Functional connectivity between motor cortex and globus pallidus in human non-REM sleep

Phase Delays between Mouse Globus Pallidus Neurons Entrained by Common Oscillatory Drive Arise from Their Intrinsic Properties, Not Their Coupling

A hallmark of Parkinson's disease is the appearance of correlated oscillatory discharge throughout the cortico-basal ganglia (BG) circuits. In the primate globus pallidus (GP), where the discharge of GP neurons is normally uncorrelated, pairs of GP neurons exhibit oscillatory spike correlations with a broad distribution of pairwise phase delays in experimental parkinsonism. The transition to oscillatory correlations is thought to indicate the collapse of the normally segregated information channels traversing the BG. The large phase delays are thought to reflect pathological changes in synaptic connectivity in the BG. Here we study the structure and phase delays of spike correlations measured from neurons in the mouse external GP (GPe) subjected to identical 1-100 Hz sinusoidal drive but recorded in separate experiments. First, we found that spectral modes of a GPe neuron's empirical instantaneous phase response curve (iPRC) elucidate at what phases of the oscillatory drive the GPe neuron locks when it is entrained and the distribution of phases at which it spikes when it is not. Then, we show that in this case the pairwise spike cross-correlation equals the cross-correlation function of these spike phase distributions. Finally, we show that the distribution of GPe phase delays arises from the diversity of iPRCs and is broadened when the neurons become entrained. Modeling GPe networks with realistic intranuclear connectivity demonstrates that the connectivity decorrelates GPe neurons without affecting phase delays. Thus, common oscillatory input gives rise to GPe correlations whose structure and pairwise phase delays reflect their intrinsic properties captured by their iPRCs.

The effects of slow wave sleep characteristics on semantic, episodic, and procedural memory in people with epilepsy

Slow wave sleep (SWS) is highly relevant for verbal and non-verbal/spatial memory in healthy individuals, but also in people with epilepsy. However, contradictory findings exist regarding the effect of seizures on overnight memory retention, particularly relating to procedural and non-verbal memory, and thorough examination of episodic memory retention with ecologically valid tests is missing. This research explores the interaction of SWS duration with epilepsy-relevant factors, as well as the relation of spectral characteristics of SWS on overnight retention of procedural, verbal, and episodic memory. In an epilepsy monitoring unit, epilepsy patients (N = 40) underwent learning, immediate and 12 h delayed testing of memory retention for a fingertapping task (procedural memory), a word-pair task (verbal memory), and an innovative virtual reality task (episodic memory). We used multiple linear regression to examine the impact of SWS duration, spectral characteristics of SWS, seizure occurrence, medication, depression, seizure type, gender, and epilepsy duration on overnight memory retention. Results indicated that none of the candidate variables significantly predicted overnight changes for procedural memory performance. For verbal memory, the occurrence of tonic-clonic seizures negatively impacted memory retention and higher psychoactive medication load showed a tendency for lower verbal memory retention. Episodic memory was significantly impacted by epilepsy duration, displaying a potential nonlinear impact with a longer duration than 10 years negatively affecting memory performance. Higher drug load of anti-seizure medication was by tendency related to better overnight retention of episodic memory. Contrary to expectations longer SWS duration showed a trend towards decreased episodic memory performance. Analyses on associations between memory types and EEG band power during SWS revealed lower alpha-band power in the frontal right region as significant predictor for better episodic memory retention. In conclusion, this research reveals that memory modalities are not equally affected by important epilepsy factors such as duration of epilepsy and medication, as well as SWS spectral characteristics.

Brain and brain-heart Granger causality during wakefulness and sleep

In this exploratory study we apply Granger Causality (GC) to investigate the brain-brain and brain-heart interactions during wakefulness and sleep. Our analysis includes electroencephalogram (EEG) and electrocardiogram (ECG) data during all-night polysomnographic recordings from volunteers with apnea, available from the Massachusetts General Hospital’s Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory. The data is manually annotated by clinical staff at the MGH in 30 second contiguous intervals (wakefulness and sleep stages 1, 2, 3, and rapid eye movement (REM). We applied GC to 4-s non-overlapping segments of available EEG and ECG across all-night recordings of 50 randomly chosen patients. To identify differences in GC between the different sleep stages, the GC for each sleep stage was subtracted from the GC during wakefulness. Positive (negative) differences indicated that GC was greater (lower) during wakefulness compared to the specific sleep stage. The application of GC to study brain-brain and brain-heart bidirectional connections during wakefulness and sleep confirmed the importance of fronto-posterior connectivity during these two states, but has also revealed differences in ipsilateral and contralateral mechanisms of these connections. It has also confirmed the existence of bidirectional brain-heart connections that are more prominent in the direction from brain to heart. Our exploratory study has shown that GC can be successfully applied to sleep data analysis and captures the varying physiological mechanisms that are related to wakefulness and different sleep stages.

Common and distinct neurofunctional representations of core and social disgust in the brain: Coordinate-based and network meta-analyses

Disgust represents a multifaceted defensive-avoidance response. On the behavioral level, the response includes withdrawal and a disgust-specific facial expression. While both serve the avoidance of pathogens, the latter additionally transmits social-communicative information. Given that common and distinct brain representation of the primary defensive-avoidance response (core disgust) and encoding of the social-communicative signal (social disgust) remain debated, we employed neuroimaging meta-analyses to (1) determine brain systems generally engaged in disgust processing, and (2) segregate common and distinct brain systems for core and social disgust. Disgust processing, in general, engaged a bilateral network encompassing the insula, amygdala, occipital and prefrontal regions. Core disgust evoked stronger reactivity in left-lateralized threat detection and defensive response network including amygdala, occipital and frontal regions, while social disgust engaged a right-lateralized superior temporal-frontal network engaged in social cognition. Anterior insula, inferior frontal and fusiform regions were commonly engaged during core and social disgust, suggesting a shared neurofunctional basis. We demonstrate a common and distinct neural basis of primary disgust responses and encoding of associated social-communicative signals.

The subcortical belly of sleep: New possibilities in neuromodulation of basal ganglia?

Early studies posited a relationship between sleep and the basal ganglia, but this relationship has received little attention recently. It is timely to revisit this relationship, given new insights into the functional anatomy of the basal ganglia and the physiology of sleep, which has been made possible by modern techniques such as chemogenetic and optogenetic mapping of neural circuits in rodents and intracranial recording, functional imaging, and a better understanding of human sleep disorders. We discuss the functional anatomy of the basal ganglia, and review evidence implicating their role in sleep. Whilst these studies are in their infancy, we suggest that the basal ganglia may play an integral role in the sleep-wake cycle, specifically by contributing to a thalamo-cortical-basal ganglia oscillatory network in slow-wave sleep which facilitates neural plasticity, and an active state during REM sleep which enables the enactment of cognitive and emotional networks. A better understanding of sleep mechanisms may pave the way for more effective neuromodulation strategies for sleep and basal ganglia disorders.

Empathy in Facial Mimicry of Fear and Disgust: Simultaneous EMG-fMRI Recordings During Observation of Static and Dynamic Facial Expressions

Real-life faces are dynamic by nature, particularly when expressing emotion. Increasing evidence suggests that the perception of dynamic displays enhances facial mimicry and induces activation in widespread brain structures considered to be part of the mirror neuron system, a neuronal network linked to empathy. The present study is the first to investigate the relations among facial muscle responses, brain activity, and empathy traits while participants observed static and dynamic (videos) facial expressions of fear and disgust. During display presentation, blood-oxygen level-dependent (BOLD) signal as well as muscle reactions of the corrugator supercilii and levator labii were recorded simultaneously from 46 healthy individuals (21 females). It was shown that both fear and disgust faces caused activity in the corrugator supercilii muscle, while perception of disgust produced facial activity additionally in the levator labii muscle, supporting a specific pattern of facial mimicry for these emotions. Moreover, individuals with higher, compared to individuals with lower, empathy traits showed greater activity in the corrugator supercilii and levator labii muscles; however, these responses were not differentiable between static and dynamic mode. Conversely, neuroimaging data revealed motion and emotional-related brain structures in response to dynamic rather than static stimuli among high empathy individuals. In line with this, there was a correlation between electromyography (EMG) responses and brain activity suggesting that the Mirror Neuron System, the anterior insula and the amygdala might constitute the neural correlates of automatic facial mimicry for fear and disgust. These results revealed that the dynamic property of (emotional) stimuli facilitates the emotional-related processing of facial expressions, especially among whose with high trait empathy.

Relationship between oscillatory activity in the cortico-basal ganglia network and parkinsonism in MPTP-treated monkeys

Parkinsonism is associated with changes in oscillatory activity patterns and increased synchronization of neurons in the basal ganglia and cortex in patients and animal models of Parkinson's disease, but the relationship between these changes and the severity of parkinsonian signs remains unclear. We examined this relationship by studying changes in local field potentials (LFPs) in the internal pallidal segment (GPi) and the subthalamic nucleus (STN), and in encephalographic signals (EEG) from the primary motor cortex (M1) in Rhesus monkeys which were rendered progressively parkinsonian by repeated systemic injections of small doses of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Observations during wakefulness and sleep (defined by EEG and video records) were analyzed separately. The severity of parkinsonism correlated with increases in spectral power at frequencies below 15.5Hz in M1 and GPi and reductions in spectral power at frequencies above 15.6Hz with little change in STN. The severity of parkinsonism also correlated with increases in the coherence between M1 EEG and basal ganglia LFPs in the low frequency band. Levodopa treatment reduced low-frequency activity and increased high-frequency activity in all three areas, but did not affect coherence. The state of arousal also affected LFP and EEG signals in all three structures, particularly in the STN. These results suggest that parkinsonism-associated changes in alpha and low-beta band oscillatory activity can be detected early in the parkinsonian state in M1 and GPi. Interestingly, oscillations detectable in STN LFP signals (including oscillations in the beta-band) do not appear to correlate strongly with the severity of mild-to-moderate parkinsonism in these animals. Levodopa-induced changes in oscillatory M1 EEG and basal ganglia LFP patterns do not necessarily represent a normalization of abnormalities caused by dopamine depletion.

Insights into sleep's role for insight: Studies with the number reduction task

In recent years, vibrant research has developed on “consolidation” during sleep: To what extent are newly experienced impressions reprocessed or even restructured during sleep? We used the number reduction task (NRT) to study if and how sleep does not only reiterate new experiences but may even lead to new insights. In the NRT, covert regularities may speed responses. This implicit acquisition of regularities may become explicitly conscious at some point, leading to a qualitative change in behavior which reflects this insight. By applying the NRT at two consecutive sessions separated by an interval, we investigated the role of sleep in this interval for attaining insight at the second session. In the first study, a night of sleep was shown to triple the number of participants attaining insight above the base rate of about 20%. In the second study, this hard core of 20% discoverers differed from other participants in their task-related EEG potentials from the very beginning already. In the third study, the additional role of sleep was specified as an effect of the deep-sleep phase of slow-wave sleep on participants who had implicitly acquired the covert regularity before sleep. It was in these participants that a specific increase of EEG during slow-wave sleep in the 10-12 Hz band was obtained. These results support the view that neuronal memory reprocessing during slow-wave sleep restructures task-related representations in the brain, and that such restructuring promotes the gain of explicit knowledge.

200-300Hz movement modulated oscillations in the internal globus pallidus of patients with Parkinson's Disease

Symptoms in Parkinson's Disease (PD) have been linked to oscillatory activity within the basal ganglia. In humans, such activity has been detected mainly in the local field potentials (LFPs) recorded from electrode contacts used for deep brain stimulation. Although most studies have focused on activity within the subthalamic nucleus (STN), the internal part of the globus pallidus (GPi) is considered an equally efficacious site for therapeutic neuromodulation. Moreover, while most investigations have evaluated changes in oscillatory activity in the beta (12-35Hz) and gamma (35-100Hz) bands, our preliminary spectral analysis of LFP signals in the GPi suggested distinct activity at higher frequencies as well. We hypothesized there is a unique LFP signature in the GPi that consists of movement modulated spectral power increases above 100Hz. Using invasive recordings from the GPi of patients undergoing DBS, in addition to confirming increased beta band activity within the GPi of patients with PD, we have identified and characterized a previously undescribed peak between 200 and 300Hz centered at approximately 235Hz, whose height and width but not center frequency are movement modulated. An increase in peak height is not transient, but rather persists for the duration of movement. The 200-300Hz rhythms in the GPi could have a functional role in the basal ganglia reentrant circuits by encoding output information entering the thalamo-cortical network or by organizing downstream activity for the successful execution of tasks.

Functional magnetic resonance imaging during emotion recognition in social anxiety disorder: an activation likelihood meta-analysis

Background: Social anxiety disorder (SAD) is characterized by abnormal fear and anxiety in social situations. Functional magnetic resonance imaging (fMRI) is a brain imaging technique that can be used to demonstrate neural activation to emotionally salient stimuli. However, no attempt has yet been made to statistically collate fMRI studies of brain activation, using the activation likelihood-estimate (ALE) technique, in response to emotion recognition tasks in individuals with SAD. Methods: A systematic search of fMRI studies of neural responses to socially emotive cues in SAD was undertaken. ALE meta-analysis, a voxel-based meta-analytic technique, was used to estimate the most significant activations during emotional recognition. Results: Seven studies were eligible for inclusion in the meta-analysis, constituting a total of 91 subjects with SAD, and 93 healthy controls. The most significant areas of activation during emotional vs. neutral stimuli in individuals with SAD compared to controls were: bilateral amygdala, left medial temporal lobe encompassing the entorhinal cortex, left medial aspect of the inferior temporal lobe encompassing perirhinal cortex and parahippocampus, right anterior cingulate, right globus pallidus, and distal tip of right postcentral gyrus. Conclusion: The results are consistent with neuroanatomic models of the role of the amygdala in fear conditioning, and the importance of the limbic circuitry in mediating anxiety symptoms.

Increased Alpha (8–12 Hz) Activity during Slow Wave Sleep as a Marker for the Transition from Implicit Knowledge to Explicit Insight

The number reduction task (NRT) allows us to study the transition from implicit knowledge of hidden task regularities to explicit insight into these regularities. To identify sleep-associated neurophysiological indicators of this restructuring of knowledge representations, we measured frequency-specific power of EEG while participants slept during the night between two sessions of the NRT. Alpha (8–12 Hz) EEG power during slow wave sleep (SWS) emerged as a specific marker of the transformation of presleep implicit knowledge to postsleep explicit knowledge (ExK). Beta power during SWS was increased whenever ExK was attained after sleep, irrespective of presleep knowledge. No such EEG predictors of insight were found during Sleep Stage 2 and rapid eye movement sleep. These results support the view that it is neuronal memory reprocessing during sleep, in particular during SWS, that lays the foundations for restructuring those task-related representations in the brain that are necessary for promoting the gain of ExK.

Accurate epileptogenic focus localization through time-variant functional connectivity analysis of intracranial electroencephalographic signals

Epilepsy is a neurological disorder characterized by seizures, i.e. abnormal synchronous activity of neurons in the brain. During a focal seizure, the abnormal synchronous activity starts in a specific brain region and rapidly propagates to neighboring regions. Intracranial ElectroEncephaloGraphy (IEEG) is the recording of brain activity at a high temporal resolution through electrodes placed within different brain regions. Intracranial electrodes are used to access structures deep within the brain and to reveal brain activity that cannot be observed with scalp EEG recordings. In order to identify the pattern of propagation across brain areas, a connectivity measure named the Adapted Directed Transfer Function (ADTF) has been developed. This measure reveals connections between different regions by exploiting statistical dependencies within multichannel recordings. The ADTF can be derived from the coefficients of a time-variant multivariate autoregressive (TVAR) model fitted to the data. In this paper the applicability to locate the epileptogenic focus by time-variant connectivity analysis of seizure onsets based on the ADTF is shown. Furthermore, different normalizations of the ADTF (the integrated ADTF, the masked ADTF and the full frequency ADTF) are compared to investigate whether one is more suitable to describe the spreading of epileptic activity during an epileptic seizure. We quantified the performance of different connectivity measures during simulations of an epileptic seizure onset. The full frequency ADTF outperforms the integrated ADTF and masked ADTF. Accordingly, we applied this full frequency ADTF to 4 seizure onset and 29 subclinical seizure IEEG recordings of a patient with refractory epilepsy. Hereby, we showed that connectivity patterns derived from IEEG recordings can provide useful information about seizure propagation and may improve the accuracy of the pre-surgical evaluation in patients with refractory epilepsy.