Risk-taking bias in human decision-making is encoded via a right-left brain push-pull system.

A person's decisions vary even when options stay the same, like when a gambler changes bets despite constant odds of winning. Internal bias (e.g., emotion) contributes to this variability and is shaped by past outcomes, yet its neurobiology during decision-making is not well understood. To map neural circuits encoding bias, we administered a gambling task to 10 participants implanted with intracerebral depth electrodes in cortical and subcortical structures. We predicted the variability in betting behavior within and across patients by individual bias, which is estimated through a dynamical model of choice. Our analysis further revealed that high-frequency activity increased in the right hemisphere when participants were biased toward risky bets, while it increased in the left hemisphere when participants were biased away from risky bets. Our findings provide electrophysiological evidence that risk-taking bias is a lateralized push-pull neural system governing counterintuitive and highly variable decision-making in humans.

An exploratory data analysis method for identifying brain regions and frequencies of interest from large-scale neural recordings.

High-resolution whole brain recordings have the potential to uncover unknown functionality but also present the challenge of how to find such associations between brain and behavior when presented with a large number of regions and spectral frequencies. In this paper, we propose an exploratory data analysis method that sorts through a massive quantity of multivariate neural recordings to quickly extract a subset of brain regions and frequencies that encode behavior. This approach combines existing tools and exploits low-rank approximation of matrices without a priori selection of regions and frequency bands for analysis. In detail, the spectral content of neural activity across all frequencies of each recording contact is computed and represented as a matrix. Then, the rank-1 approximation of the matrix is computed using singular value decomposition and the associated singular vectors are extracted. The temporal singular vector, which captures the salient features of the spectrogram, is then correlated to the trial-varying behavioral signal. The distribution of correlations for each brain region is efficiently computed and used to find a subset of regions and frequency bands of interest for further examination. As an illustration, we apply this approach to a data set of local field potentials collected using stereoelectroencephalography from a human subject performing a reaching task. Using the proposed procedure, we produced a comprehensive set of brain regions and frequencies related to our specific behavior. We demonstrate how this tool can produce preliminary results that capture neural patterns related to behavior and aid in formulating data-driven hypotheses, hence reducing the time it takes for any scientist to transition from the exploratory to the confirmatory phase.

Deep brain stimulation of the ventral striatal area for poststroke pain syndrome: a magnetoencephalography study.

Poststroke pain syndrome (PSPS) is an often intractable disorder characterized by hemiparesis associated with unrelenting chronic pain. Although traditional analgesics have largely failed, integrative approaches targeting affective-cognitive spheres have started to show promise. Recently, we demonstrated that deep brain stimulation (DBS) of the ventral striatal area significantly improved the affective sphere of pain in patients with PSPS. In the present study, we examined whether electrophysiological correlates of pain anticipation were modulated by DBS that could serve as signatures of treatment effects. We recorded event-related fields (ERFs) of pain anticipation using magnetoencephalography (MEG) in 10 patients with PSPS preoperatively and postoperatively in DBS OFF and ON states. Simple visual cues evoked anticipation as patients awaited a painful (PS) or nonpainful stimulus (NPS) to the nonaffected or affected extremity. Preoperatively, ERFs showed no difference between PS and NPS anticipation to the affected extremity, possibly due to loss of salience in a network saturated by pain experience. DBS significantly modulated the early N1, consistent with improvements in affective networks involving restoration of salience and discrimination capacity. Additionally, DBS suppressed the posterior P2 (aberrant anticipatory anxiety) while enhancing the anterior N1 (cognitive and emotional regulation) in responders. DBS-induced changes in ERFs could potentially serve as signatures for clinical outcomes. NEW & NOTEWORTHY We examined the electrophysiological correlates of pain affect in poststroke pain patients who underwent deep brain stimulation (DBS) targeting the ventral striatal area under a randomized, controlled trial. DBS significantly modulated early event-related components, particularly N1 and P2, measured with magnetoencephalography during a pain anticipatory task, compared with baseline and the DBS-OFF condition, pointing to possible mechanisms of action. DBS-induced changes in event-related fields could potentially serve as biomarkers for clinical outcomes.

Therapeutic mechanisms of high-frequency stimulation in Parkinson's disease and neural restoration via loop-based reinforcement.

High-frequency deep brain stimulation (HFS) is clinically recognized to treat parkinsonian movement disorders, but its mechanisms remain elusive. Current hypotheses suggest that the therapeutic merit of HFS stems from increasing the regularity of the firing patterns in the basal ganglia (BG). Although this is consistent with experiments in humans and animal models of Parkinsonism, it is unclear how the pattern regularization would originate from HFS. To address this question, we built a computational model of the cortico-BG-thalamo-cortical loop in normal and parkinsonian conditions. We simulated the effects of subthalamic deep brain stimulation both proximally to the stimulation site and distally through orthodromic and antidromic mechanisms for several stimulation frequencies (20-180 Hz) and, correspondingly, we studied the evolution of the firing patterns in the loop. The model closely reproduced experimental evidence for each structure in the loop and showed that neither the proximal effects nor the distal effects individually account for the observed pattern changes, whereas the combined impact of these effects increases with the stimulation frequency and becomes significant for HFS. Perturbations evoked proximally and distally propagate along the loop, rendezvous in the striatum, and, for HFS, positively overlap (reinforcement), thus causing larger poststimulus activation and more regular patterns in striatum. Reinforcement is maximal for the clinically relevant 130-Hz stimulation and restores a more normal activity in the nuclei downstream. These results suggest that reinforcement may be pivotal to achieve pattern regularization and restore the neural activity in the nuclei downstream and may stem from frequency-selective resonant properties of the loop.

Dynamics of Propofol-Induced Loss of Consciousness Across Primate Neocortex.

UNLABELLED: The precise neural mechanisms underlying transitions between consciousness and anesthetic-induced unconsciousness remain unclear. Here, we studied intracortical neuronal dynamics leading to propofol-induced unconsciousness by recording single-neuron activity and local field potentials directly in the functionally interconnecting somatosensory (S1) and frontal ventral premotor (PMv) network during a gradual behavioral transition from full alertness to loss of consciousness (LOC) and on through a deeper anesthetic level. Macaque monkeys were trained for a behavioral task designed to determine the trial-by-trial alertness and neuronal response to tactile and auditory stimulation. We show that disruption of coherent beta oscillations between S1 and PMv preceded, but did not coincide with, the LOC. LOC appeared to correspond to pronounced but brief gamma-/high-beta-band oscillations (lasting ∼3 min) in PMv, followed by a gamma peak in S1. We also demonstrate that the slow oscillations appeared after LOC in S1 and then in PMv after a delay, together suggesting that neuronal dynamics are very different across S1 versus PMv during LOC. Finally, neurons in both S1 and PMv transition from responding to bimodal (tactile and auditory) stimulation before LOC to only tactile modality during unconsciousness, consistent with an inhibition of multisensory integration in this network. Our results show that propofol-induced LOC is accompanied by spatiotemporally distinct oscillatory neuronal dynamics across the somatosensory and premotor network and suggest that a transitional state from wakefulness to unconsciousness is not a continuous process, but rather a series of discrete neural changes. SIGNIFICANCE STATEMENT: How information is processed by the brain during awake and anesthetized states and, crucially, during the transition is not clearly understood. We demonstrate that neuronal dynamics are very different within an interconnecting cortical network (primary somatosensory and frontal premotor area) during the loss of consciousness (LOC) induced by propofol in nonhuman primates. Coherent beta oscillations between these regions are disrupted before LOC. Pronounced but brief gamma-band oscillations appear to correspond to LOC. In addition, neurons in both of these cortices transition from responding to both tactile and auditory stimulation before LOC to only tactile modality during unconsciousness. We demonstrate that propofol-induced LOC is accompanied by spatiotemporally distinctive neuronal dynamics in this network with concurrent changes in multisensory processing.

Pain anticipatory phenomena in patients with central poststroke pain: a magnetoencephalography study.

Central poststroke pain (CPSP) is characterized by hemianesthesia associated with unrelenting chronic pain. The final pain experience stems from interactions between sensory, affective, and cognitive components of chronic pain. Hence, managing CPSP will require integrated approaches aimed not only at the sensory but also the affective-cognitive spheres. A better understanding of the brain's processing of pain anticipation is critical for the development of novel therapeutic approaches that target affective-cognitive networks and alleviate pain-related disability. We used magnetoencephalography (MEG) to characterize the neural substrates of pain anticipation in patients suffering from intractable CPSP. Simple visual cues evoked anticipation while patients awaited impending painful (PS), nonpainful (NPS), or no stimulus (NOS) to their nonaffected and affected extremities. MEG responses were studied at gradiometer level using event-related fields analysis and time-frequency oscillatory analysis upon source localization. On the nonaffected side, significantly greater responses were recorded during PS. PS (vs. NPS and NOS) exhibited significant parietal and frontal cortical activations in the beta and gamma bands, respectively, whereas NPS (vs. NOS) displayed greater activation in the orbitofrontal cortex. On the affected extremity, PS (vs. NPS) did not show significantly greater responses. These data suggest that anticipatory phenomena can modulate neural activity when painful stimuli are applied to the nonaffected extremity but not the affected extremity in CPSP patients. This dichotomy may stem from the chronic effects of pain on neural networks leading to habituation or saturation. Future clinically effective therapies will likely be associated with partial normalization of the neurophysiological correlates of pain anticipation.

Chronic deep cerebellar stimulation promotes long-term potentiation, microstructural plasticity, and reorganization of perilesional cortical representation in a rodent model.

Control over postinjury CNS plasticity is a major frontier of science that, if conquered, would open new avenues for treatment of neurological disorders. Here we investigate the functional, physiological, and structural changes in the cerebral cortex associated with chronic deep brain stimulation of the cerebellar output, a treatment approach that has been shown to improve postischemia motor recovery in a rodent model of cortical infarcts. Long-Evans rats were pretrained on the pasta-matrix retrieval task, followed by induction of focal cortical ischemia and implantation of a macroelectrode in the contralesional lateral cerebellar nucleus. Animals were assigned to one of three treatment groups pseudorandomly to balance severity of poststroke motor deficits: REGULAR stimulation, BURST stimulation, or SHAM. Treatment initiated 2 weeks post surgery and continued for 5 weeks. At the end, animals were randomly selected for perilesional intracortical microstimulation mapping and tissue sampling for Western blot analysis or contributed tissue for 3D electron microscopy. Evidence of enhanced cortical plasticity with therapeutically effective stimulation is shown, marked by greater perilesional reorganization in stimulation- treated animals versus SHAM. BURST stimulation was significantly effective for promoting distal forepaw cortical representation. Stimulation-treated animals showed a twofold increase in synaptic density compared with SHAM. In addition, treated animals demonstrated increased expression of synaptic markers of long-term potentiation and plasticity, including synaptophysin, NMDAR1, CaMKII, and PSD95. These findings provide a critical foundation of how deep cerebellar stimulation may guide plastic reparative reorganization after nonprogressive brain injury and indicate strong translational potential.

Defense-like behaviors evoked by pharmacological disinhibition of the superior colliculus in the primate.

Stimulation of the intermediate and deep layers of superior colliculus (DLSC) in rodents evokes both orienting/pursuit (approach) and avoidance/flight (defense) responses (Dean et al., 1989). These two classes of response are subserved by distinct output projections associated with lateral (approach) and medial (defense) DLSC (Comoli et al., 2012). In non-human primates, DLSC has been examined only with respect to orienting/approach behaviors, especially eye movements, and defense-like behaviors have not been reported. Here we examined the profile of behavioral responses evoked by activation of DLSC by unilateral intracerebral infusions of the GABA(A) receptor antagonist, bicuculline methiodide (BIC), in nine freely moving macaques. Across animals, the most consistently evoked behavior was cowering (all animals), followed by increased vocalization and escape-like behaviors (seven animals), and attack of objects (three animals). The effects of BIC were dose-dependent within the range 2.5-14 nmol (threshold dose of 4.6 nmol). The behaviors and their latencies to onset did not vary across different infusion sites within DLSC. Cowering and escape-like behaviors resembled the defense-like responses reported after DLSC stimulation in rats, but in the macaques these responses were evoked from both medial and lateral sites within DLSC. Our findings are unexpected in the context of an earlier theoretical perspective (Dean et al., 1989) that emphasized a preferential role of the primate DLSC for approach rather than defensive responses. Our data provide the first evidence for induction of defense-like behaviors by activation of DLSC in monkeys, suggesting that the role of DLSC in responding to threats is conserved across species.

Single-neuron responses in the human nucleus accumbens during a financial decision-making task.

Linking values to actions and evaluating expectations relative to outcomes are both central to reinforcement learning and are thought to underlie financial decision-making. However, neurophysiology studies of these processes in humans remain limited. Here, we recorded the activity of single human nucleus accumbens neurons while subjects performed a gambling task. We show that the nucleus accumbens encodes two signals related to subject behavior. First, we find that under relatively predictable conditions, single neuronal activity predicts future financial decisions on a trial-by-trial basis. Interestingly, we show that this activity continues to predict decisions even under conditions of uncertainty (e.g., when the probability of winning or losing is 50/50 and no particular financial choice predicts a rewarding outcome). Furthermore, we find that this activity occurs, on average, 2 s before the subjects physically manifest their decision. Second, we find that the nucleus accumbens encodes the difference between expected and realized outcomes, consistent with a prediction error signal. We show this activity occurs immediately after the subject has realized the outcome of the trial and is present on both the individual and population neuron levels. These results provide human single neuronal evidence that the nucleus accumbens is integral in making financial decisions.

Electrical stimulation-evoked dopamine release in the primate striatum.

BACKGROUND: Primate studies demonstrate that high-frequency electrical stimulation (HFS) of the caudate can enhance learning. Importantly, in these studies, stimulation was applied following the execution of behavior and the effect persisted into subsequent trials, suggesting a change in plasticity rather than a momentary facilitation of behavior. OBJECTIVES/METHODS: Although the mechanism of HFS-enhanced learning is not understood, evidence suggests that dopamine plays a critical role. Therefore, we used in vivo amperometry to evaluate the effects of HFS on striatal dopamine release in the anesthetized primate. While this does not directly examine dopamine during learning, it provides insight with relation to dopamine dynamics during electrical stimulation and specifically between different stimulation parameters and striatal compartments. RESULTS: We demonstrate that HFS results in significantly more dopamine release in the striatum compared to low-frequency stimulation. In addition, electrical stimulation operates differentially on specific neuronal elements, as the parameters for dopamine release are different for the caudate, putamen and medial forebrain bundle. CONCLUSIONS: While not direct evidence, these data suggest that HFS evokes significant dopamine release which may play a role in stimulation-enhanced learning. Moreover, these data suggest a means to modulate extracellular dopamine with a high degree of temporal and spatial precision for either research or clinical applications.

Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks.

Humans' ability to adapt and learn relies on reflecting on past performance. These experiences form latent representations called internal states that induce movement variability that improves how we interact with our environment. Our study uncovered temporal dynamics and neural substrates of two states from ten subjects implanted with intracranial depth electrodes while they performed a goal-directed motor task with physical perturbations. We identified two internal states using state-space models: one tracking past errors and the other past perturbations. These states influenced reaction times and speed errors, revealing how subjects strategize from trial history. Using local field potentials from over 100 brain regions, we found large-scale brain networks such as the dorsal attention and default mode network modulate visuospatial attention based on recent performance and environmental feedback. Notably, these networks were more prominent in higher-performing subjects, emphasizing their role in improving motor performance by regulating movement variability through internal states.

Basal ganglia neurons dynamically facilitate exploration during associative learning.

The basal ganglia (BG) appear to play a prominent role in associative learning, the process of pairing external stimuli with rewarding responses. Accumulating evidence suggests that the contributions of various BG components may be described within a reinforcement learning model, in which a broad repertoire of possible responses to environmental stimuli are evaluated before the most profitable one is chosen. The striatum receives diverse cortical inputs, providing a rich source of contextual information about environmental cues. It also receives projections from midbrain dopaminergic neurons, whose phasic activity reflects a reward prediction error signal. These coincident information streams are well suited for evaluating responses and biasing future actions toward the most profitable response. Still lacking in this model is a mechanistic description of how initial response variability is generated. To investigate this question, we recorded the activity of single neurons in the globus pallidus internus (GPi), the primary BG output nucleus, in nonhuman primates (Macaca mulatta) performing a motor associative learning task. A subset (29%) of GPi neurons showed learning-related effects, decreasing firing during the early stages of learning, then returning to higher baseline rates as associations were mastered. On a trial-by-trial basis, lower firing rates predicted exploratory behavior, whereas higher rates predicted an exploitive response. These results suggest that, during associative learning, BG output is initially permissive, allowing exploration of a variety of responses. Once a profitable response is identified, increased GPi activity suppresses alternative responses, sharpening the response profile and encouraging exploitation of the profitable learned behavior.

Heterogeneous neuronal firing patterns during interictal epileptiform discharges in the human cortex.

Epileptic cortex is characterized by paroxysmal electrical discharges. Analysis of these interictal discharges typically manifests as spike-wave complexes on electroencephalography, and plays a critical role in diagnosing and treating epilepsy. Despite their fundamental importance, little is known about the neurophysiological mechanisms generating these events in human focal epilepsy. Using three different systems of microelectrodes, we recorded local field potentials and single-unit action potentials during interictal discharges in patients with medically intractable focal epilepsy undergoing diagnostic workup for localization of seizure foci. We studied 336 single units in 20 patients. Ten different cortical areas and the hippocampus, including regions both inside and outside the seizure focus, were sampled. In three of these patients, high density microelectrode arrays simultaneously recorded between 43 and 166 single units from a small (4 mm x 4 mm) patch of cortex. We examined how the firing rates of individual neurons changed during interictal discharges by determining whether the firing rate during the event was the same, above or below a median baseline firing rate estimated from interictal discharge-free periods (Kruskal-Wallis one-way analysis, P<0.05). Only 48% of the recorded units showed such a modulation in firing rate within 500 ms of the discharge. Units modulated during the discharge exhibited significantly higher baseline firing and bursting rates than unmodulated units. As expected, many units (27% of the modulated population) showed an increase in firing rate during the fast segment of the discharge (+ or - 35 ms from the peak of the discharge), while 50% showed a decrease during the slow wave. Notably, in direct contrast to predictions based on models of a pure paroxysmal depolarizing shift, 7.7% of modulated units recorded in or near the seizure focus showed a decrease in activity well ahead (0-300 ms) of the discharge onset, while 12.2% of units increased in activity in this period. No such pre-discharge changes were seen in regions well outside the seizure focus. In many recordings there was also a decrease in broadband field potential activity during this same pre-discharge period. The different patterns of interictal discharge-modulated firing were classified into more than 15 different categories. This heterogeneity in single unit activity was present within small cortical regions as well as inside and outside the seizure onset zone, suggesting that interictal epileptiform activity in patients with epilepsy is not a simple paroxysm of hypersynchronous excitatory activity, but rather represents an interplay of multiple distinct neuronal types within complex neuronal networks.

Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation.

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is a promising intervention for treatment-resistant depression (TRD). Despite the failure of a clinical trial, multiple case series have described encouraging results, especially with the introduction of improved surgical protocols. Recent evidence further suggests that tractography targeting and intraoperative exposure to stimulation enhances early antidepressant effects that further evolve with ongoing chronic DBS. Accelerating treatment gains is critical to the care of this at-risk population, and identification of intraoperative electrophysiological biomarkers of early antidepressant effects will help guide future treatment protocols. Eight patients underwent intraoperative electrophysiological recording when bilateral DBS leads were implanted in the SCC using a connectomic approach at the site previously shown to optimize 6-month treatment outcomes. A machine learning classification method was used to discriminate between intracranial local field potentials (LFPs) recorded at baseline (stimulation-naïve) and after the first exposure to SCC DBS during surgical procedures. Spectral inputs (theta, 4-8 Hz; alpha, 9-12 Hz; beta, 13-30 Hz) to the model were then evaluated for importance to classifier success and tested as predictors of the antidepressant response. A decline in depression scores by 45.6% was observed after 1 week and this early antidepressant response correlated with a decrease in SCC LFP beta power, which most contributed to classifier success. Intraoperative exposure to therapeutic stimulation may result in an acute decrease in symptoms of depression following SCC DBS surgery. The correlation of symptom improvement with an intraoperative reduction in SCC beta power suggests this electrophysiological finding as a biomarker for treatment optimization.

Clinical outcomes of globus pallidus deep brain stimulation for Parkinson disease: a comparison of intraoperative MRI- and MER-guided lead placement.

OBJECTIVE: Deep brain stimulation (DBS) lead placement is increasingly performed with the patient under general anesthesia by surgeons using intraoperative MRI (iMRI) guidance without microelectrode recording (MER) or macrostimulation. The authors assessed the accuracy of lead placement, safety, and motor outcomes in patients with Parkinson disease (PD) undergoing DBS lead placement into the globus pallidus internus (GPi) using iMRI or MER guidance. METHODS: The authors identified all patients with PD who underwent either MER- or iMRI-guided GPi-DBS lead placement at Emory University between July 2007 and August 2016. Lead placement accuracy and adverse events were determined for all patients. Clinical outcomes were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS) part III motor scores for patients completing 12 months of follow-up. The authors also assessed the levodopa-equivalent daily dose (LEDD) and stimulation parameters. RESULTS: Seventy-seven patients were identified (MER, n = 28; iMRI, n = 49), in whom 131 leads were placed. The stereotactic accuracy of the surgical procedure with respect to the planned lead location was 1.94 ± 0.21 mm (mean ± SEM) (95% CI 1.54-2.34) with frame-based MER and 0.84 ± 0.007 mm (95% CI 0.69-0.98) with iMRI. The rate of serious complications was similar, at 6.9% for MER-guided DBS lead placement and 9.4% for iMRI-guided DBS lead placement (RR 0.71 [95% CI 0.13%-3.9%]; p = 0.695). Fifty-seven patients were included in clinical outcome analyses (MER, n = 16; iMRI, n = 41). Both groups had similar characteristics at baseline, although patients undergoing MER-guided DBS had a lower response on their baseline levodopa challenge (44.8% ± 5.4% [95% CI 33.2%-56.4%] vs 61.6% ± 2.1% [95% CI 57.4%-65.8%]; t = 3.558, p = 0.001). Greater improvement was seen following iMRI-guided lead placement (43.2% ± 3.5% [95% CI 36.2%-50.3%]) versus MER-guided lead placement (25.5% ± 6.7% [95% CI 11.1%-39.8%]; F = 5.835, p = 0.019). When UPDRS III motor scores were assessed only in the contralateral hemibody (per-lead analyses), the improvements remained significantly different (37.1% ± 7.2% [95% CI 22.2%-51.9%] and 50.0% ± 3.5% [95% CI 43.1%-56.9%] for MER- and iMRI-guided DBS lead placement, respectively). Both groups exhibited similar reductions in LEDDs (21.2% and 20.9%, respectively; F = 0.221, p = 0.640). The locations of all active contacts and the 2D radial distance from these to consensus coordinates for GPi-DBS lead placement (x, ±20; y, +2; and z, -4) did not differ statistically by type of surgery. CONCLUSIONS: iMRI-guided GPi-DBS lead placement in PD patients was associated with significant improvement in clinical outcomes, comparable to those observed following MER-guided DBS lead placement. Furthermore, iMRI-guided DBS implantation produced a similar safety profile to that of the MER-guided procedure. As such, iMRI guidance is an alternative to MER guidance for patients undergoing GPi-DBS implantation for PD.

Neural Correlates of Internal States that Capture Movement Variability.

The brain lacks the ability to perfectly replicate movements. In particular, if specific movements are cued sequentially, how you perform on past trials may influence how you move on current and future trials. Past trial outcomes may, for example, modulate motivation or attention which can play a significant role in how one moves, yet variability due to such internal factors are often ignored when modeling the sensorimotor control system. In this study, we wish to extract such internal factors by modeling variability in movements during a motor task riddled with unpredictable perturbations. Four subjects performed the task, and we simultaneously obtained Local Field Potential (LFP) activity from nonmotor brain regions via depth electrodes implanted for clinical purposes. We first show that motor behavior depends not only on current trial conditions, but also on internal state variables that accumulate past outcomes involving movement performance, movement speed, and whether or not perturbations have occurred. We further show that these internal states modulate with beta band activity in specific brain regions on a trial-by-trial basis. These results suggest a nontraditional role of nonmotor brain regions and prompt a need for further exploration.

Neural Activity from Attention Networks Predicts Movement Errors.

Traditionally, movement-related behavior is estimated using activity from motor regions in the brain. This predictive capability of interpreting neural signals into tangible outputs has led to the emergence of Brain-Computer Interface (BCI) systems. However, nonmotor regions can play a significant role in shaping how movements are executed. Our goal was to explore the contribution of nonmotor brain regions to movement using a unique experimental paradigm in which local field potential recordings of several cortical and subcortical regions were obtained from eight epilepsy patients implanted with depth electrodes as they performed goal-directed reaching movements. The instruction of the task was to move a cursor with a robotic arm to the indicated target with a specific speed, where correct trials were ones in which the subject achieved the instructed speed. We constructed subject-specific models that predict the speed error of each trial from neural activity in nonmotor regions. Neural features were found by averaging spectral power of activity in multiple frequency bands produced during the planning or execution of movement. Features with high predictive power were selected using a forward selection greedy search. Using our modeling framework, we were able to identify networks of regions related to attention that significantly contributed to predicting trial errors. Our results suggest that nonmotor brain regions contain relevant information about upcoming movements and should be further studied.

Non-motor Brain Regions in Non-dominant Hemisphere Are Influential in Decoding Movement Speed.

Sensorimotor control studies have predominantly focused on how motor regions of the brain relay basic movement-related information such as position and velocity. However, motor control is often complex, involving the integration of sensory information, planning, visuomotor tracking, spatial mapping, retrieval and storage of memories, and may even be emotionally driven. This suggests that many more regions in the brain are involved beyond premotor and motor cortices. In this study, we exploited an experimental setup wherein activity from over 87 non-motor structures of the brain were recorded in eight human subjects executing a center-out motor task. The subjects were implanted with depth electrodes for clinical purposes. Using training data, we constructed subject-specific models that related spectral power of neural activity in six different frequency bands as well as a combined model containing the aggregation of multiple frequency bands to movement speed. We then tested the models by evaluating their ability to decode movement speed from neural activity in the test data set. The best models achieved a correlation of 0.38 ± 0.03 (mean ± standard deviation). Further, the decoded speeds matched the categorical representation of the test trials as correct or incorrect with an accuracy of 70 ± 2.75% across subjects. These models included features from regions such as the right hippocampus, left and right middle temporal gyrus, intraparietal sulcus, and left fusiform gyrus across multiple frequency bands. Perhaps more interestingly, we observed that the non-dominant hemisphere (ipsilateral to dominant hand) was most influential in decoding movement speed.

BrdU-induced hyperlocomotion in the stroked rat.

5-bromo-2'-dexoyuridine (BrdU) is often used in neuroscience research as a marker of newly-divided cells. However, several studies suggest that BrdU can produce unwanted side effects, including changes in animal behavior and cellular function. In this study, we investigated the effect of BrdU injections on locomotor behavior in a rodent model of ischemic stroke. Ischemic strokes were induced in adult rats, and 50 mg/kg BrdU was intraperitoneally injected over 5 days beginning 2 weeks post-stroke, while control animals received vehicle. Locomotor activity was evaluated by videotaping the rats in their home cages for 30 min, beginning one hour after BrdU injection. BrdU-injected rats showed a nearly three-fold increase in locomotor activity compared to control animals. These findings suggest that BrdU induces a hyperlocomotor effect in rats following brain injury, pointing to the need for caution when interpreting behavioral results in such studies.

Modulations in Oscillatory Activity of Globus Pallidus Internus Neurons During a Directed Hand Movement Task-A Primary Mechanism for Motor Planning.

Globus pallidus internus (GPi) neurons in the basal ganglia are traditionally thought to play a significant role in the promotion and suppression of movement via a change in firing rates. Here, we hypothesize that a primary mechanism of movement control by GPi neurons is through specific modulations in their oscillatory patterns. We analyzed neuronal spiking activity of 83 GPi neurons recorded from two healthy nonhuman primates executing a radial center-out motor task. We found that, in directionally tuned neurons, the power in the gamma band is significantly (p < 0.05) greater than that in the beta band (a "cross-over" effect), during the planning stages of movements in their preferred direction. This cross-over effect is not observed in the non-directionally tuned neurons. These data suggest that, during movement planning, information encoding by GPi neurons may be governed by a sudden emergence and suppression of oscillatory activities, rather than simply by a change in average firing rates.