Influences on memory for naturalistic visual episodes: sleep, familiarity, and traits differentially affect forms of recall

Context reinstatement requires a schema relevant virtual environment to benefit object recall

How does our environment impact what we will later remember? Early work in real-world environments suggested that having matching encoding/retrieval contexts improves memory. However, some laboratory-based studies have not replicated this advantageous context-dependent memory effect. Using virtual reality methods, we find support for context-dependent memory effects and examine an influence of memory schema and dynamic environments. Participants (N = 240) remembered more objects when in the same virtual environment (context) as during encoding. This traded-off with falsely "recognizing" more similar lures. Experimentally manipulating the virtual objects and environments revealed that a congruent object/environment schema aids recall (but not recognition), though a dynamic background does not. These findings further our understanding of when and how context affects our memory through a naturalistic approach to studying such effects.

Sleep Differentially and Profoundly Impairs Recall Memory in a Patient with Fornix Damage

In March 2020, C.T., a kind, bright, and friendly young woman underwent surgery for a midline tumor involving her septum pellucidum and extending down into her fornices bilaterally. Following tumor diagnosis and surgery, C.T. experienced significant memory deficits: C.T.'s family reported that she could remember things throughout the day, but when she woke up in the morning or following a nap, she would expect to be in the hospital, forgetting all the information that she had learned before sleep. The current study aimed to empirically validate C.T.'s pattern of memory loss and explore its neurological underpinnings. On two successive days, C.T. and age-matched controls watched an episode of a TV show and took a nap or stayed awake before completing a memory test. Although C.T. performed numerically worse than controls in both conditions, sleep profoundly exacerbated her memory impairment, such that she could not recall any details following a nap. This effect was replicated in a second testing session. High-resolution MRI scans showed evidence of the trans-callosal surgical approach's impact on the mid-anterior corpus callosum, indicated that C.T. had perturbed white matter particularly in the right fornix column, and demonstrated that C.T.'s hippocampal volumes did not differ from controls. These findings suggest that the fornix is important for processing episodic memories during sleep. As a key output pathway of the hippocampus, the fornix may ensure that specific memories are replayed during sleep, maintain the balance of sleep stages, or allow for the retrieval of memories following sleep.

Machine-learning as a validated tool to characterize individual differences in free recall of naturalistic events

The use of naturalistic stimuli, such as narrative movies, is gaining popularity in many fields, characterizing memory, affect, and decision-making. Narrative recall paradigms are often used to capture the complexity and richness of memory for naturalistic events. However, scoring narrative recalls is time-consuming and prone to human biases. Here, we show the validity and reliability of using a natural language processing tool, the Universal Sentence Encoder (USE), to automatically score narrative recalls. We compared the reliability in scoring made between two independent raters (i.e., hand scored) and between our automated algorithm and individual raters (i.e., automated) on trial-unique video clips of magic tricks. Study 1 showed that our automated segmentation approaches yielded high reliability and reflected measures yielded by hand scoring. Study 1 further showed that the results using USE outperformed another popular natural language processing tool, GloVe. In Study 2, we tested whether our automated approach remained valid when testing individuals varying on clinically relevant dimensions that influence episodic memory, age, and anxiety. We found that our automated approach was equally reliable across both age groups and anxiety groups, which shows the efficacy of our approach to assess narrative recall in large-scale individual difference analysis. In sum, these findings suggested that machine learning approach implementing USE is a promising tool for scoring large-scale narrative recalls and perform individual difference analysis for research using naturalistic stimuli.

Organization and Priming of Long-term Memory Representations with Two-phase Plasticity

Background / Introduction

In recurrent neural networks in the brain, memories are represented by so-called Hebbian cell assemblies. Such assemblies are groups of neurons with particularly strong synaptic connections formed by synaptic plasticity and consolidated by synaptic tagging and capture (STC). To link these synaptic mechanisms to long-term memory on the level of cognition and behavior, their functional implications on the level of neural networks have to be understood.

Methods

We employ a biologically detailed recurrent network of spiking neurons featuring synaptic plasticity and STC to model the learning and consolidation of long-term memory representations. Using this, we investigate the effects of different organizational paradigms, and of priming stimulation, on the functionality of multiple memory representations. We quantify these effects by the spontaneous activation of memory representations driven by background noise.

Results

We find that the learning order of the memory representations significantly biases the likelihood of activation towards more recently learned representations, and that hub-like overlap structure counters this effect. We identify long-term depression as the mechanism underlying these findings. Finally, we demonstrate that STC has functional consequences for the interaction of long-term memory representations: 1. intermediate consolidation in between learning the individual representations strongly alters the previously described effects, and 2. STC enables the priming of a long-term memory representation on a timescale of minutes to hours.

Conclusion

Our findings show how synaptic and neuronal mechanisms can provide an explanatory basis for known cognitive effects.

Examining the effects of time of day and sleep on generalization

Extracting shared structure across our experiences allows us to generalize our knowledge to novel contexts. How do different brain states influence this ability to generalize? Using a novel category learning paradigm, we assess the effect of both sleep and time of day on generalization that depends on the flexible integration of recent information. Counter to our expectations, we found no evidence that this form of generalization is better after a night of sleep relative to a day awake. Instead, we observed an effect of time of day, with better generalization in the morning than the evening. This effect also manifested as increased false memory for generalized information. In a nap experiment, we found that generalization did not benefit from having slept recently, suggesting a role for time of day apart from sleep. In follow-up experiments, we were unable to replicate the time of day effect for reasons that may relate to changes in category structure and task engagement. Despite this lack of consistency, we found a morning benefit for generalization when analyzing all the data from experiments with matched protocols (n = 136). We suggest that a state of lowered inhibition in the morning may facilitate spreading activation between otherwise separate memories, promoting this form of generalization.

Sleep reduces the semantic coherence of memory recall: An application of latent semantic analysis to investigate memory reconstruction

Sleep is thought to help consolidate hippocampus-dependent memories by reactivating previously encoded neural representations, promoting both quantitative and qualitative changes in memory representations. However, the qualitative nature of changes to memory representations induced by sleep remains largely uncharacterized. In this study, we investigated how memories are reconstructed by hypothesizing that semantic coherence, defined as conceptual relatedness between statements of free-recall texts and quantified using latent semantic analysis (LSA), is affected by post-encoding sleep. Short naturalistic videos of events featuring six animals were presented to 115 participants who were randomly assigned to either 12- or 24-h delay groups featuring sleep or wakefulness. Participants' free-recall responses were analyzed to test for an effect of sleep on semantic coherence between adjacent statements, and overall. The presence of sleep reduced both forms of semantic coherence, compared to wakefulness. This change was robust and not due to shifts in conciseness or repetitiveness with sleep. These findings support the notion that sleep-dependent consolidation qualitatively changes the features of reconstructed memory representations by reducing semantic coherence.

On the relationship between trait autobiographical episodic memory and spatial navigation

Influential research has focused on identifying the common neural and behavioural substrates underlying episodic memory (the re-experiencing of specific details from past experiences) and spatial cognition, with some theories proposing that these are supported by the same mechanisms. However, the similarities and differences between these two forms of memory in humans require further specification. We used an individual-differences approach based on self-reported survey data collected in a large online study (n = 7,487), focusing on autobiographical episodic memory and spatial navigation and their relationship to object and spatial imagery abilities. Multivariate analyses replicated prior findings that autobiographical episodic memory abilities dissociated from spatial navigational abilities. Considering imagery, episodic autobiographical memory overlapped with imagery of objects, whereas spatial navigation overlapped with a tendency to focus on spatial schematics and manipulation. These results suggest that trait episodic autobiographical memory and spatial navigation correspond to distinct mental processes.