Clinical EEG and neuroscience最新文献

Using electroencephalography (EEG) to examine the simple mismatch negativity (MMN), a marker of auditory cortex function, has been of great interest in the exploration of biomarkers for psychotic illness. Despite many studies reporting MMN deficits in chronic schizophrenia, there are inconsistent reports of MMN reductions in the early phases of psychotic illness, suggesting the MMN elicited by traditional paradigms may not be a sensitive enough measure of vulnerability to be used as a biomarker. Recently, a more computationally complex measure of auditory cortex function (the complex mismatch negativity; cMMN) has been hypothesized to provide a more sensitive marker of illness vulnerability. The current study employed a novel dual rule paradigm, in which two pattern rules are established and violated, to examine the cMMN in 14 individuals with early phase psychosis (EPP, < 5 years illness) and 15 healthy controls (HC). Relationships between cMMN waveforms, symptom severity, and measures of functioning were explored. We found reductions of cMMN amplitudes at the site of maximal amplitude in EPP (p = .017) with large effect sizes (Hedges' g = 0.96). This study is an early step in the exploration of the cMMN as a biomarker for psychosis. Our results provide evidence that the dual rule cMMN paradigm shows promise as a method for cMMN elicitation that captures more subtle neurofunctional changes in the early stages of illness.

Auditory verbal hallucinations (AVH) are experienced by many individuals with schizophrenia (SZ), a neurodevelopmental disease that encumbers the quality of life and psychosocial outcome of those afflicted by it. While many hypotheses attempt to better define the etiology of AVHs in SZ, their neural profile and its moderation by current neuroleptics remains limited. The Mismatch Negativity (MMN) is an event related potential (ERP) measured from electroencephalographic (EEG) activity during the presentation of a deviance detection auditory paradigm. The neural regions and activity underlying the generation of the MMN include the primary auditory cortex and the prefrontal cortex which are regions also found to be activated during the experience of AVHs. Decreased MMN amplitudes have been robustly noted in SZ patients during the presentation of MMN tasks using auditory tones. However, the MMN generation to speech stimuli has not been extensively examined in SZ nor in relation to AVHs. The primary objective of this study was to examine the MMN to five speech-based deviants in SZ patients and healthy controls. Second, we assessed MMN features with AVH characteristics in 19 SZ patients and 21 HC. While AVH features did not correlate with measures of MMN, we found decreased MMN amplitudes to speech-based frequency and vowel change deviants in SZ patients compared to HC potentially reflecting deficiencies in basic speech processing mechanisms.

Mismatch negativity (MMN) event-related potential (ERP) component reduction, indexing N-methyl-D-aspartate receptor (NMDAR)-dependent auditory echoic memory and short-term plasticity, is a well-established biomarker of schizophrenia that is sensitive to psychosis risk among individuals at clinical high-risk (CHR-P). Based on the NMDAR-hypofunction model of schizophrenia, NMDAR-dependent plasticity is predicted to contribute to aberrant neurodevelopmental processes involved in the pathogenesis of schizophrenia during late adolescence or young adulthood, including gray matter loss. Moreover, stress and inflammation disrupt plasticity. Therefore, using data collected during the 8-center North American Prodrome Longitudinal Study (NAPLS-2), we explored relationships between MMN amplitudes and salivary cortisol, gray matter volumes, and inflammatory cytokines. Participants included 303 CHR-P individuals with baseline electroencephalography (EEG) data recorded during an MMN paradigm as well as structural magnetic resonance imaging (MRI) and salivary cortisol, of which a subsample (n = 57) also completed blood draws. More deficient MMN amplitudes were associated with greater salivary cortisol and pro-inflammatory cytokine levels in future CHR-Converters, but not among those who did not convert to psychosis within the next two years. More deficient MMN amplitude was also associated with smaller total gray matter volume across participants regardless of future clinical outcomes, and with subcortical gray matter volumes among future CHR-Converters only. These findings are consistent with the theory that deficient NMDAR-dependent plasticity results in an overabundance of weak synapses that are subject to over-pruning during psychosis onset, contributing to gray matter loss. Further, MMN plasticity mechanisms may interact with stress, cortisol, and neuroinflammatory processes, representing a proximal influence of psychosis.

Alterations of mismatch responses (ie, neural activity evoked by unexpected stimuli) are often considered a potential biomarker of schizophrenia. Going beyond establishing the type of observed alterations found in diagnosed patients and related cohorts, computational methods can yield valuable insights into the underlying disruptions of neural mechanisms and cognitive function. Here, we adopt a typology of model-based approaches from computational cognitive neuroscience, providing an overview of the study of mismatch responses and their alterations in schizophrenia from four complementary perspectives: (a) connectivity models, (b) decoding models, (c) neural network models, and (d) cognitive models. Connectivity models aim at inferring the effective connectivity patterns between brain regions that may underlie mismatch responses measured at the sensor level. Decoding models use multivariate spatiotemporal mismatch response patterns to infer the type of sensory violations or to classify participants based on their diagnosis. Neural network models such as deep convolutional neural networks can be used for improved classification performance as well as for a systematic study of various aspects of empirical data. Finally, cognitive models quantify mismatch responses in terms of signaling and updating perceptual predictions over time. In addition to describing the available methodology and reviewing the results of recent computational psychiatry studies, we offer suggestions for future work applying model-based techniques to advance the study of mismatch responses in schizophrenia.

Mismatch negativity (MMN) to pitch (pMMN) and to duration (dMMN) deviant stimuli is significantly more attenuated in long-term psychotic illness compared to first-episode psychosis (FEP). It was recently shown that source-modeling of magnetically recorded MMN increases the detection of left auditory cortex MMN deficits in FEP, and that computational circuit modeling of electrically recorded MMN also reveals left-hemisphere auditory cortex abnormalities. Computational modeling using dynamic causal modeling (DCM) can also be used to infer synaptic activity from EEG-based scalp recordings. We measured pMMN and dMMN with EEG from 26 FEP and 26 matched healthy controls (HCs) and used a DCM conductance-based neural mass model including α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid, N-methyl-D-Aspartate (NMDA), and Gamma-aminobutyric acid receptors to identify any changes in effective connectivity and receptor rate constants in FEP. We modeled MMN sources in bilateral A1, superior temporal gyrus, and inferior frontal gyrus (IFG). No model parameters distinguished groups for pMMN. For dMMN, reduced NMDA receptor activity in right IFG in FEP was detected. This finding is in line with literature of prefrontal NMDA receptor hypofunction in chronic schizophrenia and suggests impaired NMDA-induced synaptic plasticity may be present at psychosis onset where scalp dMMN is only moderately reduced. To the best of our knowledge, this is the first report of impaired NMDA receptor activity in FEP found through computational modeling of dMMN and shows the potential of DCM to non-invasively reveal synaptic-level abnormalities that underly subtle functional auditory processing deficits in early psychosis.

Infrequent stimulus deviations from repetitive sequences elicit mismatch negativity (MMN) even passively, making MMN practical for clinical applications. Auditory MMN is typically elicited by a change in one (or more) physical stimulus parameters (eg, pitch, duration). This lower-order simple MMN (sMMN) is impaired in long-term schizophrenia. However, sMMN contains activity from release from stimulus adaptation, clouding its face validity as purely deviance-related. More importantly, it is unreliably reduced in samples of first-episode psychosis, limiting its utility as a biomarker. Complex pattern-deviant MMN (cMMN) tasks, which elicit early and late responses, are based on higher-order abstractions and better isolate deviance detection. Their abstract nature may increase the sensitivity to processing deficits in early psychosis. However, both the early and late cMMNs are small, limiting separation between healthy and psychotic samples. In 29 healthy individuals, we tested a new dual-rule cMMN paradigm to assess additivity of deviance. Sounds alternated lateralization between left and right, and low and high pitches, creating a left-low, right-high alternating pattern. Deviants were a repeated left-low, violating lateralization and pitch patterns. Early and late cMMNs on the dual-rule task were significantly larger than those on the one-rule extra tone cMMN task (P < .05). Further, the dual-rule early cMMN was not significantly smaller than pitch or duration sMMNs (P > .48, .28, respectively). These results demonstrate additivity for cMMN pattern-violating rules. This increase in cMMN amplitude should increase group difference effect size, making it a prime candidate for a biomarker of disease presence at first psychotic episode, and perhaps even prior to the emergence of psychosis.

Objective. Perinatal hypoxia and/or hypoglycemia (PHH) is a serious condition leading to many neonatal deaths worldwide. It causes motor and cognitive deficits, visual disturbances, and seizures in survivors. There is limited information on the clinical course of seizures, EEG and MRI findings in adults. Methods. Adult patients with epilepsy due to PHH were included. Data on patients' demographic and clinical features, age at seizure onset, type and frequency of seizures, antiseizure medications and EEG features were extracted from electronic health records. Seizure outcome was classified as "seizure-free for at least one year at last follow up" versus "continuing seizures". Clinical and laboratory variables that could be associated with seizure outcome were investigated statistically in a subset of patients. Results. Forty-one patients (median age: 32 years) were included. Bilateral cerebral lesions, predominantly affecting the posterior regions, were present in 88% of the cases. Almost 80% experienced focal to bilateral tonic-clonic seizures. Approximately 60% of patients were on polytherapy. Half of the patients were seizure free at last follow-up. Seizure frequency decreased over time in 75% of the cohort. EEG demonstrated background slowing in 44% of patients, with epileptic discharges detected in 27%. The only variable correlated with seizure freedom was older age at seizure onset (P = .034). Conclusion. Almost half of the patients may reach seizure freedom. Seizure frequency decreases in 75% over time. Cranial MRI or EEG findings are not correlated with seizure outcomes. The only variable associated with seizure freedom at last follow up is older age at seizure onset.

Introduction. Vagal nerve stimulation (VNS) is a therapeutical option for the treatment of drug-resistant epileptic patients. The response to VNS varies from patient to patient and is difficult to predict. The proposed study is based on our previous work, identifying relative mean power in pre-implantation EEG as a reliable marker for VNS efficacy prediction in adult patients. Our study has two main tasks. Firstly, to confirm the utility of relative mean power as a feature correlating with VNS efficacy in children. The second is to validate the applicability of our prediction classifier, Pre-X-Stim, in the pediatric population. Material and Methods. We identified a group of children with drug-resistant epilepsy. We included only children in whom EEG contained photic stimulation (Task 1) or was recorded based on the defined acquisition protocol used for development Pre-X-Stim (Task 2). Relative mean powers were calculated. VNS responders and non-responders were compared based on relative mean powers' values. In the next step, we evaluate the utility of our classifier, Pre-X-Stim, in the children population. Results: We identified 57 children treated with VNS - 17 patients were recruited for the Task 1 and 7 patients for the Task 2. When focusing on relative mean powers in EEG spectra, we observed statistically significant differences in theta range. The Pre-X-Stim algorithm was able to predict VNS efficacy correctly in 6 out of 7 patients (the accuracy 83.3%, the sensitivity 75%, the specificity 100%). Conclusions. Based on our results, it seems that children and adults share a similar pattern of EEG relative mean power changes. These changes can be used for pre-implantation prediction of VNS efficacy.

Attention-deficit/hyperactivity disorder (ADHD) affects approximately 12% of children worldwide. With a 50% chance of persistence into adulthood and associations with impairments in various domains, including social and emotional ones, early diagnosis is crucial. The exact neural substrates of ADHD are still unclear. This study aimed to reassess the behavioral and neural metrics of executive functions and neural substrates of facial affect recognition. A total of 117 ADHD patients and 183 healthy controls were evaluated by two Go/NoGo tasks: the classic visual continuous performance test and the emotional continuous performance test, which requires facial affect encoding. Group differences between ADHD subjects and healthy controls were assessed using analysis of covariance (ANCOVA), with age and sex included as covariates. Dependent variables comprised behavioral (number of omission and commission errors, reaction time, and reaction time variability) and neurophysiological measures (event-related potentials [ERPs]). As the main result, we identified significant differences between ADHD patients and healthy controls in all behavioral metrics, one neural marker of action inhibition (P3d) and the facial processing marker (N170). The differences were moderate-to-large when expressed as effect size measures in behavioral variables and small-to-moderate for neurophysiological variables. The small-to-moderate effect sizes obtained from the neurophysiological measures suggest that ERPs are insufficient as sole markers for effectively screening emotion and face processing abnormalities in ADHD.

Recognized as a transdiagnostic factor, emotion regulation (ER) is increasingly embedded into conceptualizations of psychopathology development and maintenance, emerging as a core component of treatment methodologies. Therefore, the incorporation of ER into various facets of affective sciences, including theoretical frameworks, experimental paradigms, assessment methods, and intervention strategies, raises new challenges, particularly regarding the measurement of ER. In the evaluation and understanding of complex, multifaceted processes like ER, the combination of different assessment methods encompassing diverse units of analysis across multiple domains encompassing cerebral, physiological, and behavioral measures can prove particularly interesting. Among these approaches, the concurrent recording of electroencephalographic (EEG) and electrodermal activity (EDA) emerges as a promising strategy, enabling a more holistic exploration of the ER process at both central and peripheral levels. This brief paper aims to explore current literature concerning the utilization of EEG and EDA in the investigation of ER and to bring arguments supporting their simultaneous recording in order to gain a better understanding of ER processes.