scholarly journals NMDA receptor-dependent dynamics of hippocampal place cell ensembles

2017 ◽  
Author(s):  
Yuichiro Hayashi
Keyword(s):  
Nmda Receptor ◽  
Temporal Dynamics ◽  
Cell Activity ◽  
Memory Task ◽  
Fixed Time ◽  
Nmda Receptor Antagonist ◽  
Place Cell ◽  
Neural Representation ◽  
Time Dependent ◽  
Gradual Change

Place cell activity in the hippocampus constitutes a neural representation of space. The dynamics of the place cell activity for familiar environment changes gradually over time, suggesting that this temporal dynamics enables to allocate different neural codes for spatially identical but temporally different episodes. To understand the mechanisms determining the dynamics of place cell populations, activity of hippocampal CA1 neurons was imaged during repeated performance in a spatial memory task. Comparing ensemble representations among multiple task sessions revealed that overlap rate of active place cell population was time-dependent, but independent of the number of tasks within a fixed time. This time-dependent change of hippocampal ensemble activity was suppressed by the administration of an NMDA receptor antagonist. These results suggested that the gradual change of activity pattern works as a time code, and NMDA receptor-dependent processes forms the code.

scholarly journals Defective place cell activity in nociceptin receptor knockout mice with elevated NMDA receptor-dependent long-term potentiation

2005 ◽  
Vol 565 (2) ◽  
pp. 579-591 ◽  
Author(s):  
Franco A. Taverna ◽  
John Georgiou ◽  
Robert J. McDonald ◽  
Nancy S. Hong ◽  
Alexander Kraev ◽  
...  
Keyword(s):  
Nmda Receptor ◽  
Knockout Mice ◽  
Cell Activity ◽  
Long Term Potentiation ◽  
Place Cell ◽  
Term Potentiation ◽  
Nociceptin Receptor

scholarly journals Hippocampal place cells encode local surface texture boundaries

2019 ◽  
Author(s):  
Chia-Hsuan Wang ◽  
Joseph D. Monaco ◽  
James J. Knierim
Keyword(s):  
Flat Surface ◽  
Cell Activity ◽  
Place Cell ◽  
Cognitive Map ◽  
Neural Representation ◽  
Place Field ◽  
Experimental Conditions ◽  
Inhomogeneous Surface ◽  
Physiological Basis ◽  
Circular Track

SummaryThe cognitive map is often assumed to be a Euclidean map that isometrically represents the real world (i.e. the Euclidean distance between any two locations in the physical world should be preserved on the cognitive map). However, accumulating evidence suggests that environmental boundaries can distort the mental representations of a physical space. For example, the distance between two locations can be remembered as longer than the true physical distance if the locations are separated by a boundary. While this overestimation is observed under different experimental conditions, even when the boundary is formed by flat surface cues, its physiological basis is not well understood. We examined the neural representation of flat surface cue boundaries, and of the space segregated by these boundaries, by recording place cell activity from dorsal CA1 and CA3 while rats foraged on a circular track or square platform with inhomogeneous surface textures. About 40% of the place field edges concentrated near the surface cue boundaries on the circular track (significantly above the chance level 33%). Similarly, the place field edges were more prevalent near the boundaries on the platforms than expected by chance. In both 1-dimensional and 2-dimensional environments, the population vectors of place cell activity changed more abruptly with distance between locations that crossed cue boundaries than between locations within a bounded region. These results show that the locations of surface boundaries were evident as enhanced decorrelations of the neural representations of locations to either side of the boundaries. This enhancement might underlie the cognitive phenomenon of overestimation of distances across boundaries.

scholarly journals Rapid classification of hippocampal replay content for real-time applications

2016 ◽  
Vol 116 (5) ◽  
pp. 2221-2235 ◽  
Author(s):  
Xinyi Deng ◽  
Daniel F. Liu ◽  
Mattias P. Karlsson ◽  
Loren M. Frank ◽  
Uri T. Eden
Keyword(s):  
Real Time ◽  
Learning And Memory ◽  
Cell Activity ◽  
Memory Task ◽  
Estimation Algorithm ◽  
Place Cell ◽  
Efficient Estimation ◽  
Memory Impairments ◽  
Software And Hardware

Sharp-wave ripple (SWR) events in the hippocampus replay millisecond-timescale patterns of place cell activity related to the past experience of an animal. Interrupting SWR events leads to learning and memory impairments, but how the specific patterns of place cell spiking seen during SWRs contribute to learning and memory remains unclear. A deeper understanding of this issue will require the ability to manipulate SWR events based on their content. Accurate real-time decoding of SWR replay events requires new algorithms that are able to estimate replay content and the associated uncertainty, along with software and hardware that can execute these algorithms for biological interventions on a millisecond timescale. Here we develop an efficient estimation algorithm to categorize the content of replay from multiunit spiking activity. Specifically, we apply real-time decoding methods to each SWR event and then compute the posterior probability of the replay feature. We illustrate this approach by classifying SWR events from data recorded in the hippocampus of a rat performing a spatial memory task into four categories: whether they represent outbound or inbound trajectories and whether the activity is replayed forward or backward in time. We show that our algorithm can classify the majority of SWR events in a recording epoch within 20 ms of the replay onset with high certainty, which makes the algorithm suitable for a real-time implementation with short latencies to incorporate into content-based feedback experiments.

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