| Paper: | GS-7.2 |
| Session: | Contributed Talks VII |
| Location: | Ormandy |
| Session Time: | Saturday, September 8, 11:40 - 12:20 |
| Presentation Time: | Saturday, September 8, 12:00 - 12:20 |
| Presentation: |
Oral
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
A framework for linking computations and rhythm-based timing patterns in neural firing, such as phase precession in hippocampal place cells |
| Manuscript: |
Click here to view manuscript |
| DOI: |
https://doi.org/10.32470/CCN.2018.1263-0 |
| Authors: |
Edward Frady, Pentti Kanerva, Friedrich Sommer, UC Berkeley, United States |
| Abstract: |
A major challenge in neuroscience is to develop models that bridge between observed neural firing patterns and computational functions. Here, we demonstrate the utility of Vector Symbolic Architecture (VSA) models in building a theory framework for neuroscience. Specifically, we present a VSA model expressing computations by operations on high-dimensional vectors of complex numbers, Fourier Holographic Reduced Representations (FHRR). We have developed a novel model of synaptic integration to implement FHRR operations with spiking neurons that express periodic population firing, where the timing of a spike relative to an internal oscillation represents the phase of a complex number. We illustrate how algorithms defined on a computational level, such as associative memory or spatial navigation, can be implemented by spiking neurons that exhibit similar firing patterns as observed in neural recordings. Thus, FHRR VSAs can establish a link between concrete computations and properties of neural firing such as oscillations and phase precession in hippocampus and cortex. |
