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, 2012
"... NEURAL CIRCUITS doi: 10.3389/fncir.2012.00021 The abrupt development of adult-like grid cell firing in the medial entorhinal cortex ..."
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NEURAL CIRCUITS doi: 10.3389/fncir.2012.00021 The abrupt development of adult-like grid cell firing in the medial entorhinal cortex
Neuron Article Theta Oscillations Provide Temporal Windows for Local Circuit Computation
"... Theta oscillations are believed to play an important role in the coordination of neuronal firing in the ento-rhinal (EC)-hippocampal system but the underlying mechanisms are not known. We simultaneously re-corded from neurons in multiple regions of the EC-hippocampal loop and examined their temporal ..."
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Theta oscillations are believed to play an important role in the coordination of neuronal firing in the ento-rhinal (EC)-hippocampal system but the underlying mechanisms are not known. We simultaneously re-corded from neurons in multiple regions of the EC-hippocampal loop and examined their temporal rela-tionships. Theta-coordinated synchronous spiking of EC neuronal populations predicted the timing of current sinks in target layers in the hippocampus. However, the temporal delays between population activities in successiveanatomical stageswere longer (typically by a half theta cycle) than expected from axon conduction velocities and passive synaptic inte-gration of feed-forward excitatory inputs. We hypoth-esize that the temporal windows set by the theta cycles allow for local circuit interactions and thus a considerable degree of computational indepen-dence in subdivisions of the EC-hippocampal loop.
Neuron Article Theta Oscillations Provide Temporal Windows for Local Circuit Computation
"... Theta oscillations are believed to play an important role in the coordination of neuronal firing in the entorhinal (EC)-hippocampal system but the underlying mechanisms are not known. We simultaneously recorded from neurons in multiple regions of the EChippocampal loop and examined their temporal re ..."
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Theta oscillations are believed to play an important role in the coordination of neuronal firing in the entorhinal (EC)-hippocampal system but the underlying mechanisms are not known. We simultaneously recorded from neurons in multiple regions of the EChippocampal loop and examined their temporal relationships. Theta-coordinated synchronous spiking of EC neuronal populations predicted the timing of current sinks in target layers in the hippocampus. However, the temporal delays between population activities in successive anatomical stages were longer (typically by a half theta cycle) than expected from axon conduction velocities and passive synaptic integration of feed-forward excitatory inputs. We hypothesize that the temporal windows set by the theta cycles allow for local circuit interactions and thus a considerable degree of computational independence in subdivisions of the EC-hippocampal loop.
Contents lists available at ScienceDirect Neurobiology of Learning and Memory
"... journal homepage: www.elsevier.com/locate/ynlme A model of episodic memory: Mental time travel along encoded trajectories ..."
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journal homepage: www.elsevier.com/locate/ynlme A model of episodic memory: Mental time travel along encoded trajectories
HIPPOCAMPUS 00:000–000 (2010) Grid Cell Hexagonal Patterns Formed by Fast Self-Organized Learning Within Entorhinal Cortex
"... ABSTRACT: Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into h ..."
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ABSTRACT: Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. VC 2010 Wiley-Liss, Inc. KEY WORDS: grid cells; entorhinal cortex; self-organized learning;
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"... There has been considerable interest in the importance of oscillations in the brain and in how these oscillations relate to the firing of single neurons. Recently a number of studies have shown that the spiking of individual neurons in the medial prefrontal cortex (mPFC) become entrained to the hipp ..."
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There has been considerable interest in the importance of oscillations in the brain and in how these oscillations relate to the firing of single neurons. Recently a number of studies have shown that the spiking of individual neurons in the medial prefrontal cortex (mPFC) become entrained to the hippocampal (HPC) theta rhythm. We recently showed that theta-entrained mPFC cells lost theta-entrainment specifically on error trials even though the firing rates of these cells did not change (Hyman et al., 2010). This implied that the level of HPC theta-entrainment of mPFC units was more predictive of trial outcome than differences in firing rates and that there is more information encoded by the mPFC on working memory tasks than can be accounted for by a simple rate code. Nevertheless, the functional meaning of mPFC entrainment to HPC theta remains a mystery. It is also unclear as to whether there are any differences in the nature of the information encoded by theta-entrained and non-entrained mPFC cells. In this review we discuss mPFC entrainment to HPC theta within the context of previous results as well as provide a more detailed analysis of the Hyman et al. (2010) data set. This re-analysis revealed that thetaentrained mPFC cells selectively encoded a variety of task relevant behaviors and stimuli while never theta-entrained mPFC cells were most strongly attuned to errors or the lack of expected
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"... Temporally structured replay of neural activity in a model of entorhinal cortex, hippocampus and postsubiculum ..."
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Temporally structured replay of neural activity in a model of entorhinal cortex, hippocampus and postsubiculum
doi: 10.3389/fncir.2012.00016 Models of grid cell spatial firing published 2005–2011
, 2012
"... Since the discovery of grid cells in rat entorhinal cortex, many models of their hexagonally arrayed spatial firing fields have been suggested. We review the models and organize them according to the mechanisms they use to encode position, update the positional code, read it out in the spatial grid ..."
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Since the discovery of grid cells in rat entorhinal cortex, many models of their hexagonally arrayed spatial firing fields have been suggested. We review the models and organize them according to the mechanisms they use to encode position, update the positional code, read it out in the spatial grid pattern, and learn any patterned synaptic connections needed. We mention biological implementations of the models, but focus on the models on Marr’s algorithmic level, where they are not things to individually prove or disprove, but rather are a valuable collection of metaphors of the grid cell system for guiding research that are all likely true to some degree, with each simply emphasizing different aspects of the system. For the convenience of interested researchers, MATLAB implementations of the discussed grid cell models are provided at ModelDB accession 144006
