Primate Motor cortex
Why use macaques in this research?
Primates have precision grip as they have opposable thumbs and nails instead of claws. Sensorimotor systems of primates constitute levels of increasing size and complexity. Prosimians, monkeys, apes, and humans group to form four grade shifts with each primate level characterized by a more elaborate sensorimotor system. Despite the increase in complexity, the motor system of macaques and humans have structural similarities, comparable topographical relations, architecture and regional receptor distribution patterns all of which support the notion that there are homologous regions in the motor cortex including primary motor cortex (M1), premotor cortex (PM), supplementary motor area (SMA) and caudal cingulate motor area (CMAc). Thus macaques are used as an animal model in motor neuroscience research.
Spatial distribution of spike-related slow potentials in primate motor cortex
Introduction:
A recent study [1] in primate motor cortex has described features in the low-frequency local field potential (lf-LFP) that are time-locked to neuronal firing (so-called ‘spike-related slow potentials’, SRSPs). SRSPs associated with a single neuron exhibited considerable variation in shape, amplitude and polarity across LFPs recorded on other electrodes. We speculate that this variability reflects spatially-distinct spike-related sources arising from synaptic currents associated with the network in which the neuron is embedded.
Aims:
We examined the spatial distribution of SRSPs in order to investigate their physiological basis and to inform the design of recording arrays optimised for extracting signals for LFP-based Brain-Machine Interfaces (BMIs).
Methods:
We recorded from 12 moveable microwire electrodes implanted in the primary motor cortex of a macaque. In addition, we used two linear microelectrode arrays (LMAs; 16 channels, 0.5mm spacing), implanted through the bank of the central sulcus and the convexity of the pre-central gyrus respectively, to provide a spatial profile of the LFP.
Results:
We calculated SRSPs by fitting a multiple-input multiple output model relating firing rates to lf-LFPs [1]. Principal Component Analysis (PCA) suggested that the variability in SRSP waveform was greatest across microwires and across the sulcal LMA, while the gyral LMA exhibited stereotyped SRSPs. In general >90% of the variability of SRSPs recorded from the gyrus was explained by a single PC. Across both LMAs and microwire recordings, three PCs were able to capture ~98% of the total SRSP variability.
Conclusions:
These findings suggest that using electrodes targeting specific depths within the bank of the central sulcus may minimise the redundancy (hence maximise the information content) of the recorded lf-LFPs. A reduction in the number of channels required, alongside our use of low frequency signals, may enable recording and signal-processing using low-power electronics. This has important implications for the development and miniaturisation of robust, low-power BMIs for human patients.
Reference:
[1] Hall TM, Nazarpour K, Jackson A (2014), Real-time estimation and biofeedback of single neuron firing rates using local field potentials. Nature Communications
Poster
Here is a poster about this work