Spatial Cognition, Memory Capacity, and the Evolution of Mammalian Hippocampal Networks

Abstract

The discovery of grid cells in the medial entorhinal cortex (MEC) of the rat (Fyhn et al. 2004) and of the precise triangular pattern of their firing fields (Hafting et al. 2005) requires a substantial reformulation of the questions relating to spatial cognition. It now appears, more clearly than before, that spatial computations per se are largely performed by the rat brain before the hippocampus is ever accessed, and culminate in a sort of universal map of allocentric space, in MEC layer II. Only a portion of the EC participates in such a map, which is applied and used irrespective of context, but in combination with context-specific signals that determine the activity of other parts of entorhinal cortex. The hippocampus operates on the universal map and on context-specific signals to create context-specific metric representations of space, which are stored in memory. The capacity of the hippocampus to rapidly switch between the representations of different contexts is illustrated by hippocampal global "remapping," i.e., the transition to new, unrelated arrangements of place fields by the same population of recorded cells, after suitable behavioral manipulations, and without concurrent MEC remapping (Fyhn et al. 2007). Consequently, understanding the circuitry of the hippocampus crucially involves understanding this capacity for decorrelating spatial representations, at least in rodents. It could well be that in other species complex memories of a less spatial nature take a more prominent role, in which case it would be even more appropriate to approach hippocampal decorrelation and memory processes at an abstract level, and independent of the possibly species-specific spatial processes so finely investigated with the rat model (see also chapter 2 of this volume, by Lucia F. Jacobs).Which approaches can take us beyond a mere functional description of the role of different networks in the brain, and lead us to understand, in evolutionary terms, their design principles? In recent years I have studied three apparently disparate topics from a computational viewpoint: the lamination of the sensory cortex, the differentiation into subfields of the mammalian hippocampus, and the neuronal dynamics that might underlie the faculty for language in the human frontal lobes. These studies share a common perspective: they

Temporal Flexibility of Systems Consolidation and the Synaptic Occupancy/Reset Theory (SORT): Cues About the Nature of the Engram

“…On the other hand, in those old studies it was remarkable to notice how cortical areas use to display a longer involvement than the HPC: thus, while the ERC was sensitive to CNQX amnestic effect at 1 (Jerusalinsky et al, 1992; Izquierdo et al, 1993a), 26 (Quillfeldt et al, 1994) and 31 days after training days (Quillfeldt et al, 1996), the PPC remained responsive after 60, and even up to 90 days post-training (unpublished results). The “stepwise” or gradual “deactivation” of the involvement of these brain structures takes place in full agreement with their neuroanatomical hodology (Marr, 1971; McNaughton and Nadel, 1990; Buzsáki, 1996; Fuster, 1997) and, consistently, with their phylogeny (Sherry and Schacter, 1987; Lavenex and Amaral, 2000; Treves, 2009; Thome et al, 2017). Figure 1 summarizes these first findings.…”

“…considering that the HPC is such a small brain region in terms of number of neurons (thus, number of synapses available at each moment) – particularly in the rat (Braitenberg and Schütz, 1983; McNaughton and Nadel, 1990; Treves and Rolls, 1994; Rolls et al, 1998; Rolls and Kesner, 2006; Treves, 2009; Rolls, 2017), and…”

“…However, while the above suppositions aim to cover memory mechanisms in the HPC, that must not be the whole story for this fascinating brain region. If there is one function that is well established for the hippocampal formation and adjacent cortices is that of a Cognitive Map (O’Keefe and Nadel, 1978; Treves, 2009; Moser et al, 2015), a system that not only organizes the representation of the spatial context, but actually creates and imposes it to the surrounding space in which the animal moves/explores. This is used to anticipate needed adaptative maneuvers to be implemented, organizing real-time navigation with simultaneous well-structured (pattern-separated) capture of environment data.…”

Partial coherence and frustration in self‐organizing spherical grids

“…Together with the emerging observation that mEC outputs to the cortex, mainly from layer Va, include virtually no grid‐cell signal (A. Egorov and D. Rowland, personal communication), this weakens the theory that mEC operates as a sort of spatial computer, and suggests instead that grid maps are one input that helps set up the spatial component of hippocampal memory representations. Alternative sets of coactivity relations stored on the same synaptic connections, as well as curvature, act on the currently active grid representation as “quenched” disorder, and coexisting with such spin‐glass‐like disorder appears to be the ultimate challenge for memory systems in the brain (Treves, ).…”

Partial coherence and frustration in self-organizing spherical grids

“…Together with the emerging observation that mEC outputs to the cortex, mainly from layer Va, include virtually no grid-cell signal (Alexei Egorov and David Rowland, personal communication), this weakens the theory that mEC operates as a sort of spatial computer, and suggests instead that grid maps are one input that helps set up the spatial component of hippocampal memory representations. Alternative sets of coactivity relations stored on the same synaptic connections, as well as curvature, act on the currently active grid representation as 'quenched' disorder, and coexisting with such spin-glass-like disorder appears to be the ultimate challenge for memory systems in the brain (Treves, 2009).…”