Neuromodulation in Beta-Band Power Between Movement Execution and Inhibition in the Human Hippocampus

Campo-Vera, Roberto Martin Del; Tang, Austin M.; Gogia, Angad S.; Chen, Kuang Hsuan; Sebastian, Rinu; Gilbert, Zachary; Nune, George; Liu, Charles Y.; Kellis, Spencer; Lee, Brian

doi:10.1111/ner.13486

Cited by 5 publications

(7 citation statements)

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“…Next, a target appears along with a cue, which indicates whether the participant should reach towards the target and tap it ('Go' condition) or withhold from moving their arm ('No Go' condition). We demonstrated that hippocampal beta power increases from baseline during movement inhibition ('No Go' condition), where baseline refers to beta power during the fixation phase of the GNG task [20]. Along with similar trends seen in other brain areas such as the STN [21,22], and cortex [17,18], these findings indicate that the beta band reflects a baseline inhibitory signal that decreases during movement and increases during inhibition.…”

Section: Introductionsupporting

confidence: 73%

“…Exclusion criteria are in accordance with a previous study from our group [20]. Phase lengths were varied to prevent participants from becoming accustomed to the movement task and avoid timed responses.…”

Section: Experimental Tasksmentioning

confidence: 99%

“…Beta activity during the response phase of a GNG task signifies reactive motor inhibition (in response to the GNG cue) [19,20]. On the other hand, beta activity before the response phase of a GNG task (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Baseline hippocampal beta band power is lower in the presence of movement uncertainty

et al. 2022

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Objective This study aimed to characterize hippocampal neural signatures of uncertainty by measuring beta band power in the period prior to movement cue. Approach Participants with epilepsy were implanted with hippocampal depth electrodes for stereo electroencephalographic (SEEG) monitoring. Hippocampal beta (13-30 Hz) power changes have been observed during motor tasks such as the direct reach (DR) and Go/No-Go (GNG) tasks. The primary difference between the tasks is the presence of uncertainty about whether movement should be executed. Previous research on cortical responses to uncertainty has found that baseline beta power changes with uncertainty. SEEG data were sampled throughout phases of the DR and GNG tasks. Beta-band power during the fixation phase was compared between the DR and GNG task using a Wilcoxon rank sum test. This unpaired test was also used to analyze response times from cue to task completion between tasks. Main Results Eight patients who performed both reaching tasks were analyzed in this study. Movement response times in the GNG task were on average 210 milliseconds slower than in the DR task. All patients exhibited a significantly increased response latency in the GNG task compared to the DR task (Wilcoxon rank-sum p-value < 0.001). Six out of eight patients demonstrated statistically significant differences in beta power in single hippocampal contacts between the fixation phases of the GNG and DR tasks. At the group level, baseline beta power was significantly lower in the GNG task than in the DR task (Wilcoxon rank-sum p-value < 0.001). Significance This novel study found that, in the presence of task uncertainty, baseline beta power in the hippocampus is lower than in its absence. This finding implicates movement uncertainty as an important factor in baseline hippocampal beta power during movement preparation.

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Section: Introductionsupporting

confidence: 73%

Section: Experimental Tasksmentioning

confidence: 99%

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Baseline hippocampal beta band power is lower in the presence of movement uncertainty

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“…DG is the only main brain region of the neurogenesis in the hippocampal subregion [ 45 ] and inhibiting the hippocampal neurogenesis is one of the prominent manifestations of chronic hypertension [ 46 ]. Studies showed that the hippocampus is activated during the conflict processing resolution [ 47 ] and hippocampal beta power increases in Go/No go task [ 48 ]. SCD is an early stage in the processing of AD.…”

Section: Discussionmentioning

confidence: 99%

Hypertension Status Moderated the Relationship between the Hippocampal Subregion of the Left GC-ML-DG and Cognitive Performance in Subjective Cognitive Decline

et al. 2022

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Background. To investigate the relationship between hypertension status, hippocampus/hippocampal subregion structural alteration, and cognitive performance in subjective cognitive decline (SCD). Methods. All participants were divided into two groups according to blood pressure status: SCD without hypertension and SCD with hypertension. The cognitive assessments and T1-MPRAGE brain MRI were performed to measure the cognitive function and the volume of the hippocampus and hippocampal subregions. Association and mediating/moderating effects were analyzed between the volume of hippocampus/hippocampal subregions and cognitive scores. Results. Compared to the SCD without hypertension, we found (1) increased reaction time (RT) of the Go/No go test, compatible test, and divided attention visual task and (2) decreased volume of the left whole hippocampal/left subiculum/left CA1/left presubiculum/left parasubiculum/left molecular layer HP/left GC-ML-DG/left HATA in SCD with hypertension. There was a significant negative association between the volume of the left GC-ML-DG and Go/No go test RT in SCD without hypertension. A significant moderating effect of hypertension status on the relationship between the volume of the left GC-ML-DG and Go/No go test RT was found. Conclusion. The results suggested that hypertension status affects inhibitory control function and visual divided attention which may be related to the reduction of hippocampus/hippocampal subregion volume in SCD. Limitations. The study has several limitations. First, this study does not include a healthy control group. In further studies, healthy controls may need to assess the interaction between hypertension status and disease status on cognitive function. Second, we defined the hypertension status using with or without hypertension disease. More detailed parameters of hypertension status need to be further studied. Third, our study was a small number of participants/single-center and cross-sectional study, which may hinder its generalization. A large-sample/multicenter, longitudinal study is helpful to comprehensively understand the relationship between hypertension status and cognitive function in SCD patients.

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“…Again, since we aimed to compare the time-frequency responses to successful restraint and cancellation, the results for each participant of the successful Go and No-Go trials were separately averaged for further analysis. Based on the grand-averaged time-frequency plots in the present study and the existing literature using Go/No-Go and stop-signal tasks, we specifically examined the powers of theta [ 55 , 56 ], alpha [ 57 , 58 ], and beta oscillations [ 58 , 59 , 60 ]. The time window of interest was selected from the grand-averaged time-frequency plots.…”

Section: Methodsmentioning

confidence: 99%

Machine Learning Based on Event-Related EEG of Sustained Attention Differentiates Adults with Chronic High-Altitude Exposure from Healthy Controls

et al. 2022

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(1) Objective: The aim of this study was to examine the effect of high altitude on inhibitory control processes that underlie sustained attention in the neural correlates of EEG data, and explore whether the EEG data reflecting inhibitory control contain valuable information to classify high-altitude chronic hypoxia and plain controls. (2) Methods: 35 chronic high-altitude hypoxic adults and 32 matched controls were recruited. They were required to perform the go/no-go sustained attention task (GSAT) using event-related potentials. Three machine learning algorithms, namely a support vector machine (SVM), logistic regression (LR), and a decision tree (DT), were trained based on the related ERP components and neural oscillations to build a dichotomous classification model. (3) Results: Behaviorally, we found that the high altitude (HA) group had lower omission error rates during all observation periods than the low altitude (LA) group. Meanwhile, the ERP results showed that the HA participants had significantly shorter latency than the LAs for sustained potential (SP), indicating vigilance to response-related conflict. Meanwhile, event-related spectral perturbation (ERSP) analysis suggested that lowlander immigrants exposed to high altitudes may have compensatory activated prefrontal cortexes (PFC), as reflected by slow alpha, beta, and theta frequency-band neural oscillations. Finally, the machine learning results showed that the SVM achieved the optimal classification F1 score in the later stage of sustained attention, with an F1 score of 0.93, accuracy of 92.54%, sensitivity of 91.43%, specificity of 93.75%, and area under ROC curve (AUC) of 0.97. The results proved that SVM classification algorithms could be applied to identify chronic high-altitude hypoxia. (4) Conclusions: Compared with other methods, the SVM leads to a good overall performance that increases with the time spent on task, illustrating that the ERPs and neural oscillations may provide neuroelectrophysiological markers for identifying chronic plateau hypoxia.

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Neuromodulation in Beta-Band Power Between Movement Execution and Inhibition in the Human Hippocampus

Cited by 5 publications

References 76 publications

Baseline hippocampal beta band power is lower in the presence of movement uncertainty

Baseline hippocampal beta band power is lower in the presence of movement uncertainty

Hypertension Status Moderated the Relationship between the Hippocampal Subregion of the Left GC-ML-DG and Cognitive Performance in Subjective Cognitive Decline

Machine Learning Based on Event-Related EEG of Sustained Attention Differentiates Adults with Chronic High-Altitude Exposure from Healthy Controls

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