Inhibitory-control event-related potentials correlate with individual differences in alcohol use

The relationship between neural processing efficiency during inter-hemispheric transfer, alcohol consumption, and sleep quality in college students: an ERP study

Objective: To examine relationships between sleep, alcohol consumption, and a physiological and behavioral marker of cognitive function in college students. College students are in a high risk category for high alcohol consumption and poor sleep quality, two unhealthful behaviors which can lead to poor mental health outcomes and compromised academic performance. Participants: Thirty college students from a large midwestern institution. Methods: Participants performed an interhemispheric transfer task while their electroencephalography was recorded for later examination of event-related potentials. They were also administered the Pittsburgh Sleep Quality Index, the Alcohol Use Disorders Identification Test, and the Alcohol Timeline Follow-Back. Results: Results demonstrate that increased alcohol consumption is associated with poor right-to-left interhemispheric transfer performance, and increased frontal P1 ERP amplitudes to neuro-ipsilateral targets requiring an interhemispheric-transfer. Conclusions: These findings assist in furthering explorations into the impacts of unhealthy behaviors in college students and underlying markers of simple cognitive and behavioral function.

A Multimodal Neuroprosthetic Interface to Record, Modulate and Classify Electrophysiological Biomarkers Relevant to Neuropsychiatric Disorders

Most mental disorders, such as addictive diseases or schizophrenia, are characterized by impaired cognitive function and behavior control originating from disturbances within prefrontal neural networks. Their often chronic reoccurring nature and the lack of efficient therapies necessitate the development of new treatment strategies. Brain-computer interfaces, equipped with multiple sensing and stimulation abilities, offer a new toolbox whose suitability for diagnosis and therapy of mental disorders has not yet been explored. This study, therefore, aimed to develop a biocompatible and multimodal neuroprosthesis to measure and modulate prefrontal neurophysiological features of neuropsychiatric symptoms. We used a 3D-printing technology to rapidly prototype customized bioelectronic implants through robot-controlled deposition of soft silicones and a conductive platinum ink. We implanted the device epidurally above the medial prefrontal cortex of rats and obtained auditory event-related brain potentials in treatment-naïve animals, after alcohol administration and following neuromodulation through implant-driven electrical brain stimulation and cortical delivery of the anti-relapse medication naltrexone. Towards smart neuroprosthetic interfaces, we furthermore developed machine learning algorithms to autonomously classify treatment effects within the neural recordings. The neuroprosthesis successfully captured neural activity patterns reflecting intact stimulus processing and alcohol-induced neural depression. Moreover, implant-driven electrical and pharmacological stimulation enabled successful enhancement of neural activity. A machine learning approach based on stepwise linear discriminant analysis was able to deal with sparsity in the data and distinguished treatments with high accuracy. Our work demonstrates the feasibility of multimodal bioelectronic systems to monitor, modulate and identify healthy and affected brain states with potential use in a personalized and optimized therapy of neuropsychiatric disorders.

"My Brain Can Stop": An ERP Study of Longitudinal Prediction of Inhibitory Control in Adolescence

We examined the longitudinal predictors of electrophysiological and behavioral markers of inhibitory control in adolescence. Participants were 63 adolescent boys who have been followed since birth as part of a prospective longitudinal study on the developmental pathways to attention-deficit hyperactivity disorder (ADHD). At 17 years of age, they completed the stop-signal task (SST) while electroencephalography (EEG) was continuously recorded. Inhibitory control was evaluated by the stop-signal reaction time (SSRT) as well as by the amplitude of the event-related potential (ERP) component of N2 during successful inhibition. We found that higher inattention symptoms throughout childhood predicted reduced amplitude (i.e., less negative) of the N2 in adolescence. Furthermore, the N2 amplitude was longitudinally predicted by the early precursors of child familial risk for ADHD and early childhood temperament. Specifically, father's inattention symptoms (measured in the child's early infancy) and child's effortful control at 36 months of age directly predicted the N2 amplitude in adolescence, even beyond the consistency of inattention symptoms throughout development. The SSRT was predicted by ADHD symptoms throughout childhood but not by the early precursors. Our findings emphasize the relevance of early familial and temperamental risk for ADHD to the prediction of a later dysfunction in inhibitory control.

Persistence of Neuronal Alterations in Alcohol-Dependent Patients at Conclusion of the Gold Standard Withdrawal Treatment: Evidence From ERPs

Background: One of the main challenges for clinicians is to ensure that alcohol withdrawal treatment is the most effective possible after discharge. To address this issue, we designed a pilot study to investigate the efficacy of the rehabilitation treatment on the main stages of information processing, using an electroencephalographic method. This topic is of main importance as relapse rates after alcohol withdrawal treatment remain very high, indicating that established treatment methods are not fully effective in all patients in the long run. Method: We examined in alcohol-dependent patients (ADP) the effects of the benzodiazepine-based standard detoxification program on event-related potential components at incoming (D0) and completion (D15) of the treatment, using tasks of increasing difficulty (with and without workload) during an auditory oddball target paradigm. Untreated non-alcohol-dependent-volunteers were used as matching controls. Results: At D0, ADP displayed significantly lower amplitude for all ERP components in both tasks, as compared to controls. At D15, this difference disappeared for the amplitude of the N1 component during the workload-free task, as well as the amplitude of the P3b for both tasks. Meanwhile, the amplitude of the N2 remained lower in both tasks for ADP. At D0, latencies of N2 and P3b in both task conditions were longer in ADP, as compared to controls, whilst the latency of N1 was unchanged. At D15, the N2 latency remained longer for the workload condition only, whereas the P3b latency remained longer for the workload-free task only. Conclusion: The present pilot results provide evidence for a persistence of impaired parameters of ERP components, especially the N2 component. This suggests that neural networks related to attention processing remain dysfunctional. Longitudinal long-term follow-up of these patients is mandatory for further assessment of a link between ERP alterations and a later risk of relapse.

Aberrant reward prediction errors in young adult at-risk alcohol users

Previous studies suggest that individuals with substance use disorder have abnormally large responses to unexpected outcomes (reward prediction errors [RPEs]). However, there is much less information on RPE in individuals at risk of alcohol misuse, prior to neurobiological adaptations that might result from sustained alcohol use. Here, participants (mean age 23.77 years, range 18-32 years) performed the electrophysiological monetary incentive delay task. This task involved responding to a target stimulus following reward incentive cues to win, or avoid losing, the cued reward while brain activity was recorded under 64-channel EEG. The Alcohol Use Disorders Identification Test (AUDIT) was used to quantify at-risk alcohol use, with high (n = 22, mean AUDIT score: 13.82) and low (n = 22, mean AUDIT score: 5.77) alcohol use groups. Trial-by-trial RPEs were estimated using a Rescorla-Wagner reinforcement model based on behavioral data. A single-trial analysis revealed that the feedback-related negativity (FRN) and feedback P3 (fb-P3) event-related potential components were significantly modulated by RPEs. There was increased RPE-related fb-P3 amplitude for those in the high alcohol use group. Next, the mean amplitude of ERPs elicited by positive and negative RPEs were compared between groups. We found that high alcohol use participants had attenuated FRN amplitude in contrast with low alcohol use participants for both positive and negative RPEs but enhanced fb-P3 for both positive and negative RPE. These results, with differences in RPE in an at-risk group, suggest that RPE a potential vulnerability marker for alcohol use disorder.

Functional EEG connectivity is a neuromarker for adult attention deficit hyperactivity disorder symptoms

OBJECTIVE

Altered brain functional connectivity has been shown in youth with attention-deficit/hyperactivity disorder (ADHD). However, relatively little is known about functional connectivity in adult ADHD, and how it is linked with the heritability of ADHD.

METHODS

We measured eyes-open and eyes-closed resting electroencephalography (EEG) from 38 adults with ADHD, 45 1st degree relatives of people with ADHD and 51 healthy controls. Functional connectivity among all scalp channels was calculated using a weighted phase lag index for delta, theta, alpha, beta and gamma frequency bands. A machine learning analysis using penalized linear regression was used to identify if connectivity features (10,080 connectivity pairs) could predict ADHD symptoms. Furthermore, we examined if EEG connectivity could accurately classify participants into ADHD, 1st degree relatives and/or control groups.

RESULTS

Hyperactive symptoms were best predicted by eyes-open EEG connectivity in delta, beta and gamma bands. Inattentive symptoms were predicted by eyes-open EEG connectivity in delta, alpha and gamma bands, and eyes-closed EEG connectivity in delta and gamma bands. EEG connectivity features did not reliably classify participants into groups.

CONCLUSIONS

EEG connectivity may represent a neuromarker for ADHD symptoms.

SIGNIFICANCE

EEG connectivity may help elucidate the neural basis of adult ADHD symptoms.