Theta‐paced flickering between place‐cell maps in the hippocampus: A model based on short‐term synaptic plasticity

Abstract

Hippocampal place cells represent different environments with distinct neural activity patterns. Following an abrupt switch between two familiar configurations of visual cues defining two environments, the hippocampal neural activity pattern switches almost immediately to the corresponding representation. Surprisingly, during a transient period following the switch to the new environment, occasional fast transitions between the two activity patterns (flickering) were observed (Jezek, Henriksen, Treves, Moser, & Moser, 2011). Here we show that an attractor neural network model of place cells with connections endowed with short‐term synaptic plasticity can account for this phenomenon. A memory trace of the recent history of network activity is maintained in the state of the synapses, allowing the network to temporarily reactivate the representation of the previous environment in the absence of the corresponding sensory cues. The model predicts that the number of flickering events depends on the amplitude of the ongoing theta rhythm and the distance between the current position of the animal and its position at the time of cue switching. We test these predictions with new analysis of experimental data. These results suggest a potential role of short‐term synaptic plasticity in recruiting the activity of different cell assemblies and in shaping hippocampal activity of behaving animals.

Integration and multiplexing of positional and contextual information by the hippocampal network

“…5B). This finding is at first sight in disagreement with the exponential decay of the flickering frequency reported in [27,38]. However, the latter was obtained as a result of an averaging over many teleportation events.…”

“…The present model reproduces accurately all the observed flickering properties, without any need for a post-learning short-term plasticity of the CA3 network hypothetized in [38]. In particular, our model predicts that the flickering frequency is independent from the time spent after the teleportation event in the conflicting phase (Fig.…”

“…2C & 4C), see Methods. The combination of properties (1) and (2) explains the exponential decay in the frequency of flickers with the delay after the switch reported in [27] and [38]. While the frequency of flickers is constant and large in the conflicting phase, and constant and very low in the coherent phase, the duration of the conflicting phase is exponentially distributed.…”

Regular cycling between representations of alternatives in the hippocampus

“…spontaneously) and under naturalistic conditions (here self-paced, goal-directed navigation); these dynamics were moreover seen in the absence of overtly deliberative behaviors such as directed head scans (vicarious trial-and-error 12 ). Most immediately, these various properties suggest revised or new models of network-level theta dynamics [61][62][63][64][65][66] .…”

Dynamics of a mutual inhibition between pyramidal neurons compared to human perceptual competition

“…It has been suggested that the conflicting signals for local features such as orientation (Bonds, 1989;Sillito, 1975), motion direction (Mikami et al, 1986;Snowden et al, 1991), and edge assignment (Kogo & van Ee, 2015;Zhou et al, 2000) compete with each other through such mutual inhibition circuits. This mutual inhibition circuit has been implemented in computer models to explain bistable perception (Laing & Chow, 2002;Lankheet, 2006;Matsuoka, 1984;Mueller, 1990;Noest et al, 2007;Shpiro et al, 2009;Wilson et al, 2000;Wilson, 1999), object recognition (Masquelier et al, 2009), decision making (Heuer, 1987;Machens et al, 2005;Usher & McClelland, 2001), and place cell field generation (Mark et al, 2017). It has also been suggested that these circuits underlie mechanisms such as larger scale neural interactions and feedback systems (Beck & Kastner, 2005;Lee et al, 1999;Wang et al, 2013) that establish a globally coherent percept.…”