“Spike-timing dependent plasticity among multiple layers of motion-sensitive neurons: a feedforward mechanism for motion extrapolation”.
During this CONECT seminar, Charlie Sexton will present his recent work on “Spike-timing dependent plasticity among multiple layers of motion-sensitive neurons: a feedforward mechanism for motion extrapolation”:
The ability of the brain to represent the external world in real-time is impacted by the fact that neural processing takes time. Because neural delays accumulate as information progresses through the visual system, representations encoded at each hierarchical level are based upon input that is progressively outdated with respect to the external world. This is particularly relevant to the task of localizing a moving object – because the object’s location changes with time, neural representations of its location potentially lag behind its true location. It has therefore been proposed that the visual system utilizes the predictive nature of motion to extrapolate moving objects along their trajectory. Burkitt and Hogendoorn (2021, https://doi.org/10.1523/JNEUROSCI.2017-20.2021) showed how spike-timing dependent plasticity (STDP) can achieve motion extrapolation in a two-layer, feedforward network of velocity-tuned neurons, by shifting the receptive-fields of second-layer neurons in the opposite direction to a moving stimulus. The current study extends this work by implementing two important changes to the network to bring it more into line with biology: we expanded the network to multiple layers to reflect the depth of the visual hierarchy, and we implemented more realistic synaptic time-courses. We examine the degree to which STDP can facilitate compensation of neural delays across six layers, and show that the multi-layer network achieves cumulative compensation comparable in magnitude to the delays incurred in visual processing. We also explore the effect of additional delays imposed on the network by the integration time of the membrane potential.