Brain event-related potentials predict individual differences in inhibitory control.

Stop-signal reaction time (SSRT), the time needed to cancel an already-initiated motor response, quantifies individual differences in inhibitory control. Electrophysiological correlates of SSRT have primarily focused on late event-related potential (ERP) components over midline scalp regions from successfully inhibited stop trials. SSRT is robustly associated with the P300, there is mixed evidence for N200 involvement, and there is little information on the role of early ERP components. Here, machine learning was first used to interrogate ERPs during both successful and failed stop trials from 64 scalp electrodes at 4 ms resolution (n = 148). The most predictive model included data from both successful and failed stop trials, with a cross-validated Pearson's r of 0.32 between measured and predicted SSRT, significantly higher than null models. From successful stop trials, spatio-temporal features overlapping the N200 in right frontal areas and the P300 in frontocentral areas predicted SSRT, as did early ERP activity (<200 ms). As a demonstration of the reproducibility of these findings, the application of this model to a separate dataset of 97 participants was also significant (r = 0.29). These results show that ERPs during failed stops are relevant to SSRT, and that both early and late ERP activity contribute to individual differences in SSRT. Notably, the right lateralized N200, which predicted SSRT here, is not often observed in neurotypical adults. Both the ascending slope and peak of the P300 component predicted SSRT. These results were replicable, both within the training sample and when applied to ERPs from a separate dataset.

A comparison of resting state EEG and structural MRI for classifying Alzheimer's disease and mild cognitive impairment.

Alzheimer's disease (AD) is the leading cause of dementia, accounting for 70% of cases worldwide. By 2050, dementia prevalence will have tripled, with most new cases occurring in low- and middle-income countries. Mild cognitive impairment (MCI) is a stage between healthy aging and dementia, marked by cognitive deficits that do not impair daily living. People with MCI are at increased risk of dementia, with an average progression rate of 39% within 5 years. There is urgent need for low-cost, accessible and objective methods to facilitate early dementia detection. Electroencephalography (EEG) has potential to address this need due to its low cost and portability. Here, we collected resting state EEG, structural MRI (sMRI) and rich neuropsychological data from older adults (55+ years) with AD, amnestic MCI (aMCI) and healthy controls (~60 per group). We evaluated a range of candidate EEG markers (i.e., frequency band power and functional connectivity) for AD and aMCI classification and compared their performance with sMRI. We also tested a combined EEG and cognitive classification model (using Mini-Mental State Examination; MMSE). sMRI outperformed resting state EEG at classifying AD (AUCs â€‹= â€‹1.00 vs 0.76, respectively). However, both EEG and sMRI were only moderately good at distinguishing aMCI from healthy aging (AUCs â€‹= â€‹0.67-0.73), and neither method achieved sensitivity above 70%. The addition of EEG to MMSE scores had no added benefit relative to MMSE scores alone. This is the first direct comparison of EEG and sMRI for classification of AD and aMCI.

Change in PASAT performance correlates with change in P3 ERP amplitude over a 12-month period in multiple sclerosis patients.

OBJECTIVE: To examine the correlation between the change in PASAT and the change in P3 event-related potentials (ERPs) over a 12-month period in multiple sclerosis (MS) patients, and to compare the 12-month change in the P3 ERP between MS patients and controls. METHODS: Forty-four subjects (27 MS patients, 17 controls) completed visual and auditory two-stimulus oddball and three-stimulus oddball tasks at Month 0 and Month 12. Data were recorded from a 128-scalp channel electroencephalography array. Data from scalp channels were converted into continuous interpolated images (incorporating the entire scalp and time). Amplitude, topographical differences and correlations were then tested using statistical parametric mapping. RESULTS: The change in visual and auditory P3a correlated significantly with the change in PASAT score (r=0.56, p<0.001 and r=0.48, p=0.003, respectively). Visual P3b and P3a showed greater decrease in 12 months in MS patients relative to controls. Visual P3b, auditory P3b and auditory P3a amplitudes had significantly decreased in MS patients after 12-month period. CONCLUSIONS: Change in visual and auditory P3a ERP amplitudes correlate with change in PASAT scores in MS patients. Visual modality is more sensitive to changes in P3 ERP amplitudes over 12-month period. SIGNIFICANCE: P3 ERPs may have utility in monitoring the change in cognitive functioning in MS.

Preliminary evidence for correlation between PASAT performance and P3a and P3b amplitudes in progressive multiple sclerosis.

BACKGROUND: The no-go P3a event-related potential (ERP) is a measure of attentional engagement and the P3b is a measure of context updating. The aim of this study was to compare ERP topographies: (i) to Paced Auditory Serial Addition Test (PASAT) results, (ii) of visual and auditory P3a and P3b of patients with primary progressive multiple sclerosis (PPMS) versus patients with secondary-progressive multiple sclerosis (SPMS) and (iii) of both progressive subtypes to healthy controls. METHODS: Thirty subjects (10 PPMS, 10 SPMS and 10 age-matched controls) completed visual and auditory no-go P3a and P3b tasks whilst data were recorded from a 128-scalp channel electroencephalography (EEG) array. Data from scalp channels were converted into continuous interpolated images (incorporating the entire scalp and time). Topographical differences and correlations were then tested using statistical parametric mapping. RESULTS: For the patients with multiple sclerosis (MS), PASAT score correlated significantly with parietal regions in the auditory P3b, auditory P3a and visual P3b conditions, and with central regions in the visual P3a condition. Patients with PPMS had significantly lower amplitude than patients with SPMS in the auditory P3b condition over the parietal area. The control group had greater amplitude than the patients with MS in all the P3 tasks, with the exception of the auditory P3b. CONCLUSIONS: These data suggest that PASAT performance and P3 ERPs correlate for MS progressive subtypes and that PPMS and SPMS differ in electrophysiological responses during auditory P3b tasks.

A high-density ERP study reveals latency, amplitude, and topographical differences in multiple sclerosis patients versus controls.

OBJECTIVE: To quantify latency, amplitude and topographical differences in event-related potential (ERP) components between multiple sclerosis (MS) patients and controls and to compare ERP findings with results from the paced auditory serial addition test (PASAT). METHODS: Fifty-four subjects (17 relapsing remitting (RRMS) patients, 16 secondary progressive (SPMS) patients, and 21 controls) completed visual and auditory oddball tasks while data were recorded from 134 EEG channels. Latency and amplitude differences, calculated using composite mean amplitude measures, were tested using an ANOVA. Topographical differences were tested using statistical parametric mapping (SPM). RESULTS: In the visual modality, P2, P3 amplitudes and N2 latency were significantly different across groups. In the auditory modality, P2, N2, and P3 latencies and N1 amplitude were significantly different across groups. There were no significant differences between RRMS and SPMS patients on any ERP component. There were topographical differences between MS patients and controls for both early and late components for the visual modality, but only in the early components for the auditory modality. PASAT score correlated significantly with auditory P3 latency for MS patients. CONCLUSIONS: There were significant ERP differences between MS patients and controls. SIGNIFICANCE: The present study indicated that both early sensory and later cognitive ERP components are impaired in MS patients relative to controls.

Impaired information processing speed and attention allocation in multiple sclerosis patients versus controls: a high-density EEG study.

BACKGROUND: The no-go P3a is a variant of the P300 event-related potential (ERP) that indexes speed of information processing and attention allocation. The aim of this study was to compare ERP findings with results from the paced auditory serial addition test (PASAT) and to quantify latency, amplitude and topographical differences in P3a ERP components between multiple sclerosis (MS) patients and controls. PATIENTS AND METHODS: Seventy-four subjects (20 relapsing remitting (RRMS) patients, 20 secondary progressive (SPMS) patients and 34 controls) completed a three-stimulus oddball paradigm (target, standard, and non-target). Subjects participated in separate visual and auditory tasks while data were recorded from 134 EEG channels. Latency differences were tested using an ANCOVA. Topographical differences were tested using statistical parametric mapping. RESULTS: Visual P3a amplitude correlated with PASAT score in all MS patients over frontal and parietal areas. There were significant differences in latency, amplitude, and topography between MS patients and controls in the visual condition. RRMS and SPMS patients differed in visual P3a latency and amplitude at frontal and parietal scalp regions. In the auditory condition, there were latency differences between MS patients and controls only over the parietal region. CONCLUSION: The present results demonstrate that information processing speed and attention allocation are impaired in MS.