Short‐term plasticity based network model of place cells dynamics

Abstract

Rodent hippocampus exhibits strikingly different regimes of population activity in different behavioral states. During locomotion, hippocampal activity oscillates at theta frequency (5-12 Hz) and cells fire at specific locations in the environment, the place fields. As the animal runs through a place field, spikes are emitted at progressively earlier phases of the theta cycles. During immobility, hippocampus exhibits sharp irregular bursts of activity, with occasional rapid orderly activation of place cells expressing a possible trajectory of the animal. The mechanisms underlying this rich repertoire of dynamics are still unclear. We developed a novel recurrent network model that accounts for the observed phenomena. We assume that the network stores a map of the environment in its recurrent connections, which are endowed with short-term synaptic depression. We show that the network dynamics exhibits two different regimes that are similar to the experimentally observed population activity states in the hippocampus. The operating regime can be solely controlled by external inputs. Our results suggest that short-term synaptic plasticity is a potential mechanism contributing to shape the population activity in hippocampus.

Synchronized excitability in a network enables generation of internal neuronal sequences

“…The incoming wave of excitation arriving from CA3 and/or EC might synchronously increase the membrane potential among a large number of neurons, bringing all neurons closer to spiking at about the same time. The first neurons that fire during this wave of excitability likely activate local feed-forward inhibition and thus start to silence their 'competitor' principal neurons and dominate the activity of the network (Csicsvari et al, 1999; Wang et al, 2015; Romani and Tsodyks, 2015). Only after the competitor principal cells are silenced would these neurons be able to reliably activate their own post-synaptic principal neurons and thus trigger a sequential firing in the network.…”

“…However, these models usually utilize an alternative to such an excitatory wave, such as prominent sensory cue inputs that strongly stimulate a subset of neurons at the onset of each sequence (Tsodyks et al, 1996; Lisman et al, 2005), selective amplification of already strong synaptic connections that promotes activation of a subset of cells (Fiete et al, 2010), or very strong connectivity, which gives rise to a distinct region of high activity that perpetually activates itself due to asymmetry of connections, dynamic thresholds, or dynamic strength of synapses (Kleinfeld, 1986; Sampolinsky and Kanter, 1986; Horn and Usher, 1989; Hopfield, 2010; Itskov et al, 2011). We propose that synchronized waves of excitability are required for the generation of sequences in networks with no sensory inputs, with relatively weak connections and with relatively sparse activity (Wang et al, 2015; Romani and Tsodyks, 2015). Without such synchronized waves, the activity of the network is dominated by non-specific feed-forward inhibition that prevents activation of specific sequences.…”

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

“…There are several indications of STP presence in area CA3 of the hippocampus (Miles and Wong, ; Salin, Scanziani, Malenka, & Nicoll, ; Selig, Nicoll, & Malenka, ; Guzman et al, 2016). CANN with STP can account for several circuit dynamics observed in the hippocampus, such as phase precession, activity replays, and activity during the delay period of a spatial memory task (Romani and Tsodyks, ; Wang et al, ). In this contribution we show that CANN whose synapses are endowed with STP can account for the appearance of flickering events following the switch of environments.…”

Feature Detection in Visual Cortex during Different Functional States

“…Further we will call such kind of activity “bumps.” When effects of synaptic plasticity are taken into account, repertoire of possible activities becomes richer and can lead to generation of waves, or spontaneous bumps of activity propagating short distances and then disappearing (York and van Rossum, 2009; Romani and Tsodyks, 2014). …”

“…We also introduce short term depression as in (Tsodyks et al, 1998; Romani and Tsodyks, 2014; Equation 3).…”