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Bilateral salpingo-oophorectomy (BSO; removal of ovaries and fallopian tubes) prior to age 48 is associated with elevated risk for both Alzheimer's disease (AD) and sleep disorders such as insomnia and sleep apnea. In early midlife, individuals with BSO show reduced hippocampal volume, function, and hippocampal-dependent verbal episodic memory performance associated with changes in sleep. It is unknown whether BSO affects fine-grained sleep measurements (sleep microarchitecture) and how these changes might relate to hippocampal-dependent memory. We recruited thirty-six early midlife participants with BSO. Seventeen of these participants were taking 17ß-estradiol therapy (BSO+ET) and 19 had never taken ET (BSO). Twenty age-matched control participants with intact ovaries (AMC) were also included. Overnight at-home polysomnography recordings were collected, along with subjective sleep quality and hot flash frequency. Multivariate Partial Least Squares (PLS) analysis was used to assess how sleep varied between groups. Compared to AMC, BSO without ET was associated with significantly decreased time spent in non-rapid eye movement (NREM) stage 2 sleep as well as increased NREM stage 2 and 3 beta power, NREM stage 2 delta power, and spindle power and maximum amplitude. Increased spindle maximum amplitude was negatively correlated with verbal episodic memory performance. Decreased sleep latency, increased sleep efficiency, and increased time spent in rapid eye movement sleep were observed for BSO+ET. Findings suggest there is an association between ovarian hormone loss and sleep microarchitecture, which may contribute to poorer cognitive outcomes and be ameliorated by ET.

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During natural behavior, an action often needs to be suddenly stopped in response to an unexpected sensory input-referred to as reactive stopping. Reactive stopping has been mostly investigated in humans, which led to hypotheses about the involvement of different brain structures, in particular the hyperdirect pathway. Here, we directly investigate the contribution and interaction of two key regions of the hyperdirect pathway, the orbitofrontal cortex (OFC) and subthalamic nucleus (STN), using dual-area, multielectrode recordings in male rats performing a stop-signal task. In this task, rats have to initiate movement to a go-signal, and occasionally stop their movement to the go-signal side after a stop-signal, presented at various stop-signal delays. Both the OFC and STN show near-simultaneous field potential reductions in the beta frequency range (12-30 Hz) compared with the period preceding the go-signal and the movement period. These transient reductions (∼200 ms) only happen during reactive stopping, which is when the stop-signal was received after action initiation, and are well timed after stop-signal onset and before the estimated time of stopping. Phase synchronization analysis also showed a transient attenuation of synchronization between the OFC and STN in the beta range during reactive stopping. The present results provide the first direct quantification of local neural oscillatory activity in the OFC and STN and interareal synchronization specifically timed during reactive stopping.

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Age is a primary risk factor for Parkinson's disease (PD); however, the effects of aging on the Parkinsonian brain remain poorly understood, particularly for deep brain structures. We investigated intraoperative micro-electrode recordings from the subthalamic nucleus (STN) of PD patients aged between 42 and 76 years. Age was associated with decreased oscillatory beta power and non-oscillatory high-frequency power, independent of PD-related variables. Single unit firing and burst rates were also reduced, whereas the coefficient of variation and the structure of burst activity were unchanged. Phase synchronization (debiased weighed phase lag index [dWPLI]) between sites was pronounced in the beta band between electrodes in the superficial STN but was unaffected by age. Our results show that aging is associated with reduced neuronal activity without changes to its temporal structure. We speculate that the loss of activity in the STN may mediate the relationship between PD and age.

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Parkinson's Disease (PD) is characterized by the temporary alleviation of motor symptoms following electrode implantation (or nucleus destruction), known as the microlesion effect (MLE). Electrophysiological studies have explored different PD stages, but understanding electrophysiological characteristics during the MLE period remains unclear. The objective was to examine the characteristics of local field potential (LFP) signals in the subthalamic nucleus (STN) during the hyperacute period following implantation (within 2 days) and 1 month post-implantation. 15 patients diagnosed with PD were enrolled in this observational study, with seven simultaneous recordings of bilateral STN-LFP signals using wireless sensing technology from an implantable pulse generator. Recordings were made in both on and off medication states over 1 month after implantation. We used a method to parameterize the neuronal power spectrum to separate periodic oscillatory and aperiodic components effectively. Our results showed that beta power exhibited a significant increase in the off medication state 1 month after implantation, compared to the postoperative hyperacute period. Notably, this elevation was effectively attenuated by levodopa administration. Furthermore, both the exponents and offsets displayed a decrease at 1 month postoperatively when compared to the hyperacute postoperative period. Remarkably, levodopa medication exerted a modulatory effect on these aperiodic parameters, restoring them back to levels observed during the hyperacute period. Our findings suggest that both periodic and aperiodic components partially capture distinct electrophysiological characteristics during the MLE. It is crucial to adequately evaluate such discrepancies when exploring the mechanisms of MLE and optimizing adaptive stimulus protocols.

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Past studies have shown that spontaneous electroencephalography indicators-namely, the theta/beta power ratio and alpha oscillation-may measure individuals' attentional control processes. However, there is lack of research distinguishing these differences. This study investigated whether the theta/beta power ratio and alpha oscillation were separately related to the objective and subjective criteria of attentional control in eyes-open and eyes-closed conditions. The results showed two main findings: (1) In the eyes-open condition, the theta/beta power ratio at the Fz and Pz electrode sites were significantly negatively correlated with the attentional control scale score; the alpha power at the Pz electrode site was significantly negatively correlated with flanker RT interference effect; (2) In the eyes-closed condition, the alpha power at the Cz and Pz electrode sites were significantly positively correlated with flanker P3d. In summary, this study showed that the eyes-open spontaneous theta/beta power ratio may reflect individuals' beliefs in their attentional control ability, and the alpha oscillation may be related to individuals' attentional control ability.

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Conflict monitoring has been studied extensively using experimental paradigms that manipulate perceptual dimensions of stimuli and responses. The picture-word interference (PWI) task has historically been used to examine semantic conflict, but primarily for the purpose of examining lexical retrieval. In this study, we utilized two novel PWI tasks to assess conflict monitoring in the context of semantic conflict. Participants included nineteen young adults (14F, age = 20.79 ± 3.14) who completed two tasks: Animals and Objects. Task and conflict effects were assessed by examining behavioral (reaction time and accuracy) and neurophysiological (oscillations in theta, alpha, and beta band) measures. Results revealed conflict effects within both tasks, but the pattern of findings differed across the two semantic categories. Participants were slower to respond to unmatched versus matched trials on the Objects task only and were less accurate responding to matched versus unmatched trials in the Animals task only. We also observed task differences, with participants responding more accurately on conflict trials for Animals compared to Objects. Differences in neural oscillations were observed, including between-task differences in low beta oscillations and within-task differences in theta, alpha, and low beta. We also observed significant correlations between task performance and standard measures of cognitive control. This work provides new insights into conflict monitoring, highlighting the importance of examining conflict across different semantic categories, especially in the context of animacy. The findings serve as a benchmark to assess conflict monitoring using PWI tasks across populations of varying cognitive ability.

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Electroencephalograms (EEGs) are the gold standard test used in the medical field to diagnose epilepsy and aid in the diagnosis of many other neurological and mental disorders. Growing in popularity in terms of nonmedical applications, the EEG is also used in research, neurofeedback, and brain-computer interface, making it increasingly relevant to student learning. Recent innovations have made EEG setups more accessible and affordable, thus allowing their integration into neuroscience educational settings. Introducing students to EEGs, however, can be daunting due to intricate setup protocols, individual variation, and potentially expensive equipment. This paper aims to provide guidance for introducing students and educators to fundamental beginning and advanced level EEG concepts. Specifically, this paper tested the potential of three different setups, with varying channel number and wired or wireless connectivity, for introducing students to qualitative and quantitative exploration of alpha enhancement when eyes are closed, and observation of the alpha/beta anterior to posterior gradient. The setups were compared to determine their relative advantages and their robustness in detecting these well-established parameters. The basic 1- or 2-channel setups are sufficient for observing alpha and beta waves, while more advanced systems containing 8 or 16 channels are required for consistent observation of an anterior-posterior gradient. In terms of localization, the 16-channel setup, in principle, was more adept. The 8-channel setup, however, was more effective than the 16-channel setup with regards to displaying the anterior to posterior gradient. Thus, an 8-channel setup is sufficient in an education setting to display these known trends. Modification of the 16-channel setup may provide a better observation of the anterior to posterior gradient.

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BACKGROUND: Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for advanced Parkinson's disease (PD). Clinical outcomes after DBS can be limited by poor programming, which remains a clinically driven, lengthy and iterative process. Electrophysiological recordings in PD patients undergoing STN-DBS have shown an association between STN spectral power in the beta frequency band (beta power) and the severity of clinical symptoms. New commercially-available DBS devices now enable the recording of STN beta oscillations in chronically-implanted PD patients, thereby allowing investigation into the use of beta power as a biomarker for DBS programming. OBJECTIVE: To determine the potential advantages of beta-guided DBS programming over clinically and image-guided programming in terms of clinical efficacy and programming time. METHODS: We conducted a randomized, blinded, three-arm, crossover clinical trial in eight Parkinson's patients with STN-DBS who were evaluated three months after DBS surgery. We compared clinical efficacy and time required for each DBS programming paradigm, as well as DBS parameters and total energy delivered between the three strategies (beta-, clinically- and image-guided). RESULTS: All three programming methods showed similar clinical efficacy, but the time needed for programming was significantly shorter for beta- and image-guided programming compared to clinically-guided programming (p < 0.001). CONCLUSION: Beta-guided programming may be a useful and more efficient approach to DBS programming in Parkinson's patients with STN-DBS. It takes significantly less time to program than traditional clinically-based programming, while providing similar symptom control. In addition, it is readily available within the clinical DBS programmer, making it a valuable tool for improving current clinical practice.

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The failure to retain memory for extinguished fear plays a major role in the maintenance of posttraumatic stress disorder (PTSD), with successful extinction recall necessary for symptom reduction. Disturbed sleep, a hallmark symptom of PTSD, impairs fear extinction recall. However, our understanding of the electrophysiological mechanisms underpinning sleep's role in extinction retention remains underdetermined. We examined the relationship between the microarchitecture of sleep and extinction recall in healthy humans (n = 71, both male and females included) and a pilot study in individuals with PTSD (n = 12). Participants underwent a fear conditioning and extinction protocol over 2 days, with sleep recording occurring between conditioning and extinction. Twenty-four hours after extinction learning, participants underwent extinction recall. Power spectral density (PSD) was computed for pre- and post-extinction learning sleep. Increased beta-band PSD (~17-26 Hz) during pre-extinction learning sleep was associated with worse extinction recall in healthy participants (r = 0.41, p = .004). Beta PSD was highly stable across three nights of sleep (intraclass correlation coefficients > 0.92). Results suggest beta-band PSD is specifically implicated in difficulties recalling extinguished fear.

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Statistical modeling is a crucial phase for decision-making and predicting future events. Data arising from engineering-related fields have most often complex structures whose failure rate possesses mixed state behaviors (i.e., non-monotonic shapes). For the data sets whose failure rates are in the mixed state, the utilization of the traditional probability models is not a suitable choice. Therefore, searching for more flexible probability models that are capable of adequately describing the mixed state failure data sets is an interesting research topic for researchers. In this paper, we propose and study a new statistical model to achieve the above goal. The proposed model is called a new beta power very flexible Weibull distribution and is capable of capturing five different patterns of the failure rate such as uni-modal, decreasing-increasing-decreasing, bathtub, decreasing, increasing-decreasing-increasing shapes. The estimators of the new beta power very flexible Weibull distribution are obtained using the maximum likelihood method. The evaluation of the estimators is assessed by conducting a simulation study. Finally, the usefulness and applicability of the new beta power very flexible Weibull distribution are shown by analyzing two engineering data sets. Using four information criteria, it is observed that the new beta power very flexible Weibull distribution is the best-suited model for dealing with failure times data sets.

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Subthalamic nucleus (STN) beta-triggered adaptive deep brain stimulation (ADBS) has been shown to provide clinical improvement comparable to conventional continuous DBS (CDBS) with less energy delivered to the brain and less stimulation induced side effects. However, several questions remain unanswered. First, there is a normal physiological reduction of STN beta band power just prior to and during voluntary movement. ADBS systems will therefore reduce or cease stimulation during movement in people with Parkinson's disease and could therefore compromise motor performance compared to CDBS. Second, beta power was smoothed and estimated over a time period of 400 ms in most previous ADBS studies, but a shorter smoothing period could have the advantage of being more sensitive to changes in beta power, which could enhance motor performance. In this study, we addressed these two questions by evaluating the effectiveness of STN beta-triggered ADBS using a standard 400 ms and a shorter 200 ms smoothing window during reaching movements. Results from 13 people with Parkinson's disease showed that reducing the smoothing window for quantifying beta did lead to shortened beta burst durations by increasing the number of beta bursts shorter than 200 ms and more frequent switching on/off of the stimulator but had no behavioural effects. Both ADBS and CDBS improved motor performance to an equivalent extent compared to no DBS. Secondary analysis revealed that there were independent effects of a decrease in beta power and an increase in gamma power in predicting faster movement speed, while a decrease in beta event related desynchronization (ERD) predicted quicker movement initiation. CDBS suppressed both beta and gamma more than ADBS, whereas beta ERD was reduced to a similar level during CDBS and ADBS compared with no DBS, which together explained the achieved similar performance improvement in reaching movements during CDBS and ADBS. In addition, ADBS significantly improved tremor compared with no DBS but was not as effective as CDBS. These results suggest that STN beta-triggered ADBS is effective in improving motor performance during reaching movements in people with Parkinson's disease, and that shortening of the smoothing window does not result in any additional behavioural benefit. When developing ADBS systems for Parkinson's disease, it might not be necessary to track very fast beta dynamics; combining beta, gamma, and information from motor decoding might be more beneficial with additional biomarkers needed for optimal treatment of tremor.

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Patients diagnosed with Parkinson's disease (PD) have difficulty initiating and executing movements due to an acquired imbalance of the basal ganglia thalamocortical circuit secondary to loss of dopaminergic input into the striatum. The unbalanced circuit is hyper-synchronized, presenting as larger and longer bursts of beta-band (13-30 Hz) oscillations in the subthalamic nucleus (STN). As a first step toward a novel PD therapy that aims to improve symptoms through beta desynchronization, we sought to determine if individuals with PD could acquire volitional control of STN beta power in a neurofeedback task. We found a significant difference in STN beta power between task conditions, and relevant brain signal features could be detected and decoded in real time. This demonstration of volitional control of STN beta motivates development of a neurofeedback therapy to modulate PD symptom severity.

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How the brain responds temporally and spectrally when we listen to familiar versus unfamiliar musical sequences remains unclear. This study uses EEG techniques to investigate the continuous electrophysiological changes in the human brain during passive listening to familiar and unfamiliar musical excerpts. EEG activity was recorded in 20 participants while they passively listened to 10 s of classical music, and they were then asked to indicate their self-assessment of familiarity. We analyzed the EEG data in two manners: familiarity based on the within-subject design, i.e., averaging trials for each condition and participant, and familiarity based on the same music excerpt, i.e., averaging trials for each condition and music excerpt. By comparing the familiar condition with the unfamiliar condition and the local baseline, sustained low-beta power (12-16 Hz) suppression was observed in both analyses in fronto-central and left frontal electrodes after 800 ms. However, sustained alpha power (8-12 Hz) decreased in fronto-central and posterior electrodes after 850 ms only in the first type of analysis. Our study indicates that listening to familiar music elicits a late sustained spectral response (inhibition of alpha/low-beta power from 800 ms to 10 s). Moreover, the results showed that alpha suppression reflects increased attention or arousal/engagement due to listening to familiar music; nevertheless, low-beta suppression exhibits the effect of familiarity.NEW & NOTEWORTHY This study differentiates the dynamic temporal-spectral effects during listening to 10 s of familiar music compared with unfamiliar music. This study highlights that listening to familiar music leads to continuous suppression in the alpha and low-beta bands. This suppression starts ∼800 ms after the stimulus onset.

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There remains some debate about whether beta power effects observed during sentence comprehension reflect ongoing syntactic unification operations (beta-syntax hypothesis), or instead reflect maintenance or updating of the sentence-level representation (beta-maintenance hypothesis). In this study, we used magnetoencephalography to investigate beta power neural dynamics while participants read relative clause sentences that were initially ambiguous between a subject- or an object-relative reading. An additional condition included a grammatical violation at the disambiguation point in the relative clause sentences. The beta-maintenance hypothesis predicts a decrease in beta power at the disambiguation point for unexpected (and less preferred) object-relative clause sentences and grammatical violations, as both signal a need to update the sentence-level representation. While the beta-syntax hypothesis also predicts a beta power decrease for grammatical violations due to a disruption of syntactic unification operations, it instead predicts an increase in beta power for the object-relative clause condition because syntactic unification at the point of disambiguation becomes more demanding. We observed decreased beta power for both the agreement violation and object-relative clause conditions in typical left hemisphere language regions, which provides compelling support for the beta-maintenance hypothesis. Mid-frontal theta power effects were also present for grammatical violations and object-relative clause sentences, suggesting that violations and unexpected sentence interpretations are registered as conflicts by the brain's domain-general error detection system.

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Aging is a key risk factor for the development of Parkinson's disease (PD). PD is characterized by excessive synchrony of beta oscillations (13-30 Hz) in the basal ganglia thalamo-cortical network. However, cortical beta power is not reliably elevated in individuals with PD. Here, we sought to disentangle how resting cortical beta power compares in younger controls, older controls, and individuals with PD using scalp electroencephalogram (EEG) and a novel approach for quantifying beta power. Specifically, we used a Gaussian model to determine if sensorimotor beta power distinguishes these groups. In addition, we looked at the distribution of beta power across the entire cortex. Our findings showed that Gaussian-modeled beta power does not differentiate individuals with PD (on medication) from healthy younger or older controls in sensorimotor cortex. However, beta power (and not theta or alpha) was higher in healthy older versus younger controls. This effect was most pronounced in regions near sensorimotor cortex including the frontal and parietal areas [P < 0.05, false discovery rate (FDR) corrected]. In addition, the bandwidth of the periodic beta was also higher in healthy older than young individuals in parietal regions. Finally, the aperiodic component, specifically the exponent of the signal, was higher (steeper) in younger controls than in individuals with PD in the right parietal-occipital region (P < 0.05, FDR corrected), possibly reflecting differences in neuronal spiking. Our findings suggest that cortical Gaussian beta power is possibly modulated by age and could be further explored in longitudinal studies to determine whether sensorimotor beta increases with increasing age.NEW & NOTEWORTHY Altered sensorimotor beta activity has been shown to be a feature in aging and PD. Using a novel approach, we clarify that resting sensorimotor beta power does not distinguish subjects with PD from healthy younger and older controls. However, beta power was higher in older compared with younger controls in central sensorimotor, frontal, and parietal regions. These results provide a clearer picture of sensorimotor beta power, demonstrating that it is elevated in aging but not PD.

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Background. Cue-reactivity as a characteristic symptom of substance use disorders (SUD) is highly context dependent. Paradigms with high context validity need to be established for the investigation of underlying neurobiological mechanisms. While craving can be assessed by self-report as one aspect of cue-reactivity (CR), the assessment of biological measures such as the autonomous response and EEG promises a holistic perspective including CR at an automatized level. In a multimodal approach, smoking cue exposure (CE) effects on heart rate variability (HRV), EEG frequency power, and craving as well as their interrelation were assessed. This pilot study focused on the validity of CR measurements in a naturalistic CE paradigm. Methods. EEG frequency power, HRV, and craving were assessed during resting state (RS) and smoking CE in smokers (n = 14) and nonsmoking controls (n = 10) to investigate the psychophysiological and subjective reactions to CE. Results. Increased beta power was found only in smokers during CE compared to the control condition. There was an inverse correlation of beta power and maximum craving. Likewise, HRV correlated negatively with maximum smoking urges in smokers immediately after the measurements, without differentiation between CE and control condition. Conclusion. The increased beta power in smokers during CE is discussed as increased inhibitory control related to reduced craving in smokers. Furthermore, increased craving during CE seems to be associated to decreased vagal activity. The multimodal measurements during the CE showed ecological validity to be fundamental for CE assessment in clinical populations to evaluate its predictive value.

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During language processing, people make rapid use of contextual information to promote comprehension of upcoming words. When new words are learned implicitly, information contained in the surrounding context can provide constraints on their possible meaning. In the current study, EEG was recorded as participants listened to a series of three sentences, each containing an identical target pseudoword, with the aim of using contextual information in the surrounding language to identify a meaning representation for the novel word. In half of trials, sentences were semantically coherent so that participants could develop a single representation for the novel word that fit all contexts. Other trials contained unrelated sentence contexts so that meaning associations were not possible. We observed greater theta band enhancement over the left-hemisphere across central and posterior electrodes in response to pseudowords processed across semantically related compared to unrelated contexts. Additionally, relative alpha and beta band suppression was increased prior to pseudoword onset in trials where contextual information more readily promoted pseudoword-meaning associations. Under the hypothesis that theta enhancement indexes processing demands during lexical access, the current study provides evidence for selective online memory retrieval to novel words learned implicitly in a spoken context.

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Objective: Atypical patterns of language lateralization due to early reorganizational processes constitute a challenge in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy. There is no consensus on an optimal analysis method used for the identification of language dominance in MEG. This study examines the concordance between MEG source localization of beta power desynchronization and fMRI with regard to lateralization and localization of expressive and receptive language areas using a visual verb generation task. Methods: Twenty-five patients with pharmaco-resistant epilepsy, including six patients with atypical language lateralization, and ten right-handed controls obtained MEG and fMRI language assessment. Fourteen patients additionally underwent the Wada test. We analyzed MEG beta power desynchronization in sensor (controls) and source space (patients and controls). Beta power decrease between 13 and 35 Hz was localized applying Dynamic Imaging of Coherent Sources Beamformer technique. Statistical inferences were grounded on cluster-based permutation testing for single subjects. Results: Event-related desynchronization of beta power in MEG was seen within the language-dominant frontal and temporal lobe and within the premotor cortex. Our analysis pipeline consistently yielded left language dominance with high laterality indices in controls. Language lateralization in MEG and Wada test agreed in all 14 patients for inferior frontal, temporal and parietal language areas (Cohen's Kappa = 1, p < 0.001). fMRI agreed with Wada test in 12 out of 14 cases (85.7%) for Broca's area (Cohen's Kappa = 0.71, p = 0.024), while the agreement for temporal and temporo-parietal language areas were non-significant. Concordance between MEG and fMRI laterality indices was highest within the inferior frontal gyrus, with an agreement in 19/24 cases (79.2%), and non-significant for Wernicke's area. Spatial agreement between fMRI and MEG varied considerably between subjects and brain regions with the lowest Euclidean distances within the inferior frontal region of interest. Conclusion: Localizing the desynchronization of MEG beta power using a verb generation task is a promising tool for the identification of language dominance in the pre-surgical evaluation of epilepsy patients. The overall agreement between MEG and fMRI was lower than expected and might be attributed to differences within the baseline condition. A larger sample size and an adjustment of the experimental designs are needed to draw further conclusions.

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Decision making often requires accumulating evidence in favour of a particular option. When choices are expressed with a motor response, these actions are preceded by reductions in the power of oscillations in the alpha and beta range in motor cortices. For unimanual movements, these reductions are greater over the hemisphere contralateral to the response side. Such lateralizations are hypothesized to be an online index of the neural state of decisions as they develop over time of processing. In contrast, the lateralized readiness potential (LRP) is considered to selectively activate a response and appears shortly before the motor output. We investigated to what extent these neural signals reflect integration of decision evidence or more motor-related action preparation. Using two different experiments, we found that lateralization of alpha and beta power (APL and BPL, respectively) rapidly emerged after stimulus presentation, even when making an overt response was not yet possible. In contrast, we show that even after prolonged stimulus presentation, no LRP was present. Instead, the LRP emerged only after an imperative cue, prompting participants to indicate their choice. Furthermore, we could show that variations in sensory evidence strength modulate APL and BPL onset times, suggesting that integration of evidence is represented in these motor cortical signals. We conclude that APL and BPL reflect higher cognitive processes rather than pure action preparation, whereas LRP is more closely tied to motor performance. APL and BPL potentially encode decision information in motor areas serving the later preparation of overt decision output.

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