Dual Coding in an Auto-associative Network Model of the Hippocampus
-
1
Collegium Budapest, Hungary
-
2
University of Sussex, United Kingdom
Electrophysiology studies in a range of mammalian species have demonstrated that the firing rate of single pyramidal neurons in the hippocampus encodes for the presence of both spatial and non-spatial cues [1]. In addition, the phase of place cell firing with respect to the theta oscillation that dominates the hippocampal EEG during learning correlates with the location of an animal within the corresponding place field [2]. Importantly, it has been demonstrated that the rate and phase of neural activity can be dissociated, and may thus encode information separately and independently [3]. Here we present a spiking neural network model which is, to our knowledge, the first to utilise a dual coding system in order to integrate the learning and recall of associations that correspond to both temporally-coded (spatial) and rate-coded (non-spatial) activity patterns within a single framework.
Our model consists of a spiking auto-associative network with a novel STDP rule that replicates a BCM-type dependence of synaptic weight upon mean firing rate (figure 1). The scale of external input, recurrent synaptic currents and synaptic plasticity are each modulated by a theta frequency oscillation. Place cell activity is represented by a compressed temporal sequence of neural firing within each theta phase, while the presence of a non-spatial ‘object’ is represented by neural bursting at the trough of the theta phase. We simulate the network moving along a circular track of 50 overlapping place fields with non-spatial cues present at 5 equidistant locations (figure 2). Following learning, we demonstrate that:
1. External stimulation of any place cell generates the sequential recall of upcoming place fields on the learned route (figure 3a).
2. External stimulation of any place cell generates the recall of any ‘object’ previously encountered at that place (figure 3b).
3. External stimulation of cells which encode an ‘object’ generates recall of both the place at which that ‘object’ was observed, and the upcoming place fields on the learned route (figure 3c).
4. The network performs pattern completion, meaning that only a subset of cues is required to generate this recall activity.
This model provides the first demonstration of an asymmetric STDP rule mediating rate-coded learning in a spiking auto-associative network that is inspired by the neurobiology of the CA3 region. Furthermore, the dual coding system utilised integrates both dynamic and static activity patterns, and thus unifies the disparate (spatial and episodic) mnemonic functions ascribed to the hippocampus. This research therefore provides the foundations for a novel computational model of learning and memory in the medial temporal lobe and beyond.
References
1. O'Keefe J: Hippocampal Neurophysiology in the Behaving Animal. The Hippocampus Book, Oxford University Press (2008)
2. Huxter JR, Senior TJ, Allen K, Ciscsvari J: Theta Phase–Specific Codes for Two Dimensional Position, Trajectory and Heading in the Hippocampus. Nature Neuroscience 11 (5): 587-594 (2008)
3. Huxter JR, Burgess N, O’Keefe J: Independent Rate and Temporal Coding in Hippocampal Pyramidal Cells. Nature 425 (6960): 828-832 (2003)
Conference:
Bernstein Conference on Computational Neuroscience, Frankfurt am Main, Germany, 30 Sep - 2 Oct, 2009.
Presentation Type:
Poster Presentation
Topic:
Learning and plasticity
Citation:
Bush
D,
Philippides
A,
Husbands
P and
O-Shea
M
(2009). Dual Coding in an Auto-associative Network Model of the Hippocampus.
Front. Comput. Neurosci.
Conference Abstract:
Bernstein Conference on Computational Neuroscience.
doi: 10.3389/conf.neuro.10.2009.14.094
Copyright:
The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers.
They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.
The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.
Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.
For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.
Received:
27 Aug 2009;
Published Online:
27 Aug 2009.
*
Correspondence:
Daniel Bush, Collegium Budapest, Budapest, Hungary, d.bush@ucl.ac.uk