Tting to assess the feasibility of using neurons in subcortical motor areas to drive a human brain-machine interface. METHODS: Acute ensemble recordings from subthalamic nucleus and thalamic motor areas (ventralis oralis posterior [VOP]/ventralis intermediate nucleus [VIM]) were obtained in 11 awake patients during deep brain stimulator surgery by use of a 32-microwire array. During extracellular neuronal recordings, patients simultaneously performed a visual feedback hand-gripping force task. Offline analysis was then used to explore the relationship between neuronal modulation and gripping force. RESULTS: Individual neurons (n = 28 VOP/VIM, n = 119 subthalamic nucleus) demonstrated a variety of modulation responses both before and after onset of changes in gripping force of the contralateral hand. Overall, 61% of subthalamic nucleus neurons and 81% of VOP/VIM neurons modulated with gripping force. Remarkably, ensembles of 3 to 55 simultaneously recorded neurons were sufficiently information-rich to predict gripping force during 30-second test periods with considerable accuracy (up to R = 0.82, R2 = 0.68) after short training periods. Longer training periods and larger neuronal ensembles were associated with improved predictive accuracy. CONCLUSION: This initial feasibility study bridges the gap between the nonhuman primate laboratory and the human intraoperative setting to suggest that neuronal ensembles from human subcortical motor regions may be able to provide informative control signals to a future brain-machine interface....

Brain function depends on complex metabolic interactions among only a few different cell types, with astrocytes providing critical support for neuron

The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (ie, tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (ie, reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials, and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical or magnetic resonance imaging changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms.

Neuronal activity, astrocytic responses to this activity, and energy homeostasis are linked together during baseline, conscious conditions, and short-term rapid activation (as occurs with sensory or motor function). Nervous system energy homeostasis also varies during long-term physiological conditions (i.e., development and aging) and with adaptation to pathological conditions, such as ischemia or low glucose. Neuronal activation requires increased metabolism (i.e., ATP generation) which leads initially to substrate depletion, induction of a variety of signals for enhanced astrocytic function, and increased local blood flow and substrate delivery. Energy generation (particularly in mitochondria) and use during ATP hydrolysis also lead to considerable heat generation. The local increases in blood flow noted following neuronal activation can both enhance local substrate delivery but also provides a heat sink to help cool the brain and removal of waste by-products. In this review we highlight the interactions between short-term neuronal activity and energy metabolism with an emphasis on signals and factors regulating astrocyte function and substrate supply.

Continuous deep brain stimulation (cDBS) of the subthalamic nucleus (STN) or globus pallidus (GP) is an effective treatment for the motor symptoms of Parkinson’s Disease (PD). The relative benefit of one region over the other is of great interest but cannot usually be compared in the same patient. Simultaneous DBS of both regions may synergistically increase the therapeutic benefit. CDBS is limited by a lack of responsiveness to dynamic, fluctuating symptoms intrinsic to the disease. Adaptive DBS (aDBS) adjusts stimulation in response to biomarkers to improve efficacy, side effects, and efficiency. We combined bilateral DBS of both STN and GP (dual target DBS) in a prospective within-participant, clinical trial in six PD patients (n = 6, 55 to 65 years, two women). Dual target cDBS was tested for PD symptom control annually over 2 years, measured by motor rating scales, ON time without dyskinesia, and medication reduction. Random amplitude experiments probed system dynamics to estimate parameters for aDBS. We then implemented proportional-plus-integral (PI) aDBS using a novel distributed (off-implant) architecture. In the home setting we collected tremor and dyskinesia scores as well as individualized beta and DBS amplitudes. Dual target cDBS reduced motor symptoms as measured by UPDRS to a greater degree than either region alone (p < 0.05, Linear Mixed Model) in the cohort. The amplitude of beta oscillations in the STN correlated to the speed of hand grasp movements for five of six participants (p < 0.05, Pearson correlation). Random amplitude experiments provided insight into temporal windowing to avoid stimulation artifacts and demonstrated a correlation between STN beta amplitude and DBS amplitude. PI control of aDBS reduced average power, while preserving Unified Parkinson’s Disease Rating Scale Motor Examination (UPDRS III) scores in the clinic (p = 0.28, Wilcoxon signed rank), and tremor and dyskinesia scores during blinded testing at home (n =3, p > 0.05, Wilcoxon ranked sum). In the home setting, DBS power reductions were slight but significant. Dual target cDBS may offer an improvement in treatment of motor symptoms of PD over DBS of either the STN or GP alone. When combined with PI aDBS, stimulation power may be reduced while preserving the increased benefit of dual target DBS.