Uncovering the Neural Code Using a Rat Model during a Learning Control Task
How neuronal firing activities encode meaningful behavior is an ultimate challenge to neuroscientists. To make the problem tractable, we use a rat model to elucidate how an ensemble of single neuron firing events leads to conscious, goal-directed movement and control. This study discusses findings based on single unit, multi-channel simultaneous recordings from rats frontal areas while they learned to perform a decision and control task. To study neural firing activities, first and foremost we needed to identify single unit firing action potentials, or perform spike sorting prior to any analysis on the ensemble of neural activities. After that, we studied cortical neural firing rates to characterize their changes as rats learned a directional paddle control task. Single units from the rat’s frontal areas were inspected for their possible encoding mechanism of directional and sequential movement parameters. Our results entail both high level statistical snapshots of the neural data and more detailed neuronal roles in relation to rat’s learning control behavior.
KeywordsControl Task Primary Motor Cortex Neural Code Fano Factor Neural Recording
Unable to display preview. Download preview PDF.
- Dedual, N., Ozturk, M., Sanchez, J., Principe, J.: An associative memory readout in ESN for neural action potential detection. In: International Joint Conference on Neural Networks, IJCNN 2007, p. 2295 (2007)Google Scholar
- Fee, M.S., Mitra, P.P., Kleinfeld, D.: Variability of extracellular spike waveforms of cortical neurons. Journal of Neurophysiology 76(6), 3823–3833 (1996)Google Scholar
- Kandel, E., Schwartz, J., Jessell, T.: Principles of Neural Science (2000)Google Scholar
- Nenadic, Z.: Spike detection with the continuous wavelet transform, matlab software. University of California, Irvine, Center for BioMedical Signal Processing and Computation (2005), http://cbmspc.eng.uci.edu
- Oweiss, K., Anderson, D.: A multiresolution generalized maximum likelihood approach for the detection of unknown transient multichannel signals in colored noise with unknown covariance. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2002, vol. 3, pp. 2993–2996 (2002)Google Scholar
- Oweiss, K., Anderson, D.: A unified framework for advancing array signal processing technology of multichannel microprobe neural recording devices. In: 2nd Annual International IEEE-EMB Special Topic Conference on Microtechnologies in Medicine and Biology, pp. 245–250 (2002)Google Scholar
- Paxinos, G., Watson, C.: The Rat Brain in Stereotaxic Coordinates (2007)Google Scholar
- Shima, K., Tanji, J.: Neuronal activity in the supplementary and presupplementary motor areas for temporal organization of multiple movements. J. Neurophysiol. 84, 2148–2160 (2000)Google Scholar
- Smith, L.: Noisy spike generator, matlab software. University of Stirling, Department of Computing Science and Mathematics (2006), http://www.cs.stir.ac.uk/~lss/noisyspikes/