Hubert Cecile Francois Martens

Frequency-selectivity of a thalamocortical relay neuron during parkinson's disease and deep brain stimulation: A computational study

In this computational study, we investigated (i) the functional importance of correlated basal ganglia (BG) activity associated with Parkinson’s disease (PD) motor symptoms by analysing the effects of globus pallidus internum (GPi) bursting frequency and synchrony on a thalamocortical (TC) relay neuron, which received GABAergic projections from this nucleus; (ii) the effects of subthalamic nucleus (STN) deep brain stimulation (DBS) on the response of the TC relay neuron to synchronized GPi oscillations; and (iii) the functional basis of the inverse relationship that has been reported between DBS frequency and stimulus amplitude, required to alleviate PD motor symptoms [A. L. Benabid et al. (1991)Lancet, 337, 403–406]. The TC relay neuron selectively responded to and relayed synchronized GPi inputs bursting at a frequency located in the range 2–25 Hz. Input selectivity of the TC relay neuron is dictated by low‐threshold calcium current dynamics and passive membrane properties of the neuron. STN‐DBS prevented the TC relay neuron from relaying synchronized GPi oscillations to cortex. Our model indicates that DBS alters BG output and input selectivity of the TC relay neuron, providing an explanation for the clinically observed inverse relationship between DBS frequency and stimulus amplitude.

From Parkinsonian thalamic activity to restoring thalamic relay using deep brain stimulation: new insights from computational modeling.

We present a computational model of a thalamocortical relay neuron for exploring basal ganglia thalamocortical loop behavior in relation to Parkinsons disease and deep brain stimulation (DBS). Previous microelectrode, single-unit recording studies demonstrated that oscillatory interaction within and between basal ganglia nuclei is very often accompanied by synchronization at Parkinsonian rest tremor frequencies (3-10 Hz). These oscillations have a profound influence on thalamic projections and impair the thalamic relaying of cortical input by generating rebound action potentials. Our model describes convergent inhibitory input received from basal ganglia by the thalamocortical cells based on characteristics of normal activity, and/or low-frequency oscillations (activity associated with Parkinsons disease). In addition to simulated input, we also used microelectrode recordings as inputs for the model. In the resting state, and without additional sensorimotor input, pathological rebound activity is generated for even mild Parkinsonian input. We have found a specific stimulation window of amplitudes and frequencies for periodic input, which corresponds to high-frequency DBS, and which also suppresses rebound activity for mild and even more prominent Parkinsonian input. When low-frequency pathological rebound activity disables the thalamocortical cells ability to relay excitatory cortical input, a stimulation signal with parameter settings corresponding to our stimulation window can restore the thalamocortical cells relay functionality.

Automatic subthalamic nucleus detection from microelectrode recordings based on noise level and neuronal activity.

Microelectrode recording (MER) along surgical trajectories is commonly applied for refinement of the target location during deep brain stimulation (DBS) surgery. In this study, we utilize automatically detected MER features in order to locate the subthalamic nucleus (STN) employing an unsupervised algorithm. The automated algorithm makes use of background noise level, compound firing rate and power spectral density along the trajectory and applies a threshold-based method to detect the dorsal and the ventral borders of the STN. Depending on the combination of measures used for detection of the borders, the algorithm allocates confidence levels for the annotation made (i.e. high, medium and low). The algorithm has been applied to 258 trajectories obtained from 84 STN DBS implantations. MERs used in this study have not been pre-selected or pre-processed and include all the viable measurements made. Out of 258 trajectories, 239 trajectories were annotated by the surgical team as containing the STN versus 238 trajectories by the automated algorithm. The agreement level between the automatic annotations and the surgical annotations is 88%. Taking the surgical annotations as the golden standard, across all trajectories, the algorithm made true positive annotations in 231 trajectories, true negative annotations in 12 trajectories, false positive annotations in 7 trajectories and false negative annotations in 8 trajectories. We conclude that our algorithm is accurate and reliable in automatically identifying the STN and locating the dorsal and ventral borders of the nucleus, and in a near future could be implemented for on-line intra-operative use.

Automatic noise-level detection for extra-cellular micro-electrode recordings

Extra-cellular neuro-recording signals used for functional mapping in deep brain stimulation (DBS) surgery and invasive brain computer interfaces, may suffer from poor signal to noise ratio. Therefore, a reliable automatic noise estimate is essential to extract spikes from recordings. We show that current methods are biased toward overestimation of noise-levels with increasing neuronal activity or artifacts. An improved and novel method is proposed that is based on an estimate of the mode of the distribution of the signal envelope. Our method makes use of the inherent characteristics of the noise distribution. For band-limited Gaussian noise the envelope of the signal is known to follow the Rayleigh distribution. The location of the peak of this distribution provides a reliable noise-level estimate. It is demonstrated that this new ‘envelope’ method gives superior performance both on simulated data, and on actual micro-electrode recordings made during the implantation surgery of DBS electrodes for the treatment of Parkinson’s disease.

Steering deep brain stimulation fields using a high resolution electrode array

Deep brain stimulation (DBS) therapy relies on electrical stimulation of neuronal elements in small brain targets. However, the lack of fine spatial control over field distributions in current systems implies that stimulation easily spreads into adjacent structures that may induce adverse side-effects. This study investigates DBS field steering using a novel DBS lead design carrying a high-resolution electrode array. We apply computational models to simulate voltage distributions and DBS activation volumes in order to theoretically assess the potential of field steering in DBS. Our computational analysis demonstrates that the DBS-array is capable of accurately displacing activation volumes with sub-millimeter precision. Our findings demonstrate that future systems for DBS therapy may provide for more accurate target coverage than currently available systems achieve.

Motor cortex stimulation for Parkinson's disease: a modelling study

Chronic motor cortex stimulation (MCS) is currently being investigated as a treatment method for Parkinsons disease (PD). Unfortunately, the underlying mechanisms of this treatment are unclear and there are many uncertainties regarding the most effective stimulation parameters and electrode configuration. In this paper, we present a MCS model with a 3D representation of several axonal populations. The model predicts that the activation of either the basket cell or pyramidal tract (PT) type axons is involved in the clinical effect of MCS. We propose stimulation protocols selectively targeting one of these two axon types. To selectively target the basket cell axons, our simulations suggest using either cathodal or bipolar stimulation with the electrode strip placed perpendicular rather than parallel to the gyrus. Furthermore, selectivity can be increased by using multiple cathodes. PT type axons can be selectively targeted with anodal stimulation using electrodes with large contact sizes. Placing the electrode epidurally is advisable over subdural placement. These selective protocols, when practically implemented, can be used to further test which axon type should be activated for clinically effective MCS and can subsequently be applied to optimize treatment. In conclusion, this paper increases insight into the neuronal population involved in the clinical effect of MCS on PD and proposes strategies to improve this therapy.

Format of an 8.5-GB double-layer DVD recordable disc

A single-sided double-layer DVD one-time recordable disc with a storage capacity of 8.5 GByte has been developed for the first time. The disc format is designed for maximum compatibility with existing DVD players and DVD read only drives. The physical format of the DVD+R double-layer disc is described in detail. Physical parameters, compatibility, double-layer effects and margins are discussed. At the end a short description of the logical format is given.

Compatible 8.5-Gbyte double-layer recordable DVD disc

A single-sided double-layer recordable DVD disc with a storage capacity of 8.5 Gbyte has been developed. Backwards compatibility with the existing DVD read-only format has been achieved through the use of organic dye recording layers that have intrinsically low absorption at lasers wavelength used for recording and reading. We describe the disc technology that we have developed, present recording results for both layers, and discuss double-layer effects. We demonstrate for the first time the feasibility of a compatible double-layer recordable DVD disc.