Memory: Organization and Control

Abstract

A major goal of memory research is to understand how cognitive processes in memory are supported at the level of brain systems and network representations. Especially promising in this direction are new findings in humans and animals that converge in indicating a key role for the hippocampus in the systematic organization of memories. New findings also indicate that the prefrontal cortex may play an equally important role in the active control of memory organization during both encoding and retrieval. Observations about the dialog between the hippocampus and prefrontal cortex provide new insights into the operation of the larger brain system that serves memory.

Keywords: cognitive control; hippocampus; memory; prefrontal cortex.

Figure 1

Three forms of memory organization and the role of the hippocampus in humans and animals. (Left column) Elements A, B, and C are related in ways specific to each type of organization. (Middle column) Hippocampal activation in (a) associative (Zeithamova et al. 2012), (b) sequential (Ezzyat & Davachi 2014), and (c) schematic (Zalesak & Heckers 2009) memory organizations. (Right column) Graphs depicting the results in memory performance of rats with hippocampal lesions compared to a control group without lesions. (a) Rats with hippocampal lesions succeed in learning individual elements and associations (AB and BC) but fail in linking indirectly related elements in an associative organization (reflected in the low preference for the indirectly related element association AC) (Bunsey & Eichenbaum 1996). (b) Rats with hippocampal lesions succeed in remembering items in a list but fail in remembering the order of the items in the sequential organization (Fortin et al. 2002). (c) Rats with hippocampal lesions succeed in learning trained choices of all pairings in a five-item hierarchy (A–E; B over C and C over D are shown) but fail in inferring relations between indirectly related elements (B and D) in a hierarchical schematic organization (Dusek & Eichenbaum 1997).

Figure 2

Receiver operating characteristic (ROC) analysis of performance on variants of recognition memory in rats. (a) Item recognition. The ROC function is characterized by both an offset in the y intercept and bowing of the ROC curve, which is strikingly similar to the ROC function for item recognition in humans (Fortin et al. 2004). (b) Associative recognition. The ROCs for item pairs are characterized by loss of the bowing of the ROC function while the offset of the y intercept is maintained, as is the case when humans are tested in recognition of word pairs (Sauvage et al. 2008). (c) Response deadline. When subjects are required to respond rapidly, the offset in the y intercept of the ROC is lost and the curvilinear shape is maintained, as is also the case in humans (Sauvage et al. 2010).

Figure 3

Representational similarity analysis (RSA) of sequential organization in the hippocampus of humans and rats. (a) In a human fMRI (left), the correlation matrix shows pattern similarity across repetitions of combinations of object and temporal position sequences. The warmest colors, representing the highest similarity for repetition of each object/position element, gradually become cooler with the decreased similarity between elements that are successively more separated. Similarity scores (right) are also shown gradually decreasing with increasing temporal distance. Panel adapted with permission from Hsieh et al. (2014). (b) In rat single-neuron recordings, animals were required to remember an odor (A or B) that began each trial and match it to an odor presented after a delay. (Left) Idealized sequences of binned firing rates of three idealized hippocampal neurons; red indicates a high firing rate, yellow a lower firing rate, and blue no activity. To measure representational similarity for trials beginning with identical odors (e.g., odor A trials), average population vectors for odd- and even-numbered trials are cross-correlated. To measure representational similarity for trials beginning with different odors (A versus B), average population vectors for A trials and B trials are cross-correlated. These correlations were compared to correlations for random ordering of the neurons’ activity patterns. (Right) The greatest similarity occurred in trials beginning with the same odor. Less, but still above random, similarity occurred for different odors, indicating both coding of temporal organization of each trial type and coding of the general temporal structure common to all trials. Temporal coding was observed in neurons whose activity was temporally modulated but not in cells whose activity was not temporally modulated (nontime cells). Panel adapted with permission from MacDonald et al. (2013).

Figure 4

Representational similarity analysis (RSA) of related object memories in the hippocampus of rats. (a) Context-guided object–reward association task. Rats choose between objects A and B in either of two positions in each context. Note that object–reward associations are opposite in the two contexts. Objects were positioned as shown within each context or in the reverse positions in different trials. (b) RSA measuring hierarchical ordering of representational similarities (y axis) of the 16 object memories (x axis). The specific task dimensions are listed on the right. In trials of the dorsal hippocampus (top graph), the animals were tested with C and D objects as well as with A and B objects, allowing the distinction of reward valences and object identities, whereas in trials of the ventral and intermediate hippocampus (bottom graph) only A and B stimuli were used, so comparisons for identical trial types were made on odd and even numbered trials. Figure adapted with permission from McKenzie et al. (2016).

Figure 5

Topography of specificity and generality of representations along the long axis of the hippocampus. (a) The size of the place fields of hippocampal neurons (as well as the specificity of object and position coding) was graded along the long axis of the hippocampus in rats performing a context-guided object–reward association task. (Top) Outline of the two contexts and a typical place field in each panel. Warmer colors indicate higher firing rates. Blue indicates the area of each context explored. (Bottom) Areas where place fields of different size are found in the dHPC, mHPC, or vHPC. (b) The representational similarities of different scales of association were graded along the long axis of the hippocampus in humans performing an associative inference task. The posterior hippocampus had the highest similarity for one direct association (AB), the middle hippocampus had the highest similarity for both direct associations (AB and BC), and the anterior hippocampus had the highest similarity for the full network of associations (AB, BC, and AC). Panel b adapted with permission from Collin et al. (2015). Abbreviations: dHPC, dorsal hippocampus; mHPC, middle hippocampus; vHPC, ventral hippocampus.

Figure 6

Model of prefrontal–hippocampal interactions in memory. (a) The PFC receives direction projections from the vHPC (in rats; anterior HPC in humans) and projects indirectly (via the perirhinal and entorhinal cortices) to the HPC. In this model, when one is cued by context to recall memories, contextual cues are processed by the vHPC, which sends this information to the PFC, which then biases the retrieval of the context-appropriate memories in the dHPC. (b) Direction of the flow of information was determined by correlating the amplitude of the theta rhythm in the HPC and PFC across a range of time shifts between the two signals. These correlations reveal that during the exploration of the spatial context, information processing in the HPC leads that in the PFC, whereas during the sampling of the objects, the flow of information reverses, such that the PFC leads the HPC. Abbreviations: dHPC, dorsal hippocampus; HPC, hippocampus; PFC, prefrontal cortex; vHPC, ventral hippocampus.