Assessing mismatch negativity (MMN) and P3b within-individual sensitivity - A comparison between the local-global paradigm and two specialized oddball sequences.

Mismatch negativity (MMN) and P3b are well known for their clinical utility. There exists no gold standard, however, for acquiring them as EEG markers of consciousness in clinical settings. This may explain why the within-individual sensitivity of MMN/P3b paradigms is often quite poor and why seemingly identical EEG markers can behave differently across Disorders of consciousness (DoC) studies. Here, we compare two traditional paradigms for MMN or P3b assessment with the recently more popular local-global paradigm that promises to assess MMN and P3b orthogonally within one oddball sequence. All three paradigms were administered to healthy participants (N = 15) with concurrent EEG. A clear MMN and local effect were found for 15/15 participants. The P3b and global effect were found for 14/15 and 13/15 participants, respectively. There were no systematic differences between the global effect and P3b. Indeed, P3b amplitude was highly correlated across paradigms. The local effect differed clearly from the MMN, however. It occurred earlier than MMN and was followed by a much more prominent P3a. The peak latencies and amplitudes were also not correlated across paradigms. Caution should therefore be exercised when comparing the local effect and MMN across studies. We conclude that the within-individual MMN sensitivity is adequate for both the local-global and a dedicated MMN paradigm. The within-individual sensitivity of P3b was lower than expected for both the local-global and a dedicated P3b paradigm, which may explain the often-low sensitivity of P3b paradigms in patients with DoC.

Dissociations between spontaneous electroencephalographic features and the perturbational complexity index in the minimally conscious state.

The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n = 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power-more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients-was found in a non-negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation.

Beyond alpha power: EEG spatial and spectral gradients robustly stratify disorders of consciousness.

Neurophysiological markers can overcome the limitations of behavioural assessments of Disorders of Consciousness (DoC). EEG alpha power emerged as a promising marker for DoC, although long-standing literature reported alpha power being sustained during anesthetic-induced unconsciousness, and reduced during dreaming and hallucinations. We hypothesized that EEG power suppression caused by severe anoxia could explain this conflict. Accordingly, we split DoC patients (n = 87) in postanoxic and non-postanoxic cohorts. Alpha power was suppressed only in severe postanoxia but failed to discriminate un/consciousness in other aetiologies. Furthermore, it did not generalize to an independent reference dataset (n = 65) of neurotypical, neurological, and anesthesia conditions. We then investigated EEG spatio-spectral gradients, reflecting anteriorization and slowing, as alternative markers. In non-postanoxic DoC, these features, combined in a bivariate model, reliably stratified patients and indexed consciousness, even in unresponsive patients identified as conscious by an independent neural marker (the Perturbational Complexity Index). Crucially, this model optimally generalized to the reference dataset. Overall, alpha power does not index consciousness; rather, its suppression entails diffuse cortical damage, in postanoxic patients. As an alternative, EEG spatio-spectral gradients, reflecting distinct pathophysiological mechanisms, jointly provide a robust, parsimonious, and generalizable marker of consciousness, whose clinical application may guide rehabilitation efforts.

The maturation of aperiodic EEG activity across development reveals a progressive differentiation of wakefulness from sleep.

During development, the brain undergoes radical structural and functional changes following a posterior-to-anterior gradient, associated with profound changes of cortical electrical activity during both wakefulness and sleep. However, a systematic assessment of the developmental effects on aperiodic EEG activity maturation across vigilance states is lacking, particularly regarding its topographical aspects. Here, in a population of 160 healthy infants, children and teenagers (from 2 to 17 years, 10 subjects for each year), we investigated the development of aperiodic EEG activity in wakefulness and sleep. Specifically, we parameterized the shape of the aperiodic background of the EEG Power Spectral Density (PSD) by means of the spectral exponent and offset; the exponent reflects the rate of exponential decay of power over increasing frequencies and the offset reflects an estimate of the y-intercept of the PSD. We found that sleep and development caused the EEG-PSD to rotate over opposite directions: during wakefulness the PSD showed a flatter decay and reduced offset over development, while during sleep it showed a steeper decay and a higher offset as sleep becomes deeper. During deep sleep (N2, N3) only the spectral offset decreased over age, indexing a broad-band voltage reduction. As a result, the difference between values in deep sleep and those in both light sleep (N1) and wakefulness increased with age, suggesting a progressive differentiation of wakefulness from sleep EEG activity, most prominent over the frontal regions, the latest to complete maturation. Notably, the broad-band spectral exponent values during deep sleep stages were entirely separated from wakefulness values, consistently across developmental ages and in line with previous findings in adults. Concerning topographical development, the location showing the steepest PSD decay and largest offset shifted from posterior to anterior regions with age. This shift, particularly evident during deep sleep, paralleled the migration of sleep slow wave activity and was consistent with neuroanatomical and cognitive development. Overall, aperiodic EEG activity distinguishes wakefulness from sleep regardless of age; while, during development, it reveals a postero-anterior topographical maturation and a progressive differentiation of wakefulness from sleep. Our study could help to interpret changes due to pathological conditions and may elucidate the neurophysiological processes underlying the development of wakefulness and sleep.

An in-vivo validation of ESI methods with focal sources.

Electrophysiological source imaging (ESI) aims at reconstructing the precise origin of brain activity from measurements of the electric field on the scalp. Across laboratories/research centers/hospitals, ESI is performed with different methods, partly due to the ill-posedness of the underlying mathematical problem. However, it is difficult to find systematic comparisons involving a wide variety of methods. Further, existing comparisons rarely take into account the variability of the results with respect to the input parameters. Finally, comparisons are typically performed using either synthetic data, or in-vivo data where the ground-truth is only roughly known. We use an in-vivo high-density EEG dataset recorded during intracranial single pulse electrical stimulation, in which the true sources are substantially dipolar and their locations are precisely known. We compare ten different ESI methods, using their implementation in the MNE-Python package: MNE, dSPM, LORETA, sLORETA, eLORETA, LCMV beamformers, irMxNE, Gamma Map, SESAME and dipole fitting. We perform comparisons under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of such parameters on the localization performance. Best reconstructions often fall within 1 cm from the true source, with most accurate methods hitting an average localization error of 1.2 cm and outperforming least accurate ones erring by 2.5 cm. As expected, dipolar and sparsity-promoting methods tend to outperform distributed methods. For several distributed methods, the best regularization parameter turned out to be the one in principle associated with low SNR, despite the high SNR of the available dataset. Depth weighting played no role for two out of the six methods implementing it. Sensitivity to input parameters varied widely between methods. While one would expect high variability being associated with low localization error at the best solution, this is not always the case, with some methods producing highly variable results and high localization error, and other methods producing stable results with low localization error. In particular, recent dipolar and sparsity-promoting methods provide significantly better results than older distributed methods. As we repeated the tests with "conventional" (32 channels) and dense (64, 128, 256 channels) EEG recordings, we observed little impact of the number of channels on localization accuracy; however, for distributed methods denser montages provide smaller spatial dispersion. Overall findings confirm that EEG is a reliable technique for localization of point sources and therefore reinforce the importance that ESI may have in the clinical context, especially when applied to identify the surgical target in potential candidates for epilepsy surgery.

Measures of differentiation and integration: One step closer to consciousness.

Interpreting empirical measures of integration and differentiation as indices of cortical performance and memory consolidation during wakefulness rather than consciousness per se is inconsistent with the literature. Recent studies show that these theory-inspired measures can dissociate from such processes and reliably index the brain's capacity for experience. We consider this as a positive trend in consciousness research.

Thalamic and neocortical differences in the relationship between the time course of delta and sigma power during NREM sleep in humans.

Sleep spindles and slow waves are the hallmarks of non-rapid eye movement (NREM) sleep and are produced by the dynamic interplay between thalamic and cortical regions. Several studies in both human and animal models have focused their attention on the relationship between electroencephalographic (EEG) spindles and slow waves during NREM, using the power in the sigma and delta bands as a surrogate for the production of spindles and slow waves. A typical report is an overall inverse relationship between the time course of sigma and delta power as measured by a single correlation coefficient both within and across NREM episodes. Here we analysed stereotactically implanted intracerebral electrode (Stereo-EEG [SEEG]) recordings during NREM simultaneously acquired from thalamic and from several neocortical sites in six neurosurgical patients. We investigated the relationship between the time course of delta and sigma power and found that, although at the cortical level it shows the expected inverse relationship, these two frequency bands follow a parallel time course at the thalamic level. Both these observations were consistent across patients and across different cortical as well as thalamic regions. These different temporal dynamics at the neocortical and thalamic level are discussed, considering classical as well as more recent interpretations of the neurophysiological determinants of sleep spindles and slow waves. These findings may also help understanding the regulatory mechanisms of these fundamental sleep EEG graphoelements across different brain compartments.

Local sleep-like cortical reactivity in the awake brain after focal injury.

The functional consequences of focal brain injury are thought to be contingent on neuronal alterations extending beyond the area of structural damage. This phenomenon, also known as diaschisis, has clinical and metabolic correlates but lacks a clear electrophysiological counterpart, except for the long-standing evidence of a relative EEG slowing over the injured hemisphere. Here, we aim at testing whether this EEG slowing is linked to the pathological intrusion of sleep-like cortical dynamics within an awake brain. We used a combination of transcranial magnetic stimulation and electroencephalography (TMS/EEG) to study cortical reactivity in a cohort of 30 conscious awake patients with chronic focal and multifocal brain injuries of ischaemic, haemorrhagic and traumatic aetiology. We found that different patterns of cortical reactivity typically associated with different brain states (coma, sleep, wakefulness) can coexist within the same brain. Specifically, we detected the occurrence of prominent sleep-like TMS-evoked slow waves and off-periods-reflecting transient suppressions of neuronal activity-in the area surrounding focal cortical injuries. These perilesional sleep-like responses were associated with a local disruption of signal complexity whereas complex responses typical of the awake brain were present when stimulating the contralesional hemisphere. These results shed light on the electrophysiological properties of the tissue surrounding focal brain injuries in humans. Perilesional sleep-like off-periods can disrupt network activity but are potentially reversible, thus representing a principled read-out for the neurophysiological assessment of stroke patients, as well as an interesting target for rehabilitation.

Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness.

Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified.

The spectral exponent of the resting EEG indexes the presence of consciousness during unresponsiveness induced by propofol, xenon, and ketamine.

Despite the absence of responsiveness during anesthesia, conscious experience may persist. However, reliable, easily acquirable and interpretable neurophysiological markers of the presence of consciousness in unresponsive states are still missing. A promising marker is based on the decay-rate of the power spectral density (PSD) of the resting EEG. We acquired resting electroencephalogram (EEG) in three groups of healthy participants (n = 5 each), before and during anesthesia induced by either xenon, propofol or ketamine. Dosage of each anesthetic agent was tailored to yield unresponsiveness (Ramsay score = 6). Delayed subjective reports assessed whether conscious experience was present ('Conscious report') or absent/inaccessible to recall ('No Report'). We estimated the decay of the PSD of the resting EEG-after removing oscillatory peaks-via the spectral exponent ß, for a broad band (1-40 Hz) and narrower sub-bands (1-20 Hz, 20-40 Hz). Within-subject anesthetic changes in ß were assessed. Furthermore, based on ß, 'Conscious report' states were discriminated against 'no report' states. Finally, we evaluated the correlation of the resting spectral exponent with a recently proposed index of consciousness, the Perturbational Complexity Index (PCI), derived from a previous TMS-EEG study. The spectral exponent of the resting EEG discriminated states in which consciousness was present (wakefulness, ketamine) from states where consciousness was reduced or abolished (xenon, propofol). Loss of consciousness substantially decreased the (negative) broad-band spectral exponent in each subject undergoing xenon or propofol anesthesia-indexing an overall steeper PSD decay. Conversely, ketamine displayed an overall PSD decay similar to that of wakefulness-consistent with the preservation of consciousness-yet it showed a flattening of the decay in the high-frequencies (20-40 Hz)-consistent with its specific mechanism of action. The spectral exponent was highly correlated to PCI, corroborating its interpretation as a marker of the presence of consciousness. A steeper PSD of the resting EEG reliably indexed unconsciousness in anesthesia, beyond sheer unresponsiveness.

Levodopa-induced dyskinesia in Parkinson disease: Sleep matters.

OBJECTIVE: The spectrum of clinical symptom changes during the course of Parkinson disease (PD). Levodopa therapy, while offering remarkable control of classical motor symptoms, causes abnormal involuntary movements as the disease progresses. This levodopa-induced dyskinesia (LID) has been associated with abnormal cortical plasticity. Because slow wave activity (SWA) of nonrapid eye movement (NREM) sleep underlies adjustment of cortical excitability, we sought to elucidate the relationship between this physiological process and LID. METHODS: Thirty-six patients at different stages of PD underwent whole-night video polysomnography-high-density electroencephalography (vPSG-hdEEG), preceded by 1 week of actigraphy. To represent the broad spectrum of the disease, patients were divided into 3 groups by disease stage-(1) de novo (n = 9), (2) advanced (n = 13), and (3) dyskinetic (DYS; n = 14)-were compared to an age-matched control group (n = 12). The SWA-NREM content of the vPSG-hdEEG was then temporally divided into 10 equal parts, from T1 to T10, and power and source analyses were performed. T2-T3-T4 were considered early sleep and were compared to T7-T8-T9, representing late sleep. RESULTS: We found that all groups, except the DYS group, manifested a clear-cut SWA decrease between early and late sleep. INTERPRETATION: Our data demonstrate a strong pathophysiological association between sleep and PD. Given that SWA may be a surrogate for synaptic strength, our data suggest that DYS patients do not have adequate synaptic downscaling. Further analysis is needed to determine the effect of drugs that can enhance cortical SWA in LID. Ann Neurol 2018;84:905-917.

Human fronto-parietal response scattering subserves vigilance at night.

Lack of sleep has a considerable impact on vigilance: we perform worse, we make more errors, particularly at night, when we should be sleeping. Measures of brain functional connectivity suggest that decrease in vigilance during sleep loss is associated with an impaired cross-talk within the fronto-parietal cortex. However, fronto-parietal effective connectivity, which is more closely related to the causal cross-talk between brain regions, remains unexplored during prolonged wakefulness. In addition, no study has simultaneously investigated brain effective connectivity and wake-related changes in vigilance, preventing the concurrent incorporation of the two aspects. Here, we used electroencephalography (EEG) to record responses evoked by Transcranial Magnetic Stimulation (TMS) applied over the frontal lobe in 23 healthy young men (18-30 yr.), while they simultaneously performed a vigilance task, during 8 sessions spread over 29 h of sustained wakefulness. We assessed Response Scattering (ReSc), an estimate of effective connectivity, as the propagation of TMS-evoked EEG responses over the fronto-parietal cortex. Results disclose a significant change in fronto-parietal ReSc with time spent awake. When focusing on the night-time period, when one should be sleeping, participants with lower fronto-parietal ReSc performed worse on the vigilance task. Conversely, no association was detected during the well-rested, daytime period. Night-time fronto-parietal ReSc also correlated with objective EEG measures of sleepiness and alertness. These changes were not accompanied by variations in fronto-parietal response complexity. These results suggest that decreased brain response propagation within the fronto-parietal cortex is associated to increased vigilance failure during night-time prolonged wakefulness. This study reveals a novel facet of the detrimental effect on brain function of extended night-time waking hours, which is increasingly common in our societies.

Stratification of unresponsive patients by an independently validated index of brain complexity.

OBJECTIVE: Validating objective, brain-based indices of consciousness in behaviorally unresponsive patients represents a challenge due to the impossibility of obtaining independent evidence through subjective reports. Here we address this problem by first validating a promising metric of consciousness-the Perturbational Complexity Index (PCI)-in a benchmark population who could confirm the presence or absence of consciousness through subjective reports, and then applying the same index to patients with disorders of consciousness (DOCs). METHODS: The benchmark population encompassed 150 healthy controls and communicative brain-injured subjects in various states of conscious wakefulness, disconnected consciousness, and unconsciousness. Receiver operating characteristic curve analysis was performed to define an optimal cutoff for discriminating between the conscious and unconscious conditions. This cutoff was then applied to a cohort of noncommunicative DOC patients (38 in a minimally conscious state [MCS] and 43 in a vegetative state [VS]). RESULTS: We found an empirical cutoff that discriminated with 100% sensitivity and specificity between the conscious and the unconscious conditions in the benchmark population. This cutoff resulted in a sensitivity of 94.7% in detecting MCS and allowed the identification of a number of unresponsive VS patients (9 of 43) with high values of PCI, overlapping with the distribution of the benchmark conscious condition. INTERPRETATION: Given its high sensitivity and specificity in the benchmark and MCS population, PCI offers a reliable, independently validated stratification of unresponsive patients that has important physiopathological and therapeutic implications. In particular, the high-PCI subgroup of VS patients may retain a capacity for consciousness that is not expressed in behavior. Ann Neurol 2016;80:718-729.

Sleep Spindle Deficit in Schizophrenia: Contextualization of Recent Findings.

Sleep spindles are wax and waning brain oscillations at a frequency range of 11-16 Hz, lasting 0.5-2 s, that define non-rapid eye movement sleep stage 2. Over the past few years, several independent studies pointed to a decrease of sleep spindles in schizophrenia. The aim of this review is to contextualize these findings within the growing literature on these oscillations across other neuro-psychiatric disorders. Indeed, spindles reflect the coordinated activity of thalamocortical networks, and their abnormality can be observed in a variety of conditions that disrupt local or global thalamocortical connectivity. Although the broad methodological variability across studies limits the possibility of drawing firm conclusions, impaired spindling activity has been observed in several neurodevelopmental and neurodegenerative disorders. Despite such lack of specificity, schizophrenia remains the only condition with a typical late adolescence to young adulthood onset in which impaired spindling has been consistently reported. Further research is necessary to clearly define the pathogenetic mechanisms that lead to this deficit and the validity of its widespread use as a clinical biomarker.

Parietal Fast Sleep Spindle Density Decrease in Alzheimer's Disease and Amnesic Mild Cognitive Impairment.

Several studies have identified two types of sleep spindles: fast (13-15 Hz) centroparietal and slow (11-13 Hz) frontal spindles. Alterations in spindle activity have been observed in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). Only few studies have separately assessed fast and slow spindles in these patients showing a reduction of fast spindle count, but the possible local specificity of this phenomenon and its relation to cognitive decline severity are not clear. Moreover, fast and slow spindle density have never been assessed in AD/MCI. We have assessed fast and slow spindles in 15 AD patients, 15 amnesic MCI patients, and 15 healthy elderly controls (HC). Participants underwent baseline polysomnographic recording (19 cortical derivations). Spindles during nonrapid eye movements sleep were automatically detected, and spindle densities of the three groups were compared in the derivations where fast and slow spindles exhibited their maximum expression (parietal and frontal, resp.). AD and MCI patients showed a significant parietal fast spindle density decrease, positively correlated with Minimental State Examination scores. Our results suggest that AD-related changes in spindle density are specific for frequency and location, are related to cognitive decline severity, and may have an early onset in the pathology development.

Bistability breaks-off deterministic responses to intracortical stimulation during non-REM sleep.

During non-rapid eye movement (NREM) sleep (stage N3), when consciousness fades, cortico-cortical interactions are impaired while neurons are still active and reactive. Why is this? We compared cortico-cortical evoked-potentials recorded during wakefulness and NREM by means of time-frequency analysis and phase-locking measures in 8 epileptic patients undergoing intra-cerebral stimulations/recordings for clinical evaluation. We observed that, while during wakefulness electrical stimulation triggers a chain of deterministic phase-locked activations in its cortical targets, during NREM the same input induces a slow wave associated with an OFF-period (suppression of power>20Hz), possibly reflecting a neuronal down-state. Crucially, after the OFF-period, cortical activity resumes to wakefulness-like levels, but the deterministic effects of the initial input are lost, as indicated by a sharp drop of phase-locked activity. These findings suggest that the intrinsic tendency of cortical neurons to fall into a down-state after a transient activation (i.e. bistability) prevents the emergence of stable patterns of causal interactions among cortical areas during NREM. Besides sleep, the same basic neurophysiological dynamics may play a role in pathological conditions in which thalamo-cortical information integration and consciousness are impaired in spite of preserved neuronal activity.

Reduced mediodorsal thalamic volume and prefrontal cortical spindle activity in schizophrenia.

BACKGROUND: We recently found marked deficits in sleep spindles, non-rapid eye movement (NREM) sleep oscillations that are generated within the thalamus and then amplified and sustained in the cortex, in patients with schizophrenia compared to both healthy and psychiatric controls. Here, we investigated the thalamic and cortical contributions to these sleep spindle deficits. METHODS: Anatomical volume of interest analysis (i.e., thalamic volumes) and electroencephalogram (EEG) source modeling (i.e., spindle-related cortical currents) were performed in patients with schizophrenia and healthy comparison subjects. FINDINGS: Schizophrenia patients had reduced mediodorsal (MD) thalamic volumes, especially on the left side, compared to healthy controls, whereas whole thalami and lateral geniculate nuclei did not differ between groups. Furthermore, left MD volumes were strongly correlated with the number of scalp-recorded spindles in an anterior frontal region, and cortical currents underlying these anterior frontal spindles were localized in the prefrontal cortex, in Brodmann area (BA) 10. Finally, prefrontal currents at the peak of spindle activity were significantly reduced in schizophrenia patients and correlated with their performance in an abstraction/working memory task. CONCLUSION: Altogether, these findings point to deficits in a specific thalamo-cortical circuitry in schizophrenia, which is associated with some cognitive deficits commonly reported in those patients.

Sleep-like cortical dynamics during wakefulness and their network effects following brain injury.

By connecting old and recent notions, different spatial scales, and research domains, we introduce a novel framework on the consequences of brain injury focusing on a key role of slow waves. We argue that the long-standing finding of EEG slow waves after brain injury reflects the intrusion of sleep-like cortical dynamics during wakefulness; we illustrate how these dynamics are generated and how they can lead to functional network disruption and behavioral impairment. Finally, we outline a scenario whereby post-injury slow waves can be modulated to reawaken parts of the brain that have fallen asleep to optimize rehabilitation strategies and promote recovery.

Proof-of-concept evidence for high-density EEG investigation of sleep slow wave traveling in First-Episode Psychosis.

Schizophrenia is thought to reflect aberrant connectivity within cortico-cortical and reentrant thalamo-cortical loops, which physiologically integrate and coordinate the function of multiple cortical and subcortical structures. Despite extensive research, reliable biomarkers of such "dys-connectivity" remain to be identified at the onset of psychosis, and before exposure to antipsychotic drugs. Because slow waves travel across the brain during sleep, they represent an ideal paradigm to study pathological conditions affecting brain connectivity. Here, we provide proof-of-concept evidence for a novel approach to investigate slow wave traveling properties in First-Episode Psychosis (FEP) with high-density electroencephalography (EEG). Whole-night sleep recordings of 5 drug-naïve FEP and 5 age- and gender-matched healthy control subjects were obtained with a 256-channel EEG system. One patient was re-recorded after 6 months and 3 years of continuous clozapine treatment. Slow wave detection and traveling properties were obtained with an open-source toolbox. Slow wave density and slow wave traveled distance (measured as the line of longest displacement) were significantly lower in patients (p < 0.05). In the patient who was tested longitudinally during effective clozapine treatment, slow wave density normalized, while traveling distance only partially recovered. These preliminary findings suggest that slow wave traveling could be employed in larger samples to detect cortical "dys-connectivity" at psychosis onset.

Spectral exponent assessment and neurofilament light chain: a comprehensive approach to describe recovery patterns in stroke.

Introduction: Understanding the residual recovery potential in stroke patients is crucial for tailoring effective neurorehabilitation programs. We propose using EEG and plasmatic Neurofilament light chain (NfL) levels as a model to depict longitudinal patterns of stroke recovery. Methods: We enrolled 13 patients (4 female, mean age 74.7 ± 8.8) who underwent stroke in the previous month and were hospitalized for 2-months rehabilitation. Patients underwent blood withdrawal, clinical evaluation and high-definition EEG at T1 (first week of rehabilitation) and at T2 (53 ± 10 days after). We assessed the levels of NfL and we analyzed the EEG signal extracting Spectral Exponent (SE) values. We compared our variables between the two timepoint and between cortical and non-cortical strokes. Results: We found a significant difference in the symmetry of SE values between cortical and non-cortical stroke at both T1 (p = 0.005) and T2 (p = 0.01). SE in the affected hemisphere showed significantly steeper values at T1 when compared with T2 (p = 0.001). EEG measures were consistently related to clinical scores, while NfL at T1 was related to the volume of ischemic lesions (r = 0.75; p = 0.003). Additionally, the combined use of NfL and SE indicated varying trends in longitudinal clinical recovery. Conclusion: We present proof of concept of a promising approach for the characterization of different recovery patterns in stroke patients.