Resolving equivocal gain modulation of corticospinal excitability.

The ratio between the input and output of neuronal populations, usually referred to as gain modulation, is rhythmically modulated along the oscillatory cycle. Previous research on spinal neurons, however, revealed contradictory findings: both uni- and bimodal patterns of increased responsiveness for synaptic input have been proposed for the oscillatory beta rhythm. In this study, we compared previous approaches of phase estimation directly on simulated data and empirically tested the corresponding predictions in healthy males and females. We applied single-pulse transcranial magnetic stimulation over the primary motor cortex at rest, and assessed the spinal output generated by this input. Specifically, the peak-to-peak amplitude of the motor evoked potential in the contralateral forearm was estimated as a function of the EMG phase at which the stimulus was applied. The findings indicated that human spinal neurons adhere to a unimodal pattern of increased responsiveness, and suggest that the rising phase of the upper beta band maximizes gain modulation. Importantly, a bimodal pattern of increased responsiveness was shown to result in an artifact during data analysis and filtering. This observation of invalid preprocessing could be generalized to other frequency bands (i.e., delta, theta, alpha, and gamma), different task conditions (i.e., voluntary muscle contraction), and EEG-based phase estimations. Appropriate analysis algorithms, such as broad-band filtering, enable us to accurately determine gain modulation of neuronal populations and to avoid erroneous phase estimations. This may facilitate novel phase-specific interventions for targeted neuromodulation.

When do bursts matter in the primary motor cortex? Investigating changes in the intermittencies of beta rhythms associated with movement states.

Brain activity exhibits significant temporal structure that is not well captured in the power spectrum. Recently, attention has shifted to characterising the properties of intermittencies in rhythmic neural activity (i.e. bursts), yet the mechanisms that regulate them are unknown. Here, we present evidence from electrocorticography recordings made over the motor cortex to show that the statistics of bursts, such as duration or amplitude, in the beta frequency (14-30 Hz) band, significantly aid the classification of motor states such as rest, movement preparation, execution, and imagery. These features reflect nonlinearities not detectable in the power spectrum, with states increasing in nonlinearity from movement execution to preparation to rest. Further, we show using a computational model of the cortical microcircuit, constrained to account for burst features, that modulations of laminar specific inhibitory interneurons are responsible for the temporal organisation of activity. Finally, we show that the temporal characteristics of spontaneous activity can be used to infer the balance of cortical integration between incoming sensory information and endogenous activity. Critically, we contribute to the understanding of how transient brain rhythms may underwrite cortical processing, which in turn, could inform novel approaches for brain state classification, and modulation with novel brain-computer interfaces.

[Influence of biofeedback training on beta rhythm of the brain on the level of anxiety and endogenous time estimation of athletes]. / Vliyanie BOS-treninga po beta-ritmu golovnogo mozga na uroven' trevozhnosti i endogennuyu otsenku vremeni sportsmenami.

The optimal psychophysiological state reflects a high level of adaptation, physical and psychological fitness of athletes for the effective implementation of sports and training activity. The biofeedback technology, based on the principles of biofeedback, allows one to master the skills of regulating the psychophysiological state according to the selected parameters for controlling the physiological function of the body. There is insufficient data on application of neurofeedback of the beta rhythm for regulation of the psychophysiological state in conditions of complex sports activity. OBJECTIVE: To examine the effect of biofeedback training on the beta rhythm of the brain on the level of anxiety and the endogenous time estimation of athletes, depending on the nature of motor activity. MATERIAL AND METHODS: 1020 young men aged 18-21 years old were studied. The biofeedback training on the beta rhythm of the brain was carried out with active wakefulness and open eyes, with a bipolar installation of electrodes in the Fz-Cz lead and a free electrode on the earlobe. The level of anxiety of athletes was identified with the Ch. Spielberger questionnaire [1]. The endogenous time estimation was carried out according to the «Individual minute¼ test (according to F. Halberg) [2]. RESULTS: The biofeedback training contributed to multidirectional changes in the studied psychophysiological indicators, depending on the nature of the motor activity of athletes. After the training, in the group of cyclic sports athletes, there was a decrease in anxiety, remaining in the range of values of a high level, which may reflect the processes of fatigue or under-recovery. Representatives of speed-strength sports had a decrease in anxiety with varying values in the range of a moderate level, which reflects the achievement of a generally comfortable psychophysiological state. In the group of athletes of single combat sports, accelerated perception of time was noted, accompanied by anxiety, fussiness, decreased attention span and increased stress. Athletes of team sports had a unidirectional tendency of increasing anxiety with a variation of values in the range of moderate stress levels, which may be associated with an adaptive transition to a new level of the body functioning after the training. CONCLUSION: The use of the biofeedback training on the beta rhythm of the brain in the practice of sports and rehabilitation medicine requires a thorough and detailed study of its effect on various parameters of the psychophysiological state of athletes. The development of methods for the differential application of the method, taking into account the polymetric characteristics of the initial state, type of sports activity and other factors, calls for special attention.

Phase-adaptive brain stimulation of striatal D1 medium spiny neurons in dopamine-depleted mice.

Brain rhythms are strongly linked with behavior, and abnormal rhythms can signify pathophysiology. For instance, the basal ganglia exhibit a wide range of low-frequency oscillations during movement, but pathological "beta" rhythms at ~ 20 Hz have been observed in Parkinson's disease (PD) and in PD animal models. All brain rhythms have a frequency, which describes how often they oscillate, and a phase, which describes the precise time that peaks and troughs of brain rhythms occur. Although frequency has been extensively studied, the relevance of phase is unknown, in part because it is difficult to causally manipulate the instantaneous phase of ongoing brain rhythms. Here, we developed a phase-adaptive, real-time, closed-loop algorithm to deliver optogenetic stimulation at a specific phase with millisecond latency. We combined this Phase-Adaptive Brain STimulation (PABST) approach with cell-type-specific optogenetic methods to stimulate basal ganglia networks in dopamine-depleted mice that model motor aspects of human PD. We focused on striatal medium spiny neurons expressing D1-type dopamine receptors because these neurons can facilitate movement. We report three main results. First, we found that our approach delivered PABST within system latencies of 13 ms. Second, we report that closed-loop stimulation powerfully influenced the spike-field coherence of local brain rhythms within the dorsal striatum. Finally, we found that both 4 Hz PABST and 20 Hz PABST improved movement speed, but we found differences between phase only with 4 Hz PABST. These data provide causal evidence that phase is relevant for brain stimulation, which will allow for more precise, targeted, and individualized brain stimulation. Our findings are applicable to a broad range of preclinical brain stimulation approaches and could also inform circuit-specific neuromodulation treatments for human brain disease.

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.

The phase of sensorimotor mu and beta oscillations has the opposite effect on corticospinal excitability.

BACKGROUND: Neural oscillations in the primary motor cortex (M1) shape corticospinal excitability. Power and phase of ongoing mu (8-13 Hz) and beta (14-30 Hz) activity may mediate motor cortical output. However, the functional dynamics of both mu and beta phase and power relationships and their interaction, are largely unknown. OBJECTIVE: Here, we employ recently developed real-time targeting of the mu and beta rhythm, to apply phase-specific brain stimulation and probe motor corticospinal excitability non-invasively. For this, we used instantaneous read-out and analysis of ongoing oscillations, targeting four different phases (0°, 90°, 180°, and 270°) of mu and beta rhythms with suprathreshold single-pulse transcranial magnetic stimulation (TMS) to M1. Ensuing motor evoked potentials (MEPs) in the right first dorsal interossei muscle were recorded. Twenty healthy adults took part in this double-blind randomized crossover study. RESULTS: Mixed model regression analyses showed significant phase-dependent modulation of corticospinal output by both mu and beta rhythm. Strikingly, these modulations exhibit a double dissociation. MEPs are larger at the mu trough and rising phase and smaller at the peak and falling phase. For the beta rhythm we found the opposite behavior. Also, mu power, but not beta power, was positively correlated with corticospinal output. Power and phase effects did not interact for either rhythm, suggesting independence between these aspects of oscillations. CONCLUSION: Our results provide insights into real-time motor cortical oscillation dynamics, which offers the opportunity to improve the effectiveness of TMS by specifically targeting different frequency bands.

Processing of embedded response plans is modulated by an interplay of frontoparietal theta and beta activity.

Even simple actions like opening a door require integration/binding and flexible reactivation of different motor elements. Yet, the neural mechanisms underlying the processing of such "embedded response plans" are largely elusive, despite theoretical frameworks, such as the theory of event coding, describing the involved cognitive processes. In a sample of n = 40 healthy participants, we combine time-frequency decomposition and various beamforming methods to examine the neurophysiological dynamics of such action plans, with special emphasis on the interplay of theta and beta frequency activity during the processing of these plans. We show that the integration and rule-guided reactivation of embedded response plans is modulated by a complex interplay of theta and beta activity. Pretrial beta-band activity (BBA) is related to different functional neuroanatomical structures that are activated in a consecutive fashion. Enhanced preparatory activity is positively associated with higher binding-related BBA in the precuneus/parietal areas, indicating that activity in the precuneus/parietal cortex facilitates the execution of an embedded action sequence. Increased preparation subsequently leads to reduced working memory retrieval demands. A cascading pattern of interactions between pretrial and within-trial activity indicates the importance of preparatory brain activity. The study shows that there are multiple roles of beta and theta oscillations associated with different functional neuroanatomical structures during the integration and reactivation of motor elements during actions.NEW & NOTEWORTHY Even simple actions like opening a door require integration/binding and flexible reactivation of different motor elements. Yet, the neural mechanisms underlying the processing of such "embedded response plans" are largely elusive. The study shows that there are multiple roles of beta and theta oscillations associated with different functional neuroanatomical structures during the integration and reactivation of motor elements during actions.

The rubber hand illusion is accompanied by a distributed reduction of alpha and beta power in the EEG.

Previous studies have reported correlates of bodily self-illusions such as the rubber hand in signatures of rhythmic brain activity. However, individual studies focused on specific variations of the rubber hand paradigm, used different experimental setups to induce this, or used different control conditions to isolate the neurophysiological signatures related to the illusory state, leaving the specificity of the reported illusion-signatures unclear. We here quantified correlates of the rubber hand illusion in EEG-derived oscillatory brain activity and asked two questions: which of the observed correlates are robust to the precise nature of the control conditions used as contrast for the illusory state, and whether such correlates emerge directly around the subjective illusion onset. To address these questions, we relied on two experimental configurations to induce the illusion, on different non-illusion conditions to isolate neurophysiological signatures of the illusory state, and we implemented an analysis directly focusing on the immediate moment of the illusion onset. Our results reveal a widespread suppression of alpha and beta-band activity associated with the illusory state in general, whereby the reduction of beta power prevailed around the immediate illusion onset. These results confirm previous reports of a suppression of alpha and beta rhythms during body illusions, but also highlight the difficulties to directly pinpoint the precise neurophysiological correlates of the illusory state.

The modulatory effect of self-paced and cued motor execution on subthalamic beta-bursts in Parkinson's disease: Evidence from deep brain recordings in humans.

Deep brain stimulation (DBS) electrodes provide an unparalleled window to record and investigate neuronal activity right at the core of pathological brain circuits. In Parkinson's disease (PD), basal ganglia beta-oscillatory activity (13-35 Hz) seems to play an outstanding role. Conventional DBS, which globally suppresses beta-activity, does not meet the requirements of a targeted treatment approach given the intricate interplay of physiological and pathological effects of beta-frequencies. Here, we wanted to characterise the local field potential (LFP) in the subthalamic nucleus (STN) in terms of beta-burst prevalence, amplitude and length between movement and rest as well as during self-paced as compared to goal-directed motor control. Our electrophysiological recordings from externalised DBS-electrodes in nine patients with PD showed a marked decrease in beta-burst durations and prevalence during movement as compared to rest as well as shorter and less frequent beta-bursts during cued as compared to self-paced movements. These results underline the importance of beta-burst modulation in movement generation and are in line with the clinical observation that cued motor control is better preserved than self-paced movements. Furthermore, our findings motivate the use of adaptive DBS based on beta-bursts, which selectively trim longer beta-bursts, as it is more suitable and efficient over a range of motor behaviours than conventional DBS.

Self-regulation of the brain's right frontal Beta rhythm using a brain-computer interface.

Neural oscillations, or brain rhythms, fluctuate in a manner reflecting ongoing behavior. Whether these fluctuations are instrumental or epiphenomenal to the behavior remains elusive. Attempts to experimentally manipulate neural oscillations exogenously using noninvasive brain stimulation have shown some promise, but difficulty with tailoring stimulation parameters to individuals has hindered progress in this field. We demonstrate here using electroencephalography (EEG) neurofeedback in a brain-computer interface that human participants (n = 44) learned over multiple sessions across a 6-day period to self-regulate their Beta rhythm (13-20 Hz), either up or down, over the right inferior frontal cortex. Training to downregulate Beta was more effective than training to upregulate Beta. The modulation was evident only during neurofeedback task performance but did not lead to offline alteration of Beta rhythm characteristics at rest, nor to changes in subsequent cognitive behavior. Likewise, a control group (n = 38) who underwent training to up or downregulate the Alpha rhythm (8-12 Hz) did not exhibit behavioral changes. Although the right frontal Beta rhythm has been repeatedly implicated as a key component of the brain's inhibitory control system, the present data suggest that its manipulation offline prior to cognitive task performance does not result in behavioral change in healthy individuals. Whether this form of neurofeedback training could serve as a useful therapeutic target for disorders with dysfunctional inhibitory control as their basis remains to be tested in a context where performance is abnormally poor and neural dynamics are different.

[Interhemispheric asymmetry of EEG rhythm connections during spontaneous awakenings after short sleep episodes during a monotonous psychomotor test]. / Mezhpolusharnaya asimmetriya svyazei ritmov EEG pri spontannykh probuzhdeniyakh posle kratkovremennykh epizodov sna pri vypolnenii monotonnogo psikhomotornogo testa.

OBJECTIVE: To study interhemispheric asymmetry (IHA) according to electroencephalography (EEG) data of a healthy person during cognitive awakening from the second stage of daytime sleep before restoring the performance of the psychomotor test. MATERIAL AND METHODS: In 23 healthy adult subjects, we studied IHA in the amplitude-amplitude interaction of EEG rhythms for 20 sec segments before spontaneous awakening determined by the moment the alpha-rhythm appearance on the EEG and the subsequent onset of psychomotor activity. The state of the subject during this period (in the initial stage of the so-called cognitive awakening preceding the behavioral awakening), when the person is unable to move, but is able to perceive external stimuli, is an experimental model for highlighting signs of conscious activity of patients when coming out of a coma. Wavelet transform was used to calculate the rhythmic characteristics of bioelectrical activity. The Kendall correlation coefficient served as a measure of rhythm interaction. RESULTS: IHA in the interaction of EEG rhythms is dynamic nature and formed by theta rhythm connections with alpha2- and beta-rhythms in the left brain hemisphere and delta-type connections in the right. CONCLUSION: Possibly, the greater activation of the left hemisphere is related to the retrieval of an instruction from memory, which subsequently allows to return to the activity interrupted by sleep.

Spectral and spatial distribution of subthalamic beta peak activity in Parkinson's disease patients.

Current efforts to optimise subthalamic deep brain stimulation in Parkinson's disease patients aim to harness local oscillatory activity in the beta frequency range (13-35 Hz) as a feedback-signal for demand-based adaptive stimulation paradigms. A high prevalence of beta peak activity is prerequisite for this approach to become routine clinical practice. In a large dataset of postoperative rest recordings from 106 patients we quantified occurrence and identified determinants of spectral peaks in the alpha, low and high beta bands. At least one peak in beta band occurred in 92% of patients and 84% of hemispheres off medication, irrespective of demographic parameters, clinical subtype or motor symptom severity. Distance to previously described clinical sweet spot was significantly related both to beta peak occurrence and to spectral power (rho -0.21, p 0.006), particularly in the high beta band. Electrophysiological landscapes of our cohort's dataset in normalised space showed divergent heatmaps for alpha and beta but found similar regions for low and high beta frequency bands. We discuss potential ramifications for clinicians' programming decisions. In summary, this report provides robust evidence that spectral peaks in beta frequency range can be detected in the vast majority of Parkinsonian subthalamic nuclei, increasing confidence in the broad applicability of beta-guided deep brain stimulation.

Voluntary Motor Command Release Coincides with Restricted Sensorimotor Beta Rhythm Phases.

Sensory perception and memory are enhanced during restricted phases of ongoing brain rhythms, but whether voluntary movement is constrained by brain rhythm phase is not known. Voluntary movement requires motor commands to be released from motor cortex (M1) and transmitted to spinal motoneurons and effector muscles. Here, we tested the hypothesis that motor commands are preferentially released from M1 during circumscribed phases of ongoing sensorimotor rhythms. Healthy humans of both sexes performed a self-paced finger movement task during electroencephalography (EEG) and electromyography (EMG) recordings. We first estimated the time of motor command release preceding each finger movement by subtracting individually measured corticomuscular transmission latencies from EMG-determined movement onset times. Then, we determined the phase of ipsilateral and contralateral sensorimotor mu (8-12 Hz) and beta (13-35 Hz) rhythms during release of each motor command. We report that motor commands were most often released between 120 and 140° along the contralateral beta cycle but were released uniformly along the contralateral mu cycle. Motor commands were also released uniformly along ipsilateral mu and beta cycles. Results demonstrate that motor command release coincides with restricted phases of the contralateral sensorimotor beta rhythm, suggesting that sensorimotor beta rhythm phase may sculpt the timing of voluntary human movement.SIGNIFICANCE STATEMENT Perceptual and cognitive function is optimal during specific brain rhythm phases. Although brain rhythm phase influences motor cortical neuronal activity and communication between the motor cortex and spinal cord, its role in voluntary movement is poorly understood. Here, we show that the motor commands needed to produce voluntary movements are preferentially released from the motor cortex during contralateral sensorimotor beta rhythm phases. Our findings are consistent with the notion that sensorimotor rhythm phase influences the timing of voluntary human movement.

Periodic and aperiodic contributions to theta-beta ratios across adulthood.

The ratio of fronto-central theta (4-7 Hz) to beta oscillations (13-30 Hz), known as the theta-beta ratio, is negatively correlated with attentional control, reinforcement learning, executive function, and age. Although theta-beta ratios have been found to decrease with age in adolescents and young adults, theta has been found to increase with age in older adults. Moreover, age-related decrease in individual alpha peak frequency and flattening of the 1/f aperiodic component may artifactually inflate the association between theta-beta ratio and age. These factors lead to an incomplete understanding of how theta-beta ratio varies across the lifespan and the extent to which variation is due to a conflation of aperiodic and periodic activity. We conducted a partially preregistered analysis examining the cross-sectional associations between age and resting canonical fronto-central theta-beta ratio, individual alpha peak frequency, and aperiodic component (n = 268; age 36-84, M = 55.8, SD = 11.0). Age was negatively associated with theta-beta ratios, individual peak alpha frequencies, and the aperiodic exponent. The correlation between theta-beta ratios and age remained after controlling for individual peak alpha frequencies, but was nonsignificant when controlling for the aperiodic exponent. Aperiodic exponent fully mediated the relationship between theta-beta ratio and age, although beta remained significantly associated with age after controlling for theta, individual peak alpha, and aperiodic exponent. Results replicate previous observations and show age-related decreases in theta-beta ratios are not due to age-related decrease in individual peak alpha frequencies but primarily explained by flattening of the aperiodic component with age.

Reduced sensorimotor beta dynamics could represent a "slowed movement state" in healthy individuals.

It is well established that the amplitude of beta oscillations (∼13-30 Hz)-recorded over the sensorimotor cortex-distinctly change throughout movement. Specifically, a movement-related beta decrease (MRBD) occurs before and during movement, and a post-movement beta rebound (PMBR) follows. We investigated how the magnitude of the MRBD and PMBR vary when participants are put in an experimentally induced slow versus fast movement state. Individuals performed a task with blocks that elicited longer reaction times (RTs) and shorter RTs (SLOW and FAST blocks, respectively) while scalp-electroencephalography (EEG) was recorded. The timing of an upcoming movement was also modulated to create blocks with certain and uncertain response timing (FIXED and VARIED blocks, respectively). We found that beta modulation was reduced in SLOW blocks compared to FAST blocks (i.e., a less negative MRBD and less positive PMBR). For the movement certainty manipulation, we saw mixed behavioral and EEG results. Our primary finding of reduced beta modulation during an experimentally induced "slowed movement state" aligns with previous work showing reduced movement-related beta activity in patients with Parkinson's disease.

Cortical beta burst dynamics are altered in Parkinson's disease but normalized by deep brain stimulation.

Exaggerated subthalamic beta oscillatory activity and increased beta range cortico-subthalamic synchrony have crystallized as the electrophysiological hallmarks of Parkinson's disease. Beta oscillatory activity is not tonic but occurs in 'bursts' of transient amplitude increases. In Parkinson's disease, the characteristics of these bursts are altered especially in the basal ganglia. However, beta oscillatory dynamics at the cortical level and how they compare with healthy brain activity is less well studied. We used magnetoencephalography (MEG) to study sensorimotor cortical beta bursting and its modulation by subthalamic deep brain stimulation in Parkinson's disease patients and age-matched healthy controls. We show that the changes in beta bursting amplitude and duration typical of Parkinson's disease can also be observed in the sensorimotor cortex, and that they are modulated by chronic subthalamic deep brain stimulation, which, in turn, is reflected in improved motor function at the behavioural level. In addition to the changes in individual beta bursts, their timing relative to each other was altered in patients compared to controls: bursts were more clustered in untreated Parkinson's disease, occurring in 'bursts of bursts', and re-burst probability was higher for longer compared to shorter bursts. During active deep brain stimulation, the beta bursting in patients resembled healthy controls' data. In summary, both individual bursts' characteristics and burst patterning are affected in Parkinson's disease, and subthalamic deep brain stimulation normalizes some of these changes to resemble healthy controls' beta bursting activity, suggesting a non-invasive biomarker for patient and treatment follow-up.

Response-related sensorimotor rhythms under scopolamine and MK-801 exposures in the touchscreen visual discrimination test in rats.

The human mu rhythm has been suggested to represent an important function in information processing. Rodent homologue rhythms have been assumed though no study has investigated them from the cognitive aspect yet. As voluntary goal-directed movements induce the desynchronization of mu rhythm, we aimed at exploring whether the response-related brain activity during the touchscreen visual discrimination (VD) task is suitable to detect sensorimotor rhythms and their change under cognitive impairment. Different doses of scopolamine or MK-801 were injected subcutaneously to rats, and epidural electroencephalogram (EEG) was recorded during task performance. Arciform ~ 10 Hz oscillations appeared during visual processing, then two characteristic alpha/beta desynchronization-resynchronization patterns emerged mainly above the sensorimotor areas, serving presumably different motor functions. Beyond causing cognitive impairment, both drugs supressed the touch-related upper alpha (10-15 Hz) reactivity for desynchronization. Reaction time predominantly correlated positively with movement-related alpha and beta power both in normal and impaired conditions. These results support the existence of a mu homologue rodent rhythm whose upper alpha component appeared to be modulated by cholinergic and glutamatergic mechanisms and its power change might indicate a potential EEG correlate of processing speed. The VD task can be utilized for the investigation of sensorimotor rhythms in rats.

Conflict Detection in a Sequential Decision Task Is Associated with Increased Cortico-Subthalamic Coherence and Prolonged Subthalamic Oscillatory Response in the ß Band.

Making accurate decisions often involves the integration of current and past evidence. Here, we examine the neural correlates of conflict and evidence integration during sequential decision-making. Female and male human patients implanted with deep-brain stimulation (DBS) electrodes and age-matched and gender-matched healthy controls performed an expanded judgment task, in which they were free to choose how many cues to sample. Behaviorally, we found that while patients sampled numerically more cues, they were less able to integrate evidence and showed suboptimal performance. Using recordings of magnetoencephalography (MEG) and local field potentials (LFPs; in patients) in the subthalamic nucleus (STN), we found that ß oscillations signaled conflict between cues within a sequence. Following cues that differed from previous cues, ß power in the STN and cortex first decreased and then increased. Importantly, the conflict signal in the STN outlasted the cortical one, carrying over to the next cue in the sequence. Furthermore, after a conflict, there was an increase in coherence between the dorsal premotor cortex and STN in the ß band. These results extend our understanding of cortico-subcortical dynamics of conflict processing, and do so in a context where evidence must be accumulated in discrete steps, much like in real life. Thus, the present work leads to a more nuanced picture of conflict monitoring systems in the brain and potential changes because of disease.SIGNIFICANCE STATEMENT Decision-making often involves the integration of multiple pieces of information over time to make accurate predictions. We simultaneously recorded whole-head magnetoencephalography (MEG) and local field potentials (LFPs) from the human subthalamic nucleus (STN) in a novel task which required integrating sequentially presented pieces of evidence. Our key finding is prolonged ß oscillations in the STN, with a concurrent increase in communication with frontal cortex, when presented with conflicting information. These neural effects reflect the behavioral profile of reduced tendency to respond after conflict, as well as relate to suboptimal cue integration in patients, which may be directly linked to clinically reported side-effects of deep-brain stimulation (DBS) such as impaired decision-making and impulsivity.