Long term, stable brain machine interface performance using local field potentials and multiunit spikes

Abstract

Objective Brain machine interfaces (BMIs) have the potential to restore movement to people with paralysis. However, a clinically-viable BMI must enable consistently accurate control over time spans ranging from years to decades, which has not yet been demonstrated. Most BMIs that use single-unit spikes as inputs will experience degraded performance over time without frequent decoder re-training. Two other signals, local field potentials (LFPs) and multi-unit spikes (MSPs), may offer greater reliability over long periods and better performance stability than single-unit spikes. Here, we demonstrate that LFPs can be used in a biomimetic BMI to control a computer cursor. Approach We implanted two rhesus macaques with intracortical microelectrodes in primary motor cortex. We recorded LFP and MSP signals from the monkeys while they performed a continuous reaching task, moving a cursor to randomly-placed targets on a computer screen. We then used the LFP and MSP signals to construct biomimetic decoders for control of the cursor. Main results Both monkeys achieved high-performance, continuous control that remained stable or improved over nearly 12 months using an LFP decoder that was not retrained or adapted. In parallel, the monkeys used MSPs to control a BMI without retraining or adaptation and had similar or better performance, and that predominantly remained stable over more than six months. In contrast to their stable online control, both LFP and MSP signals showed substantial variability when used offline to predict hand movements. Significance Our results suggest that the monkeys were able to stabilize the relationship between neural activity and cursor movement during online BMI control, despite variability in the relationship between neural activity and hand movements.

Extracting kinetic information from human motor cortical signals

“…The 11th fold was used to test the decoder performance. We selected values for the other parameters, such as the Fourier window length (256 points), bin size (0.1 s), and bin overlap (156 points), consistent with previous offline and online decoding of movement (Flint et al, 2012b(Flint et al, , 2013.…”

Emergence of Chimera-like States in Prefrontal-Cortex Macaque Intracranial Recordings

“…In [5], both power spectra features of Local Field Potentials (LFPs) and firingrates of Multi-unit Spikes (MSPs) from the brain of a macaque were used to train the monkey to move a cursor towards a target on a computer screen. In a more ambitious study [6], Event-Related Potentials (ERPs) and EEG spectral features were combined to decode the direction of movement.…”

A CMOS-based neural implantable optrode for optogenetic stimulation and electrical recording

“…To achieve this, rather than recording individual action potentials (APs), we have decided to tune our electronics to local field potentials (LFPs) of neuron activity. There is some evidence in the literature that recording LFPs are more stable than APs for chronic recordings [11,12], and potentially require less complex post-processing [12].…”