Attentional fluctuations and the temporal organization of memory

Age-Related differences in the relationship between sustained attention and associative memory and Memory-Guided inference

Episodic memory enables the encoding and retrieval of novel associations, as well as the bridging across learned associations to draw novel inferences. A fundamental goal of memory science is to understand the factors that give rise to individual and age-related differences in memory-dependent cognition. Variability in episodic memory could arise, in part, from both individual differences in sustained attention and diminished attention in aging. We first report that, relative to young adults (N = 23; M = 20.0 years), older adults (N = 26, M = 68.7 years) demonstrated lower associative memory and memory-guided associative inference performance and that this age-related reduction in associative inference occurs even when controlling for associative memory performance. Next, we confirm these age-related memory differences by using a high-powered, online replication study (young adults: N = 143, M = 26.2 years; older adults N = 133, M = 67.7 years), further demonstrating that age-related differences in memory do not reflect group differences in sustained attention (as assayed by the gradual-onset continuous performance task; gradCPT). Finally, we report that individual differences in sustained attention explain between-person variability in associative memory and inference performance in the present, online young adult sample, but not in the older adult sample. These findings extend understanding of the links between attention and memory in young adults, demonstrating that differences in sustained attention was related to differences in memory-guided inference. By contrast, our data suggest that the present age-related differences in memory-dependent behavior and the memory differences between older adults are due to attention-independent mechanisms.

Reading stories while responding to colors: The attentional boost effect for coherent verbal stimuli

Background stimuli presented with an unrelated target in a detection task are better remembered than those presented with a distractor. This attentional boost effect (ABE) has been shown with randomly sequenced, unrelated background images or words. This study examines whether coherent narratives providing meaningful temporal structure interfere with the ABE. Participants studied a series of words for a later memory test while monitoring a concurrent stream of colored squares, pressing the spacebar for target colors and ignoring distractor colors. The words either formed a coherent story (Experiments 1, 3, and 5) or were scrambled in order (Experiments 2 and 4), with a target-to-distractor ratio of 1:1 (Experiments 1-3) or 1:4 (Experiments 4 and 5). Results showed that words paired with the target color were better remembered than those paired with the distractor color, confirming the ABE. However, the ABE was equivalent for coherent and incoherent words, suggesting that narrative coherence did not affect its temporal precision. Contrary to the idea that coherence or temporal relatedness may impose its own temporal structure, the results support the temporal orienting account of the ABE, indicating that target detection triggers a temporally precise orienting response that enhances concurrent task processing. However, constructing a narrative from related words may increase cognitive load, leading to a consistently small ABE across experiments.

Opposite effects of emotion and event segmentation on temporal order memory and object-context binding

Our daily lives unfold continuously, yet our memories are organised into distinct events, situated in a specific context of space and time, and chunked when this context changes (at event boundaries). Previous research showed that this process, termed event segmentation, enhances object-context binding but impairs temporal order memory. Physiologically, peaks in pupil dilation index event segmentation, similar to emotion-induced bursts of autonomic arousal. Emotional arousal also modulates object-context binding and temporal order memory. Yet, these two critical factors have not been systematically studied together. To address this gap, we ran a behavioural experiment using a paradigm validated to study event segmentation and extended it with emotion manipulation. During encoding, we sequentially presented greyscale objects embedded in coloured frames (colour changes defining events), with a neutral or aversive sound. During retrieval, we tested participants' memory of temporal order memory and object-colour binding. We found opposite effects of emotion and event segmentation on episodic memory. While event segmentation enhanced object-context binding, emotion impaired it. On the contrary, event segmentation impaired temporal order memory, but emotion enhanced it. These findings increase our understanding of episodic memory organisation in laboratory settings, and potentially in real life with perceptual changes and emotion fluctuations constantly interacting.

Shift happens: aging alters the content but not the organization of memory for complex events

While cognitive aging research has compared episodic memory accuracy between younger and older adults, less work has described differences in how memories are encoded and recalled. This is important for memories of real-world experiences, since there is immense variability in which details can be accessed and organized into narratives. We investigated age effects on the organization and content of memory for complex events. In two independent samples (N = 45; 60), young and older adults encoded and recalled the same short-movie. We applied a novel scoring on the recollections to quantify recall accuracy, temporal organization (temporal contiguity, forward asymmetry), and content (perceptual, conceptual). No age-effects on recall accuracy nor on metrics of temporal organization emerged. Older adults provided more conceptual and non-episodic content, whereas younger adults reported a higher proportion of event-specific information. Our results indicate that age-related differences in episodic recall reflect distinctions in what details are assembled from the past.

The Ubiquity of Time in Latent-cause Inference

Humans have an outstanding ability to generalize from past experiences, which requires parsing continuously experienced events into discrete, coherent units, and relating them to similar past experiences. Time is a key element in this process; however, how temporal information is used in generalization remains unclear. Latent-cause inference provides a Bayesian framework for clustering experiences, by building a world model in which related experiences are generated by a shared cause. Here, we examine how temporal information is used in latent-cause inference, using a novel task in which participants see "microbe" stimuli and explicitly report the latent cause ("strain") they infer for each microbe. We show that humans incorporate time in their inference of latent causes, such that recently inferred latent causes are more likely to be inferred again. In particular, a "persistent" model, in which the latent cause inferred for one observation has a fixed probability of continuing to cause the next observation, explains the data significantly better than two other time-sensitive models, although extensive individual differences exist. We show that our task and this model have good psychometric properties, highlighting their potential use for quantifying individual differences in computational psychiatry or in neuroimaging studies.

The attentional boost effect in free recall dynamics

With the attentional boost effect (ABE), responding to a briefly presented target in a detection task enhances the encoding of other items presented at the same time. However, the effects of target detection on context memory for the event in which the stimulus appeared remain unclear. Here, we present findings from verbal free recall and recognition experiments that test the effects of target detection during encoding on temporal and relational aspects of context memory. Consistent with prior demonstrations of limited effects of target detection on context memory, in Experiment 1 there was no evidence that target detection influenced the likelihood of transitioning to items that were presented at similar times during encoding, or that were in the same encoding condition. These null effects were replicated in a second experiment, which added an old/new recognition and relational memory test. These results indicate that target detection during encoding has minimal effects on the formation of temporal associations between words in memory.

Edge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention

Although we must prioritize the processing of task-relevant information to navigate life, our ability to do so fluctuates across time. Previous work has identified fMRI functional connectivity (FC) networks that predict an individual's ability to sustain attention and vary with attentional state from 1 min to the next. However, traditional dynamic FC approaches typically lack the temporal precision to capture moment-to-moment network fluctuations. Recently, researchers have "unfurled" traditional FC matrices in "edge cofluctuation time series" which measure timepoint-by-timepoint cofluctuations between regions. Here we apply event-based and parametric fMRI analyses to edge time series to capture moment-to-moment fluctuations in networks related to attention. In two independent fMRI datasets examining young adults of both sexes in which participants performed a sustained attention task, we identified a reliable set of edges that rapidly deflects in response to rare task events. Another set of edges varies with continuous fluctuations in attention and overlaps with a previously defined set of edges associated with individual differences in sustained attention. Demonstrating that edge-based analyses are not simply redundant with traditional regions-of-interest-based approaches, up to one-third of reliably deflected edges were not predicted from univariate activity patterns alone. These results reveal the large potential in combining traditional fMRI analyses with edge time series to identify rapid reconfigurations in networks across the brain.

Retrieval of temporal structure at recall can occur automatically

Temporal-structure, namely, the order in which events unfold over time, is one of the fundamental principles of episodic memory organization. A seminal empirical demonstration of the prominence of temporal structure in memory organization is the Temporal Contiguity Effect (TCE), whereby the proximity between two items at encoding predicts the likelihood of those two items being retrieved consecutively during recall. Recent studies have found that TCE occurs under a wide variety of conditions in which strategic control processes at encoding are reduced or even eliminated. This suggests that the encoding of temporal structure occurs automatically. Extending these findings, in the current study we asked whether the retrieval of temporal structure, as reflected by indices of the TCE, is influenced by strategic control processes at retrieval. To manipulate participants' ability to rely on strategic control processes, we compared standard recall performance (Full Attention condition) to a condition in which attention was divided between recall and a concurrent task (Divided Attention condition), which has been shown to disrupt such control processes. Across two experiments-one with standard encoding conditions and one with continual distraction during encoding-we found no differences in any index of the TCE between the two conditions. These results are all the more striking considering that in both experiments, dividing attention negatively affected overall recall performance compared to the Full Attention condition. Thus, while recall performance is reduced when disrupting strategic processes, the ability to use temporal structure to drive recall is not affected.

Edge-based general linear models capture high-frequency fluctuations in attention

Although we must prioritize the processing of task-relevant information to navigate life, our ability to do so fluctuates across time. Previous work has identified fMRI functional connectivity (FC) networks that predict an individual's ability to sustain attention and vary with attentional state from one minute to the next. However, traditional dynamic FC approaches typically lack the temporal precision to capture moment-by-moment network fluctuations. Recently, researchers have 'unfurled' traditional FC matrices in 'edge cofluctuation time series' which measure time point-by-time point cofluctuations between regions. Here we apply event-based and parametric fMRI analyses to edge time series to capture high-frequency fluctuations in networks related to attention. In two independent fMRI datasets in which participants performed a sustained attention task, we identified a reliable set of edges that rapidly deflects in response to rare task events. Another set of edges varies with continuous fluctuations in attention and overlaps with a previously defined set of edges associated with individual differences in sustained attention. Demonstrating that edge-based analyses are not simply redundant with traditional regions-of-interest based approaches, up to one-third of reliably deflected edges were not predicted from univariate activity patterns alone. These results reveal the large potential in combining traditional fMRI analyses with edge time series to identify rapid reconfigurations in networks across the brain.