Sensory abnormalities have been reported in Parkinson's disease and may contribute to the motor deficits. Peripheral sensory stimulation inhibits the motor cortex, and the effects depend on the interstimulus interval (ISI) between the sensory stimulus and transcranial magnetic stimulation (TMS) to the motor cortex. Short latency afferent inhibition (SAI) occurs at an ISI of approximately 20 ms, and long latency afferent inhibition (LAI) at an ISI of approximately 200 ms. We studied SAI and LAI in 10 Parkinson's disease patients with the aim of assessing whether sensorimotor processing is altered in Parkinson's disease. Patients were studied on and off medication, and the findings were compared with 10 age-matched controls. Median nerve and middle finger stimulation were delivered 20-600 ms before TMS to the contralateral motor cortex. The motor evoked potentials were recorded from the relaxed first dorsal interosseous (FDI) muscle. SAI was normal in Parkinson's disease patients off dopaminergic medications, but it was reduced on the more affected side in Parkinson's disease patients on medication. LAI was reduced in Parkinson's disease patients compared with controls independent of their medication status. LAI reduced long interval intracortical inhibition in normal subjects but not in Parkinson's disease patients. The different results for SAI and LAI indicate that it is likely that separate mechanisms mediate these two forms of afferent inhibition. SAI probably represents the direct interaction of a sensory signal with the motor cortex. This pathway is unaffected by Parkinson's disease but is altered by dopaminergic medication in Parkinson's disease patients and may contribute to the side effects of dopaminergic drugs. LAI probably involves other pathways such as the basal ganglia or cortical association areas. This defective sensorimotor integration may be a non-dopaminergic manifestation of Parkinson's disease.

A bi-directional neural interface (NI) system was designed and built by incorporating a novel neural recording and processing subsystem into a commercially approved neural stimulator. The NI system prototype leverages the system infrastructure from a market-approved neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing approved therapy capabilities, the device adds key elements to facilitate chronic clinical research, such as four channels of ECoG/LFP amplification and spectral analysis, a three axis accelerometer, algorithm processing, event-based data logging, and wireless telemetry for data uploads and algorithm/configuration updates. The custom integrated micropower sensor and interface circuits facilitate extended operation in a power-limited device. The prototype underwent significant verification testing to ensure reliability, and meets the requirements for a class CF instrument per IEC-60601 protocols. The ability of the device system to process and aid in classifying brain states was preclinically validated using an in-vivo non-human primate model for brain control of a computer cursor (i.e., brain machine interface or BMI). The primate BMI model was chosen for its ability to quantitatively measure signal decoding performance from brain activity that is similar in both amplitude and spectral content to other biomarkers used to detect disease states (e.g. Parkinson’s). A key goal of this research prototype is to help broaden the clinical scope and acceptance of NI techniques, particularly real-time brain state detection. These techniques can be generalized beyond motor prosthesis, to include significant unmet needs in other neurological conditions such as movement disorders, stroke, and epilepsy.

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The purpose of this work is to present a new method that can be used to estimate and mitigate RF induced currents on Deep Brain Stimulation (DBS) leads. Here, we demonstrate the effect of RF induced current mitigation on both RF heating and image quality for a variety of brain MRI sequences at 3 T. We acquired pre-scan images around a DBS lead (in-situ and ex-vivo) using conventional Gradient Echo Sequence (GRE) accelerated by parallel imaging (i.e GRAPPA) and quantified the magnitude and phase of RF induced current using the relative location of the B1+ null with respect to the lead position. We estimated the RF induced current on a DBS lead implanted in a gel phantom as well as in a cadaver head study for a variety of RF excitation patterns. We also measured the increase in tip temperature using fiber-optic probes for both phantom and cadaver studies. Using the magnitude and phase information of the current induced separately by two transmit channels of the body coil, we calculated an implant friendly (IF) excitation. Using the IF excitation, we acquired T1, T2 weighted Turbo Spin Echo (TSE), T2 weighted SPACE-Dark Fluid, and Ultra Short Echo Time (UTE) sequences around the lead. Our induced current estimation demonstrated linear relationship between the magnitude of the induced current and the square root SAR at the tip of the lead as measured in phantom studies. The “IF excitation pattern” calculated after the pre-scan mitigated RF artifacts and increased the image quality around the lead. In addition, it reduced the tip temperature significantly in both phantom and cadaver studies compared to a conventional quadrature excitation while keeping equivalent overall image quality. We present a relatively fast method that can be used to calculate implant friendly excitation, reducing image artifacts as well as the temperature around the DBS electrodes. When combined with a variety of MR sequences, the proposed method can improve the image quality and patient safety in clinical imaging scenarios.

To investigate the mechanism of action of deep brain stimulation (DBS), the authors studied the effects of thalamic DBS on the cerebellothalamocortical (CTC) pathway. With DBS turned off, excitability of the CTC pathway was reduced. Turning DBS on resulted in facilitation of the CTC pathway. Therefore, thalamic DBS appears to activate rather than inhibit the target area.

Cortical inhibitory systems play an important role in motor output. The motor cortex can be inhibited by intracortical mechanisms and by peripheral sensory inputs. We examined whether cortical inhibition from peripheral sensory input is mediated through previously identified intracortical inhibitory systems and how these inhibitory systems interact. Two types of intracortical inhibition were assessed by paired‐pulse transcranial magnetic stimulation (TMS). Short‐interval intracortical inhibition (SICI) was determined with a subthreshold conditioning stimulus (CS) followed by a test stimulus 2 ms later and long‐interval intracortical inhibition (LICI) with suprathreshold conditioning and test stimuli 100 ms apart. Cortical inhibition from peripheral sensory input was induced by median nerve stimulation (MNS) of the right hand and followed by a suprathreshold TMS over the left motor cortex 200 ms later. The first set of experiments tested the effects of different test stimulus intensities on SICI, LICI and cortical inhibition induced by median nerve stimulation (MNSI). With higher test stimulus intensities, LICI and MNSI decreased whereas SICI showed a trend towards an increase. The extent of SICI, LICI and MNSI did not correlate. The second experiment assessed the interaction between MNSI and LICI. The results of applying MNSI and LICI simultaneously were compared with MNSI and LICI alone. MNSI was virtually abolished in the presence of LICI and LICI was also significantly decreased in the presence of MNSI. Thus, the effects of MNSI and LICI when applied together were much less than their expected additive effects when applied alone. The degree of interaction between MNSI and LICI was related to the combined strength of MNSI and LICI but not to the strength of LICI alone. The third experiment investigated the interaction between SICI and MNSI. MNSI and SICI were applied together and the results were compared with MNSI and SICI alone. SICI remained unchanged in the presence of MNSI. We conclude that MNSI is mediated by circuits distinct from those mediating LICI or SICI. The MNSI circuits seem to have an inhibitory interaction with the LICI circuits, whereas the SICI and MNSI circuits do not seem to interact.