Stability and variability of place cell activity during behavior: Functional implications for dynamic coding of spatial information

2012 ◽  
Vol 106 (3-4) ◽  
pp. 62-71 ◽  
Author(s):  
B. Poucet ◽  
V. Hok ◽  
F. Sargolini ◽  
E. Save
2019 ◽  
Author(s):  
Kathryn McClain ◽  
David Tingley ◽  
David Heeger ◽  
György Buzsáki

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.


2018 ◽  
Vol 119 (2) ◽  
pp. 476-489 ◽  
Author(s):  
Brian J. Gereke ◽  
Alexandra J. Mably ◽  
Laura Lee Colgin

CA1 place cells become more anticipatory with experience, an effect thought to be caused by NMDA receptor-dependent plasticity in the CA3–CA1 network. Theta (~5–12 Hz), slow gamma (~25–50 Hz), and fast gamma (~50–100 Hz) rhythms are thought to route spatial information in the hippocampal formation and to coordinate place cell ensembles. Yet, it is unknown whether these rhythms exhibit experience-dependent changes concurrent with those observed in place cells. Slow gamma rhythms are thought to indicate inputs from CA3 to CA1, and such inputs are thought to be strengthened with experience. Thus, we hypothesized that slow gamma rhythms would become more evident with experience. We tested this hypothesis using mice freely traversing a familiar circular track for three 10-min sessions per day. We found that slow gamma amplitude was reduced in the early minutes of the first session of each day, even though both theta and fast gamma amplitudes were elevated during this same period. However, in the first minutes of the second and third sessions of each day, all three rhythms were elevated. Interestingly, theta was elevated to a greater degree in the first minutes of the first session than in the first minutes of later sessions. Additionally, all three rhythms were strongly influenced by running speed in dynamic ways, with the influence of running speed on theta and slow gamma changing over time within and across sessions. These results raise the possibility that experience-dependent changes in hippocampal rhythms relate to changes in place cell activity that emerge with experience. NEW & NOTEWORTHY We show that CA1 theta, slow gamma, and fast gamma rhythms exhibit characteristic changes over time within sessions in familiar environments. These effects in familiar environments evolve across repeated sessions.


2019 ◽  
Vol 116 (52) ◽  
pp. 27035-27042 ◽  
Author(s):  
Kathryn McClain ◽  
David Tingley ◽  
David J. Heeger ◽  
György Buzsáki

Spiking 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 conditions; 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.


2005 ◽  
Vol 565 (2) ◽  
pp. 579-591 ◽  
Author(s):  
Franco A. Taverna ◽  
John Georgiou ◽  
Robert J. McDonald ◽  
Nancy S. Hong ◽  
Alexander Kraev ◽  
...  

Neuroscience ◽  
2003 ◽  
Vol 117 (4) ◽  
pp. 1025-1035 ◽  
Author(s):  
T Kobayashi ◽  
A.H Tran ◽  
H Nishijo ◽  
T Ono ◽  
G Matsumoto

2021 ◽  
Author(s):  
Jake Ormond ◽  
John O'Keefe

One function of the Hippocampal Cognitive Map is to provide information about salient locations in familiar environments such as those containing reward or danger, and to support navigation towards or away from those locations. Although much is known about how the hippocampus encodes location in world-centred coordinates, how it supports flexible navigation is less well understood. We recorded from CA1 place cells while rats navigated to a goal or freely foraged on the honeycomb maze. The maze tests the animal's ability to navigate using indirect as well as direct paths to the goal and allows the directionality of place cells to be assessed at each choice point during traversal to the goal. Place fields showed strong directional polarization in the navigation task, and to a lesser extent during random foraging. This polarization was characterized by vector fields which converged to sinks distributed throughout the environment. The distribution of these convergence sinks was centred near the goal location, and the population vector field converged on the goal, providing a strong navigational signal. Changing the goal location led to the movement of ConSinks and vector fields towards the new goal and within-days, the ConSink distance to the goal decreased with continued training. The honeycomb maze allows the independent assessment of spatial representation and spatial action in place cell activity and shows how the latter depends on the former. The results suggest a vector-based model of how the hippocampus supports flexible navigation, allowing animals to select optimal paths to destinations from any location in the environment.


Cell Reports ◽  
2018 ◽  
Vol 23 (1) ◽  
pp. 32-38 ◽  
Author(s):  
Maria Diamantaki ◽  
Stefano Coletta ◽  
Khaled Nasr ◽  
Roxana Zeraati ◽  
Sophie Laturnus ◽  
...  

Neuroscience ◽  
2008 ◽  
Vol 157 (1) ◽  
pp. 254-270 ◽  
Author(s):  
S.A. Ho ◽  
E. Hori ◽  
T. Kobayashi ◽  
K. Umeno ◽  
A.H. Tran ◽  
...  

2000 ◽  
Vol 114 (2) ◽  
pp. 273-284 ◽  
Author(s):  
Jérôme Rossier ◽  
Yulii Kaminsky ◽  
Françoise Schenk ◽  
Jan Bures

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