Low and high beta rhythms have different motor cortical sources and distinct roles in movement control and spatiotemporal attention.

Low and high beta frequency rhythms were observed in the motor cortex, but their respective sources and behavioral correlates remain unknown. We studied local field potentials (LFPs) during pre-cued reaching behavior in macaques. They contained a low beta band (<20 Hz) dominant in primary motor cortex and a high beta band (>20 Hz) dominant in dorsal premotor cortex (PMd). Low beta correlated positively with reaction time (RT) from visual cue onset and negatively with uninstructed hand postural micro-movements throughout the trial. High beta reflected temporal task prediction, with selective modulations before and during cues, which were enhanced in moments of increased focal attention when the gaze was on the work area. This double-dissociation in sources and behavioral correlates of motor cortical low and high beta, with respect to both task-instructed and spontaneous behavior, reconciles the largely disparate roles proposed for the beta rhythm, by suggesting band-specific roles in both movement control and spatiotemporal attention.

Suspending the Embodied Self in Meditation Attenuates Beta Oscillations in the Posterior Medial Cortex.

Human experience is imbued by the sense of being an embodied agent. The investigation of such basic self-consciousness has been hampered by the difficulty of comprehensively modulating it in the laboratory while reliably capturing ensuing subjective changes. The present preregistered study fills this gap by combining advanced meditative states with principled phenomenological interviews: 46 long-term meditators (19 female, 27 male) were instructed to modulate and attenuate their embodied self-experience during magnetoencephalographic monitoring. Results showed frequency-specific (high-beta band) activity reductions in frontoparietal and posterior medial cortices (PMC). Importantly, PMC reductions were driven by a subgroup describing radical embodied self-disruptions, including suspension of agency and dissolution of a localized first-person perspective. Neural changes were correlated with lifetime meditation and interview-derived experiential changes, but not with classical self-reports. The results demonstrate the potential of integrating in-depth first-person methods into neuroscientific experiments. Furthermore, they highlight neural oscillations in the PMC as a central process supporting the embodied sense of self.

Synaptic Changes in Pallidostriatal Circuits Observed in the Parkinsonian Model Triggers Abnormal Beta Synchrony with Accurate Spatio-temporal Properties across the Basal Ganglia.

Excessive oscillatory activity across basal ganglia (BG) nuclei in the ß frequencies (12-30 Hz) is a hallmark of Parkinson's disease (PD). While the link between oscillations and symptoms remains debated, exaggerated ß oscillations constitute an important biomarker for therapeutic effectiveness in PD. The neuronal mechanisms of ß-oscillation generation however remain unknown. Many existing models rely on a central role of the subthalamic nucleus (STN) or cortical inputs to BG. Contrarily, neural recordings and optogenetic manipulations in normal and parkinsonian rats recently highlighted the central role of the external pallidum (GPe) in abnormal ß oscillations, while showing that the integrity of STN or motor cortex is not required. Here, we evaluate the mechanisms for the generation of abnormal ß oscillations in a BG network model where neuronal and synaptic time constants, connectivity, and firing rate distributions are strongly constrained by experimental data. Guided by a mean-field approach, we show in a spiking neural network that several BG sub-circuits can drive oscillations. Strong recurrent STN-GPe connections or collateral intra-GPe connections drive γ oscillations (>40 Hz), whereas strong pallidostriatal loops drive low-ß (10-15 Hz) oscillations. We show that pathophysiological strengthening of striatal and pallidal synapses following dopamine depletion leads to the emergence of synchronized oscillatory activity in the mid-ß range with spike-phase relationships between BG neuronal populations in-line with experiments. Furthermore, inhibition of GPe, contrary to STN, abolishes oscillations. Our modeling study uncovers the neural mechanisms underlying PD ß oscillations and may thereby guide the future development of therapeutic strategies.

Human Sensorimotor Beta Event Characteristics and Aperiodic Signal Are Highly Heritable.

Individuals' phenotypes, including the brain's structure and function, are largely determined by genes and their interplay. The resting brain generates salient rhythmic patterns that can be characterized noninvasively using functional neuroimaging such as magnetoencephalography (MEG). One of these rhythms, the somatomotor (rolandic) beta rhythm, shows intermittent high amplitude "events" that predict behavior across tasks and species. Beta rhythm is altered in neurological disease. The aperiodic (1/f) signal present in electrophysiological recordings is also modulated by some neurological conditions and aging. Both sensorimotor beta and aperiodic signal could thus serve as biomarkers of sensorimotor function. Knowledge about the extent to which these brain functional measures are heritable could shed light on the mechanisms underlying their generation. We investigated the heritability and variability of human spontaneous sensorimotor beta rhythm events and aperiodic activity in 210 healthy male and female adult siblings' spontaneous MEG activity. The most heritable trait was the aperiodic 1/f signal, with a heritability of 0.87 in the right hemisphere. Time-resolved beta event amplitude parameters were also highly heritable, whereas the heritabilities for overall beta power, peak frequency, and measures of event duration remained nonsignificant. Human sensorimotor neural activity can thus be dissected into different components with variable heritability. We postulate that these differences partially reflect different underlying signal-generating mechanisms. The 1/f signal and beta event amplitude measures may depend more on fixed, anatomical parameters, whereas beta event duration and its modulation reflect dynamic characteristics, guiding their use as potential disease biomarkers.

Aperiodic and periodic components of oscillatory brain activity in relation to cognition and symptoms in pediatric ADHD.

Children with attention-deficit/hyperactivity disorder show deficits in processing speed, as well as aberrant neural oscillations, including both periodic (oscillatory) and aperiodic (1/f-like) activity, reflecting the pattern of power across frequencies. Both components were suggested as underlying neural mechanisms of cognitive dysfunctions in attention-deficit/hyperactivity disorder. Here, we examined differences in processing speed and resting-state-Electroencephalogram neural oscillations and their associations between 6- and 12-year-old children with (n = 33) and without (n = 33) attention-deficit/hyperactivity disorder. Spectral analyses of the resting-state EEG signal using fast Fourier transform revealed increased power in fronto-central theta and beta oscillations for the attention-deficit/hyperactivity disorder group, but no differences in the theta/beta ratio. Using the parameterization method, we found a higher aperiodic exponent, which has been suggested to reflect lower neuronal excitation-inhibition, in the attention-deficit/hyperactivity disorder group. While fast Fourier transform-based theta power correlated with clinical symptoms for the attention-deficit/hyperactivity disorder group only, the aperiodic exponent was negatively correlated with processing speed across the entire sample. Finally, the aperiodic exponent was correlated with fast Fourier transform-based beta power. These results highlight the different and complementary contribution of periodic and aperiodic components of the neural spectrum as metrics for evaluation of processing speed in attention-deficit/hyperactivity disorder. Future studies should further clarify the roles of periodic and aperiodic components in additional cognitive functions and in relation to clinical status.

Single-neuron bursts encode pathological oscillations in subcortical nuclei of patients with Parkinson's disease and essential tremor.

Deep brain stimulation procedures offer an invaluable opportunity to study disease through intracranial recordings from awake patients. Here, we address the relationship between single-neuron and aggregate-level (local field potential; LFP) activities in the subthalamic nucleus (STN) and thalamic ventral intermediate nucleus (Vim) of patients with Parkinson's disease (n = 19) and essential tremor (n = 16), respectively. Both disorders have been characterized by pathologically elevated LFP oscillations, as well as an increased tendency for neuronal bursting. Our findings suggest that periodic single-neuron bursts encode both pathophysiological beta (13 to 33 Hz; STN) and tremor (4 to 10 Hz; Vim) LFP oscillations, evidenced by strong time-frequency and phase-coupling relationships between the bursting and LFP signals. Spiking activity occurring outside of bursts had no relationship to the LFP. In STN, bursting activity most commonly preceded the LFP oscillation, suggesting that neuronal bursting generated within STN may give rise to an aggregate-level LFP oscillation. In Vim, LFP oscillations most commonly preceded bursting activity, suggesting that neuronal firing may be entrained by periodic afferent inputs. In both STN and Vim, the phase-coupling relationship between LFP and high-frequency oscillation (HFO) signals closely resembled the relationships between the LFP and single-neuron bursting. This suggests that periodic single-neuron bursting is likely representative of a higher spatial and temporal resolution readout of periodic increases in the amplitude of HFOs, which themselves may be a higher resolution readout of aggregate-level LFP oscillations. Overall, our results may reconcile "rate" and "oscillation" models of Parkinson's disease and shed light on the single-neuron basis and origin of pathophysiological oscillations in movement disorders.

Random Tactile Noise Stimulation Reveals Beta-Rhythmic Impulse Response Function of the Somatosensory System.

Both passive tactile stimulation and motor actions result in dynamic changes in beta band (15-30 Hz Hz) oscillations over somatosensory cortex. Similar to alpha band (8-12 Hz) power decrease in the visual system, beta band power also decreases following stimulation of the somatosensory system. This relative suppression of α and ß oscillations is generally interpreted as an increase in cortical excitability. Here, next to traditional single-pulse stimuli, we used a random intensity continuous right index finger tactile stimulation (white noise), which enabled us to uncover an impulse response function of the somatosensory system. Contrary to previous findings, we demonstrate a burst-like initial increase rather than decrease of beta activity following white noise stimulation (human participants, N = 18, 8 female). These ß bursts, on average, lasted for 3 cycles, and their frequency was correlated with resonant frequency of somatosensory cortex, as measured by a multifrequency steady-state somatosensory evoked potential paradigm. Furthermore, beta band bursts shared spectro-temporal characteristics with evoked and resting-state ß oscillations. Together, our findings not only reveal a novel oscillatory signature of somatosensory processing that mimics the previously reported visual impulse response functions, but also point to a common oscillatory generator underlying spontaneous ß bursts in the absence of tactile stimulation and phase-locked ß bursts following stimulation, the frequency of which is determined by the resonance properties of the somatosensory system.SIGNIFICANCE STATEMENT The investigation of the transient nature of oscillations has gained great popularity in recent years. The findings of bursting activity, rather than sustained oscillations in the beta band, have provided important insights into its role in movement planning, working memory, inhibition, and reactivation of neural ensembles. In this study, we show that also in response to tactile stimulation the somatosensory system responds with ∼3 cycle oscillatory beta band bursts, whose spectro-temporal characteristics are shared with evoked and resting-state beta band oscillatory signatures of the somatosensory system. As similar bursts have been observed in the visual domain, these oscillatory signatures might reflect an important supramodal mechanism in sensory processing.

Bursting with Potential: How Sensorimotor Beta Bursts Develop from Infancy to Adulthood.

Beta activity is thought to play a critical role in sensorimotor processes. However, little is known about how activity in this frequency band develops. Here, we investigated the developmental trajectory of sensorimotor beta activity from infancy to adulthood. We recorded EEG from 9-month-old, 12-month-old, and adult humans (male and female) while they observed and executed grasping movements. We analyzed "beta burst" activity using a novel method that combines time-frequency decomposition and principal component analysis. We then examined the changes in burst rate and waveform motifs along the selected principal components. Our results reveal systematic changes in beta activity during action execution across development. We found a decrease in beta burst rate during movement execution in all age groups, with the greatest decrease observed in adults. Additionally, we identified three principal components that defined waveform motifs that systematically changed throughout the trial. We found that bursts with waveform shapes closer to the median waveform were not rate-modulated, whereas those with waveform shapes further from the median were differentially rate-modulated. Interestingly, the decrease in the rate of certain burst motifs occurred earlier during movement and was more lateralized in adults than in infants, suggesting that the rate modulation of specific types of beta bursts becomes increasingly refined with age.SIGNIFICANCE STATEMENT We demonstrate that, like in adults, sensorimotor beta activity in infants during reaching and grasping movements occurs in bursts, not oscillations like thought traditionally. Furthermore, different beta waveform shapes were differentially modulated with age, including more lateralization in adults. Aberrant beta activity characterizes various developmental disorders and motor difficulties linked to early brain injury, so looking at burst waveform shape could provide more sensitivity for early identification and treatment of affected individuals before any behavioral symptoms emerge. More generally, comparison of beta burst activity in typical versus atypical motor development will also be instrumental in teasing apart the mechanistic functional roles of different types of beta bursts.

From Motivation to Action: Action Cost Better Predicts Changes in Premovement Beta-Band Activity than Speed.

Although premovement beta-band event-related desynchronization (ß-ERD; 13-30 Hz) from sensorimotor regions is modulated by movement speed, current evidence does not support a strict monotonic association between the two. Given that ß-ERD is thought to increase information encoding capacity, we tested the hypothesis that it might be related to the expected neurocomputational cost of movement, here referred to as action cost. Critically, action cost is greater both for slow and fast movements compared with a medium or "preferred" speed. Thirty-one right-handed participants performed a speed-controlled reaching task while recording their EEG. Results revealed potent modulations of beta power as a function of speed, with ß-ERD being significantly greater both for movements performed at high and low speeds compared with medium speed. Interestingly, medium-speed movements were more often chosen by participants than low-speed and high-speed movements, suggesting that they were evaluated as less costly. In line with this, modeling of action cost revealed a pattern of modulation across speed conditions that strikingly resembled the one found for ß-ERD. Indeed, linear mixed models showed that estimated action cost predicted variations of ß-ERD significantly better than speed. This relationship with action cost was specific to beta power, as it was not found when averaging activity in the mu band (8-12 Hz) and gamma band (31-49 Hz) bands. These results demonstrate that increasing ß-ERD may not merely speed up movements, but instead facilitate the preparation of high-speed and low-speed movements through the allocation of additional neural resources, thereby enabling flexible motor control.SIGNIFICANCE STATEMENT Heightened beta activity has been associated with movement slowing in Parkinson's disease, and modulations of beta activity are commonly used to decode movement parameters in brain-computer interfaces. Here we show that premovement beta activity is better explained by the neurocomputational cost of the action rather than its speed. Instead of being interpreted as a mere reflection of changes in movement speed, premovement changes in beta activity might therefore be used to infer the amount of neural resources that are allocated for motor planning.

The phase of tACS-entrained pre-SMA beta oscillations modulates motor inhibition.

Inhibitory control has been linked to beta oscillations in the fronto-basal ganglia network. Here we aim to investigate the functional role of the phase of this oscillatory beta rhythm for successful motor inhibition. We applied 20 Hz transcranial alternating current stimulation (tACS) to the pre-supplementary motor area (pre-SMA) while presenting stop signals at 4 (Experiment 1) and 8 (Experiment 2) equidistant phases of the tACS entrained beta oscillations. Participants showed better inhibitory performance when stop signals were presented at the trough of the beta oscillation whereas their inhibitory control performance decreased with stop signals being presented at the oscillatory beta peak. These results are consistent with the communication through coherence theory, in which postsynaptic effects are thought to be greater when an input arrives at an optimal phase within the oscillatory cycle of the target neuronal population. The current study provides mechanistic insights into the neural communication principles underlying successful motor inhibition and may have implications for phase-specific interventions aimed at treating inhibitory control disorders such as PD or OCD.

Quantifying local field potential dynamics with amplitude and frequency stability between ON and OFF medication and stimulation in Parkinson's disease.

Neural oscillations are critical to understanding the synchronisation of neural activities and their relevance to neurological disorders. For instance, the amplitude of beta oscillations in the subthalamic nucleus has gained extensive attention, as it has been found to correlate with medication status and the therapeutic effects of continuous deep brain stimulation in people with Parkinson's disease. However, the frequency stability of subthalamic nucleus beta oscillations, which has been suggested to be associated with dopaminergic information in brain states, has not been well explored. Moreover, the administration of medicine can have inverse effects on changes in frequency and amplitude. In this study, we proposed a method based on the stationary wavelet transform to quantify the amplitude and frequency stability of subthalamic nucleus beta oscillations and evaluated the method using simulation and real data for Parkinson's disease patients. The results suggest that the amplitude and frequency stability quantification has enhanced sensitivity in distinguishing pathological conditions in Parkinson's disease patients. Our quantification shows the benefit of combining frequency stability information with amplitude and provides a new potential feedback signal for adaptive deep brain stimulation.

Premotor cortical beta synchronization and the network neuromodulation of externally paced finger tapping in Parkinson's disease.

Parkinson's disease (PD) is characterized by the disruption of repetitive, concurrent and sequential motor actions due to compromised timing-functions principally located in cortex-basal ganglia (BG) circuits. Increasing evidence suggests that motor impairments in untreated PD patients are linked to an excessive synchronization of cortex-BG activity at beta frequencies (13-30 Hz). Levodopa and subthalamic nucleus deep brain stimulation (STN-DBS) suppress pathological beta-band reverberation and improve the motor symptoms in PD. Yet a dynamic tuning of beta oscillations in BG-cortical loops is fundamental for movement-timing and synchronization, and the impact of PD therapies on sensorimotor functions relying on neural transmission in the beta frequency-range remains controversial. Here, we set out to determine the differential effects of network neuromodulation through dopaminergic medication (ON and OFF levodopa) and STN-DBS (ON-DBS, OFF-DBS) on tapping synchronization and accompanying cortical activities. To this end, we conducted a rhythmic finger-tapping study with high-density EEG-recordings in 12 PD patients before and after surgery for STN-DBS and in 12 healthy controls. STN-DBS significantly ameliorated tapping parameters as frequency, amplitude and synchrony to the given auditory rhythms. Aberrant neurophysiologic signatures of sensorimotor feedback in the beta-range were found in PD patients: their neural modulation was weaker, temporally sluggish and less distributed over the right cortex in comparison to controls. Levodopa and STN-DBS boosted the dynamics of beta-band modulation over the right hemisphere, hinting to an improved timing of movements relying on tactile feedback. The strength of the post-event beta rebound over the supplementary motor area correlated significantly with the tapping asynchrony in patients, thus indexing the sensorimotor match between the external auditory pacing signals and the performed taps. PD patients showed an excessive interhemispheric coherence in the beta-frequency range during the finger-tapping task, while under DBS-ON the cortico-cortical connectivity in the beta-band was normalized. Ultimately, therapeutic DBS significantly ameliorated the auditory-motor coupling of PD patients, enhancing the electrophysiological processing of sensorimotor feedback-information related to beta-band activity, and thus allowing a more precise cued-tapping performance.

Cholinergic modulation of motor sequence learning.

The cholinergic system plays a key role in motor function, but whether pharmacological modulation of cholinergic activity affects motor sequence learning is unknown. The acetylcholine receptor antagonist biperiden, an established treatment in movement disorders, reduces attentional modulation, but whether it influences motor sequence learning is not clear. Using a randomized, double-blind placebo-controlled crossover design, we tested 30 healthy young participants and showed that biperiden impairs the ability to learn sequential finger movements, accompanied by widespread oscillatory broadband power changes (4-25 Hz) in the motor sequence learning network after receiving biperiden, with greater power in the theta, alpha and beta bands over ipsilateral motor and bilateral parietal-occipital areas. The reduced early theta power during a repeated compared with random sequence, likely reflecting disengagement of top-down attention to sensory processes, was disrupted by biperiden. Alpha synchronization during repeated sequences reflects sensory gating and lower visuospatial attention requirements compared with visuomotor responses to random sequences. After biperiden, alpha synchronization was greater, potentially reflecting excessive visuospatial attention reduction, affecting visuomotor responding required to enable sequence learning. Beta oscillations facilitate sequence learning by integrating visual and somatosensory inputs, stabilizing repeated sequences and promoting prediction of the next stimulus. The beta synchronization after biperiden fits with a disruption of the selective visuospatial attention enhancement associated with initial sequence learning. These findings highlight the role of cholinergic processes in motor sequence learning.

Post-task responses following working memory and movement are driven by transient spectral bursts with similar characteristics.

The post-movement beta rebound has been studied extensively using magnetoencephalography (MEG) and is reliably modulated by various task parameters as well as illness. Our recent study showed that rebounds, which we generalise as "post-task responses" (PTRs), are a ubiquitous phenomenon in the brain, occurring across the cortex in theta, alpha, and beta bands. Currently, it is unknown whether PTRs following working memory are driven by transient bursts, which are moments of short-lived high amplitude activity, similar to those that drive the post-movement beta rebound. Here, we use three-state univariate hidden Markov models (HMMs), which can identify bursts without a priori knowledge of frequency content or response timings, to compare bursts that drive PTRs in working memory and visuomotor MEG datasets. Our results show that PTRs across working memory and visuomotor tasks are driven by pan-spectral transient bursts. These bursts have very similar spectral content variation over the cortex, correlating strongly between the two tasks in the alpha (R2 = .89) and beta (R2 = .53) bands. Bursts also have similar variation in duration over the cortex (e.g., long duration bursts occur in the motor cortex for both tasks), strongly correlating over cortical regions between tasks (R2 = .56), with a mean over all regions of around 300 ms in both datasets. Finally, we demonstrate the ability of HMMs to isolate signals of interest in MEG data, such that the HMM probability timecourse correlates more strongly with reaction times than frequency filtered power envelopes from the same brain regions. Overall, we show that induced PTRs across different tasks are driven by bursts with similar characteristics, which can be identified using HMMs. Given the similarity between bursts across tasks, we suggest that PTRs across the cortex may be driven by a common underlying neural phenomenon.

Active and Passive Cycling Decrease Subthalamic ß Oscillations in Parkinson's Disease.

BACKGROUND: Preserved cycling capabilities in patients with Parkinson's disease, especially in those with freezing of gait are still poorly understood. Previous research with invasive local field potential recordings in the subthalamic nucleus has shown that cycling causes a stronger suppression of ß oscillations compared to walking, which facilitates motor continuation. METHODS: We recorded local field potentials from 12 patients with Parkinson's disease (six without freezing of gait, six with freezing of gait) who were bilaterally implanted with deep brain stimulation electrodes in the subthalamic nucleus. We investigated ß (13-30 Hz) and high γ (60-100 Hz) power during both active and passive cycling with different cadences and compared patients with and without freezing of gait. The passive cycling experiment, where a motor provided a fixed cadence, allowed us to study the effect of isolated sensory inputs without physical exercise. RESULTS: We found similarly strong suppression of pathological ß activity for both active and passive cycling. In contrast, there was stronger high γ band activity for active cycling. Notably, the effects of active and passive cycling were all independent of cadence. Finally, ß suppression was stronger for patients with freezing of gait, especially during passive cycling. CONCLUSIONS: Our results provide evidence for a link between proprioceptive input during cycling and ß suppression. These findings support the role of continuous external sensory input and proprioceptive feedback during rhythmic passive cycling movements and suggest that systematic passive mobilization might hold therapeutic potential. © 2023 International Parkinson and Movement Disorder Society.

Re-emergent Tremor in Parkinson's Disease: Evidence of Pathologic ß and Prokinetic γ Activity.

BACKGROUND: Re-emergent tremor is characterized as a continuation of resting tremor and is often highly therapy refractory. This study examines variations in brain activity and oscillatory responses between resting and re-emergent tremors in Parkinson's disease. METHODS: Forty patients with Parkinson's disease (25 males, mean age, 66.78 ± 5.03 years) and 40 age- and sex-matched healthy controls were included in the study. Electroencephalogram and electromyography signals were simultaneously recorded during resting and re-emergent tremors in levodopa on and off states for patients and mimicked by healthy controls. Brain activity was localized using the beamforming technique, and information flow between sources was estimated using effective connectivity. Cross-frequency coupling was used to assess neuronal oscillations between tremor frequency and canonical frequency oscillations. RESULTS: During levodopa on, differences in brain activity were observed in the premotor cortex and cerebellum in both the patient and control groups. However, Parkinson's disease patients also exhibited additional activity in the primary sensorimotor cortex. On withdrawal of levodopa, different source patterns were observed in the supplementary motor area and basal ganglia area. Additionally, levodopa was found to suppress the strength of connectivity (P < 0.001) between the identified sources and influence the tremor frequency-related coupling, leading to a decrease in ß (P < 0.001) and an increase in γ frequency coupling (P < 0.001). CONCLUSIONS: Distinct variations in cortical-subcortical brain activity are evident in tremor phenotypes. The primary sensorimotor cortex plays a crucial role in the generation of re-emergent tremor. Moreover, oscillatory neuronal responses in pathological ß and prokinetic γ activity are specific to tremor phenotypes. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Dynamic large-scale connectivity of intrinsic cortical oscillations supports adaptive listening in challenging conditions.

In multi-talker situations, individuals adapt behaviorally to this listening challenge mostly with ease, but how do brain neural networks shape this adaptation? We here establish a long-sought link between large-scale neural communications in electrophysiology and behavioral success in the control of attention in difficult listening situations. In an age-varying sample of N = 154 individuals, we find that connectivity between intrinsic neural oscillations extracted from source-reconstructed electroencephalography is regulated according to the listener's goal during a challenging dual-talker task. These dynamics occur as spatially organized modulations in power-envelope correlations of alpha and low-beta neural oscillations during approximately 2-s intervals most critical for listening behavior relative to resting-state baseline. First, left frontoparietal low-beta connectivity (16 to 24 Hz) increased during anticipation and processing of a spatial-attention cue before speech presentation. Second, posterior alpha connectivity (7 to 11 Hz) decreased during comprehension of competing speech, particularly around target-word presentation. Connectivity dynamics of these networks were predictive of individual differences in the speed and accuracy of target-word identification, respectively, but proved unconfounded by changes in neural oscillatory activity strength. Successful adaptation to a listening challenge thus latches onto two distinct yet complementary neural systems: a beta-tuned frontoparietal network enabling the flexible adaptation to attentive listening state and an alpha-tuned posterior network supporting attention to speech.

Rhythmic modulation of prediction errors: A top-down gating role for the beta-range in speech processing.

Natural speech perception requires processing the ongoing acoustic input while keeping in mind the preceding one and predicting the next. This complex computational problem could be handled by a dynamic multi-timescale hierarchical inferential process that coordinates the information flow up and down the language network hierarchy. Using a predictive coding computational model (Precoss-ß) that identifies online individual syllables from continuous speech, we address the advantage of a rhythmic modulation of up and down information flows, and whether beta oscillations could be optimal for this. In the model, and consistent with experimental data, theta and low-gamma neural frequency scales ensure syllable-tracking and phoneme-level speech encoding, respectively, while the beta rhythm is associated with inferential processes. We show that a rhythmic alternation of bottom-up and top-down processing regimes improves syllable recognition, and that optimal efficacy is reached when the alternation of bottom-up and top-down regimes, via oscillating prediction error precisions, is in the beta range (around 20-30 Hz). These results not only demonstrate the advantage of a rhythmic alternation of up- and down-going information, but also that the low-beta range is optimal given sensory analysis at theta and low-gamma scales. While specific to speech processing, the notion of alternating bottom-up and top-down processes with frequency multiplexing might generalize to other cognitive architectures.

Frontoparietal beta event characteristics are associated with early life stress and psychiatric symptoms in adults.

Recent work has found that the presence of transient, oscillatory burst-like events, particularly within the beta band (15-29 Hz), is more closely tied to disease state and behavior across species than traditional electroencephalography (EEG) power metrics. This study sought to examine whether features of beta events over frontoparietal electrodes were associated with early life stress (ELS) and the related clinical presentation. Eighteen adults with documented ELS (n = 18; ELS + ) and eighteen adults without documented ELS (n = 18; ELS-) completed eyes-closed resting state EEG as part of their participation in a larger childhood stress study. The rate, power, duration, and frequency span of transient oscillatory events were calculated within the beta band at five frontoparietal electrodes. ELS variables were positively associated with beta event rate at Fp2 and beta event duration at Pz, in that greater ELS was associated with higher resting rates and longer durations. These beta event characteristics were used to successfully distinguish between ELS + and ELS- groups. In an independent clinical dataset (n = 25), beta event power at Pz was positively correlated with ELS. Beta events deserve ongoing investigation as a potential disease marker of ELS and subsequent psychiatric treatment outcomes.

Exploring neural correlates of social dominance: Insights from behavioral, resting- state EEG, and ERP indices.

Numerous studies have explored the concept of social dominance and its implications for leadership within the behavioral and cognitive sciences in recent years. The current study aims to address the gap regarding the neural correlates of social dominance by investigating the associations between psychological measures of social dominance and neural features among a sample of leaders. Thirty healthy male volunteers engaged in a monetary gambling task while their resting-state and task-based electroencephalography data were recorded. The results revealed a positive association between social dominance and resting-state beta oscillations in central electrodes. Furthermore, a negative association was observed between social dominance and task-based reaction time as well as the amplitude of the feedback-related negativity component of the event-related potentials during the gain, but not the loss condition. These findings suggest that social dominance is associated with enhanced reward processing which has implications for social and interpersonal interactions.