TY - JOUR T1 - Mapping broadband electrocorticographic recordings to two-dimensional hand trajectories in humans Motor control features. JF - Neural Netw Y1 - 2009 A1 - Gunduz, Aysegul A1 - Sanchez, Justin C A1 - Carney, Paul R A1 - Principe, Jose KW - Algorithms KW - Brain KW - Brain Mapping KW - Electrodes, Implanted KW - Electrodiagnosis KW - Epilepsy KW - Feasibility Studies KW - Hand KW - Humans KW - Linear Models KW - Motor Activity KW - Neural Networks (Computer) KW - Nonlinear Dynamics KW - Signal Processing, Computer-Assisted AB -

Brain-machine interfaces (BMIs) aim to translate the motor intent of locked-in patients into neuroprosthetic control commands. Electrocorticographical (ECoG) signals provide promising neural inputs to BMIs as shown in recent studies. In this paper, we utilize a broadband spectrum above the fast gamma ranges and systematically study the role of spectral resolution, in which the broadband is partitioned, on the reconstruction of the patients' hand trajectories. Traditionally, the power of ECoG rhythms (<200-300 Hz) has been computed in short duration bins and instantaneously and linearly mapped to cursor trajectories. Neither time embedding, nor nonlinear mappings have been previously implemented in ECoG neuroprosthesis. Herein, mapping of neural modulations to goal-oriented motor behavior is achieved via linear adaptive filters with embedded memory depths and as a novelty through echo state networks (ESNs), which provide nonlinear mappings without compromising training complexity or increasing the number of model parameters, with up to 85% correlation. Reconstructed hand trajectories are analyzed through spatial, spectral and temporal sensitivities. The superiority of nonlinear mappings in the cases of low spectral resolution and abundance of interictal activity is discussed.

VL - 22 UR - http://www.ncbi.nlm.nih.gov/pubmed/19647981 IS - 9 ER - TY - JOUR T1 - Extraction and localization of mesoscopic motor control signals for human ECoG neuroprosthetics. JF - J Neurosci Methods Y1 - 2008 A1 - Sanchez, Justin C A1 - Gunduz, Aysegul A1 - Carney, Paul R A1 - Principe, Jose KW - Adolescent KW - Biofeedback, Psychology KW - Brain Mapping KW - Cerebral Cortex KW - Electroencephalography KW - Epilepsies, Partial KW - Female KW - Hand KW - Humans KW - Magnetic Resonance Imaging KW - Physical Therapy Modalities KW - Psychomotor Performance KW - Signal Processing, Computer-Assisted KW - Spectrum Analysis KW - User-Computer Interface AB -

Electrocorticogram (ECoG) recordings for neuroprosthetics provide a mesoscopic level of abstraction of brain function between microwire single neuron recordings and the electroencephalogram (EEG). Single-trial ECoG neural interfaces require appropriate feature extraction and signal processing methods to identify and model in real-time signatures of motor events in spontaneous brain activity. Here, we develop the clinical experimental paradigm and analysis tools to record broadband (1Hz to 6kHz) ECoG from patients participating in a reaching and pointing task. Motivated by the significant role of amplitude modulated rate coding in extracellular spike based brain-machine interfaces (BMIs), we develop methods to quantify spatio-temporal intermittent increased ECoG voltages to determine if they provide viable control inputs for ECoG neural interfaces. This study seeks to explore preprocessing modalities that emphasize amplitude modulation across frequencies and channels in the ECoG above the level of noisy background fluctuations in order to derive the commands for complex, continuous control tasks. Preliminary experiments show that it is possible to derive online predictive models and spatially localize the generation of commands in the cortex for motor tasks using amplitude modulated ECoG.

VL - 167 UR - http://www.ncbi.nlm.nih.gov/pubmed/17582507 IS - 1 ER - TY - JOUR T1 - Analysis of the correlation between local field potentials and neuronal firing rate in the motor cortex. JF - Conf Proc IEEE Eng Med Biol Soc Y1 - 2006 A1 - Wang, Yiwen A1 - Sanchez, Justin C A1 - Principe, Jose A1 - Mitzelfelt, Jeremiah D A1 - Gunduz, Aysegul KW - Action Potentials KW - Animals KW - Brain KW - Brain Mapping KW - Electric Stimulation KW - Electrodes KW - Evoked Potentials, Motor KW - Male KW - Models, Statistical KW - Motor Cortex KW - Neurons KW - Rats KW - Rats, Sprague-Dawley KW - Signal Processing, Computer-Assisted KW - Synaptic Transmission AB -

Neuronal firing rate has been the signal of choice for invasive motor brain machine interfaces (BMI). The use of local field potentials (LFP) in BMI experiments may provide additional dendritic information about movement intent and may improve performance. Here we study the time-varying amplitude modulated relationship between local field potentials (LFP) and single unit activity (SUA) in the motor cortex. We record LFP and SUA in the primary motor cortex of rats trained to perform a lever pressing task, and evaluate the correlation between pairs of peri-event time histograms (PETH) and movement evoked local field potentials (mEP) at the same electrode. Three different correlation coefficients were calculated and compared between the neuronal PETH and the magnitude and power of the mEP. Correlation as high as 0.7 for some neurons occurred between the PETH and the mEP magnitude. As expected, the correlations between the single trial LFP and SUV are much lower due to the inherent variability of both signals.

VL - 1 UR - http://www.ncbi.nlm.nih.gov/pubmed/17946745 ER -