Hippocampal Place Fields, the Internal Compass, and the Learning of Landmark Stability,

1994 ◽  
Author(s):  
James J. Knierim ◽  
Hemant S. Kudrimoti ◽  
Bruce L. McNaughton
Keyword(s):  
Place Fields

Local Feedback Inhibition Tightly Controls Rapid Formation of Hippocampal Place Fields

2021 ◽  
Author(s):  
Sebi V. Rolotti ◽  
Mohsin Ahmed ◽  
Miklos Szoboszlay ◽  
Tristan Geiller ◽  
Adrian Negran ◽  
...  
Keyword(s):  
Feedback Inhibition ◽  
Rapid Formation ◽  
Place Fields ◽  
Local Feedback

Task-Dependent Representations in Rat Hippocampal Place Neurons

1997 ◽  
Vol 78 (2) ◽  
pp. 597-613 ◽  
Author(s):  
Tsuneyuki Kobayashi ◽  
Hisao Nishijo ◽  
Masaji Fukuda ◽  
Jan Bures ◽  
Taketoshi Ono
Keyword(s):  
Open Field ◽  
Hippocampal Neurons ◽  
Hippocampal Formation ◽  
Movement Speed ◽  
Neuron Activity ◽  
Place Field ◽  
Complex Spike ◽  
Place Fields ◽  
Sequential Trials ◽  
Self Stimulation

Kobayashi, Tsuneyuki, Hisao Nishijo, Masaji Fukuda, Jan Bures, and Taketoshi Ono. Task-dependent representations in rat hippocampal place neurons. J. Neurophysiol. 78: 597–613, 1997. It is suggested that the hippocampal formation is essential to spatial representations by flexible encoding of diverse information during navigation, which includes not only externally generated sensory information such as visual and auditory sensation but also ideothetic information concerning locomotion (i.e., internally generated information such as proprioceptive and vestibular sensation) as well as information concerning reward. In the present study, we investigated how various types of information are represented in the hippocampal formation, by recording hippocampal complex-spike cells from rats that performed three types of place learning tasks in a circular open field with the use of intracranial self-stimulation as reward. The intracranial self-stimulation reward was delivered in the following three contexts: if the rat 1) entered an experimenter-determined reward place within the open field, and this place was randomly varied in sequential trials; 2) entered two specific places, one within and one outside the place field (an area identified by change in activity of a place neuron); or 3) entered an experimenter-specified place outside the place field. Because the behavioral trails during navigation were more constant in the second task than in the first task, ideothetic information concerning locomotion was more relevant to acquiring reward in the second task than in the first task. Of 43 complex-spike cells recorded, 37 displayed place fields under the first task. Of these 37 place neurons, 34 also had significant reward correlates only inside the place field. Although reward and place correlates of the place neuron activity did not change between the first and second tasks, neuronal correlates to behavioral variables for locomotion such as movement speed, direction, and turning angle significantly increased in the second task. Furthermore, 6 of 31 place neurons tested with the third task, in which the reward place was located outside the original place field, shifted place fields. The results indicated that neuronal correlates of most place neurons flexibly increased their sensitivity to relevant information in a given context and environment, and some place neurons changed the place field per se with place reward association. These results suggest two strategies for how hippocampal neurons incorporate an incredible variety of perceptions into a unified representation of the environment: through flexible use of information and the creation of new representations.

Hippocampal Place-Cell Firing During Movement in Three-Dimensional Space

2001 ◽  
Vol 85 (1) ◽  
pp. 105-116 ◽  
Author(s):  
James J. Knierim ◽  
Bruce L. McNaughton
Keyword(s):  
Hippocampal Neurons ◽  
Horizontal Plane ◽  
Three Dimensional ◽  
Place Cell ◽  
Place Cells ◽  
Limbic Cortex ◽  
Head Direction ◽  
Head Direction Cells ◽  
Recording Apparatus ◽  
Place Fields

“Place” cells of the rat hippocampus are coupled to “head direction” cells of the thalamus and limbic cortex. Head direction cells are sensitive to head direction in the horizontal plane only, which leads to the question of whether place cells similarly encode locations in the horizontal plane only, ignoring the z axis, or whether they encode locations in three dimensions. This question was addressed by recording from ensembles of CA1 pyramidal cells while rats traversed a rectangular track that could be tilted and rotated to different three-dimensional orientations. Cells were analyzed to determine whether their firing was bound to the external, three-dimensional cues of the environment, to the two-dimensional rectangular surface, or to some combination of these cues. Tilting the track 45° generally provoked a partial remapping of the rectangular surface in that some cells maintained their place fields, whereas other cells either gained new place fields, lost existing fields, or changed their firing locations arbitrarily. When the tilted track was rotated relative to the distal landmarks, most place fields remapped, but a number of cells maintained the same place field relative to the x-y coordinate frame of the laboratory, ignoring the z axis. No more cells were bound to the local reference frame of the recording apparatus than would be predicted by chance. The partial remapping demonstrated that the place cell system was sensitive to the three-dimensional manipulations of the recording apparatus. Nonetheless the results were not consistent with an explicit three-dimensional tuning of individual hippocampal neurons nor were they consistent with a model in which different sets of cells are tightly coupled to different sets of environmental cues. The results are most consistent with the statement that hippocampal neurons can change their “tuning functions” in arbitrary ways when features of the sensory input or behavioral context are altered. Understanding the rules that govern the remapping phenomenon holds promise for deciphering the neural circuitry underlying hippocampal function.

scholarly journals Hippocampal Place Fields Maintain a Coherent and Flexible Map across Long Timescales

2018 ◽  
Vol 28 (22) ◽  
pp. 3578-3588.e6 ◽  
Author(s):  
Nathaniel R. Kinsky ◽  
David W. Sullivan ◽  
William Mau ◽  
Michael E. Hasselmo ◽  
Howard B. Eichenbaum
Keyword(s):  
Place Fields ◽  
Long Timescales

scholarly journals Behavioral Time Scale Plasticity of Place Fields: Mathematical Analysis

2021 ◽  
Vol 15 ◽  
Author(s):  
Ian Cone ◽  
Harel Z. Shouval
Keyword(s):  
Synaptic Plasticity ◽  
Fixed Points ◽  
Time Scales ◽  
Convergence Time ◽  
Simple Mathematical Model ◽  
System Parameters ◽  
Temporal Correlations ◽  
Postsynaptic Activity ◽  
Naturally Occurring ◽  
Place Fields

Traditional synaptic plasticity experiments and models depend on tight temporal correlations between pre- and postsynaptic activity. These tight temporal correlations, on the order of tens of milliseconds, are incompatible with significantly longer behavioral time scales, and as such might not be able to account for plasticity induced by behavior. Indeed, recent findings in hippocampus suggest that rapid, bidirectional synaptic plasticity which modifies place fields in CA1 operates at behavioral time scales. These experimental results suggest that presynaptic activity generates synaptic eligibility traces both for potentiation and depression, which last on the order of seconds. These traces can be converted to changes in synaptic efficacies by the activation of an instructive signal that depends on naturally occurring or experimentally induced plateau potentials. We have developed a simple mathematical model that is consistent with these observations. This model can be fully analyzed to find the fixed points of induced place fields and how these fixed points depend on system parameters such as the size and shape of presynaptic place fields, the animal's velocity during induction, and the parameters of the plasticity rule. We also make predictions about the convergence time to these fixed points, both for induced and pre-existing place fields.

scholarly journals Position-theta-phase model of hippocampal place cell activity applied to quantification of running speed modulation of firing rate

2019 ◽  
Author(s):  
Kathryn McClain ◽  
David Tingley ◽  
David Heeger ◽  
György Buzsáki
Keyword(s):  
Firing Rate ◽  
Spatial Information ◽  
Cell Activity ◽  
Gain Control ◽  
Place Cell ◽  
Small Subset ◽  
Running Speed ◽  
Speed Modulation ◽  
Place Fields ◽  
Theta Phase

AbstractSpiking activity of place cells in the hippocampus encodes the animal’s position as it moves through an environment. Within a cell’s place field, both the firing rate and the phase of spiking in the local theta oscillation contain spatial information. We propose a position-theta-phase (PTP) model that captures the simultaneous expression of the firing-rate code and theta-phase code in place cell spiking. This model parametrically characterizes place fields to compare across cells, time and condition, generates realistic place cell simulation data, and conceptualizes a framework for principled hypothesis testing to identify additional features of place cell activity. We use the PTP model to assess the effect of running speed in place cell data recorded from rats running on linear tracks. For the majority of place fields we do not find evidence for speed modulation of the firing rate. For a small subset of place fields, we find firing rates significantly increase or decrease with speed. We use the PTP model to compare candidate mechanisms of speed modulation in significantly modulated fields, and determine that speed acts as a gain control on the magnitude of firing rate. Our model provides a tool that connects rigorous analysis with a computational framework for understanding place cell activity.SignificanceThe hippocampus is heavily studied in the context of spatial navigation, and the format of spatial information in hippocampus is multifaceted and complex. Furthermore, the hippocampus is also thought to contain information about other important aspects of behavior such as running speed, though there is not agreement on the nature and magnitude of their effect. To understand how all of these variables are simultaneously represented and used to guide behavior, a theoretical framework is needed that can be directly applied to the data we record. We present a model that captures well-established spatial-encoding features of hippocampal activity and provides the opportunity to identify and incorporate novel features for our collective understanding.

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