONS

DCS language mapping appears to be more appropriate for an extensive temporal mapping than induced HFA mapping. Furthermore, induced HFA should be used as a complement to DCS to preselect the number of stimulated sites during DCS, by omitting those reported as HFA-. This may be a considerable advantage because it allows a reduction in the duration of the stimulation procedure. Several parameters to be used for each method are discussed and the results are interpreted in relation to previous results reported in ECOG studies.

A Switch and Wave of Neuronal Activity in the Cerebral Cortex During the First Second of Conscious Perception

Conscious perception occurs within less than 1 s. To study events on this time scale we used direct electrical recordings from the human cerebral cortex during a conscious visual perception task. Faces were presented at individually titrated visual threshold for 9 subjects while measuring broadband 40-115 Hz gamma power in a total of 1621 intracranial electrodes widely distributed in both hemispheres. Surface maps and k-means clustering analysis showed initial activation of visual cortex for both perceived and non-perceived stimuli. However, only stimuli reported as perceived then elicited a forward-sweeping wave of activity throughout the cerebral cortex accompanied by large-scale network switching. Specifically, a monophasic wave of broadband gamma activation moves through bilateral association cortex at a rate of approximately 150 mm/s and eventually reenters visual cortex for perceived but not for non-perceived stimuli. Meanwhile, the default mode network and the initial visual cortex and higher association cortex networks are switched off for the duration of conscious stimulus processing. Based on these findings, we propose a new "switch-and-wave" model for the processing of consciously perceived stimuli. These findings are important for understanding normal conscious perception and may also shed light on its vulnerability to disruption by brain disorders.

Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE

Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice.

OBJECTIVE

To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment.

DESIGN, SETTING, AND PARTICIPANTS

In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019.

INTERVENTIONS

Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks.

MAIN OUTCOMES AND MEASURES

Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit.

RESULTS

Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points.

CONCLUSIONS AND RELEVANCE

These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01407094.

A real-time marker of object-based attention in the human brain. A possible component of a "gate-keeping mechanism" performing late attentional selection in the Ventro-Lateral Prefrontal Cortex

The decision to process an incoming stimulus attentively - and to trigger a follow-up cascade of high-level processes - is strategic for the human brain as it becomes transiently unavailable to subsequent stimulus processing. In this study, we set to identify brain networks that carry out such evaluations. We therefore assessed the time-course of neural responses with intracerebral EEG in human patients during an attentional reading task, contrasting to-be-attended vs. to-be-ignored items. We measured High-Frequency Activity [50-150 ​Hz] as a proxy of population-level spiking activity and we identified a crucial component of a Gate-Keeping Mechanism bilateral in the mid-Ventro-Lateral Prefrontal Cortex (VLPFC), at the interplay of the Ventral and Dorsal Attention Networks, that selectively reacts before domain specialized cortical regions that engage in full stimulus analysis according to task demands.

Electrophysiological dynamics of antagonistic brain networks reflect attentional fluctuations

Neuroimaging evidence suggests that the default mode network (DMN) exhibits antagonistic activity with dorsal attention (DAN) and salience (SN) networks. Here we use human intracranial electroencephalography to investigate the behavioral relevance of fine-grained dynamics within and between these networks. The three networks show dissociable profiles of task-evoked electrophysiological activity, best captured in the high-frequency broadband (HFB; 70-170 Hz) range. On the order of hundreds of milliseconds, HFB responses peak fastest in the DAN, at intermediate speed in the SN, and slowest in the DMN. Lapses of attention (behavioral errors) are marked by distinguishable patterns of both pre- and post-stimulus HFB activity within each network. Moreover, the magnitude of temporally lagged, negative HFB coupling between the DAN and DMN (but not SN and DMN) is associated with greater sustained attention performance and is reduced during wakeful rest. These findings underscore the behavioral relevance of temporally delayed coordination between antagonistic brain networks.

Random Recurrent Networks Near Criticality Capture the Broadband Power Distribution of Human ECoG Dynamics

Brain electric field potentials are dominated by an arrhythmic broadband signal, but the underlying mechanism is poorly understood. Here we propose that broadband power spectra characterize recurrent neural networks of nodes (neurons or clusters of neurons), endowed with an effective balance between excitation and inhibition tuned to keep the network on the edge of dynamical instability. These networks show a fast mode reflecting local dynamics and a slow mode emerging from distributed recurrent connections. Together, the 2 modes produce power spectra similar to those observed in human intracranial EEG (i.e., electrocorticography, ECoG) recordings. Moreover, such networks convert spatial input correlations across nodes into temporal autocorrelation of network activity. Consequently, increased independence between nodes reduces low-frequency power, which may explain changes observed during behavioral tasks. Lastly, varying network coupling causes activity changes that resemble those observed in human ECoG across different arousal states. The model links macroscopic features of empirical ECoG power to a parsimonious underlying network structure, and suggests mechanisms for changes observed across behavioral and arousal states. This work provides a computational framework to generate and test hypotheses about cellular and network mechanisms underlying whole brain electrical dynamics, their variations across states, and potential alterations in brain diseases.

Advancing Our Understandings of Healthcare Team Dynamics From the Simulation Room to the Operating Room: A Neurodynamic Perspective

The initial models of team and team member dynamics using biometric data in healthcare will likely come from simulations. But how confident are we that the simulation-derived high-resolution dynamics will reflect those of teams working with live patients? We have developed neurodynamic models of a neurosurgery team while they performed a peroneal nerve decompression surgery on a patient to approach this question. The models were constructed from EEG-derived measures that provided second-by-second estimates of the neurodynamic responses of the team and team members to task uncertainty. The anesthesiologist and two neurosurgeons developed peaks, often coordinated, of elevated neurodynamic organization during the patient preparation and surgery which were similar to those seen during simulation training, and which occurred near important episodes of the patient preparation and surgery. As the analyses moved down the neurodynamic hierarchy, and the simulation and live patient neurodynamics occurring during the intubation procedure were compared at progressively smaller time scales, differences emerged across scalp locations and EEG frequencies. The most significant was the pronounced suppression of gamma rhythms detected by the frontal scalp sensors during the live patient intubation which was absent in simulation trials of the intubation procedure. These results indicate that while profiles of the second-by-second neurodynamics of teams were similar in both the simulation and live patient environments, a deeper analysis revealed differences in the EEG frequencies and scalp locations of the signals responsible for those team dynamics. As measures of individual and team performance become more micro-scale and dynamic, and simulations become extended into virtual environments, these results argue for the need for parallel studies in live environments to validate the dynamics of cognition being observed.

Default mode and visual network activity in an attention task: Direct measurement with intracranial EEG

Dynamic attention states are necessary to navigate the ever changing task demands of daily life. Previous investigations commonly utilize a block paradigm to study sustained and transient changes in attention networks. fMRI investigations have shown that sustained attention in visual block design attention tasks corresponds to decreased signal in the default mode and visual processing networks. While task negative networks are anticipated to decrease during active task engagement, it is unexpected that visual networks would also be suppressed during a visual task where event-related fMRI studies have found transient increases to visual stimuli. To resolve these competing results, the current investigations utilized intracranial EEG to directly interrogate visual and default mode network dynamics during a visual continuous performance task. We used the electrophysiological data to model expected fMRI signals and to maximize interpretation of current results with previous investigations. Results show broadband gamma power decreases in the default mode network, corresponding to previous EEG and fMRI findings. Meanwhile, visual processing regions including the primary visual cortex and fusiform gyrus demonstrate both sustained decreases during task engagement and stimuli-driven transient increases in gamma power. Modeled fMRI based on gamma power reproduces signal decreases reported in the fMRI literature, and emphasizes the insensitivity of fMRI to transient, regularly spaced signal changes embedded within sustained network dynamics. The signal processing functions of the dynamic visual and default mode network changes explored in this study are unknown but may be elucidated through further investigation.

Power-spectra and cross-frequency coupling changes in visual and Audio-visual acquired equivalence learning

The three phases of the applied acquired equivalence learning test, i.e. acquisition, retrieval and generalization, investigate the capabilities of humans in associative learning, working memory load and rule-transfer, respectively. Earlier findings denoted the role of different subcortical structures and cortical regions in the visual test. However, there is a lack of information about how multimodal cues modify the EEG-patterns during acquired equivalence learning. To test this we have recorded EEG from 18 healthy volunteers and analyzed the power spectra and the strength of cross-frequency coupling, comparing a unimodal visual-guided and a bimodal, audio-visual-guided paradigm. We found that the changes in the power of the different frequency band oscillations were more critical during the visual paradigm and they showed less synchronized activation compared to the audio-visual paradigm. These findings indicate that multimodal cues require less prominent, but more synchronized cortical contribution, which might be a possible biomarker of forming multimodal associations.

Neural efficiency in basketball players is associated with bidirectional reductions in cortical activation and deactivation during multiple-object tracking task performance

Although sports expertise has been shown to have transferable cognitive benefits, it is unclear how motor expertise influences brain activity during perceptual-cognitive tasks. The aim of the present study was to investigate whether improved perceptual-cognitive behavioral task performance in individuals with well-developed motor skills is associated with characteristic cortical activation and deactivation. Blood oxygenation-level dependent (BOLD) functional MRI (fMRI) was conducted in 23 athletes and 24 age- and education-matched non-athletes performing a multiple object tracking (MOT) task with graded levels of attentional load (two, three, or four targets). Compared to non-athletes, athletes had better performance in the three- and four-target conditions of the MOT task. Less activation of the left frontal eye field (FEF) and bilateral anterior intraparietal sulcus (aIPS) and less deactivation in the bilateral medial superior frontal gyrus (mSFG) were observed in athletes compared to non-athletes. Importantly, as the attentional load was increased, differences in deactivation of the left middle temporal gyrus (MTG) between athletes and non-athletes became larger. Behavioral performance in the high attentional load condition correlated negatively with activation in the left FEF and right aIPS, and correlated positively with that in the mSFG and left MTG. Better performance in elite athletes may transfer from the sport domain to a general cognitive domain owing to higher neural efficiency, which may be represented by a bidirectional reduction phenomenon encompassing both reduced activation of areas associated with task execution and reduced deactivation of areas associated with irrelevant information processing.