Objective: Brain–computer interfaces (BCIs) could potentially be used to interact with pathological brain signals to intervene and ameliorate their effects in disease states. Here, we provide proof-of-principle of this approach by using a BCI to interpret pathological brain activity in patients with advanced Parkinson disease (PD) and to use this feedback to control when therapeutic deep brain stimulation (DBS) is delivered. Our goal was to demonstrate that by personalizing and optimizing stimulation in real time, we could improve on both the efficacy and efficiency of conventional continuous DBS.Methods: We tested BCI-controlled adaptive DBS (aDBS) of the subthalamic nucleus in 8 PD patients. Feedback was provided by processing of the local field potentials recorded directly from the stimulation electrodes. The results were compared to no stimulation, conventional continuous stimulation (cDBS), and random intermittent stimulation. Both unblinded and blinded clinical assessments of motor effect were performed using the Unified Parkinson's Disease Rating Scale.Results: Motor scores improved by 66% (unblinded) and 50% (blinded) during aDBS, which were 29% (p = 0.03) and 27% (p = 0.005) better than cDBS, respectively. These improvements were achieved with a 56% reduction in stimulation time compared to cDBS, and a corresponding reduction in energy requirements (p < 0.001). aDBS was also more effective than no stimulation and random intermittent stimulation.Interpretation BCI-controlled DBS is tractable and can be more efficient and efficacious than conventional continuous neuromodulation for PD. Ann Neurol 2013;74:449–457
SummaryIf humans are faced with difficult choices when making decisions, the ability to slow down responses becomes critical in order to avoid suboptimal choices. Current models of decision making assume that the subthalamic nucleus (STN) mediates this function by elevating decision thresholds, thereby requiring more evidence to be accumulated before responding [1, 2, 3, 4, 5, 6, 7, 8, 9]. However, direct electrophysiological evidence for the exact role of STN during adjustment of decision thresholds is lacking. Here, we show that trial-by-trial variations in STN low-frequency oscillatory activity predict adjustments of decision thresholds before subjects make a response. The relationship between STN activity and decision thresholds critically depends on the subjects’ level of cautiousness. While increased oscillatory activity of the STN predicts elevated decision thresholds during high levels of cautiousness, it predicts decreased decision thresholds during low levels of cautiousness. This context-dependent relationship may be mediated by increased influence of the medial prefrontal cortex (mPFC)-STN pathway on decision thresholds during high cautiousness. Subjects who exhibit a stronger increase in phase alignment of low-frequency oscillatory activity in mPFC and STN before making a response have higher decision thresholds and commit fewer erroneous responses. Together, our results demonstrate that STN low-frequency oscillatory activity and corresponding mPFC-STN coupling are involved in determining how much evidence subjects accumulate before making a decision. This finding might explain why deep-brain stimulation of the STN can impair subjects’ ability to slow down responses and can induce impulsive suboptimal decisions.
Use-dependent forms of synaptic plasticity have been extensively characterized at chemical synapses, but a relationship between natural activity and strength at electrical synapses remains elusive. The thalamic reticular nucleus (TRN), a brain area rich in gap-junctional (electrical) synapses, regulates cortical attention to the sensory surround and participates in shifts between arousal states; plasticity of electrical synapses may be a key mechanism underlying these processes. We observed long-term depression resulting from coordinated burst firing in pairs of coupled TRN neurons. Changes in gap-junctional communication were asymmetrical, indicating that regulation of connectivity depends on the direction of use. Modification of electrical synapses resulting from activity in coupled neurons is likely to be a widespread and powerful mechanism for dynamic reorganization of electrically coupled neuronal networks.
Making the right decision from conflicting information takes time. Recent computational, electrophysiological, and clinical studies have implicated two brain areas as being crucial in assuring sufficient time is taken for decision-making under conditions of conflict: the medial prefrontal cortex and the subthalamic nucleus (STN). Both structures exhibit an elevation of activity at low frequencies (Ͻ10 Hz) during conflict that correlates with the amount of time taken to respond. This suggests that the two sites could become functionally coupled during conflict. To establish the nature of this interaction we recorded from deep-brain stimulation electrodes implanted bilaterally in the STN of 13 Parkinson's disease patients while they performed a sensory integration task involving randomly moving dots. By gradually increasing the number of dots moving coherently in one direction, we were able to determine changes in the STN associated with response execution. Furthermore, by occasionally having 10% of the dots move in the opposite direction as the majority, we were able to identify an independent increase in STN theta-delta activity triggered by conflict. Crucially, simultaneous midline frontal electroencephalographic recordings revealed an increase in the theta-delta band coherence between the two structures that was specific to high-conflict trials. Activity over the midline frontal cortex was Granger causal to that in STN. These results establish the corticosubcortical circuit enabling successful choices to be made under conditions of conflict and provide support for the hypothesis that the brain uses frequency-specific channels of communication to convey behaviorally relevant information.
The subthalamic nucleus (STN) is thought to play a central role in modulating responses during conflict. Computational models have suggested that the location of the STN in the basal ganglia, as well as its numerous connections to conflict-related cortical structures, allows it to be ideally situated to act as a global inhibitor during conflict. Additionally, recent behavioral experiments have shown that deep brain stimulation to the STN results in impulsivity during high-conflict situations. However, the precise mechanisms that mediate the "hold-your-horses" function of the STN remain unclear. We recorded from deep brain stimulation electrodes implanted bilaterally in the STN of 13 human subjects with Parkinson's disease while they performed a flanker task. The incongruent trials with the shortest reaction times showed no behavioral or electrophysiological differences from congruent trials, suggesting that the distracter stimuli were successfully ignored. In these trials, cue-locked STN theta band activity demonstrated phase alignment across trials and was followed by a periresponse increase in theta power. In contrast, incongruent trials with longer reaction times demonstrated a relative reduction in theta phase alignment followed by higher theta power. Theta phase alignment negatively correlated with subject reaction time, and theta power positively correlated with trial reaction time. Thus, when conflicting stimuli are not properly ignored, disruption of STN theta phase alignment may help operationalize the hold-your-horses role of the nucleus, whereas later increases in the amplitude of theta oscillations may help overcome this function.
The subthalamic nucleus (STN), which is currently the most common target for deep brain stimulation for Parkinson’s disease, has received increased attention over the past few years for the roles it may play in functions beyond simple motor control. In this article we will highlight several of the theoretical, interventional, and electrophysiological studies that have implicated the STN in response inhibition. Most influential amongst this evidence has been the reported effect of STN deep brain stimulation in increasing impulsive responses in the laboratory setting. Yet, how this relates to pathological impulsivity in patient’s everyday lives remains uncertain.
There is increasing evidence that the medial prefrontal cortex participates in conflict and feedback monitoring while the subthalamic nucleus adjusts actions. Yet how these two structures coordinate their activity during cognitive control remains poorly understood. We recorded from the human prefrontal cortex and the subthalamic nucleus simultaneously while participants (n = 22) performed a novel task involving high conflict trials, complete response inhibition trials, and trial-to-trial behavioural adaptations to conflict and errors. Overall, we found that within-trial adaptions to both conflict and complete response inhibition involved changes in the theta band while across-trial behavioural adaptations to both conflict and errors involved changes in the beta band (P < 0.05). Yet the role each region’s theta and beta oscillations played during the task differed significantly between the two sites. Trials that involved either within-trial conflict or complete response inhibition were associated with increased theta phase synchrony between the medial prefrontal cortex and the subthalamic nucleus (P < 0.05). Despite increased synchrony, however, increases in prefrontal theta power were associated with response inhibition, while increases in subthalamic theta power were associated with response execution (P < 0.05). In the beta band, post-response increases in prefrontal beta power were suppressed when the completed trial contained either conflict or an erroneous response (P < 0.05). Subthalamic beta power, on the other hand, was only modified during the subsequent trial that followed a conflict or error trial. Notably, these adaptation trials exhibited slower response times (P < 0.05), suggesting that both brain regions contribute to across-trial adaptations but do so at different stages of the adaptation process. Taken together, our data shed light on the mechanisms underlying within-trial and across-trial cognitive control and how disruption of this network can negatively impact cognition. More broadly, however, our data also demonstrate that the specific role of a brain region, rather than the frequency being utilized, governs the behavioural correlates of oscillatory activity.
The medial prefrontal cortex (mPFC) is thought to control the shift from automatic to controlled action selection when conflict is present or when mistakes have been recently committed. Growing evidence suggests that this process involves frequency specific communication in the theta (4–8 Hz) band between the mPFC and the subthalamic nucleus (STN), which is the main target of deep brain stimulation (DBS) for Parkinson's disease. Key in this hypothesis is the finding that DBS can lead to impulsivity by disrupting the correlation between higher mPFC oscillations and slower reaction times during conflict. In order to test whether theta band coherence between the mPFC and the STN underlies adjustments to conflict and to errors, we simultaneously recorded mPFC and STN electrophysiological activity while DBS patients performed an arrowed flanker task. These recordings revealed higher theta phase coherence between the two sites during the high conflict trials relative to the low conflict trials. These differences were observed soon after conflicting arrows were displayed, but before a response was executed. Furthermore, trials that occurred after an error was committed showed higher phase coherence relative to trials that followed a correct trial, suggesting that mPFC–STN connectivity may also play a role in error related adjustments in behavior. Interestingly, the phase coherence we observed occurred before increases in theta power, implying that the theta phase and power may influence behavior at separate times during cortical monitoring. Finally, we showed that pre-stimulus differences in STN theta power were related to the reaction time on a given trial, which may help adjust behavior based on the probability of observing conflict during a task.
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