Self-organizing continuous attractor network models of hippocampal spatial view cells

Single neuron recording studies have demonstrated the existence of hippocampal spatial view neurons which encode information about the spatial location at which a primate is looking in the environment. These neurons are able to maintain their firing even in the absence of visual input. The standard neuronal network approach to model networks with memory that represent continuous spaces is that of continuous attractor networks. It has recently been shown how idiothetic (self-motion) inputs could update the activity packet of neuronal firing for a one-dimensional case (head direction cells), and for a two-dimensional case (place cells which represent the place where a rat is located). In this paper, we describe three models of primate hippocampal spatial view cells, which not only maintain their spatial firing in the absence of visual input, but can also be updated in the dark by idiothetic input. The three models presented in this paper represent different ways in which a continuous attractor network could integrate a number of different kinds of velocity signal (e.g., head rotation and eye movement) simultaneously. The first two models use velocity information from head angular velocity and from eye velocity cells, and make use of a continuous attractor network to integrate this information. A fundamental feature of the first two models is their use of a 'memory trace' learning rule which incorporates a form of temporal average of recent cell activity. Rules of this type are able to build associations between different patterns of neural activities that tend to occur in temporal proximity, and are incorporated in the model to enable the recent change in the continuous attractor to be associated with the contemporaneous idiothetic input. The third model uses positional information from head direction cells and eye position cells to update the representation of where the agent is looking in the dark. In this case the integration of idiothetic velocity signals is performed in the earlier layer of head direction cells.

[1]  R U Muller,et al.  Head-direction cells recorded from the postsubiculum in freely moving rats. I. Description and quantitative analysis , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[2]  R. Andersen,et al.  Models of the Posterior Parietal Cortex Which Perform Multimodal Integration and Represent Space in Several Coordinate Frames , 2000, Journal of Cognitive Neuroscience.

[3]  Thomas P. Trappenberg,et al.  Self-organising continuous attractor networks with multiple activity packets, and the representation of space , 2004, Neural Networks.

[4]  H. T. Blair,et al.  The anatomical and computational basis of the rat head-direction cell signal , 2001, Trends in Neurosciences.

[5]  B L McNaughton,et al.  Path Integration and Cognitive Mapping in a Continuous Attractor Neural Network Model , 1997, The Journal of Neuroscience.

[6]  J. Droulez,et al.  Some collicular efferent neurons code saccadic eye velocity , 1986, Neuroscience Letters.

[7]  Alessandro Treves,et al.  Attractor neural networks storing multiple space representations: A model for hippocampal place fields , 1998, cond-mat/9807101.

[8]  E. Rolls,et al.  Spatial View Cells in the Primate Hippocampus , 1997, The European journal of neuroscience.

[9]  E. Oja Simplified neuron model as a principal component analyzer , 1982, Journal of mathematical biology.

[10]  R. H. R. Hahnloser,et al.  Emergence of neural integration in the head-direction system by visual supervision , 2003, Neuroscience.

[11]  D. Amaral,et al.  Organization of intrahippocampal projections originating from CA3 pyramidal cells in the rat , 1990, The Journal of comparative neurology.

[12]  E. Rolls,et al.  Self-organizing continuous attractor networks and path integration: two-dimensional models of place cells , 2002, Network.

[13]  James Park,et al.  The Brain's Sense of Movement , 2003, The Yale Journal of Biology and Medicine.

[14]  E. Rolls Spatial view cells and the representation of place in the primate hippocampus , 1999, Hippocampus.

[15]  Christof Koch,et al.  Biophysics of Computation: Information Processing in Single Neurons (Computational Neuroscience Series) , 1998 .

[16]  Gustavo Deco,et al.  Computational neuroscience of vision , 2002 .

[17]  David S. Touretzky,et al.  The Role of the Hippocampus in Solving the Morris Water Maze , 1998, Neural Computation.

[18]  E. Rolls,et al.  Self-organizing continuous attractor networks and path integration: one-dimensional models of head direction cells , 2002, Network.

[19]  A. Berthoz,et al.  Neurons responding to whole-body motion in the primate hippocampus , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[20]  S. Amari Dynamics of pattern formation in lateral-inhibition type neural fields , 1977, Biological Cybernetics.

[21]  Hilla Peretz,et al.  The , 1966 .

[22]  E T Rolls,et al.  Information about spatial view in an ensemble of primate hippocampal cells. , 1998, Journal of neurophysiology.

[23]  E. Rolls,et al.  Spatial view cells in the primate hippocampus: allocentric view not head direction or eye position or place. , 1999, Cerebral cortex.

[24]  D. Touretzky,et al.  Modeling attractor deformation in the rodent head-direction system. , 2000, Journal of neurophysiology.

[25]  E. Rolls,et al.  Head direction cells in the primate pre‐subiculum , 1999, Hippocampus.

[26]  M Tsodyks,et al.  Attractor neural network models of spatial maps in hippocampus , 1999, Hippocampus.

[27]  B. McNaughton,et al.  Interactions between idiothetic cues and external landmarks in the control of place cells and head direction cells. , 1998, Journal of neurophysiology.

[28]  J. G. Taylor,et al.  Neural ‘bubble’ dynamics in two dimensions: foundations , 1999, Biological Cybernetics.

[29]  R. Muller,et al.  The hippocampus as a cognitive graph (abridged version) , 1991, Hippocampus.

[30]  X. Wang,et al.  Synaptic Basis of Cortical Persistent Activity: the Importance of NMDA Receptors to Working Memory , 1999, The Journal of Neuroscience.

[31]  A. Redish Beyond the Cognitive Map: From Place Cells to Episodic Memory , 1999 .

[32]  E. Rolls,et al.  Neural networks and brain function , 1998 .

[33]  K. Zhang,et al.  Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: a theory , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[34]  Leonard K. Kaczmarek,et al.  The inside story: subcellular mechanisms of neuromodulation , 1999 .

[35]  D. Debanne,et al.  Long‐term synaptic plasticity between pairs of individual CA3 pyramidal cells in rat hippocampal slice cultures , 1998, The Journal of physiology.

[36]  Bruce L. McNaughton,et al.  A Model of the Neural Basis of the Rat's Sense of Direction , 1994, NIPS.

[37]  E. Rolls,et al.  A unified model of spatial and episodic memory , 2002, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[38]  A David Redishyx,et al.  A coupled attractor model of the rodent head direction system , 1996 .

[39]  E. Rolls,et al.  Spatial view cells in the primate hippocampus: effects of removal of view details. , 1998, Journal of neurophysiology.

[40]  E T Rolls,et al.  Invariant object recognition in the visual system with error correction and temporal difference learning , 2001, Network.