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Background: Recently, it was reported that the extent of cortico-cortical functional connections can be estimated by the correlation coefficient based on electroencephalography (EEG) monitoring. We aimed to investigate whether the EEG correlation coefficient change with motor task activation can predict the functional outcomes of hemiparetic stroke patients. Methods: Sixteen post-stroke hemiparetic patients admitted to our rehabilitation ward were studied. On admission, EEG recording to calculate the correlation coefficient was performed at rest and during motor task activation. For the analysis of the EEG data, the program software FOCUS (NIHON KOHDEN, Japan) was used. The motor function of paretic limbs was evaluated with the Fugl–Meyer Assessment (FMA) on admission and 4 weeks after admission. Results: Significant increases in the correlation coefficient with motor task activation were noted in C3-F3 or C4-F4, C3-F7 or C4-F8, and F3-F7 or F4-F8 of the lesional hemisphere. Among them, the rate of the correlation coefficient change in F3-F7 or F4-F8 in the lesional hemisphere was significantly correlated with the rate of the upper-limb FMA score change. Conclusion: The extent of the EEG correlation coefficient change with motor task activation in F3-F7 or F4-F8 of the lesional hemisphere may help predict the motor functional outcomes of hemiparetic upper limbs after stroke. [ABSTRACT FROM AUTHOR]

Highlights: Increased postural task difficulty was associated with greater responses for pupillary response, posterior alpha power, and fronto-central theta/beta power ratio. Greater pupillary response correlated with lower posterior EEG alpha power during eyes occluded standing with and without dual-task. Lastly, a greater pupillary response was associated with lower CoP displacement in the anterior-posterior direction during dual-task eyes occluded. The pupillary response reflects mental effort (or cognitive workload) during cognitive and/or motor tasks including standing postural control. EEG has been shown to be a non-invasive measure to assess the cortical involvement of postural control. The purpose of this study was to understand the effect of increasing postural task difficulty on the pupillary response and EEG outcomes and their relationship in young adults. Fifteen adults completed multiple trials of standing: eyes open, eyes open while performing a dual-task (auditory two-back), eyes occluded, and eyes occluded with a dual-task. Participants stood on a force plate and wore an eye tracker and 256-channel EEG cap during the conditions. The power spectrum was analyzed for absolute theta (4–7 Hz), alpha (8–13 Hz), and beta (13–30 Hz) frequency bands. Increased postural task difficulty was associated with greater pupillary response (p < 0.001) and increased posterior region alpha power (p = 0.001) and fronto-central region theta/beta power ratio (p = 0.01). Greater pupillary response correlated with lower posterior EEG alpha power during eyes-occluded standing with (r = −0.67, p = 0.01) and without (r = −0.69, p = 0.01) dual-task. A greater pupillary response was associated with lower CoP displacement in the anterior–posterior direction during dual-task eyes-occluded standing (r = −0.60, p = 0.04). The pupillary response and EEG alpha power appear to capture similar cortical processes that are increasingly utilized during progressively more challenging postural task conditions. As the pupillary response also correlated with task performance, this measurement may serve as a valuable stand-alone or adjunct tool to understand the underlying neurophysiological mechanisms of postural control. [ABSTRACT FROM AUTHOR]

Value-driven attention capture (VDAC) occurs when previously rewarded stimuli capture attention and impair goal-directed behavior. In a working memory (WM) task with VDAC-related distractors, we observe behavioral variability both within and across individuals. Individuals differ in their ability to maintain relevant information and ignore distractions. These cognitive components shift over time with changes in motivation and attention, making it difficult to identify underlying neural mechanisms of individual differences. In this study, we develop the first participant-specific feedforward neural network models of reaction time from neural data during a VDAC WM task. We used short epochs of electroencephalography (EEG) data from 16 participants to develop the feedforward neural network (NN) models of RT aimed at understanding both WM and VDAC. Using general linear models (GLM), we identified 20 EEG features to predict RT across participants ( r = 0.53 ± 0.08 ). The linear model was compared to the NN model, which improved the predicted trial-by-trial RT for all participants ( r = 0.87 ± 0.04 ). We found that right frontal gamma-band activity and fronto-posterior functional connectivity in the alpha, beta, and gamma bands explain individual differences. Our study shows that NN models can link neural activity to highly variable behavior and can identify potential new targets for neuromodulation interventions. [ABSTRACT FROM AUTHOR]

This paper investigated the effect of task complexity on time estimation in the virtual reality environment (VRE) using behavioral, subjective, and physiological measurements. Virtual reality (VR) is not a perfect copy of the real world, and individuals perceive time duration differently in the VRE than they do in reality. Though many researchers have found a connection between task complexity and time estimation under non-VR conditions, the influence of task complexity on time estimation in the VRE is yet unknown. In this study, twenty-nine participants performed a VR jigsaw puzzle task at two levels of task complexity. We observed that as task complexity increased, participants showed larger time estimation errors, reduced relative beta-band power at Fz and Pz, and higher NASA-Task Load Index scores. Our findings indicate the importance of controlling task complexity in the VRE and demonstrate the potential of using electroencephalography (EEG) as real-time indicators of complexity level. [ABSTRACT FROM AUTHOR]

Theta phase-gamma amplitude coupling (TGC) plays an important role in several different cognitive processes. Although spontaneous brain activity at the resting state is crucial in preparing for cognitive performance, the functional role of resting-state TGC remains unclear. To investigate the role of resting-state TGC, electroencephalogram recordings were obtained for 56 healthy volunteers while they were in the resting state, with their eyes closed, and then when they were engaged in a retention interval period in the visual memory task. The TGCs of the two different conditions were calculated and compared. The results indicated that the modulation index of TGC during the retention interval of the visual working memory (VWM) task was not higher than that during the resting state; however, the topographical distribution of TGC during the resting state was negatively correlated with TGC during VWM task at the local level. The topographical distribution of TGC during the resting state was negatively correlated with TGC coordinates' engagement of brain areas in local and large-scale networks and during task performance at the local level. These findings support the view that TGC reflects information-processing and signal interaction across distant brain areas. These results demonstrate that TGC could explain the efficiency of competing brain networks. [ABSTRACT FROM AUTHOR]

Heart rate variability (HRV) has been suggested to reflect executive function and related neural activity. Executive dysfunction has been suggested to play an important role in the pathophysiology of emotional disorders. The purpose of this study was to investigate whether HRV showed a significant correlation with electroencephalogram (EEG) during a working memory performance in patients with depressive or anxiety disorder. A retrospective analysis was conducted with data from 61 patients with depressive disorder (43 women and 18 men) and 59 patients with anxiety disorder (35 women and 24 men). HRV was measured in the resting state, and EEG was recorded in the resting state and during the execution of a working memory task. It was performed in patients with depressive and anxiety disorder, and the paired sample t-test between resting state and task performance, as well as the partial correlation analysis between HRV and EEG, was conducted. Both depressed and anxious patients showed weaker beta relative power during the working memory task compared to the rest period. The resting-state EEG did not correlate with HRV parameters in both groups. In depressed patients, HRV showed a positive correlation with delta power during the task and a negative correlation with beta relative power during the task. In patients with anxiety disorder, HRV showed a significant positive correlation with theta power of the right frontal region during the task. Our results suggest that HRV would be related to executive-function-related neural activity in patients with depressive or anxiety disorder. Future studies with more subjects, including healthy controls, are needed to verify the correlation between HRV and EEG and to come up with a more comprehensive picture of neurobiological changes in emotional disorders. [ABSTRACT FROM AUTHOR]