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Several decades of behavioral research have established that variations in socioeconomic status (SES) are related to differences in cognitive performance. Neuroimaging and psychophysiological techniques have recently emerged as a method of choice to better understand the neurobiological processes underlying this phenomenon. Here we present a systematic review of a particular sub-domain of this field. Specifically, we used the PICOS approach to review studies investigating potential relationships between SES and scalp event-related brain potentials (ERP). This review found evidence that SES is related to amplitude variations in a diverse range of ERPs P1, N1, N2, Error-Related Negativities (ERN), N400, auditory evoked potentials, negative difference waves (Nd), P3 and slow waves (SW). These ERPs include early, mid-latency and late potentials that reflect a broad range of cognitive processes (e.g., automatic attentional processes, overt attention, language, executive function, etc.). https://www.selleckchem.com/products/fluorescein-5-isothiocyanate-fitc.html In this review, all SES effects on ERPs appeared to reflect an impairment or a less efficient form of task-related neural activity for low-SES compared to high-SES individuals. Overall, these results confirm that a wide variety of distinct neural processes with different functional meanings are sensitive to SES differences. The findings of this review also suggest that the relationship between SES and some ERP components may depend on the developmental stage of study participants. Results are further discussed in terms of the current limitations of this field and future avenues of research.Introduction Although deep brain stimulation (DBS) often improves levodopa-responsive gait symptoms, robust therapies for gait dysfunction from Parkinson's disease (PD) remain a major unmet need. Walking speed could represent a simple, integrated tool to assess DBS efficacy but is often not examined systematically or quantitatively during DBS programming. Here we investigate the reliability and functional significance of changes in gait by directional DBS in the subthalamic nucleus. Methods Nineteen patients underwent unilateral subthalamic nucleus DBS surgery with an eight-contact directional lead (1-3-3-1 configuration) in the most severely affected hemisphere. They arrived off dopaminergic medications >12 h preoperatively and for device activation 1 month after surgery. We measured a comfortable walking speed using an instrumented walkway with DBS off and at each of 10 stimulation configurations (six directional contacts, two virtual rings, and two circular rings) at the midpoint of the therapeutic window.subthalamic DBS in appropriate configurations elicit acute and clinically significant improvements in gait dysfunction related to PD. Next-generation directional DBS technologies have significant potential to enhance gait by individually tailoring stimulation parameters to optimize efficacy.Adaptive behavior critically depends on performance monitoring (PM), the ability to monitor action outcomes and the need to adapt behavior. PM-related brain activity has been linked to guiding decisions about whether action adaptation is warranted. The present study examined whether PM-related brain activity in a flanker task, as measured by electroencephalography (EEG), was associated with adaptive behavior in daily life. Specifically, we were interested in the employment of self-control, operationalized as self-control failures (SCFs), and measured using ecological momentary assessment. Analyses were conducted using an adaptive elastic net regression to predict SCFs from EEG in a sample of 131 participants. The model was fit using within-subject averaged response-locked EEG activity at each electrode and time point within an epoch surrounding the response. We found that higher amplitudes of the error-related negativity (ERN) were related to fewer SCFs. This suggests that lower error-related activity may relate to lower recruitment of interventive self-control in daily life. Altered cognitive control processes, like PM, have been proposed as underlying mechanisms for various mental disorders. Understanding how alterations in PM relate to regulatory control might therefore aid in delineating how these alterations contribute to different psychopathologies.Motivation There is an ongoing search for definitive and reliable biomarkers to forecast or predict imminent seizure onset, but to date most research has been limited to EEG with sampling rates less then 1,000 Hz. High-frequency oscillations (HFOs) have gained acceptance as an indicator of epileptic tissue, but few have investigated the temporal properties of HFOs or their potential role as a predictor in seizure prediction. Here we evaluate time-varying trends in preictal HFO rates as a potential biomarker of seizure prediction. Methods HFOs were identified for all interictal and preictal periods with a validated automated detector in 27 patients who underwent intracranial EEG monitoring. We used LASSO logistic regression with several features of the HFO rate to distinguish preictal from interictal periods in each individual. We then tested these models with held-out data and evaluated their performance with the area-under-the-curve (AUC) of their receiver-operating curve (ROC). Finally, we assessed the significance of these results using non-parametric statistical tests. Results There was variability in the ability of HFOs to discern preictal from interictal states across our cohort. We identified a subset of 10 patients in whom the presence of the preictal state could be successfully predicted better than chance. For some of these individuals, average AUC in the held-out data reached higher than 0.80, which suggests that HFO rates can significantly differentiate preictal and interictal periods for certain patients. Significance These findings show that temporal trends in HFO rate can predict the preictal state better than random chance in some individuals. Such promising results indicate that future prediction efforts would benefit from the inclusion of high-frequency information in their predictive models and technological architecture.Working memory (WM) deficits are pervasive co-morbidities of epilepsy. Although the pathophysiological mechanisms underpinning these impairments remain elusive, it is thought that WM depends on oscillatory interactions within and between nodes of large-scale functional networks. These include the hippocampus and default mode network as well as the prefrontal cortex and frontoparietal central executive network. Here, we review the functional roles of neural oscillations in subserving WM and the putative mechanisms by which epilepsy disrupts normative activity, leading to aberrant oscillatory signatures. We highlight the particular role of interictal epileptic activity, including interictal epileptiform discharges and high frequency oscillations (HFOs) in WM deficits. We also discuss the translational opportunities presented by greater understanding of the oscillatory basis of WM function and dysfunction in epilepsy, including potential targets for neuromodulation.Although the neural systems that underlie spoken language are well-known, how they adapt to evolving social cues during natural conversations remains an unanswered question. In this work we investigate the neural correlates of face-to-face conversations between two individuals using functional near infrared spectroscopy (fNIRS) and acoustical analyses of concurrent audio recordings. Nineteen pairs of healthy adults engaged in live discussions on two controversial topics where their opinions were either in agreement or disagreement. Participants were matched according to their a priori opinions on these topics as assessed by questionnaire. Acoustic measures of the recorded speech including the fundamental frequency range, median fundamental frequency, syllable rate, and acoustic energy were elevated during disagreement relative to agreement. Consistent with both the a priori opinion ratings and the acoustic findings, neural activity associated with long-range functional networks, rather than the canonical language areas, was also differentiated by the two conditions. Specifically, the frontoparietal system including bilateral dorsolateral prefrontal cortex, left supramarginal gyrus, angular gyrus, and superior temporal gyrus showed increased activity while talking during disagreement. In contrast, talking during agreement was characterized by increased activity in a social and attention network including right supramarginal gyrus, bilateral frontal eye-fields, and left frontopolar regions. Further, these social and visual attention networks were more synchronous across brains during agreement than disagreement. link2 Rather than localized modulation of the canonical language system, these findings are most consistent with a model of distributed and adaptive language-related processes including cross-brain neural coupling that serves dynamic verbal exchanges.The future of awake bruxism assessment will incorporate physiological data, possibly electromyography (EMG) of the temporal muscles. But up to now, temporal muscle contraction patterns in awake bruxism have not been characterized to demonstrate clinical utility. The present study aimed to perform surface EMG evaluations of people assessed for awake bruxism to identify possible different subtypes. A 2-year active search for people with awake bruxism in three regions of the country resulted in a total of 303 participants (223 women, 38 ± 13 years, mean and SD). Their inclusion was confirmed through non-instrumental approaches for awake bruxism self-reported questionnaire and clinical exam, performed by three experienced and calibrated dentists (Kappa = 0.75). Also, 77 age- and sex-matched healthy controls were recruited (49 women, 36 ± 14 years). Temporalis surface EMG was performed with a portable device (Myobox; NeuroUp, Brazil). link3 EMG signals were sent to a computer via Bluetooth 4.0 at a sampling rate of 1,000 Hz. Digital signal processing was performed using the commercial neuroUP software, transformed in RMS and then normalized for peak detection (EMG peaks/min), in a 10 min session. Cluster analysis revealed three distinct subtypes of awake bruxism phasic, tonic, and intermediate. Individuals with a predominance of EMG peaks/min were classified as the "phasic" subtype (16.8%). Those with the highest EMG rest power were classified as the "tonic" subtype (32.3%). There was also an "intermediate" subtype (50.8%), when both variables remained low. Characterization of awake bruxism physiology is important for future establishment of instrumental assessment protocols and treatment strategies.For patients with multiple sclerosis (MS), deficits in gait significantly reduce the quality of life. Using the concept of muscle synergies, this study investigated the modular organization of motor control during level and inclined walking in MS patients (MSP) compared with healthy participants (HP) to identify the potential demand-specific adjustments in motor control in MSP. We hypothesized a widening of the time-dependent activation patterns (motor primitives) in MSP to increase the overlap of temporally-adjacent muscle synergies, especially during inclined walking, as a strategy to increase the robustness of motor control, thus compensating pathology-related deficits. We analyzed temporal gait parameters and muscle synergies from myoelectric signals of 13 ipsilateral leg muscles using non-negative matrix factorization. Compared with HP, MSP demonstrated a widening in the time-dependent coefficients (motor primitives), as well as altered relative muscle contribution (motor modules), in certain synergies during level and inclined walking.
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