Gamma Power Research Articles

Abnormal patterns of sleep and waking behaviors are accompanied by neocortical oscillation disturbances in an Ank3 mouse model of epilepsy-bipolar disorder comorbidity

ANK3 is a leading bipolar disorder (BD) candidate gene in humans and provides a unique opportunity for studying epilepsy-BD comorbidity. Previous studies showed that deletion of Ank3-1b, a BD-associated variant of Ank3 in mice leads to increased firing threshold and diminished action potential dynamic range of parvalbumin (PV) interneurons and absence epilepsy, thus providing a biological mechanism linking epilepsy and BD. To explore the behavioral overlap of these disorders, we characterized behavioral patterns of Ank3-1b KO mice during overnight home-cage activity and examined network activity during these behaviors using paired video and EEG recordings. Since PV interneurons contribute to the generation of high-frequency gamma oscillations, we anticipated changes in the power of neocortical EEG signals in the gamma frequency range (> 25 Hz) during behavioral states related to human BD symptoms, including abnormal sleep, hyperactivity, and repetitive behaviors. Ank3-1b KO mice exhibited an overall increase in slow gamma (~25-45 Hz) power compared to controls, and slow gamma power correlated with seizure phenotype severity across behaviors. During sleep, increased slow gamma power correlated with decreased time spent in the rapid eye movement (REM) stage of sleep. Seizures were more common during REM sleep compared to non-REM (NREM) sleep. We also found that Ank3-1b KO mice were hyperactive and exhibited a repetitive behavior phenotype that co-occurred with increased slow gamma power. Our results identify a novel EEG biomarker associating Ank3 genetic variation with BD and epilepsy and suggest modulation of gamma oscillations as a potential therapeutic target.

Thalamo-cortical evoked potentials during stimulation of the dentato-rubro-thalamic tract demonstrate synaptic filtering

Essential tremor DBS targeting the ventral intermediate nucleus (Vim) of the thalamus and its input, the dentato-rubro-thalamic tract (DRTt), has proven to be an effective treatment strategy. We examined thalamo-cortical evoked potentials (TCEPs) and cortical dynamics during stimulation of the DRTt. We recorded TCEPs in primary motor cortex during clinical and supra-clinical stimulation of the DRTt in ten essential tremor patients. Stimulation was varied over pulse amplitude (2–10 ​mA) and pulse width (30–250 ​μs) to allow for strength-duration testing. Testing at clinical levels (3 ​mA, 60 ​μs) for stimulation frequencies of 1–160 ​Hz was performed and phase amplitude coupling (PAC) of beta phase and gamma power was calculated. Primary motor cortex TCEPs displayed two responses: early and all-or-none (<20 ​ms) or delayed and charge-dependent (>50 ​ms). Strength-duration curve approximation indicates that the chronaxie of the neural elements related to the TCEPs is <200 ​μs. At the range of clinical stimulation (amplitude 2–5 ​mA, pulse width 30–60 ​μs), TCEPs were not noted over primary motor cortex. Decreased pathophysiological phase-amplitude coupling was seen above 70 ​Hz stimulation without changes in power spectra and below the threshold of TCEPs. Our findings demonstrate that DRTt stimulation within normal clinical bounds does not excite fibers directly connected with primary motor cortex but that supra-clinical stimulation can excite a direct axonal tract. Both clinical efficacy and phase-amplitude coupling were frequency-dependent, favoring a synaptic filtering model as a possible mechanism of action.

Evaluation of an English language phoneme-based imagined speech brain computer interface with low-cost electroencephalography.

Paralyzed and physically impaired patients face communication difficulties, even when they are mentally coherent and aware. Electroencephalographic (EEG) brain-computer interfaces (BCIs) offer a potential communication method for these people without invasive surgery or physical device controls. Although virtual keyboard protocols are well documented in EEG BCI paradigms, these implementations are visually taxing and fatiguing. All English words combine 44 unique phonemes, each corresponding to a unique EEG pattern. In this study, a complete phoneme-based imagined speech EEG BCI was developed and tested on 16 subjects. Using open-source hardware and software, machine learning models, such as k-nearest neighbor (KNN), reliably achieved a mean accuracy of 97 ± 0.001%, a mean F1 of 0.55 ± 0.01, and a mean AUC-ROC of 0.68 ± 0.002 in a modified one-versus-rest configuration, resulting in an information transfer rate of 304.15 bits per minute. In line with prior literature, the distinguishing feature between phonemes was the gamma power on channels F3 and F7. However, adjustments to feature selection, trial window length, and classifier algorithms may improve performance. In summary, these are iterative changes to a viable method directly deployable in current, commercially available systems and software. The development of an intuitive phoneme-based EEG BCI with open-source hardware and software demonstrates the potential ease with which the technology could be deployed in real-world applications.

Transcranial direct-current stimulation of the prefrontal cortex enhances working memory and suppresses pathological gamma power elevation in schizophrenia

ABSTRACT Background This investigation examines the clinical benefits of prefrontal cortex transcranial direct current stimulation (tDCS) treatment of working memory (WM) dysfunction in chronic schizophrenia patients. Research design and methods 34 schizophrenia (SZ) patients were evaluated at baseline, and 29 patients were randomly assigned to either active tDCS intervention or sham tDCS intervention. tDCS intervention applied 10 consecutive sessions (20 minutes, 2 mA, two sessions a day) over 5 days. WM performance (N = 25), symptom severity (N = 29), and resting EEG (N = 17) were assessed from pre- to post-tDCS intervention. Additionally, symptom severity was noted over a 12-week follow-up period. Results WM accuracy significantly improved in the active tDCS group while WM accuracy in the sham tDCS group was unchanged. Significant symptom-severity reduction was sustained for one week after active tDCS intervention. Sustained resting gamma stability (RGS) was noted from baseline to post tDCS in the active-treatment group versus a significant elevation in pathological gamma power in the sham-tDCS group. Conclusions Examining treatment effects on RGS in SZ could be critical in identifying effective novel treatment strategies that promote left-DLPFC excitability and enhance WM functioning. Further empirical support is warranted to support the clinical benefits over longer periods of time. Trial Registration ClinicalTrials.gov Identifier: NCT04637724. Ethics Approval Registration No 337–19

Sleep-EEG in comorbid pain and insomnia: implications for the treatment of pain disorders.

Patients with chronic pain experience a high prevalence of comorbid insomnia, which is associated with functional impairment. Recent advances in sleep electroencephalography (sleep-EEG) may clarify the mechanisms that link sleep and chronic pain. In this clinical update, we outline current advancements in sleep-EEG assessments for pain and provide research recommendations. Promising preliminary work suggests that sleep-EEG spectral bands, particularly beta, gamma, alpha, and delta power, may create candidate neurophysiological signatures of pain, and macro-architectural parameters (e.g., total sleep time, arousals, and sleep continuity) may facilitate EEG-derived sleep phenotyping and may enable future stratification in the treatment of pain. Integration of measures obtained through sleep-EEG represent feasible and scalable approaches that could be adopted in the future. We provide research recommendations to progress the field towards a deeper understanding of their utility and potential future applications in clinical practice.

How Do Event‐Related Gamma Oscillations Differ in Alzheimer’s Disease From Other Types of Dementia ?

AbstractBackgroundAlthough recent studies showed that gamma frequency entrainment might have therapeutic effects on Alzheimer’s Disease (AD) (Iaccarino et al. 2016), the gamma band abnormalities in AD patients are still poorly understood, while some studies presented increased gamma responses in AD, others showed reduced gamma responses (Güntekin et al., 2022). The differentiation of gamma responses between different dementia types is also not known. The present study aims to analyze the event‐related gamma responses in AD patients and to find out how the event‐related gamma responses differentiate between AD, Parkinson’s disease dementia (PDD), and Lewy Body dementia (DLB).MethodEEG of 17 DLB, 19 PDD, 20 AD patients, and 20 healthy controls was recorded with a 32‐channel EEG device. Subjects had performed visual oddball paradigm during EEG recordings. Event‐related phase locking and Event‐related power were analyzed in three gamma frequency bands (25‐30 Hz, 30‐35 Hz, 35‐48 Hz) in three different time windows (0 200 ms, 200 400 ms, 400‐600 ms) for target and non‐target stimuli. Repeated measures of ANOVA were used with the between‐subjects and within‐subjects factors.ResultTarget responses elicited higher gamma phase locking than the non‐target responses (p&lt;0.05). Healthy subjects had higher gamma phase locking than AD, PDD, and DLB patients (p&lt;0.05). The healthy control group had increased gamma power in the 0‐200 ms time window at frontal and central locations (p&lt;0.05); however, patient groups did not have this early time window increase of gamma responses. Furthermore, although it was non‐significant, gamma phase locking values of PDD and DLB patients were worse than AD.ConclusionThe present study showed that AD, PDD, and DLB patients had reduced event‐related gamma phase locking and power in the early time window compared to healthy elderly controls. The gamma phase locking values of PDD and DLB patients were worse than those of AD patients. The present study showed that similar to AD patients and other dementia types could also have deficits in the gamma frequency band. Since the PDD and DLB patients had even more abnormal gamma band activities, the gamma entrainment could also have positive effects in these groups of patients.

Identifying Individualized Neurophysiological Causal Features for Working Memory Performance: Implications for Non‐Invasive Brain Stimulation

AbstractBackgroundNon‐invasive brain stimulation (NIBS) has been extensively used to target specific neural oscillations with the aim of improving working memory performance. However, current NIBS paradigms have two main limitations: first, lack of personalization and second, a need for a randomized controlled trial (RCT) to infer causality between targets of NIBS and subsequent performance. RCT is a powerful measure to infer causality, but its implementation is expensive, time consuming, and sometimes simply not possible. Therefore, our aim was to use computational models and observational data to discover causal relations between neural oscillations and working memory performance to identify potential targets and stimulation parameters for personalized NIBS paradigms.MethodWe used electroencephalography (EEG) data of 66 young healthy participants collected while performing a 3‐back working memory task. Using graphical causal modeling, we extracted individualized causal brain oscillations of 3‐back performance and compared the causal features between two groups: high and low performers.ResultTotal number of causal features in high performers was higher than low performers. Among the causal features, right temporal gamma oscillation was ∼5 times (z‐score = 3.87, p = 0.003) more frequently a causal feature among high performers than low performers. However, the power of causal temporal gamma oscillation was not different between the two groups.ConclusionOur findings suggest that a potential approach to improve working memory performance using NIBS is to induce more causal gamma oscillations by, for example, generating more local gamma entrainment over the right temporal cortex and not necessarily by increasing gamma power.

Single-pulse electrical stimulation artifact removal using the novel matching pursuit-based artifact reconstruction and removal method (MPARRM)

Objective. Single-pulse electrical stimulation (SPES) has been widely used to probe effective connectivity. However, analysis of the neural response is often confounded by stimulation artifacts. We developed a novel matching pursuit-based artifact reconstruction and removal method (MPARRM) capable of removing artifacts from stimulation-artifact-affected electrophysiological signals. Approach. To validate MPARRM across a wide range of potential stimulation artifact types, we performed a bench-top experiment in which we suspended electrodes in a saline solution to generate 110 types of real-world stimulation artifacts. We then added the generated stimulation artifacts to ground truth signals (stereoelectroencephalography signals from nine human subjects recorded during a receptive speech task), applied MPARRM to the combined signal, and compared the resultant denoised signal with the ground truth signal. We further applied MPARRM to artifact-affected neural signals recorded from the hippocampus while performing SPES on the ipsilateral basolateral amygdala in nine human subjects. Main results. MPARRM could remove stimulation artifacts without introducing spectral leakage or temporal spread. It accommodated variable stimulation parameters and recovered the early response to SPES within a wide range of frequency bands. Specifically, in the early response period (5–10 ms following stimulation onset), we found that the broadband gamma power (70–170 Hz) of the denoised signal was highly correlated with the ground truth signal ( R=0.98±0.02 , Pearson), and the broadband gamma activity of the denoised signal faithfully revealed the responses to the auditory stimuli within the ground truth signal with 94%±1.47% sensitivity and 99%±1.01% specificity. We further found that MPARRM could reveal the expected temporal progression of broadband gamma activity along the anterior-posterior axis of the hippocampus in response to the ipsilateral amygdala stimulation. Significance. MPARRM could faithfully remove SPES artifacts without confounding the electrophysiological signal components, especially during the early-response period. This method can facilitate the understanding of the neural response mechanisms of SPES.

Discrete tactile feature comparison subprocess in human brain during a decision-making process

From sensory input to motor action, encoded sensory features flow sequentially along cortical networks for decision-making. Despite numerous studies probing the decision-making process, the subprocess that compares encoded sensory features before making a decision has not been fully elucidated in humans. In this study, we investigated sensory feature comparison by presenting two different tasks (a discrimination task, in which participants made decisions by comparing two sequential tactile stimuli; and a detection task, in which participants responded to the second tactile stimulus in two sequential stimuli) to epilepsy patients while recording electrocorticography (ECoG). By comparing tactile-specific gamma band (30–200 Hz) power between the two tasks, the decision-making process was divided into three subprocesses—categorization, comparison, and decision—consistent with a previous study (Heekeren et al., 2004). These subprocesses occurred sequentially in the dorsolateral prefrontal cortex, premotor cortex, secondary somatosensory cortex, and parietal lobe. Gamma power showed two different patterns of correlation with response time. In the inferior parietal lobule (IPL), there was a negative correlation. This means that as gamma power increased, response time decreased. In the secondary somatosensory cortex (S2), there was a positive correlation. Here, as gamma power increased, response time also increased. These results indicate that the IPL and S2 encode tactile feature comparison differently. Our connectivity analysis showed that the S2 transmitted tactile information to the IPL. Our findings suggest that multiple areas in the parietal lobe encode sensory feature comparison differently before making a decision.

The role of brain oscillations in feature integration.

Our sensory system is able to build a unified perception of the world, which although rich, is limited and inaccurate. Sometimes, features from different objects are erroneously combined. At the neural level, the role of the parietal cortex in feature integration is well-known. However, the brain dynamics underlying correct and incorrect feature integration are less clear. To explore the temporal dynamics of feature integration, we studied the modulation of different frequency bands in trials in which feature integration was correct or incorrect. Participants responded to the color of a shape target, surrounded by distractors. A calibration procedure ensured that accuracy was around 70% in each participant. To explore the role of expectancy in feature integration, we introduced an unexpected feature to the target in the last blocks of trials. Results demonstrated the contribution of several frequency bands to feature integration. Alpha and beta power was reduced for hits compared to illusions. Moreover, gamma power was overall larger during the experiment for participants who were aware of the unexpected target presented during the last blocks of trials (as compared to unaware participants). These results demonstrate that feature integration is a complex process that can go wrong at different stages of information processing and is influenced by top-down expectancies.

CNSC-12. PATHOLOGY SPECIFIC, PHARMACOLOGICALLY REVERSIBLE LOSS OF NEURONAL FUNCTION IN HUMAN GLIOMAS

Abstract Prior evidence has demonstrated that neuronal activity is preserved within glioma-infiltrated cortex and maintains the ability to engage in task specific computations albeit with information loss. These findings support a potential therapeutic target to rescue cognitive impairments seen in nearly all afflicted patients if neuronal activity can be recovered. We developed an in vivo human behavioral and electrophysiological model to assess neuronal population tuning responses within primary sensory cortex including the decodability of stimuli and task-related changes in population spiking in a cohort of 14 human patients undergoing awake resection. We placed high-density electrode arrays to record human local field potentials from gliomas projecting to the cortical surface. We next designed a static sensory detection threshold task, stimulating with a tachometer at two different face and hand sites totaling 11,200 trials while recording from macroelectrode cortical contacts over both tumor-infiltrated (50 electrodes) and normal appearing cortex (52 electrodes). In tumor-infiltrated cortex, the ability to decode the site of stimulation using the oscillatory power in both theta (4-8 Hz) and gamma (32-70 Hz) bands was reduced compared to normal appearing cortex. However, tumor-infiltrated cortex-maintained selectivity between hand and face stimulation. Targeted next-generation tumor sequencing uncovered novel molecular targets of glioma-neuronal integration. The degree of loss of selectivity correlated with WHO grade and pathology. WHO grade 4 tumors and oligodendrogliomas compared to astrocytomas demonstrating greater loss of selectivity. Gabaergic agonist has been postulated to restore neuronal selectivity in aging and neurodegenerative disease. Therefore, we next computed GABA agonist dose (estimated by time off Propofol and beginning of behavioral testing). Higher concentrations of GABA agonist correlated with improved theta band selectivity and decodability. These results suggest that loss of neuronal computations in glioma-infiltrated cortex is caused by loss of neuronal selectivity and is both tumor selective and pharmacologically reversible.

Alpha and SSVEP power outperform gamma power in capturing attentional modulation in human EEG.

Attention typically reduces power in the alpha (8-12Hz) band and increases power in gamma (>30Hz) band in brain signals, as reported in macaque local field potential (LFP) and human electro/magneto-encephalogram (EEG/MEG) studies. In addition, EEG studies often use flickering stimuli that produce a specific measure called steady-state-visually-evoked-potential (SSVEP), whose power also increases with attention. However, effectiveness of these neural measures in capturing attentional modulation is unknown since stimuli and task paradigms vary widely across studies. In a recent macaque study, attentional modulation was more salient in the gamma band of the LFP, compared to alpha or SSVEP. To compare this with human EEG, we designed an orientation change detection task where we presented both static and counterphasing stimuli of matched difficulty levels to 26 subjects and compared attentional modulation of various measures under similar conditions. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, non-foveal stimuli produced weak gamma despite various stimulus optimizations and showed negligible attentional modulation although full-screen gratings showed robust gamma activity. Our results are useful for brain-machine-interfacing studies where suitable features are used for decoding attention, and also provide clues about spatial scales of neural mechanisms underlying attention.

32 Altered Resting State EEG Spectral Properties in Older Individuals at High Risk for Alzheimer’s Disease

Objective:Onset of Alzheimer’s disease (AD) pathology is estimated to begin 20-30 years prior to clinical symptom onset. Resting state EEG may yield useful early biomarkers of pathology, but its use along the AD clinical continuum is still limited, especially in individuals who are at high risk for AD but have yet to show symptoms. EEG waveform oscillations are classified based by frequency range (alpha, beta, theta, delta). Changes within these frequency bands have been identified in individuals with AD-dementia as compared to those with MCI and normal aging. Typical changes involve increases in low frequency power bands of delta and theta and decreases in beta and alpha frequencies, particularly in more posterior brain regions. However, these methods have yet to be explored in cognitively normal individuals who are at high risk for AD, as work has shown between individuals with MCI and healthy older adults.Participants and Methods:We compared differences in resting state EEG between older adults (age 60+) at high risk for AD (positive family history, genetic risk defined as carrying 1 + ApoE ε4 alleles) and individuals at low risk (negative family history, no ε4 allele). We collected 1) neuropsychological test performance; 2) self-report measures of subjective cognitive complaints and cognitive reserve; and 3) five minutes of eyes-open resting state EEG using 64-channel active electrodes. Clusters of three electrodes were average for regions and absolute power within 5 frequency bands was calculated. Theta/beta ratio was calculated by dividing absolute power of bands at its respective site. Correlations between absolute power for specific regions, self-report measures, and neuropsychological test scores.Results:Analysis of 20 individuals collected to date (14 high risk, 6 low risk) found associations (p&lt;0.05) between risk group and beta and gamma power across multiple electrode clusters, with high-risk individuals having higher power. Significant correlations were also found between calculated measures of cognitive reserve and posterior theta/beta ratio, subjective cognitive complaints and beta power, and neuropsychological test composites of learning performance with delta and executive functioning with frontal theta power.Conclusions:This work provides preliminary evidence for differences in resting state EEG activity in those at risk for AD, prior to onset of clinical symptoms. Future work will examine patients with mild cognitive impairment as a comparison group to characterize resting state EEG across the early AD continuum.

Oscillatory network markers of subcallosal cingulate deep brain stimulation for depression

Identifying functional biomarkers related to treatment success can aid in expediting therapy optimization, as well as contribute to a better understanding of the neural mechanisms of the treatment-resistant depression (TRD) and subcallosal cingulate deep brain stimulation (SCC-DBS).Magnetoencephalography data were obtained from 16 individuals with SCC-DBS for TRD and 25 healthy subjects. The first objective of the study was to identify region-specific oscillatory modulations that both (i) discriminate individuals with TRD (with SCC-DBS OFF) from healthy controls, and (ii) discriminate TRD treatment responders from non-responders (with SCC-DBS ON). The second objective of this work was to further explore the effects of stimulation intensity and frequency on oscillatory activity in the identified brain regions of interest.Oscillatory power analyses led to the identification of brain regions that differentiated responders from non-responders based on modulations of increased alpha (8–12 Hz) and decreased gamma (32–116 Hz) power within nodes of the default mode, central executive, and somatomotor networks, Broca's area, and lingual gyrus. Within these nodes, it was also found that low stimulation frequency had stronger effects on oscillatory modulation than increased stimulation intensity.The identified functional network biomarkers implicate modulation of TRD-related activity in brain regions involved in emotional control/processing, motor control, and the interaction between speech, vision, and memory, which have all been implicated in depression. These electrophysiological biomarkers have the potential to be used as functional proxies for therapy optimization. Additional stimulation parameter analyses revealed that oscillatory modulations can be strengthened by increasing stimulation intensity or reducing frequency, which may represent potential avenues of direction in non-responders.

Altered resting-state brain oscillation and the associated cognitive impairments in late-life depression with different depressive severity: An EEG power spectrum and functional connectivity study

ObjectiveCognitive impairments are prevalent in late-life depression (LLD). However, it remains unclear whether there are concurrent brain oscillation alterations in resting condition across varying level of depression severity. This cross-sectional study aims to investigate the characteristics of altered resting-state oscillations, including power spectrum and functional connectivity, and their association with the cognitive impairments in LLD with different depression severity. MethodsA total of 65 patients with LLD and 40 elder participants without depression were recruited. Global cognition and subtle cognitive domains were evaluated. A five-minute resting-state electroencephalography (EEG) was conducted under eyes-closed conditions. Measurements included the ln-transformed absolute power for power spectrum analysis and the weighted phase lag index (wPLI) for functional connectivity analysis. ResultsAttentional and executive dysfunction were exhibited in Moderate-Severe LLD group. Enhanced posterior upper gamma power was observed in both LLD groups. Additionally, enhanced parietal and fronto-parietal/occipital theta connectivity were observed in Moderate-Severe LLD group, which were associated with the attentional impairment. LimitationsLimitations include a small sample size, concomitant medication use, and a relatively higher proportion of females. ConclusionsCurrent study observed aberrant brain activity patterns in LLD across different levels of depression severity, which were linked to cognitive impairments. The altered posterior brain oscillations may be trait marker of LLD. Moreover, cognitive impairments and associated connectivity alterations were exhibited in moderate-severe group, which may be a state-like marker of moderate-to severe LLD. The study deepens understanding of cognitive impairments with the associated oscillation changes, carrying implications for neuromodulation targets in LLD.

Dynamic Changes in Local Activity and Network Interactions among the Anterior Cingulate, Amygdala, and Cerebellum during Associative Learning.

Communication between the cerebellum and forebrain structures is necessary for motor learning and has been implicated in a variety of cognitive functions. The exact nature of cerebellar-forebrain interactions supporting behavior and cognition is not known. We examined how local and network activity support learning by simultaneously recording neural activity in the cerebellum, amygdala, and anterior cingulate cortex while male and female rats were trained in trace eyeblink conditioning. Initially, the cerebellum and forebrain signal the contingency between external stimuli through increases in theta power and synchrony. Neuronal activity driving expression of the learned response was observed in the cerebellum and became evident in the anterior cingulate and amygdala as learning progressed. Aligning neural activity to the training stimuli or learned response provided a way to differentiate between learning-related activity driven by different mechanisms. Stimulus and response-related increases in theta power and coherence were observed across all three areas throughout learning. However, increases in slow gamma power and coherence were only observed when oscillations were aligned to the cerebellum-driven learned response. Percentage of learned responses, learning-related local activity, and slow gamma communication from cerebellum to forebrain all progressively increased during training. The relatively fast frequency of slow gamma provides an ideal mechanism for the cerebellum to communicate learned temporal information to the forebrain. This cerebellar response-aligned slow gamma then provides enrichment of behavior-specific temporal information to local neuronal activity in the forebrain. These dynamic network interactions likely support a wide range of behaviors and cognitive tasks that require coordination between the forebrain and cerebellum.SIGNIFICANCE STATEMENT This study presents new evidence for how dynamic learning-related changes in single neurons and neural oscillations in a cerebellar-forebrain network support associative motor learning. The current results provide an integrated mechanism for how bidirectional communication between the cerebellum and forebrain represents important external events and internal neural drive. This bidirectional communication between the cerebellum and forebrain likely supports a wide range of behaviors and cognitive tasks that require temporal precision.

The effects of distraction on younger drivers: A neurophysiological perspective

Distracted driving remains a significant cause of traffic accidents globally, including in Australia. However, many younger drivers still admit to using a phone while driving. A simulated driving study investigated the neurophysiological effects of visual, auditory, and higher-order cognitive (i.e., requiring the use of executive functions) distraction on young drivers. In total, 24 young adults aged 18–25 years completed four 8 min simulated driving sessions while concurrently engaging in various distractor tasks. Neurophysiological arousal was measured via EEG. Additionally, subjective workload and objective driving performance were assessed. Frontal beta and gamma power exhibited their highest levels during tasks involving higher-order cognitive and visual demands. The higher-order cognitive condition was rated as the most mentally demanding. In comparison, the visual condition had the most significant impact on both the standard deviation of speed and standard deviation of lateral positioning. This study has significant implications for all road users, particularly those aged 18–25 years, and it reinforces the importance of not using a phone while driving.

Gamma Power as an Index of Sustained Attention in Simulated Vigilance Tasks.

Performance on the psychomotor vigilance test (PVT; Dinges & Powell, 1985)-a common index of sustained attention-is affected by the opposing forces of fatigue and sustained effort, where reaction times and error rates typically increase across trials and are sometimes offset by additional efforts deployed toward the end of the task (i.e., an "end-spurt"; cf. Bergum & Klein, 1961). In ACT-R (Adaptive Control of Thought-Rational; Anderson etal., 2004), these influences on task performance have been modeled as latent variables that are inferred from performance (e.g., Jongman, 1998; Veksler & Gunzelmann, 2018) without connections to directly observable variables. We propose the use of frontal gamma (γ) spectral power as a direct measure of vigilant effort and demonstrate its efficacy in modeling performance on the PVT in both the aggregate and inindividuals.

Region-specific changes in brain activity and memory after continuous positive airway pressure therapy in obstructive sleep apnea: a pilot high-density electroencephalography study.

Limited channel electroencephalography (EEG) investigations in obstructive sleep apnea (OSA) have revealed deficits in slow wave activity (SWA) and spindles during sleep and increased EEG slowing during resting wakefulness. High-density EEG (Hd-EEG) has also detected local parietal deficits in SWA (delta power) during NREM. It is unclear whether effective continuous positive airway pressure (CPAP) treatment reverses regional SWA deficits, and other regional sleep and wake EEG abnormalities, and whether any recovery relates to improved overnight memory consolidation. A clinical sample of men with moderate-severe OSA underwent sleep and resting wake recordings with 256-channel Hd-EEG before and after 3 months of CPAP. Declarative and procedural memory tasks were administered pre- and post-sleep. Topographical spectral power maps and differences between baseline and treatment were compared using t-tests and statistical nonparametric mapping (SnPM). In 11 compliant CPAP users (5.2 ± 1.1 hours/night), total sleep time did not differ after CPAP but N1 and N2 sleep were lower and N3 was higher. Centro-parietal gamma power during N3 increased and fronto-central slow spindle activity during N2 decreased (SnPM < 0.05). No other significant differences in EEG power were observed. When averaged specifically within the parietal region, N3 delta power increased after CPAP (p = 0.0029) and was correlated with the change in overnight procedural memory consolidation (rho = 0.79, p = 0.03). During resting wakefulness, there were trends for reduced delta and theta power. Effective CPAP treatment of OSA may correct regional EEG abnormalities, and regional recovery of SWA may relate to procedural memory improvements in the short term.

Analysis of Brain Stress in Response to Temperature Changes under Agricultural Work Using Electroencephalogram Measurement

Agricultural workers suffer from various physical problems and mental stress, including depression and insomnia. Various factors affect brain stress, including harsh agricultural working conditions. Further brain stress may also be due to changes in working conditions such as temperature, noise, and vibration. This study aimed to determine the brain stress in response to ambient temperature changes under agricultural work using agricultural machinery. The electroencephalograms (EEGs) of 17 agricultural workers who work using various agricultural machines was measured and analyzed. The EEG was measured for 3 min at the inactive and active state of agricultural work, respectively, at 24 °C, 28 °C, and 32 °C. The EEG was analyzed using the stress indices such as spectral edge frequency 95% (SEF95%), relative gamma power (RGP), and EEG-based working index (EWI). The EEG analysis indicated that brain stress was generated when the subjects performed the agricultural work after an inactive state. Additionally, as the temperature increased to ≥24 °C, the brain regions where SEF95%, RGP, and EWI exhibited an increase were identified. The findings of this study can be used as basic data in determining the working stress in agricultural workers during work as the ambient temperature changes from 24 °C to 32 °C.