One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response.

Introduction: To date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response. Methods: Resting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients. Results: Responders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization. Discussion: Our single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability. Clinical trial registration: https://clinicaltrials.gov, identifier NCT00519428.

Investigating the Effect of Contextual Cueing with Face Stimuli on Electrophysiological Measures in Younger and Older Adults.

Extracting repeated patterns from our surroundings plays a crucial role in contextualizing information, making predictions, and guiding our behavior implicitly. Previous research showed that contextual cueing enhances visual search performance in younger adults. In this study, we investigated whether contextual cueing could also improve older adults' performance and whether age-related differences in the neural processes underlying implicit contextual learning could be detected. Twenty-four younger and 25 older participants performed a visual search task with contextual cueing. Contextual information was generated using repeated face configurations alongside random new configurations. We measured RT difference between new and repeated configurations; ERPs to uncover the neural processes underlying contextual cueing for early (N2pc), intermediate (P3b), and late (r-LRP) processes; and multiscale entropy and spectral power density analyses to examine neural dynamics. Both younger and older adults showed similar contextual cueing benefits in their visual search efficiency at the behavioral level. In addition, they showed similar patterns regarding contextual information processing: Repeated face configurations evoked decreased finer timescale entropy (1-20 msec) and higher frequency band power (13-30 Hz) compared with new configurations. However, we detected age-related differences in ERPs: Younger, but not older adults, had larger N2pc and P3b components for repeated compared with new configurations. These results suggest that contextual cueing remains intact with aging. Although attention- and target-evaluation-related ERPs differed between the age groups, the neural dynamics of contextual learning were preserved with aging, as both age groups increasingly utilized more globally grouped representations for repeated face configurations during the learning process.

A dose-response characterization of transcranial magnetic stimulation intensity and evoked potential amplitude in the dorsolateral prefrontal cortex.

By combining transcranial magnetic stimulation (TMS) with electroencephalography, human cortical circuits can be directly interrogated. The resulting electrical trace contains TMS-evoked potential (TEP) components, and it is not known whether the amplitudes of these components are stimulus intensity dependent. We examined this in the left dorsolateral prefrontal cortex in nineteen healthy adult participants and extracted TEP amplitudes for the N40, P60, N120, and P200 components at 110%, 120%, and 130% of resting motor threshold (RMT). To probe plasticity of putative stimulus intensity dose-response relationships, this was repeated after participants received intermittent theta burst stimulation (iTBS; 600 pulses, 80% RMT). The amplitude of the N120 and P200 components exhibited a stimulus intensity dose-response relationship, however the N40 and P60 components did not. After iTBS, the N40 and P60 components continued to exhibit a lack of stimulus intensity dose-dependency, and the P200 dose-response was unchanged. In the N120 component, however, we saw evidence of change within the stimulus intensity dose-dependent relationship characterized by a decrease in absolute peak amplitudes at lower stimulus intensities. These data suggest that TEP components have heterogeneous dose-response relationships, with implications for standardizing and harmonizing methods across experiments. Moreover, the selective modification of the N120 dose-response relationship may provide a novel marker for iTBS plasticity in health and disease.

Functional brain network features specify DBS outcome for patients with treatment resistant depression.

Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influences large-scale network function, we hypothesized that network features can be used as biomarkers to inform outcome. In this pilot project, we used resting-state EEG recorded longitudinally from 10 TRD patients with SCG-DBS (11 at baseline). EEGs were recorded before DBS-surgery, 1-3 months, and 6 months post surgery. We used graph theoretical analysis to calculate clustering coefficient, global efficiency, eigenvector centrality, energy, and entropy of source-localized EEG networks to determine their topological/dynamical features. Patients were classified as responders based on achieving a 50% or greater reduction in Hamilton Depression (HAM-D) scores from baseline to 12 months post surgery. In the delta band, false discovery rate analysis revealed that global brain network features (segregation, integration, synchronization, and complexity) were significantly lower and centrality of subgenual anterior cingulate cortex (ACC) was higher in responders than in non-responders. Accordingly, longitudinal analysis showed SCG-DBS increased global network features and decreased centrality of subgenual ACC. Similarly, a clustering method separated two groups by network features and significant correlations were identified longitudinally between network changes and depression symptoms. Despite recent speculation that certain subtypes of TRD are more likely to respond to DBS, in the SCG it seems that underlying brain network features are associated with ability to respond to DBS. SCG-DBS increased segregation, integration, and synchronizability of brain networks, suggesting that information processing became faster and more efficient, in those patients in whom it was lower at baseline. Centrality results suggest these changes may occur via altered connectivity in specific brain regions especially ACC. We highlight potential mechanisms of therapeutic effect for SCG-DBS.

EEG complexity during mind wandering: A multiscale entropy investigation.

Our attention often drifts away from the ongoing task to task-unrelated thoughts, a phenomenon commonly referred to as mind wandering. Ample studies dedicated to delineating its electrophysiological correlates have revealed distinct event-related potentials (ERP) and spectral patterns associated with mind wandering. It remains less clear whether the complexity of the electroencephalography (EEG) changes when our minds wander, a metric that captures the predictability of the time series at varying timescales. Accordingly, this study investigated whether mind wandering impacts EEG signal complexity. We further explored whether such effects differ across timescales, and change in a context-dependent manner as indexed by global and local levels of processing. To address this, we recorded participants' EEG while they completed Navon's global and local processing task and occasionally reported whether they were on-task or mind wandering throughout the task. We found that brain signal complexity as indexed by multiscale entropy decreased at medium timescales in centro-parietal regions and increased at coarse timescales in anterior and posterior regions during mind wandering, as compared to the on-task state, for global processing. Moreover, global processing showed increased complexity at fine to medium timescales compared to local processing. Finally, behavioral performance revealed a context-dependent effect in accuracy measures, with mind wandering showing lower accuracy compared to the on-task state only during the local condition. Taken together, these results indicate that changes in brain signal complexity across timescales may be an important feature of mind wandering.

Sex differences in the relationship between age, performance, and BOLD signal variability during spatial context memory processing.

Recent work suggests that the relationship between age and memory-related brain activity are different for men and women. We sought to extend this work by examining sex differences in the association between age, memory performance, and brain signal variability during context memory tasks in neurotypical adults (aged 19-76 years; N = 128, 87 women). We measured blood oxygen level-dependent standard deviation (BOLD SD) during encoding and retrieval in easy and difficult spatial context memory tasks and investigated sex-specific, age- and performance-associated BOLD SD patterns. Behavioral analysis revealed age-related decreases in memory retrieval, but no sex differences nor an age-by-sex interaction. Imaging results indicated that both sexes showed a negative correlation between BOLD SD and retrieval accuracy in memory-related regions. We also identified significant sex differences: women exhibited age-associated increases in BOLD SD which were negatively associated with performance. Men exhibited both age-associated decreases and increases, which were not related to performance. Our results revealed sex differences in the relationship between age and BOLD SD during high-demand episodic memory tasks.

The modulatory effect of adaptive task-switching training on resting-state neural network dynamics in younger and older adults.

With increasing life expectancy and active aging, it becomes crucial to investigate methods which could compensate for generally detected cognitive aging processes. A promising candidate is adaptive cognitive training, during which task difficulty is adjusted to the participants' performance level to enhance the training and potential transfer effects. Measuring intrinsic brain activity is suitable for detecting possible distributed training-effects since resting-state dynamics are linked to the brain's functional flexibility and the effectiveness of different cognitive processes. Therefore, we investigated if adaptive task-switching training could modulate resting-state neural dynamics in younger (18-25 years) and older (60-75 years) adults (79 people altogether). We examined spectral power density on resting-state EEG data for measuring oscillatory activity, and multiscale entropy for detecting intrinsic neural complexity. Decreased coarse timescale entropy and lower frequency band power as well as increased fine timescale entropy and higher frequency band power revealed a shift from more global to local information processing with aging before training. However, cognitive training modulated these age-group differences, as coarse timescale entropy and lower frequency band power increased from pre- to post-training in the old-training group. Overall, our results suggest that cognitive training can modulate neural dynamics even when measured outside of the trained task.

Context matters: How do task demands modulate the recruitment of sensorimotor information during language processing?

Many theories of semantic representation propose that simulations of sensorimotor experience contribute to language processing. This can be seen in the body-object interaction effect (BOI; how easily the human body can interact with a word's referent). Words with high BOI ratings (e.g., ball) are processed more quickly than words with low BOI ratings (e.g., cloud) in various language tasks. This effect can be modulated by task demands. Previous research established that when asked to decide if a word is an object (entity condition), a BOI effect is observed, but when asked to decide if a word is an action (action condition), there is no BOI effect. It is unclear whether the null behavioral effect in the action condition reflects top-down modulation of task-relevant sensorimotor information or the absence of bottom-up activation of sensorimotor simulations. We investigated this question using EEG. In Experiment 1 we replicated the previous behavioral findings. In Experiment 2, 50 participants were assigned to either the entity or action conditions and responded to the same word stimuli. In both conditions we observed differences in ERP components related to the BOI effect. In the entity condition the P2 mean amplitude was significantly more positive for high compared to low BOI words. In the action condition the N400 peak latency was significantly later for high compared to low BOI words. Our findings suggest that BOI information is generated bottom-up regardless of task demands and modulated by top-down processes that recruit sensorimotor information relevant to the task decision.

Baseline Functional Connectivity in Resting State Networks Associated with Depression and Remission Status after 16 Weeks of Pharmacotherapy: A CAN-BIND Report.

Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior cingulate cortex, insula and dorsolateral prefrontal cortex) and all other brain voxels. Partial least squares was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission (MADRS ≤ 10) early (within 8 weeks), late (within 16 weeks), or not at all. We replicated previous findings of altered connectivity in patients. In addition, baseline connectivity of the anterior/posterior cingulate and insula seeds differentiated patients with different treatment outcomes. The stability of these differences was established in the largest single-site subsample. Our replication and extension of altered connectivity highlighted previously reported and new differences between patients and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration:ClinicalTrials.gov: NCT01655706.

High-resolution virtual brain modeling personalizes deep brain stimulation for treatment-resistant depression: Spatiotemporal response characteristics following stimulation of neural fiber pathways.

Over the past 15 years, deep brain stimulation (DBS) has been actively investigated as a groundbreaking therapy for patients with treatment-resistant depression (TRD); nevertheless, outcomes have varied from patient to patient, with an average response rate of ∼50%. The engagement of specific fiber tracts at the stimulation site has been hypothesized to be an important factor in determining outcomes, however, the resulting individual network effects at the whole-brain scale remain largely unknown. Here we provide a computational framework that can explore each individual's brain response characteristics elicited by selective stimulation of fiber tracts. We use a novel personalized in-silico approach, the Virtual Big Brain, which makes use of high-resolution virtual brain models at a mm-scale and explicitly reconstructs more than 100,000 fiber tracts for each individual. Each fiber tract is active and can be selectively stimulated. Simulation results demonstrate distinct stimulus-induced event-related potentials as a function of stimulation location, parametrized by the contact positions of the electrodes implanted in each patient, even though validation against empirical patient data reveals some limitations (i.e., the need for individual parameter adjustment, and differential accuracy across stimulation locations). This study provides evidence for the capacity of personalized high-resolution virtual brain models to investigate individual network effects in DBS for patients with TRD and opens up novel avenues in the personalized optimization of brain stimulation.

The longitudinal relationship between BOLD signal variability changes and white matter maturation during early childhood.

Intra-individual transient temporal fluctuations in brain signal, as measured by fMRI blood oxygenation level dependent (BOLD) variability, is increasingly considered an important signal rather than measurement noise. Evidence from computational and cognitive neuroscience suggests that signal variability is a good proxy-measure of brain functional integrity and information processing capacity. Here, we sought to explore across-participant and longitudinal relationships between BOLD variability, age, and white matter structure in early childhood. We measured standard deviation of BOLD signal, total white matter volume, global fractional anisotropy (FA) and mean diffusivity (MD) during passive movie viewing in a sample of healthy children (aged 2-8 years; N = 83). We investigated how age and white matter development related to changes in BOLD variability both across- and within-participants. Our across-participant analyses using behavioural partial least squares (bPLS) revealed that the influence of age and white matter maturation on BOLD variability was highly interrelated. BOLD variability increased in widespread frontal, temporal and parietal regions, and decreased in the hippocampus and parahippocampal gyrus with age and white matter development. Our longitudinal analyses using linear mixed effects modelling revealed significant associations between BOLD variability, age and white matter microstructure. Analyses using artificial neural networks demonstrated that BOLD variability and white matter micro and macro-structure at earlier ages were strong predictors of BOLD variability at later ages. By characterizing the across-participant and longitudinal features of the association between BOLD variability and white matter micro- and macrostructure in early childhood, our results provide a novel perspective to understand structure-function relationships in the developing brain.

Increased Neural Efficiency in Visual Word Recognition: Evidence from Alterations in Event-Related Potentials and Multiscale Entropy.

Visual word recognition is a relatively effortless process, but recent research suggests the system involved is malleable, with evidence of increases in behavioural efficiency after prolonged lexical decision task (LDT) performance. However, the extent of neural changes has yet to be characterized in this context. The neural changes that occur could be related to a shift from initially effortful performance that is supported by control-related processing, to efficient task performance that is supported by domain-specific processing. To investigate this, we replicated the British Lexicon Project, and had participants complete 16 h of LDT over several days. We recorded electroencephalography (EEG) at three intervals to track neural change during LDT performance and assessed event-related potentials and brain signal complexity. We found that response times decreased during LDT performance, and there was evidence of neural change through N170, P200, N400, and late positive component (LPC) amplitudes across the EEG sessions, which suggested a shift from control-related to domain-specific processing. We also found widespread complexity decreases alongside localized increases, suggesting that processing became more efficient with specific increases in processing flexibility. Together, these findings suggest that neural processing becomes more efficient and optimized to support prolonged LDT performance.

Tactile cortical responses and association with tactile reactivity in young children on the autism spectrum.

BACKGROUND: Unusual behavioral reactions to sensory stimuli are frequently reported in individuals on the autism spectrum (AS). Despite the early emergence of sensory features (< age 3) and their potential impact on development and quality of life, little is known about the neural mechanisms underlying sensory reactivity in early childhood autism. METHODS: Here, we used electroencephalography (EEG) to investigate tactile cortical processing in young children aged 3-6 years with autism and in neurotypical (NT) children. Scalp EEG was recorded from 33 children with autism, including those with low cognitive and/or verbal abilities, and 45 age- and sex-matched NT children during passive tactile fingertip stimulation. We compared properties of early and later somatosensory-evoked potentials (SEPs) and their adaptation with repetitive stimulation between autistic and NT children and assessed whether these neural measures are linked to "real-world" parent-reported tactile reactivity. RESULTS: As expected, we found elevated tactile reactivity in children on the autism spectrum. Our findings indicated no differences in amplitude or latency of early and mid-latency somatosensory-evoked potentials (P50, N80, P100), nor adaptation between autistic and NT children. However, latency of later processing of tactile information (N140) was shorter in young children with autism compared to NT children, suggesting faster processing speed in young autistic children. Further, correlational analyses and exploratory analyses using tactile reactivity as a grouping variable found that enhanced early neural responses were associated with greater tactile reactivity in autism. LIMITATIONS: The relatively small sample size and the inclusion of a broad range of autistic children (e.g., with low cognitive and/or verbal abilities) may have limited our power to detect subtle group differences and associations. Hence, replications are needed to verify these results. CONCLUSIONS: Our findings suggest that electrophysiological somatosensory cortex processing measures may be indices of "real-world" tactile reactivity in early childhood autism. Together, these findings advance our understanding of the neurophysiological mechanisms underlying tactile reactivity in early childhood autism and, in the clinical context, may have therapeutic implications.

Heterogeneity in abstract verbs: An ERP study.

It has been well documented that different types of nouns and action verbs are associated with behavioral and neural differences. In contrast, abstract verbs (e.g., think, dissolve) are often treated as a homogeneous category. We compared event-related potentials recorded during a syntactic classification task of four verb types; 1) abstract mental, 2) abstract emotional, 3) abstract nonbodily, and 4) concrete. Abstract nonbodily state verbs showed a sustained negativity at frontocentral electrodes and sustained positivity at parietal and occipital electrodes beginning 400 ms post-stimulus onset relative to abstract mental state and concrete verbs. Discrete source localization revealed a right inferior parietal source for all verbs and a distributed source estimation localized sources that distinguished between abstract mental state and abstract nonbodily state verbs to bilateral parietal cortex, left temporal cortex and right ventromedial prefrontal cortex. These findings suggest that different types of abstract verbs are associated with representational differences.

Revisiting mental rotation with stereoscopic disparity: A new spin for a classic paradigm.

To understand how the presence of stereoscopic disparity influences cognitive and neural processing, we recorded participants' behavior and scalp electrical activity while they performed a mental rotation task. Participants wore active shutter 3D goggles, allowing us to present stimuli with or without stereoscopic disparity on a trial-by-trial basis. Participants were more accurate and faster when stimuli were presented with stereoscopic disparity. This improvement in performance was accompanied by changes in neural activity recorded from scalp electrodes at parietal and occipital regions; stereoscopic disparity produced earlier P2 peaks, larger N2 amplitudes, and earlier, smaller P300 peak amplitudes. The presence of stereoscopic disparity also produced greater neural entropy at occipital electrode sites, and lower entropy at frontal sites. These findings suggest that the nature of the benefit afforded by stereoscopic disparity occurs at both low-level perceptual processing and higher-level cognitive processing, and results in more accurate and rapid performance.

Getting a grip on sensorimotor effects in lexical-semantic processing.

One of the strategies that researchers have used to investigate the role of sensorimotor information in lexical-semantic processing is to examine the effects of words' rated body-object interaction (BOI; i.e., the ease with which the human body can interact with a word's referent). Processing tends to be facilitated for words with high as compared with low BOI, across a wide variety of tasks. Such effects have been referenced in debates over the nature of semantic representations, but their theoretical import has been limited by the fact that BOI is a fairly coarse measure of sensorimotor experience with words' referents. In the present study, we collected ratings for 621 words on seven semantic dimensions (graspability, ease of pantomime, number of actions, animacy, size, danger, and usefulness), in order to investigate which attributes are most strongly related to BOI ratings and to lexical-semantic processing. BOI ratings were obtained from previous norming studies (Bennett, Burnett, Siakaluk, & Pexman in Behavior Research Methods, 43, 1100-1109, 2011; Tillotson, Siakaluk, & Pexman in Behavior Research Methods, 40, 1075-1078, 2008), and measures of lexical-semantic processing were obtained from previous behavioral megastudies involving either the semantic categorization task (concrete/abstract decision; Pexman, Heard, Lloyd, & Yap in Behavior Research Methods, 49, 407-417, 2017) or the lexical decision task (Balota et al., Behavior Research Methods, 39, 445-459, 2007). The results showed that the motor dimensions of graspability, ease of pantomime, and number of actions were all related to BOI, and that these dimensions together explained more variance in semantic processing than did the BOI ratings alone. These ratings will be useful for researchers who wish to study how different kinds of bodily interactions influence lexical-semantic processing and cognition.

Effects on Cognitive Functioning of Acute, Subacute and Repeated Exposures to High Altitude.

Objective: Neurocognitive functions are affected by high altitude, however the altitude effects of acclimatization and repeated exposures are unclear. We investigated the effects of acute, subacute and repeated exposure to 5,050 m on cognition among altitude-naïve participants compared to control subjects tested at low altitude. Methods: Twenty-one altitude-naïve individuals (25.3 ± 3.8 years, 13 females) were exposed to 5,050 m for 1 week (Cycle 1) and re-exposed after a week of rest at sea-level (Cycle 2). Baseline (BL, 520 m), acute (Day 1, HA1) and acclimatization (Day 6, HA6, 5,050 m) measurements were taken in both cycles. Seventeen control subjects (24.9 ± 2.6 years, 12 females) were tested over a similar period in Calgary, Canada (1,103 m). The Reaction Time (RTI), Attention Switching Task (AST), Rapid Visual Processing (RVP) and One Touch Stockings of Cambridge (OTS) tasks were administered and outcomes were expressed in milliseconds/frequencies. Lake Louise Score (LLS) and blood oxygen saturation (SpO2) were recorded. Results: In both cycles, no significant changes were found with acute exposure on the AST total score, mean latency and SD. Significant changes were found upon acclimatization solely in the altitude group, with improved AST Mean Latency [HA1 (588 ± 92) vs. HA6 (526 ± 91), p < 0.001] and Latency SD [HA1 (189 ± 86) vs. HA6 (135 ± 65), p < 0.001] compared to acute exposure, in Cycle 1. No significant differences were present in the control group. When entering Acute SpO2 (HA1-BL), Acclimatization SpO2 (HA6-BL) and LLS score as covariates for both cycles, the effects of acclimatization on AST outcomes disappeared indicating that the changes were partially explained by SpO2 and LLS. The changes in AST Mean Latency [ΔBL (-61.2 ± 70.2) vs. ΔHA6 (-28.0 ± 58), p = 0.005] and the changes in Latency SD [ΔBL (-28.4 ± 41.2) vs. ΔHA6 (-0.2235 ± 34.8), p = 0.007] across the two cycles were smaller with acclimatization. However, the percent changes did not differ between cycles. These results indicate independent effects of altitude across repeated exposures. Conclusions: Selective and sustained attention are impaired at altitude and improves with acclimatization.The observed changes are associated, in part, with AMS score and SpO2. The gains in cognition with acclimatization during a first exposure are not carried over to repeated exposures.

The relation between Scrabble expertise and brain aging as measured with EEG brain signal variability.

Recent empirical work suggests that the dynamics of brain function, as measured by brain signal variability, differs between younger and older adults. We extended this work by examining how the relationship between brain signal variability and age is altered in the context of expertise. We recorded electroencephalography from Scrabble experts and controls during a visual word recognition task. To measure variability, we used multiscale entropy, which emphasizes the way brain signals behave over a range of timescales and can differentiate the variability of a complex system (the brain) from a purely random system. We replicated previously identified shifts from long-range interactions among neural populations to more local processing in late adulthood. In addition, we demonstrated an age-related increase in midrange neural interactions for experts, suggesting greater maintenance of network integration into late adulthood. Our results indicate that expertise-related differences in the context of age and brain dynamics occur across different timescales and that these differences are linked to task performance.

Largely Typical Electrophysiological Affective Responses to Special Interest Stimuli in Adolescents with Autism Spectrum Disorder.

Circumscribed interests are a symptom of autism spectrum disorder (ASD) that may be related to exaggerated affective neural responses. However, the use of generic ASD-interest image stimuli has left an open question as to whether affective responses towards individual interests are greater in ASD compared to typically developing (TD) controls. We compared amplitudes of the late positive potential (LPP), an affective electroencephalographic response, between adolescents with ASD (N = 19) and TD adolescents (N = 20), using images tailored to individual likes and dislikes. We found an LPP response for liked and disliked images, relative to neutral, with no difference in amplitude between groups. This suggests that the LPP is not atypical in adolescents with ASD towards images of individual interests.

Pre-treatment EEG signal variability is associated with treatment success in depression.

BACKGROUND: Previous work suggests that major depressive disorder (MDD) is associated with disturbances in global connectivity among brain regions, as well as local connectivity within regions. However, the relative importance of these global versus local changes for successful antidepressant treatment is unknown. We used multiscale entropy (MSE), a measure of brain signal variability, to examine how the propensity for local (fine scale MSE) versus global (coarse scale MSE) neural processing measured prior to antidepressant treatment is related to subsequent treatment response. METHODS: We collected resting-state EEG activity during eyes-open and closed conditions from unmedicated individuals with MDD prior to antidepressant pharmacotherapy (N = 36) as well as from non-depressed controls (N = 36). Treatment response was assessed after 12 weeks of treatment using the Montgomery-Åsberg Depression Rating Scale (MADRS), at which time participants with MDD were characterized as either responders (≥ 50% MADRS decrease) or non-responders. MSE was calculated from baseline EEG, and compared between controls, future treatment responders and non-responders. Putative interactions with the well-documented age effect on signal variability (increased reliance on local neural communication with increasing age, indexed by greater finer-scale variability) were assessed. RESULTS: Only in responders, we found that reduced MSE at fine temporal scales (especially fronto-centrally) and increased MSE diffusely at coarser temporal scales was related to the magnitude of the antidepressant response. In controls and MDD non-responders, but not MDD responders, there was an increase in MSE with age at fine temporal scales and a decrease in MSE with age at coarse temporal scales. CONCLUSION: Our results suggest that an increased propensity toward global processing, indexed by greater MSE at coarser timescales, at baseline appears to facilitate eventual antidepressant treatment response.