Ongoing Spontaneous Activity Controls Access to Consciousness: A Neuronal Model for Inattentional Blindness

Even in the absence of sensory inputs, cortical and thalamic neurons can show structured patterns of ongoing spontaneous activity, whose origins and functional significance are not well understood. We use computer simulations to explore the conditions under which spontaneous activity emerges from a simplified model of multiple interconnected thalamocortical columns linked by long-range, top-down excitatory axons, and to examine its interactions with stimulus-induced activation. Simulations help characterize two main states of activity. First, spontaneous gamma-band oscillations emerge at a precise threshold controlled by ascending neuromodulator systems. Second, within a spontaneously active network, we observe the sudden “ignition” of one out of many possible coherent states of high-level activity amidst cortical neurons with long-distance projections. During such an ignited state, spontaneous activity can block external sensory processing. We relate those properties to experimental observations on the neural bases of endogenous states of consciousness, and particularly the blocking of access to consciousness that occurs in the psychophysical phenomenon of “inattentional blindness,” in which normal subjects intensely engaged in mental activity fail to notice salient but irrelevant sensory stimuli. Although highly simplified, the generic properties of a minimal network may help clarify some of the basic cerebral phenomena underlying the autonomy of consciousness

Pre-stimulus antero-posterior EEG connectivity predicts performance in a UAV monitoring task

Long monitoring tasks without regular actions, are becoming increasingly common from aircraft pilots to train conductors as these systems grow more automated. These task contexts are challenging for the human operator because they require inputs at irregular and highly interspaced moments even though these actions are often critical. It has been shown that such conditions lead to divided and distracted attentional states which in turn reduce the processing of external stimuli (e.g. alarms) and may lead to miss critical events. In this study we explored to which extent it is possible to predict an operator’s behavioural performance in a Unmanned Aerial Vehicle (UAV) monitoring task using electroencephalographic (EEG) activity. More specifically we investigated the relevance of large-scale EEG connectivity for performance prediction by correlating relative coherence with reaction times (RT). We show that long-range EEG relative coherence, i.e. between occipital and frontal electrodes, is significantly correlated with RT and that different frequency bands exhibit opposite effects. More specifically we observed that coherence between occipital and frontal electrodes was: negatively correlated with RT at 6Hz (theta band), more coherence leading to better performance, and positively correlated with RT at 8Hz (lower alpha band), more coherence leading to worse performance. Our results suggest that EEG connectivity measures could be useful in predicting an operator’s attentional state and her/his performances in ecological settings. Hence these features could potentially be used in a neuro-adaptive interface to improve operator-system interaction and safety in critical systems

Acetylcholine neuromodulation in normal and abnormal learning and memory: vigilance control in waking, sleep, autism, amnesia, and Alzheimer's disease

This article provides a unified mechanistic neural explanation of how learning, recognition, and cognition break down during Alzheimer's disease, medial temporal amnesia, and autism. It also clarifies whey there are often sleep disturbances during these disorders. A key mechanism is how acetylcholine modules vigilance control in cortical layer

Alpha power increase after transcranial alternating current stimulation at alpha frequency (α-tacs) reflects plastic changes rather than entrainment

Background: Periodic stimulation of occipital areas using transcranial alternating current stimulation (tACS) at alpha (α) frequency (8–12 Hz) enhances electroencephalographic (EEG) α-oscillation long after tACS-offset. Two mechanisms have been suggested to underlie these changes in oscillatory EEG activity: tACS-induced entrainment of brain oscillations and/or tACS-induced changes in oscillatory circuits by spike-timing dependent plasticity.<p></p> Objective: We tested to what extent plasticity can account for tACS-aftereffects when controlling for entrainment “echoes.” To this end, we used a novel, intermittent tACS protocol and investigated the strength of the aftereffect as a function of phase continuity between successive tACS episodes, as well as the match between stimulation frequency and endogenous α-frequency.<p></p> Methods: 12 healthy participants were stimulated at around individual α-frequency for 15–20 min in four sessions using intermittent tACS or sham. Successive tACS events were either phase-continuous or phase-discontinuous, and either 3 or 8 s long. EEG α-phase and power changes were compared after and between episodes of α-tACS across conditions and against sham.<p></p> Results: α-aftereffects were successfully replicated after intermittent stimulation using 8-s but not 3-s trains. These aftereffects did not reveal any of the characteristics of entrainment echoes in that they were independent of tACS phase-continuity and showed neither prolonged phase alignment nor frequency synchronization to the exact stimulation frequency.<p></p> Conclusion: Our results indicate that plasticity mechanisms are sufficient to explain α-aftereffects in response to α-tACS, and inform models of tACS-induced plasticity in oscillatory circuits. Modifying brain oscillations with tACS holds promise for clinical applications in disorders involving abnormal neural synchrony

Analytical methods and experimental approaches for electrophysiological studies of brain oscillations

Brain oscillations are increasingly the subject of electrophysiological studies probing their role in the functioning and dysfunction of the human brain. In recent years this research area has seen rapid and significant changes in the experimental approaches and analysis methods. This article reviews these developments and provides a structured overview of experimental approaches, spectral analysis techniques and methods to establish relationships between brain oscillations and behaviour

State dependency of inhibitory control performance: an electrical neuroimaging study

Behavioral and brain responses to stimuli not only depend on their physical features but also on the individuals' neurocognitive states before stimuli onsets. While the influence of pre-stimulus fluctuations in brain activity on low-level perceptive processes is well established, the state dependency of high-order executive processes remains unclear. Using a classical inhibitory control Go/NoGo task, we examined whether and how fluctuations in the brain activity during the period preceding the stimuli triggering inhibition influenced inhibitory control performance. Seventeen participants completed the Go/NoGo task while 64-channel electroencephalogram was recorded. We compared the event-related potentials preceding the onset of the NoGo stimuli associated with inhibition failures false alarms (FA) vs. successful inhibition correct rejections (CR) with data-driven statistical analyses of global measures of the topography and strength of the scalp electric field. Distributed electrical source estimations were used to localize the origin of the event-related potentials modulations. We observed differences in the global field power of the event-related potentials (FA > CR) without concomitant topographic modulations over the 40 ms period immediately preceding NoGo stimuli. This result indicates that the same brain networks were engaged in the two conditions, but more strongly before FA than CR. Source estimations revealed that this effect followed from a higher activity before FA than CR within bilateral inferior frontal gyri and the right inferior parietal lobule. These findings suggest that uncontrolled quantitative variations in pre-stimulus activity within attentional and control brain networks influence inhibition performance. The present data thereby demonstrate the state dependency of cognitive processes of up to high- order executive levels

Event-related potentials reveal preserved attention allocation but impaired emotion regulation in patients with epilepsy and comorbid negative affect

Patients with epilepsy have a high prevalence of comorbid mood disorders. This study aims to evaluate whether negative affect in epilepsy is associated with dysfunction of emotion regulation. Event-related potentials (ERPs) are used in order to unravel the exact electrophysiological time course and investigate whether a possible dysfunction arises during early (attention) and/or late (regulation) stages of emotion control. Fifty epileptic patients with (n = 25) versus without (n = 25) comorbid negative affect plus twenty-five matched controls were recruited. ERPs were recorded while subjects performed a face- or house-matching task in which fearful, sad or neutral faces were presented either at attended or unattended spatial locations. Two ERP components were analyzed: the early vertex positive potential (VPP) which is normally enhanced for faces, and the late positive potential (LPP) that is typically larger for emotional stimuli. All participants had larger amplitude of the early face-sensitive VPP for attended faces compared to houses, regardless of their emotional content. By contrast, in patients with negative affect only, the amplitude of the LPP was significantly increased for unattended negative emotional expressions. These VPP results indicate that epilepsy with or without negative affect does not interfere with the early structural encoding and attention selection of faces. However, the LPP results suggest abnormal regulation processes during the processing of unattended emotional faces in patients with epilepsy and comorbid negative affect. In conclusion, this ERP study reveals that early object-based attention processes are not compromised by epilepsy, but instead, when combined with negative affect, this neurological disease is associated with dysfunction during the later stages of emotion regulation. As such, these new neurophysiological findings shed light on the complex interplay of epilepsy with negative affect during the processing of emotional visual stimuli and in turn might help to better understand the etiology and maintenance of mood disorders in epilepsy

Modeling Brain Resonance Phenomena Using a Neural Mass Model

Stimulation with rhythmic light flicker (photic driving) plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment) is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM) of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect

Early error detection predicted by reduced pre-response control process: an ERP topographic mapping study

Advanced ERP topographic mapping techniques were used to study error monitoring functions in human adult participants, and test whether proactive attentional effects during the pre-response time period could later influence early error detection mechanisms (as measured by the ERN component) or not. Participants performed a speeded go/nogo task, and made a substantial number of false alarms that did not differ from correct hits as a function of behavioral speed or actual motor response. While errors clearly elicited an ERN component generated within the dACC following the onset of these incorrect responses, I also found that correct hits were associated with a different sequence of topographic events during the pre-response baseline time-period, relative to errors. A main topographic transition from occipital to posterior parietal regions (including primarily the precuneus) was evidenced for correct hits similar to 170-150 ms before the response, whereas this topographic change was markedly reduced for errors. The same topographic transition was found for correct hits that were eventually performed slower than either errors or fast (correct) hits, confirming the involvement of this distinctive posterior parietal activity in top-down attentional control rather than motor preparation. Control analyses further ensured that this pre-response topographic effect was not related to differences in stimulus processing. Furthermore, I found a reliable association between the magnitude of the ERN following errors and the duration of this differential precuneus activity during the pre-response baseline, suggesting a functional link between an anticipatory attentional control component subserved by the precuneus and early error detection mechanisms within the dACC. These results suggest reciprocal links between proactive attention control and decision making processes during error monitoring

Origine des états actifs spontanés dans le néocortex pendant les oscillations du sommeil

Le sommeil à ondes lentes est composé d’une alternance entre un état actif et un état silencieux dans le système thalamocortical. Les mécanismes produisant l’état actif et l’état silencieux sont inconnus. Afin d’étudier l’origine des états actifs, nous avons procédé à l’enregistrement intracellulaire simultané de 2 à 4 neurones dans un environnement local (< 200μm) et dans un environnement distant (jusqu’à 12mm). Aussi, nous avons procédé à l’enregistrement simultané de potentiels de champ locaux (jusqu’à 16). Ces expériences ont été menées chez le chat anesthésié et chez le chat non-anesthésié. Nous avons trouvé que les cellules à bouffées de potentiels d’action ainsi que les cellules situées profondément ont tendance à être les premières à entrer dans l’état actif. Aussi, nous avons observé une grande variabilité dans les délais d’activation des cellules et ce, qu’elles soient situées près l’une de l’autre ou qu’elles soient distantes. De plus, nous avons observé que le déclenchement de l’état silencieux était beaucoup plus synchrone que le déclenchement de l’état actif.The slow-wave sleep is composed of an alternating period of active and silence state in the thalamocortical system. The mechanisms producing the active and silence state are unknown. In order to investigate the origin of active states, we performed simultaneous intracellular recording of 2 to 4 closely located (< 200μm) neurons and in a distant environment (up to 12mm). In addition, we performed simultaneous local field potentials (up to 16) recordings. These experiments were conducted on anesthetized and nonanesthetized cats. We found that Intrinsically-Bursting cells and deeply located cells have tendency to lead in the onset of the active state. We also observed a high, but similar, variability in the activation delay for closely located cells as well as for distantly located cells. In addition, we observed that the onset of silent state is much more synchronous than the onset of active state