Recently, we proposed a Kalman filter method to model the probabilistic relationship between neural firing in motor cortex and hand kinematics. In this paper, we demonstrate on-line, closed-loop, neural control of cursor motion using the Kalman filter. In this task a monkey moves a cursor on a computer monitor using either a manipulandum or their neural activity recorded with a chronically implanted micro-electrode array. A number of advantages of the Kalman filter were explored during the on-line tasks and we found that the Kalman filter had superior performance to previously reported linear regression methods. While the results suggest the applicability of the Kalman filter for neural prosthesis applications, we observed the decoded cursor position was noisier under brain control as compared with manual control using the manipulandum. To smooth the cursor motion without decreasing accuracy we propose a method that smoothes the neural firing rates. This smoothing method is described and its validity is quantitatively evaluated with recorded data.

BACKGROUND AND PURPOSE: Reperfusion following intra-arterial stroke therapy is associated with improved clinical outcomes. However, the degree of reperfusion needed to achieve successful outcomes is unknown. The purpose of this analysis was to determine whether the degree of reperfusion has an impact on final infarct volumes and clinical outcomes. MATERIALS AND METHODS: A retrospective analysis identified 88 consecutive patients who underwent intra-arterial therapy for acute anterior circulation stroke. Reperfusion was graded by using the TICI scale into none (TICI 0 or 1), partial (TICI 2a), or near-complete (TICI 2b/3). Baseline characteristics were compared. For each of these groups, we compared discharge disposition and final infarct volumes. RESULTS: Near-complete, partial, and no reperfusion occurred in 44.3%, 26.1%, and 29.6% of patients, respectively. Baseline characteristics were similar across all 3 groups. The median NIHSS score was 15. Significant differences in discharge disposition were seen, with 41.0% of the TICI 2b/3 group discharged home versus 17.4% of TICI 2a and 7.7% of TICI 0/1. In-hospital mortality was 12.8% for TICI 2b/3 compared with 39.1% for TICI 2a and 34.6% for TICI 0/1. Patients with near-complete reperfusion were significantly more likely to have infarct volumes ≤70 mL (OR = 12.1; 95% CI, 2.7–54.2), compared with patients with partial reperfusion (OR = 2.2; 95% CI, 0.5–9.6). CONCLUSIONS: Significant differences exist in outcomes and infarct volumes between partial (TICI 2a) and near-complete (TICI 2b/3) reperfusion following intra-arterial stroke therapy. Further trials should separately report these groups to facilitate comparison among treatment paradigms.

Introducing neural sensing and decoding to open-loop neurostimulation technologies has the potential to significantly improve the diagnosis and treatment of a wide variety of diseases treated through bioelectronic medicine. Chronically implanted multi-electrode arrays (MEA) can be used for such neural sensing and are critical for obtaining data of high spatial and temporal resolution to provide accurate decoding. Signals recorded from these arrays include local field potentials (LFP), and multiunit (MU) and single-unit (SU) activity. LFP offer signal stability over time, but at the expense of decreased spatial resolution. SU activity, on the other hand, offers better spatial resolution, but is considered less stable in chronic applications. MU activity, which represents an aggregate spiking activity of a population of neurons on the order of several hundred microns away from the recording tip, is considered a signal that can offer a compromise between the two signals. Here we used a wavelet decomposition method to extract and characterize the LFP, MU and SU signals obtained from a 96-channel MEA implanted in the motor cortex of a nonhuman primate over a 7.5-month period. We observed that not only are the MU signals more stable over time compared with SU activity, but that they are also significantly less correlated among electrodes compared with LFP over the spatial scale of the implanted array. Histological analysis of tissue sections also revealed a 51% reduction in the number of neuronal cell bodies within a radius around the electrode tips of the implanted tissue compared with control tissue. Our results indicate that MU activity offers long-term signal stability with less correlated signals, potentially providing an effective signal for neural sensing in bioelectronic medicine.

Primary motor cortex (M1), a key region for voluntary motor control, has been considered a first choice as the source of neural signals to control prosthetic devices for humans with paralysis. Less is known about the potential for other areas of frontal cortex as prosthesis signal sources. The frontal cortex is widely engaged in voluntary behavior. Single-neuron recordings in monkey frontal cortex beyond M1 have readily identified activity related to planning and initiating movement direction, remembering movement instructions over delays, or mixtures of these features. Human functional imaging and lesion studies also support this role. Intraoperative mapping during deep brain stimulator placement in humans provides a unique opportunity to evaluate potential prosthesis control signals derived from nonprimary areas and to expand our understanding of frontal lobe function and its role in movement disorders. This study shows that recordings from small groups of human prefrontal/premotor cortex neurons can provide information about movement planning, production, and decision-making sufficient to decode the planned direction of movement. Thus, additional frontal areas, beyond M1, may be valuable signal sources for human neuromotor prostheses.