Attention promotes episodic encoding by stabilizing hippocampal representations

Attention influences what is later remembered, but little is known about how this occurs in the brain. We hypothesized that behavioral goals modulate the attentional state of the hippocampus to prioritize goal-relevant aspects of experience for encoding. Participants viewed rooms with paintings, attending to room layouts or painting styles on different trials during high-resolution functional MRI. We identified template activity patterns in each hippocampal subfield that corresponded to the attentional state induced by each task. Participants then incidentally encoded new rooms with art while attending to the layout or painting style, and memory was subsequently tested. We found that when task-relevant information was better remembered, the hippocampus was more likely to have been in the correct attentional state during encoding. This effect was specific to the hippocampus, and not found in medial temporal lobe cortex, category-selective areas of the visual system, or elsewhere in the brain. These findings provide mechanistic insight into how attention transforms percepts into memories.Why do we remember some things and not others? Consider a recent experience, such as the last movie complex you visited, flight you took, or restaurant at which you ate. More information was available to your senses than was stored in memory, such as the theater number of the movie, the faces of other passengers, and the color of the napkins. The selective nature of memory is adaptive, because encoding carries a cost: newly stored memories can interfere with existing ones and with our ability to learn new information in the future. What is the mechanism by which information gets selected for encoding?Attention offers a means of prioritizing information in the environment that is most relevant to behavioral goals. Attended information, in turn, has stronger control over behavior and is represented more robustly in the brain (1, 2). If attention gates which information we perceive and act upon, then it may also determine what information we remember. Indeed, attention during encoding affects both subsequent behavioral expressions of memory (3) and the extent to which activity levels in the brain predict memory formation (4–7). Although these findings suggest that attention modulates processes related to memory, how it does so is unclear.According to biased competition and other theories of attention (1, 8), task-relevant stimuli are more robustly represented in sensory systems, and thus fare better in competition with task-irrelevant stimuli for downstream processing. Indeed, there is extensive evidence that attention enhances overall activity in visual areas that represent attended vs. unattended features and locations (2, 9). Moreover, attention modulates cortical areas of the medial temporal lobe that provide input to the hippocampus (10–12).Attention can also modulate the hippocampus itself. Specifically, there is growing evidence that attention stabilizes distributed hippocampal representations of task-relevant information (10, 13, 14). For example, in rodents, distinct ensembles of hippocampal place cells activate when different spatial reference frames are task-relevant (15, 16; see also ref. 17) and place fields are more reliable when animals engage in a task for which spatial information is important (18, 19). Such representational stability has been found in the hippocampus more generally, such as for olfactory representations when odor information is task-relevant (19). In humans, attention similarly modulates patterns of hippocampal activity, but over voxels measured with functional magnetic resonance imaging (fMRI); for example, attention to different kinds of information induces distinct activity patterns in all hippocampal subfields (10).Thus, attention can modulate sensory cortex, medial temporal lobe cortex, and the hippocampus. Here, we explored which of these neural signatures of attention is most closely linked to the formation of memory. We hypothesized that attention induces state-dependent patterns of activity in the cortex and hippocampus, but that representational stability in the hippocampus itself may be the mechanism by which attention enhances memory. That is, attention serves to focus and maintain hippocampal processing on one particular aspect of a complex stimulus, strengthening the resulting memory trace and improving later recognition. We also hypothesized that the interplay between the hippocampus and visual processing regions would be closely related to memory formation, and thus examined the coupling of attentional states across these regions and its relationship to memory.To test these hypotheses, we designed a three-part study that allowed us to identify attentional-state representations in the hippocampus (phase 1) and then examine whether more evidence for the goal-relevant attentional state during the encoding of new information (phase 2) predicted later success in remembering that information (phase 3). We describe each of these three phases in more detail below.Phase 1 took place during fMRI and consisted of an “art gallery” paradigm (10). Participants were cued to attend to either the paintings or room layouts in a rendered gallery (Fig. 1A). After the cue, they were shown a “base image” (a room with a painting) and then searched a stream of other images for a painting from the same artist as the painting in the base image (art state) or for a room with the same layout as the room in the base image (room state). After the search stream, participants were probed about whether there had been a matching painting or room. The comparison of valid trials (e.g., cued for painting, probed for painting) vs. invalid trials (e.g., cued for painting, probed for layout) provided a behavioral measure of attention. Specifically, if attention was engaged by the cue, participants should be better at detecting matches on valid trials. Importantly, identical images were used for both tasks, allowing us to isolate the effects of top-down attention. We used phase 1 to identify neural representations of the two attentional states in each hippocampal subfield—that is, “template” patterns of activity for each of the art and room states.Open in a separate windowFig. 1.Task design and behavioral results. The study consisted of three phases. In phase 1 (A, Upper), participants performed a task in which they paid attention to paintings or rooms on different trials. One room trial is illustrated. For visualization, the cued match is outlined in green and the uncued match in red. Task performance (A, Lower) is shown as sensitivity in making present/absent judgments as a function of attentional state and probe type. Error bars depict ±1 SEM of the within-participant valid vs. invalid difference. In phase 2 (B, Upper), participants performed an incidental encoding task in which they viewed trial-unique images and looked for one-back repetitions of artists or room layouts in different blocks. Task performance (B, Lower) is shown as sensitivity in detecting one-back repetitions as a function of attentional state. Error bars depict ±1 SEM. In phase 3 (C, Upper), participants’ memory for the attended aspect of phase 2 images was tested. Memory performance (C, Lower) is shown as sensitivity in identifying previously studied items, as a function of response confidence and attentional state. Error bars depict ±1 SEM of the within-participant high- vs. low-confidence difference. Dashed line indicates chance performance. **P < 0.01, ***P < 0.001.Phase 2 also took place during fMRI and consisted of an incidental encoding paradigm. Participants performed a cover task while being exposed to a new set of trial-unique images (rooms with paintings). The cover task was used to manipulate art vs. room states (Fig. 1B): in art blocks, participants looked for two paintings in a row painted by the same artist; in room blocks, participants looked for two rooms in a row with the same layout. Because each image contained both a painting and a layout, top-down attention was needed to select the information relevant for the current block and to ignore irrelevant information. The demands for selection and comparison were thus similar to those of the art and room states in phase 1. For each phase 2 encoding trial, we quantified the match between the state of the hippocampus on that trial and the attentional-state representations defined from phase 1. Specifically, we correlated the activity pattern on each trial with the template that was relevant for the current block (e.g., art state during art block) and with the template that was irrelevant for the current block (e.g., room state during art block). We measured the extent to which the hippocampus was in the correct attentional state by calculating the difference of the relevant minus irrelevant pattern correlations.Phase 3 was conducted outside the scanner and involved a recognition memory test. Task-relevant aspects of the images from phase 2 (i.e., paintings in the art block, layouts in the room block) were presented one at a time and participants made memory judgments on a four-point scale: old or new, with high or low confidence (Fig. 1C). The test was divided into blocks: in the art block, old and new paintings were presented in isolation without background rooms; in the room block, old and new rooms were presented without paintings. To increase reliance on the kind of detailed episodic memory supported by the hippocampus, the memory test included a highly similar lure for each encoded item (20, 21): a novel painting from the same artist or the same layout from a novel perspective, for the art and room blocks, respectively. We used memory performance on this task to sort the fMRI data from phase 2, which allowed us to relate attentional states during encoding to subsequent memory (22, 23).To summarize our hypothesis: (i) Attention should modulate representational stability in the hippocampus, inducing distinct activity patterns for each of the art and room states (10). (ii) If attention is properly oriented during encoding, the hippocampus should be more strongly in the task-relevant state. (iii) This will result in a greater difference in correlation between the pattern of activity at encoding and the predefined template patterns for the task-relevant vs. task-irrelevant states. (iv) A greater correlation difference should be associated with better processing of task-relevant stimulus information, better encoding of that information into long-term memory, and a higher likelihood of later retrieval.We also explored the roles of different hippocampal subfields. In our prior study, one hippocampal subfield region of interest (ROI) in particular—comprising subfields CA2/3 and dentate gyrus (DG)—showed behaviorally relevant attentional modulation (10). This finding, together with work linking univariate activity and pattern similarity in CA2/CA3/DG to memory encoding (24–27), raised the possibility that this region might be especially important for the attentional modulation of episodic memory behavior. Thus, we hypothesized that the attentional state of CA2/CA3/DG during encoding would predict the formation of memory. Another candidate for the attentional modulation of memory is CA1. Activity in the CA1 subfield is modulated by goal states during memory retrieval (28), and this region serves as a “comparator” of expectations—which may be induced by attentional cues—and percepts (29, 30).To test these hypotheses, we acquired high-resolution fMRI data and manually segmented CA1 and a combined CA2/CA3/DG ROI in the hippocampus (Fig. 2). We also defined an ROI for the remaining subfield, the subiculum, for completeness and to mirror prior high-resolution fMRI studies of the hippocampus (31). We report results for these three subfield ROIs, as well as for a single hippocampal ROI collapsing across subfield labels. Moreover, motivated by computational theories and work with animal models, which highlight different roles for CA3 and DG in memory (32), as well as recent human neuroimaging studies that have examined these regions separately (33, 34), we report supplemental exploratory analyses for separate CA2/3 and DG ROIs (Fig. S1). To test the specificity of effects in the hippocampus, we also defined ROIs in the medial temporal lobe (MTL) cortex, including entorhinal cortex (ERc), perirhinal cortex (PRc), and parahippocampal cortex (PHc), and in category-selective areas of occipitotemporal and parietal cortices. Finally, in follow-up analyses of which other regions support attentional modulation of hippocampal encoding, we examined functional connectivity of multivariate representations in the hippocampus with those in MTL cortex and category-selective areas.Open in a separate windowFig. 2.MTL ROIs. Example segmentation from one participant is depicted for one anterior and one posterior slice. ROIs consisted of three hippocampal regions [subiculum (Sub), CA1, and CA2/CA3/DG], and three MTL cortical regions (ERc, PRc, and PHc). We also conducted analyses across the hippocampus as a single ROI, and exploratory analyses with separate CA2/3 and DG ROIs (Fig. S1). For segmentation guide, see ref. 10.Open in a separate windowFig. S1.Comparison of attention and memory effects in CA2/3 and DG. (A) We conducted exploratory analyses with separate ROIs for CA2/3 and DG, shown here for an example participant. We conducted these analyses because of reported dissociations across CA2/3 and DG with 3T fMRI (33, 34). These analyses should be interpreted with caution, however, because separation of CA2/3 and DG signals is difficult, even with the 1.5-mm isotropic voxels used in the present study. Specifically, the intertwined nature of these subfields means that a functional voxel could include both CA2/3 and DG. Thus, in the main text, we used the standard approach of collapsing across CA2, CA3, and DG in a single ROI (31). Here we report separated analyses for completeness and to contribute data to the discussion of this issue in the field. (B) In the phase 1 attention task, both regions showed state-dependent patterns of activity, with more similar patterns of activity for trials of the same vs. different states (CA2/3: t₃₁ = 7.97, P < 0.0001; DG: t₃₁ = 6.53, P < 0.0001) (compare with Fig. 3C). Error bars depict ±1 SEM of the within-participant same vs. different state difference. (C) In the phase 1 attention task, individual differences in room-state pattern similarity in CA2/3 were correlated with individual differences in behavioral performance (A′) on valid trials of the room task (r₂₃ = 0.39, P = 0.05). This effect was not found in DG [r₂₅ = 0.20, P = 0.31; note that degrees-of-freedom differ because of the robust correlation methods used (60)]. Additionally, the CA2/3 correlation was specific to room-state pattern similarity and room-state behavior: room-state activity did not predict room-state behavior (r₂₉ = −0.03, P = 0.87) and room-state pattern similarity did not predict art-state behavior (r₂₇ = 0.11, P = 0.58). Finally, controlling for room-state pattern similarity, art-state pattern similarity did not predict room-state behavior (r₂₃ = 0.12, P = 0.58). (D) During the phase 2 encoding task, there was greater pattern similarity with the task-relevant vs. task-irrelevant state template for subsequent hits vs. misses in CA2/3 (F_1,30 = 7.86, P = 0.009), but this effect was not reliable in DG (F_1,30 = 2.82, P = 0.10) (compare with Fig. 4D). Error bars depict ±1 SEM of the within-participant hits vs. misses difference. (E) Individual differences in room memory were positively correlated with the match between CA2/3 encoding activity patterns and the room- vs. art-state template (r₂₃ = 0.44, P = 0.03). This correlation was not reliable in DG [r₂₄ = 0.15, P = 0.46; note that degrees-of-freedom differ because of the robust correlation methods used (60)]. *P = 0.05, **P < 0.01, ***P < 0.001.