Exploring aperiodic activity in first episode schizophrenia spectrum psychosis: A resting-state EEG analysis.

Abnormalities in brain oscillatory patterns have long been observed in schizophrenia and psychotic disorders more broadly. However, far less is known about aperiodic neural activity in these disorders, which has been linked to excitation/inhibition balance and neuronal population spiking within the brain. Here, we analysed resting-state electroencephalographic (EEG) recordings from 43 first episode schizophrenia spectrum psychosis (FESSP) patients and 28 healthy controls to examine whether aperiodic activity is disrupted in FESSP. We further assessed potential associations between aperiodic activity in FESSP and clinical symptom severity using the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), and the Scale for the Assessment of Positive Symptoms (SAPS). We found no significant differences in either the 1/f-like aperiodic exponent or the broadband aperiodic offset between the FESSP and healthy control groups when analysing the global neural signal averaged across all EEG electrodes. Bayesian analyses further supported these non-significant findings. However, additional non-parametric cluster-based permutation analyses did identify reduced aperiodic offset in the FESSP group, relative to controls across broad central, temporal, parietal and select frontal regions. No associations were found between either exponent or offset and clinical symptom severity when examining all FESSP participants, irrespective of antipsychotic medication status. However, offset was shown to predict BPRS and SANS scores in medication naive patients. In sum, this research presents an initial analysis of aperiodic neural activity in FESSP, offering preliminary evidence of altered aperiodic offset in this disorder. This contributes to a broader understanding of disrupted neural dynamics in early psychosis.

Pupillometry reveals resting state alpha power correlates with individual differences in adult auditory language comprehension.

Although individual differences in adult language processing are well-documented, the neural basis of this variability remains largely unexplored. The current study addressed this gap in the literature by examining the relationship between resting state alpha activity and individual differences in auditory language comprehension. Alpha oscillations modulate cortical excitability, facilitating efficient information processing in the brain. While resting state alpha oscillations have been tied to individual differences in cognitive performance, their association with auditory language comprehension is less clear. Participants in the study were 80 healthy adults with a mean age of 25.8 years (SD = 7.2 years). Resting state alpha activity was acquired using electroencephalography while participants looked at a benign stimulus for 3 min. Participants then completed a language comprehension task that involved listening to 'syntactically simple' subject-relative clause sentences and 'syntactically complex' object-relative clause sentences. Pupillometry measured real-time processing demand changes, with larger pupil dilation indicating increased processing loads. Replicating past research, comprehending object relative clauses, compared to subject relative clauses, was associated with lower accuracy, slower reaction times, and larger pupil dilation. Resting state alpha power was found to be positively correlated with the pupillometry data. That is, participants with higher resting state alpha activity evidenced larger dilation during sentence comprehension. This effect was more pronounced for the 'complex' object sentences compared to the 'simple' subject sentences. These findings suggest the brain's capacity to generate a robust resting alpha rhythm contributes to variability in processing demands associated with auditory language comprehension, especially when faced with challenging syntactic structures. More generally, the study demonstrates that the intrinsic functional architecture of the brain likely influences individual differences in language comprehension.

Atypical alpha band microstates produced during eyes-closed resting state EEG in autism.

Electroencephalogram (EEG) microstates, which represent quasi-stable patterns of scalp topography, are a promising tool that has the temporal resolution to study atypical spatial and temporal networks in autism spectrum disorder (ASD). While current literature suggests microstates are atypical in ASD, their clinical utility, i.e., relationship with the core behavioural characteristics of ASD, is not fully understood. The aim of this study was to examine microstate parameters in ASD, and examine the relationship between these parameters and core behavioural characteristics in ASD. We compared duration, occurrence, coverage, global explained variance percentage, global field power and spatial correlation of EEG microstates between autistic and neurotypical (NT) adults. Modified k-means cluster analysis was used on eyes-closed, resting state EEG from 30 ASD (10 females, 28.97 ± 9.34 years) and 30 age-equated NT (13 females, 29.33 ± 8.88 years) adults. Five optimal microstates, A to E, were selected to best represent the data. Five microstate maps explaining 80.44% of the NT and 78.44% of the ASD data were found. The ASD group was found to have atypical parameters of microstate A, C, D, and E. Of note, all parameters of microstate C in the ASD group were found to be significantly less than NT. While parameters of microstate D, and E were also found to significantly correlate with subscales of the Ritvo Autism Asperger Diagnostic Scale - Revised (RAADS-R), these findings did not survive a Bonferroni Correction. These findings, in combination with previous findings, highlight the potential clinical utility of EEG microstates and indicate their potential value as a neurophysiologic marker that can be further studied.

Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction.

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators' brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.

Inhibitory dysfunction and social processing difficulties in autism: A comprehensive narrative review.

The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) has a prominent role in regulating neural development and function, with disruption to GABAergic signalling linked to behavioural phenotypes associated with neurodevelopmental disorders, particularly autism. Such neurochemical disruption, likely resulting from diverse genetic and molecular mechanisms, particularly during early development, can subsequently affect the cellular balance of excitation and inhibition in neuronal circuits, which may account for the social processing difficulties observed in autism and related conditions. This comprehensive narrative review integrates diverse streams of research from several disciplines, including molecular neurobiology, genetics, epigenetics, and systems neuroscience. In so doing it aims to elucidate the relevance of inhibitory dysfunction to autism, with specific focus on social processing difficulties that represent a core feature of this disorder. Many of the social processing difficulties experienced in autism have been linked to higher levels of the excitatory neurotransmitter glutamate and/or lower levels of inhibitory GABA. While current therapeutic options for social difficulties in autism are largely limited to behavioural interventions, this review highlights the psychopharmacological studies that explore the utility of GABA modulation in alleviating such difficulties.

Magnetic seizure therapy and electroconvulsive therapy increase aperiodic activity.

Major depressive disorder (MDD) is a leading cause of disability worldwide. One of the most efficacious treatments for treatment-resistant MDD is electroconvulsive therapy (ECT). Recently, magnetic seizure therapy (MST) was developed as an alternative to ECT due to its more favorable side effect profile. While these approaches have been very successful clinically, the neural mechanisms underlying their therapeutic effects are unknown. For example, clinical "slowing" of the electroencephalogram beginning in the postictal state and extending days to weeks post-treatment has been observed in both treatment modalities. However, a recent longitudinal study of a small cohort of ECT patients revealed that, rather than delta oscillations, clinical slowing was better explained by increases in aperiodic activity, an emerging EEG signal linked to neural inhibition. Here we investigate the role of aperiodic activity in a cohort of patients who received ECT and a cohort of patients who received MST treatment. We find that aperiodic neural activity increases significantly in patients receiving either ECT or MST. Although not directly related to clinical efficacy in this dataset, increased aperiodic activity is linked to greater amounts of neural inhibition, which is suggestive of a potential shared neural mechanism of action across ECT and MST.

The effects of anodal tDCS on pain reduction in people with knee osteoarthritis: A systematic review and meta-analysis.

OBJECTIVES: To synthesise the literature on the efficacy of primary motor cortex anodal transcranial direct current stimulation (M1-a-tDCS), as a standalone or priming technique, for pain reduction in people with knee osteoarthritis (KOA). METHODS: The systematic literature search was conducted in MEDLINE, CINAHL, Embase and CENTRAL according to PRISMA statement. RESULTS: Fourteen studies involving 740 people with KOA were included. In the meta-analysis, six studies compared a-tDCS alone with sham stimulation, and five studies compared a-tDCS combined with other methods with sham stimulation. We found positive effect of a-tDCS alone on pain in KOA (standard mean difference (SMD) -0.52; 95% CI, -0.78 to -0.25; P=0.001; I2 = 69%). Further, a-tDCS with other treatments showed positive effect (SMD -1.23; 95% CI, -1.59 to -0.88; P<0.001; I2 = 48%) on pain in people with KOA. This evidence showed low certainty due to a high risk of bias and imprecision. DISCUSSION AND CONCLUSION: A-tDCS could be considered as standalone and an adjunct treatment for pain reduction in people with KOA. Future randomised studies should address quality issues, including small sample size, to enhance the overall certainty of the findings. SIGNIFICANCE: A-tDCS can be used as a standalone and adjunct treatment for KOA. STUDY REGISTRATION: PROSPERO number CRD42021255114.

EEG microstates in early-to-middle childhood show associations with age, biological sex, and alpha power.

Electroencephalographic (EEG) microstates can provide a unique window into the temporal dynamics of large-scale brain networks across brief (millisecond) timescales. Here, we analysed fundamental temporal features of microstates extracted from the broadband EEG signal in a large (N = 139) cohort of children spanning early-to-middle childhood (4-12 years of age). Linear regression models were used to examine if participants' age and biological sex could predict the temporal parameters GEV, duration, coverage, and occurrence, for five microstate classes (A-E) across both eyes-closed and eyes-open resting-state recordings. We further explored associations between these microstate parameters and posterior alpha power after removal of the 1/f-like aperiodic signal. The microstates obtained from our neurodevelopmental EEG recordings broadly replicated the four canonical microstate classes (A to D) frequently reported in adults, with the addition of the more recently established microstate class E. Biological sex served as a significant predictor in the regression models for four of the five microstate classes (A, C, D, and E). In addition, duration and occurrence for microstate E were both found to be positively associated with age for the eyes-open recordings, while the temporal parameters of microstates C and E both exhibited associations with alpha band spectral power. Together, these findings highlight the influence of age and sex on large-scale functional brain networks during early-to-middle childhood, extending understanding of neural dynamics across this important period for brain development.

Neurophysiological correlates of non-motor symptoms in late premanifest and early-stage manifest huntington's disease.

OBJECTIVE: To find sensitive neurophysiological correlates of non-motor symptoms in Huntington's disease (HD), which are essential for the development and assessment of novel treatments. METHODS: We used resting state EEG to examine differences in oscillatory activity (analysing the isolated periodic as well as the complete EEG signal) and functional connectivity in 22 late premanifest and early stage people with HD and 20 neurotypical controls. We then assessed the correlations between these neurophysiological markers and clinical measures of apathy and processing speed. RESULTS: Significantly lower theta and greater delta resting state power was seen in the HD group, as well as significantly greater delta connectivity. There was a significant positive correlation between theta power and processing speed, however there were no associations between the neurophysiological and apathy measures. CONCLUSIONS: We speculate that these changes in oscillatory power and connectivity reflect ongoing, frontally concentrated degenerative and compensatory processes associated with HD. SIGNIFICANCE: Our findings support the potential utility of quantitative EEG as a proximate marker of processing speed, but not apathy in HD.

Resting state electroencephalography power correlates with individual differences in implicit sequence learning.

Neuroimaging resting state paradigms have revealed synchronised oscillatory activity is present even in the absence of completing a task or mental operation. One function of this neural activity is likely to optimise the brain's sensitivity to forthcoming information that, in turn, likely promotes subsequent learning and memory outcomes. The current study investigated whether this extends to implicit forms of learning. A total of 85 healthy adults participated in the study. Resting state electroencephalography was first acquired from participants before they completed a serial reaction time task. On this task, participants implicitly learnt a visuospatial-motor sequence. Permutation testing revealed a negative correlation between implicit sequence learning and resting state power in the upper theta band (6-7 Hz). That is, lower levels of resting state power in this frequency range were associated with superior levels of implicit sequence learning. This association was observed at midline-frontal, right-frontal and left-posterior electrodes. Oscillatory activity in the upper theta band supports a range of top-down processes including attention, inhibitory control and working memory, perhaps just for visuospatial information. Our results may be indicating that disengaging theta-supported top-down attentional processes improves implicit learning of visuospatial-motor information that is embedded in sensory input. This may occur because the brain's sensitivity to this type of information is optimally achieved when learning is driven by bottom-up processes. Moreover, the results of this study further demonstrate that resting state synchronised brain activity influences subsequent learning and memory.

Isolating sensory artifacts in the suprathreshold TMS-EEG signal over DLPFC.

Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is an effective way to evaluate neurophysiological processes at the level of the cortex. To further characterize the TMS-evoked potential (TEP) generated with TMS-EEG, beyond the motor cortex, we aimed to distinguish between cortical reactivity to TMS versus non-specific somatosensory and auditory co-activations using both single-pulse and paired-pulse protocols at suprathreshold stimulation intensities over the left dorsolateral prefrontal cortex (DLPFC). Fifteen right-handed healthy participants received six blocks of stimulation including single and paired TMS delivered as active-masked (i.e., TMS-EEG with auditory masking and foam spacing), active-unmasked (TMS-EEG without auditory masking and foam spacing) and sham (sham TMS coil). We evaluated cortical excitability following single-pulse TMS, and cortical inhibition following a paired-pulse paradigm (long-interval cortical inhibition (LICI)). Repeated measure ANOVAs revealed significant differences in mean cortical evoked activity (CEA) of active-masked, active-unmasked, and sham conditions for both the single-pulse (F(1.76, 24.63) = 21.88, p < 0.001, η2 = 0.61) and LICI (F(1.68, 23.49) = 10.09, p < 0.001, η2 = 0.42) protocols. Furthermore, global mean field amplitude (GMFA) differed significantly across the three conditions for both single-pulse (F(1.85, 25.89) = 24.68, p < 0.001, η2 = 0.64) and LICI (F(1.8, 25.16) = 14.29, p < 0.001, η2 = 0.5). Finally, only active LICI protocols but not sham stimulation ([active-masked (0.78 ± 0.16, P < 0.0001)], [active-unmasked (0.83 ± 0.25, P < 0.01)]) resulted in significant signal inhibition. While previous findings of a significant somatosensory and auditory contribution to the evoked EEG signal are replicated by our study, an artifact attenuated cortical reactivity can reliably be measured in the TMS-EEG signal with suprathreshold stimulation of DLPFC. Artifact attenuation can be accomplished using standard procedures, and even when masked, the level of cortical reactivity is still far above what is produced by sham stimulation. Our study illustrates that TMS-EEG of DLPFC remains a valid investigational tool.

Medial prefrontal transcranial alternating current stimulation for apathy in Huntington's disease.

We investigated the effects of transcranial alternating current stimulation (tACS) targeted to the bilateral medial prefrontal cortex (mPFC) and administered at either delta or alpha frequencies, on brain activity and apathy in people with Huntington's disease (HD) (n = 17). Given the novelty of the protocol, neurotypical controls (n = 20) were also recruited. All participants underwent three 20-min sessions of tACS; one session at alpha frequency (Individualised Alpha Frequency (IAF), or 10 Hz when an IAF was not detected); one session at delta frequency (2 Hz); and a session of sham tACS. Participants completed the Monetary Incentive Delay (MID) task with simultaneous recording of EEG immediately before and after each tACS condition. The MID task presents participants with cues signalling potential monetary gains or losses that increase activity in key regions of the cortico-basal ganglia-thalamocortical networks, with dysfunction of the latter network being implicated in the pathophysiology of apathy. We used the P300 and Contingent Negative Variation (CNV) event-related potentials elicited during the MID task as markers of mPFC engagement. HD participants' CNV amplitude significantly increased in response to alpha-tACS, but not delta-tACS or sham. Neurotypical controls' P300 and CNV were not modulated by any of the tACS conditions, but they did demonstrate a significant decrease in post-target response times following alpha-tACS. We present this as preliminary evidence of the ability of alpha-tACS to modulate brain activity associated with apathy in HD.

Effects of medial prefrontal transcranial alternating current stimulation on neural activity and connectivity in people with Huntington's disease and neurotypical controls.

We investigated the effects of transcranial alternating current stimulation (tACS) targeted to the medial prefrontal cortex (mPFC) on resting electroencephalographic (EEG) indices of oscillatory power, aperiodic exponent and offset, and functional connectivity in 22 late premanifest and early manifest stage individuals with HD and 20 neurotypical controls. Participants underwent three 20-minute sessions of tACS at least 72 hours apart; one session at alpha frequency (either each participant's Individualised Alpha Frequency (IAF), or 10 Hz when an IAF was not detected); one session at delta frequency (2 Hz); and a session of sham tACS. Session order was randomised and counterbalanced across participants. EEG recordings revealed a reduction of the spectral exponent ('flattening' of the 1/f slope) of the eyes-open aperiodic signal in participants with HD following alpha-tACS, suggestive of an enhancement in excitatory tone. Contrary to expectation, there were no changes in oscillatory power or functional connectivity in response to any of the tACS conditions in the participants with HD. By contrast, alpha-tACS increased delta power in neurotypical controls, who further demonstrated significant increases in theta power and theta functional connectivity in response to delta-tACS. This study contributes to the rapidly growing literature on the potential experimental and therapeutic applications of tACS by examining neurophysiological outcome measures in people with HD as well as neurotypical controls.

Pre-Stimulus Power but Not Phase Predicts Prefrontal Cortical Excitability in TMS-EEG.

The cortical response to transcranial magnetic stimulation (TMS) has notable inter-trial variability. One source of this variability can be the influence of the phase and power of pre-stimulus neuronal oscillations on single-trial TMS responses. Here, we investigate the effect of brain oscillatory activity on TMS response in 49 distinct healthy participants (64 datasets) who had received single-pulse TMS over the left dorsolateral prefrontal cortex. Across all frequency bands of theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz), there was no significant effect of pre-TMS phase on single-trial cortical evoked activity. After high-powered oscillations, whether followed by a TMS pulse or not, the subsequent activity was larger than after low-powered oscillations. We further defined a measure, corrected_effect, to enable us to investigate brain responses to the TMS pulse disentangled from the power of ongoing (spontaneous) oscillations. The corrected_effect was significantly different from zero (meaningful added effect of TMS) only in theta and beta bands. Our results suggest that brain state prior to stimulation might play some role in shaping the subsequent TMS-EEG response. Specifically, our findings indicate that the power of ongoing oscillatory activity, but not phase, can influence brain responses to TMS. Aligning the TMS pulse with specific power thresholds of an EEG signal might therefore reduce variability in neurophysiological measurements and also has the potential to facilitate more robust therapeutic effects of stimulation.

Magnetic seizure therapy and electroconvulsive therapy increase aperiodic activity.

Major depressive disorder (MDD) is a leading cause of disability worldwide. One of the most efficacious treatments for treatment-resistant MDD is electroconvulsive therapy (ECT). Recently, magnetic seizure therapy (MST) was developed as an alternative to ECT due to its more favorable side effect profile. While these approaches have been very successful clinically, the neural mechanisms underlying their therapeutic effects are unknown. For example, clinical "slowing" of the electroencephalogram beginning in the postictal state and extending days to weeks post-treatment has been observed in both treatment modalities. However, a recent longitudinal study of a small cohort of ECT patients revealed that, rather than delta oscillations, clinical slowing was better explained by increases in aperiodic activity, an emerging EEG signal linked to neural inhibition. Here we investigate the role of aperiodic activity in a cohort of patients who received ECT and a cohort of patients who received MST treatment. We find that aperiodic neural activity increases significantly in patients receiving either ECT or MST. Although not directly related to clinical efficacy in this dataset, increased aperiodic activity is linked to greater amounts of neural inhibition, which is suggestive of a potential shared neural mechanism of action across ECT and MST.

Neural basis of implicit motor sequence learning: Modulation of cortical power.

Implicit sequence learning describes the acquisition of serially ordered movements and sequentially structured cognitive information, that occurs without awareness. Theta, alpha and beta cortical oscillations are present during implicit motor sequence learning, but their role in this process is unclear. The current study addressed this gap in the literature. A total of 50 healthy adults aged between 19 and 37 years participated in the study. Implicit motor sequence learning was examined using the Serial Reaction Time task where participants unknowingly repeat a sequence of finger movements in response to a visual stimulus. Sequence learning was examined by comparing reaction times and oscillatory power between sequence trials and a set of control trials comprising random stimulus presentations. Electroencephalography was recorded as participants completed the task. Analyses of the behavioral data revealed participants learnt the sequence. Analyses of oscillatory activity, using permutation testing, revealed sequence learning was associated with a decrease in theta band (4-7 Hz) power recorded over frontal and central electrode sites. Sequence learning effects were not observed in the alpha (7-12 Hz) or beta bands (12-20 Hz). Even though alpha and beta power modulations have long been associated with executing a motor response, it seems theta power is a correlate of sequence learning in the manual domain. Theta power modulations on the serial reaction time task may reflect disengagement of attentional resources, either promoting or occurring as a consequence of implicit motor sequence learning.

Functional brain connectivity during exposure to the scale and color of interior built environments.

Understanding brain activity linked to built environment exposure is important, as it may affect underlying cognitive, perceptual, and emotional processes, which have a critical influence in our daily life. As our time spent inside buildings is rising, and mental health problems have become more prevalent, it is important we investigate how design characteristics of the built environment impact brain function. In this study, we utilized electroencephalography to understand whether the design elements of scale and color of interior built environments modulate functional brain connectivity (i.e., brain network communication). Using a Cave Automatic Virtual Environment, while controlling indoor environmental quality responsible for physiological comfort, healthy adult participants aged 18-55 years (66 for scale, subset of 18 for color), were exposed to context-neutral indoor room scenes presented for two-minutes each. Our results show that both enlarging and reducing scale enhanced theta connectivity across the left temporoparietal region and right frontal region. We also found when reducing the built environment scale, there was a network exhibiting greater high-gamma connectivity, over the right frontoparietal region. For color, the condition (blue) contrasted to our achromatic control (white) increased theta connectivity in the frontal hemispheres. These findings identify a link between theta and gamma oscillations during exposure to the scale and color of the built environment, showing that design characteristics of the built environment could affect our cognitive processes and mental health. This suggests that, through the design of buildings, we may be able to mediate performance and health outcomes, which could lead to major health and economic benefits for society.

Right anterior theta connectivity predicts autistic social traits in typically developing children.

Growing evidence supports functional network alterations in autism spectrum disorder, however much less is known about the neural mechanisms underlying autistic traits in typically developing children. Using resting-state electroencephalographic (EEG) recordings, we examined whether functional connectivity could predict autistic trait expression in 127 children aged between 4 and 12 years. Regression models showed that right anterior theta connectivity was a significant predictor of autistic traits (p = 0.013), with increased connectivity in this region associated with greater autistic trait expression. These results corroborate similar recent findings in adults, extending this observation to a cohort of children spanning early-to-middle childhood. These findings further highlight EEG-derived functional connectivity as a sensitive physiological correlate of autistic trait expression in typically developing children.

Motivationally salient cue processing measured using the monetary incentive delay (MID) task with electroencephalography (EEG): A potential marker of apathy in Huntington's disease.

We explored the utility of the Monetary Incentive Delay (MID) task with concurrent encephalography (EEG) as a marker of apathy in people with Huntington's disease (HD) as well as neurotypical controls. Specifically, we assessed between and within-group differences in the amplitude of the P300 and Contingent Negative Variation (CNV) event-related potentials as a function of motivational salience. In contrast to neurotypical controls, HD participants' ERP amplitudes were not differentially modulated by motivationally salient cues (i.e., signalling potential 'gain' or 'loss') compared to 'neutral' cues. Difference waves isolating amplitude specific to the motivationally salient cues were calculated for the P300 and CNV. Only the difference waves for ERPs elicited by 'gain' cues differentiated the groups. The CNV difference wave was also significantly correlated with clinical measures of apathy and processing speed in the HD group. These findings provide initial support for the use of the MID with EEG as a marker of apathy in HD, and its potential as a sensitive outcome measure for novel treatment development.