Research Overview

Classical approaches to motor systems research (and much of neuroscience) involve measuring the properties of single neurons (Hubel, 1957) and characterizing their responses during complex behaviour. However, with the advent of more sophisticated recording techniques, such as floating microelectrode arrays and optical imaging (O'Shea et al. 2017), we can probe the dynamics of large neural populations by recording thousands, or even 10s of thousands (Pachitariu et al. 2016), of neurons in parallel.

Using these techniques to understand how reaching movements are controlled, we can move away from the neuron doctrine — which posits that the neuron is the functional and perceptual unit of the nervous system, and towards a network view — in which ensembles of distributed neurons form functional units with their own emergent properties.

Publications

Intveld RW, Dann B, Michaels JA, Scherberger H (2018). Neural coding of intended and executed grasp force in macaque areas AIP, F5, and M1. Scientific Reports, 8(17985). doi:10.1038/s41598-018-35488-z.

Michaels JA^*, Dann B^*, Intveld RW, Scherberger H (2018). Neural dynamics of variable grasp movement preparation in the macaque fronto-parietal network. Journal of Neuroscience, 38(25), 5759-5773. doi:10.1523/JNEUROSCI.2557-17.2018.

Michaels JA, Scherberger H (2018). Population coding of grasp and laterality-related information in the macaque fronto-parietal network. Scientific Reports, 8(1710). doi:10.1038/s41598-018-20051-7.

Michaels JA, Dann B, Scherberger H (2016). Neural population dynamics during reaching are better explained by a dynamical system than representational tuning. PLOS Computational Biology, 12(11), e1005175. doi:10.1371/journal.pcbi.1005175.

Michaels JA, Scherberger H (2016). hebbRNN: A reward-modulated Hebbian learning rule for recurrent neural networks. The Journal of Open Source Software. doi:10.21105/joss.00060. pdf.

Dann B, Michaels JA, Schaffelhofer S, Scherberger H (2016). Uniting functional network topology and oscillations in the fronto-parietal single unit network of behaving primates. eLife. doi:10.7554/eLife.15719.

Dann B, Michaels JA, Scherberger H (2016). Separable decoding of cue, intention, and movement information from the fronto-parietal grasping-network. Proceedings of the Sixth International Brain-Computer Interface Meeting: BCI Past, Present, and Future, 218. doi:10.3217/978-3-85125-467-9.

Michaels JA, Dann B, Intveld RW, Scherberger H (2015). Predicting reaction time from the neural state space of the premotor and parietal grasping network. Journal of Neuroscience, 35(32), 11415–11432. doi:10.1523/JNEUROSCI.1714-15.2015.

Yang L, Michaels JA, Pruszynski JA, Scott SH (2011). Rapid motor responses quickly integrate visuospatial task constraints. Experimental Brain Research, 211(2): 231-242. doi:10.1007/s00221-011-2674-3.