Representation of memories in the cortical–hippocampal system: Results from the application of population similarity analyses

Abstract

Here we consider the value of neural population analysis as an approach to understanding how information is represented in the hippocampus and cortical areas and how these areas might interact as a brain system to support memory. We argue that models based on sparse coding of different individual features by single neurons in these areas (e.g., place cells, grid cells) are inadequate to capture the complexity of experience represented within this system. By contrast, population analyses of neurons with denser coding and mixed selectivity reveal new and important insights into the organization of memories. Furthermore, comparisons of the organization of information in interconnected areas suggest a model of hippocampal-cortical interactions that mediates the fundamental features of memory.

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated

“…It should be noted, however, that the degree of sparsity and similarity-based overlap varies across subregions of the hippocampus and neocortex (Boxes 4 and 5). While some of the relevant findings have been seen as supporting other theories [48], such differences are fully consistent with CLS and have long been exploited in CLS-based accounts of the roles of specific hippocampal subregions (Boxes 2-4). Similarly, learning rates vary across hippocampal areas in the theory (Box 2) and, likewise, there may be variation in learning rates across neocortical areas (Box 5).…”

Distributed Representation of "What" and "Where" Information in the Parahippocampal Region

“…The present study illustrates the usefulness of population analysis of neuronal representations (McKenzie et al, 2015). However, one caveat is that all analyses relied exclusively on firing rates.…”

“…Cells that are traditionally considered purely spatialcoding cells (e.g., grid cells) showed strong selectivity for object identity in some cases, just as so-called "place cells" in the hippocampus encode objects under some circumstances. In tasks in which keeping track of elapsed time is important for reward, hippocampal and MEC cells show temporal coding as well (Kraus et al, 2013). These results can be interpreted as an evidence of a more general phenomenon: associative cortical areas can flexibly support multiple representations according to behavioral demands.…”

“…Another possibility is that dentate granular cell ensembles that receive inputs from both LEC and MEC store these combined representations. In favor of this hypothesis, it has been shown that selective reactivation of granular cells active during a fear experience is sufficient to induce memory recall (Liu et al, 2012).…”

“…This hypothesis is supported by reports showing more precise spatial coding by proximal CA1 place cells (Henriksen et al, 2010) and stronger modulation by objects of distal CA1 place cells (Burke et al, 2011). However, CA1 cells also integrate conjunctive representations from CA3, so the information encoded in their firing patterns is likely more complex that those in the entorhinal cortex, as evidenced by the flexible expression of place and "time" cells in this region (Kraus et al, 2013). A possible reconciliation of these findings may be found in the temporal organization of the inputs arriving to CA1.…”