A hippocampal network for spatial coding during immobility and sleep

Abstract

How does an animal know where it is when it stops moving? Hippocampal place cells fire at discrete locations as subjects traverse space, thereby providing an explicit neural code for current location during locomotion. In contrast, during awake immobility, the hippocampus is thought to be dominated by neural firing representing past and possible future experience. The question of whether and how the hippocampus constructs a representation of current location in the absence of locomotion has stood unresolved. Here we report that a distinct population of hippocampal neurons, located in the CA2 subregion, signals current location during immobility, and furthermore does so in association with a previously unidentified hippocampus-wide network pattern. In addition, signaling of location persists into brief periods of desynchronization prevalent in slow-wave sleep. The hippocampus thus generates a distinct representation of current location during immobility, pointing to mnemonic processing specific to experience occurring in the absence of locomotion.

Predicting the past, remembering the future

“…The fact that some place cells show no predictive properties during early exposure to an environment [49] aligns well with the classic finding that contextual fear conditioning is more effective if the animal is first pre-exposed to the environment (an effect that is hippocampus-dependent [56]). According to the SR theory, predictive relationships between states allow the shock association to propagate to other states (i.e., locations within the environment), leading to a more robust fear memory.…”

“…According to this view, place cells do not actually encode spatial location; they encode expectations about future locations (though see [49] for evidence that some place cells have no predictive properties during immobility). In an open field, these future locations will tend to be in the vicinity of the animal's current location, yielding classical radially symmetric place fields.…”

Sublayer-Specific Coding Dynamics during Spatial Navigation and Learning in Hippocampal Area CA1

“…Deep CA1 PCs are preferentially targeted by area CA2 (Kohara et al, 2014), which was recently shown to exhibit similarly unstable coding of context and space (Kay et al, 2016; Lee et al, 2015; Lu et al, 2015; Mankin et al, 2015). In addition, the work by Mizuseki et al, 2011, suggested deep CA1 PCs are more strongly driven by entorhinal input, and it is possible that cortical and subcortical (thalamic or neuromodulatory) inputs – which are known to be crucial for the stability and remapping of hippocampal representations (Brandon et al, 2014; Ito et al, 2015; Lu et al, 2013; Miao et al, 2015) – also contributed to the observed differences.…”

Multiple Running Speed Signals in Medial Entorhinal Cortex

“…In addition to identifying putative positive speed cells, we also found a sizable proportion of negatively speed modulated cells (16%). This is an intriguing property given recent work on the presence of negatively speed modulated cells in CA2 that code for space during immobility (Kay et al, 2016) and thus could be recipients of input from negatively speed modulated MEC cells via entorhinal-hippocampal synapses (Chevaleyre and Siegelbaum, 2010) or alternatively could provide negatively speed modulated output back to MEC via hippocampal-entorhinal projections (Rowland et al., 2013). …”