Memory Content Research Articles

A way forward for design and analysis of neuroimaging studies of memory consolidation

ABSTRACT Several novel ideas and suggestions were made in response to our discussion paper (Tallman et al., this issue). Careful consideration of the content and context of memory while accounting for the neuroanatomy and functional specialization of the hippocampus may reveal more consistent patterns in fMRI studies of memory consolidation. Below we address these ideas as well as issues that arise when interpreting the fMRI signal in memory consolidation studies. In addition, we describe new analyses suggested by the commentators that clarify our findings with respect to current theories.

Event boundaries structure the contents of long-term memory in younger and older adults

ABSTRACT Event boundaries impose structure on how events are stored in long-term memory. Research with young adults has shown that associations within events are stronger than those that cross event boundaries. Recently, this effect was observed in both young and old adults using movie stimuli (Davis, Chemnitz, et al., 2021). Here, we test whether this effect extends to written narratives. Young and old participants read a series of narratives that were interspersed with temporal shifts in the storyline meant to elicit the perception of an event boundary. Later, participants were cued with sentences and were asked to recall the sentence that immediately followed. We expected participants would have worse memory when a cue and correct answer flanked a boundary than when it did not. In Experiment 1, we found that despite older adults’ lower performance overall, both age groups had lower accuracy for cues that flanked a boundary, compared to cues that elicited a response from within the same event. Experiment 2 replicated the results from Experiment 1. Our results support past work that did not find age differences in event perception and demonstrate that older and younger adults may store events similarly in long-term memory.

Directed forgetting of pictures of everyday objects.

Directed forgetting is a laboratory task in which subjects are explicitly cued to forget certain items and remember others. Volitional control over the contents of memory has been used to study clinical disorders, with successful intentional control of memory being a hallmark of a healthy mind. Yet the degree of volitional forgetting over the content of visual long-term memory is unclear when compared to words. Different kinds of visual stimuli (e.g., abstract symbols, line drawings, scenes) may not equally be susceptible to voluntary control in memory, and intentional forgetting studies have shown both twice as much forgetting of pictures compared to words (think/no-think task) and half as much forgetting of pictures compared to words (directed forgetting task). In the present study, we systematically test volitional control over pictures of everyday objects using item-method directed forgetting procedures. We find that subjects are able to intentionally prioritize memory for pictures cued as to be remembered over pictures cued to be forgotten. Here we show that directed forgetting effects are observed using pictures of everyday objects (albeit to a weaker extent compared to directed forgetting of words), suggesting increased confidence for generalization of directed forgetting literature to real-world applications. However, we caution clinical applications of intentional memory control until the underlying direction causing this effect (upregulation of remember-cued items or downregulation of forget-cued items) is known.

Amygdala-cortical collaboration in reward learning and decision making.

Adaptive reward-related decision making requires accurate prospective consideration of the specific outcome of each option and its current desirability. These mental simulations are informed by stored memories of the associative relationships that exist within an environment. In this review, I discuss recent investigations of the function of circuitry between the basolateral amygdala (BLA) and lateral (lOFC) and medial (mOFC) orbitofrontal cortex in the learning and use of associative reward memories. I draw conclusions from data collected using sophisticated behavioral approaches to diagnose the content of appetitive memory in combination with modern circuit dissection tools. I propose that, via their direct bidirectional connections, the BLA and OFC collaborate to help us encode detailed, outcome-specific, state-dependent reward memories and to use those memories to enable the predictions and inferences that support adaptive decision making. Whereas lOFC→BLA projections mediate the encoding of outcome-specific reward memories, mOFC→BLA projections regulate the ability to use these memories to inform reward pursuit decisions. BLA projections to lOFC and mOFC both contribute to using reward memories to guide decision making. The BLA→lOFC pathway mediates the ability to represent the identity of a specific predicted reward and the BLA→mOFC pathway facilitates understanding of the value of predicted events. Thus, I outline a neuronal circuit architecture for reward learning and decision making and provide new testable hypotheses as well as implications for both adaptive and maladaptive decision making.

CBA-Detector: A Self-Feedback Detector Against Cache-Based Attacks

Cloud computing is convenient to provide adequate resources for tenants. However, since multiple tenants share the underlying hardware resources, malicious tenants can use the shared processor to launch cache-based attacks. Such attacks can help malicious tenants steal private data of other tenants bypassing isolation mechanisms provided by the system, resulting in information leakage. Moreover, Spectre and Meltdown vulnerabilities can even extract memory contents arbitrarily with the help of cache attacks. Therefore, cache-based attacks pose a serious threat to the security of cloud platforms. To defeat such attacks, many detection methods have been proposed. However, most methods induce high false positives because they completely rely on the hardware performance counters (HPCs) and detect attacks with static criteria. To solve this problem, this article proposes a self-feedback detector named CBA-Detector to detect cache-based attacks in real time. Specifically, CBA-Detector first uses machine learning technologies to create models for identifying suspicious programs with abnormal hardware behaviors, then analyzes suspicious programs from the instruction level to identify real attacks and provide feedback. Based on the feedback, the models can be updated to further improve their detection accuracy. As our experiments show, CBA-Detector can accurately identify cache-based attacks in real time and introduces a little overhead. Besides, the misjudgment rate decreases with the running time.

The reciprocal relationship between episodic memory and future thinking: How the outcome of predictions is subsequently remembered.

Evidence suggests that memory is involved in making simulations and predictions about the future (i.e., future thinking), but less work has examined how the outcome of those predictions (whether events play out as predicted or expected) subsequently affects episodic memory. In this investigation, we examine whether memory is better for outcomes that are consistent with predictions, or whether memory is enhanced for outcomes that are inconsistent with predictions, after the predicted event occurs. In this experiment, participants learned a core trait associated with social targets (e.g., high in extroversion), before making predictions about behaviors targets would perform. Participants then were shown behaviors the social targets actually performed (i.e., prediction outcome), which was either consistent or inconsistent with predictions. After that, participants completed a memory test (recognition; recall) for the prediction outcomes. For recognition, the results revealed better memory for outcomes that were consistent with traits associated with targets (i.e., trait‐consistent outcomes), compared to outcomes that were inconsistent (i.e., trait‐inconsistent outcomes). Finding a memory advantage for trait‐consistent outcomes suggests that outcomes that are in line with the contents of memory (e.g., what one knows; schemas) are more readily remembered than those that are inconsistent with memory, which may reflect an adaptive memory process. For recall, memory did not differ between trait‐consistent and trait‐inconsistent outcomes. Altogether, the results of this experiment advance understanding of the reciprocal relationship between episodic memory and future thinking and show that outcome of predictions has an influence on subsequent episodic memory, at least as measured by recognition.

Cognitive and social well-being in older adulthood: The CoSoWELL corpus of written life stories.

This paper presents the Cognitive and Social WELL-being (CoSoWELL) project that consists of two components. One is a large corpus of narratives written by over 1000 North American older adults (55+ years old) in five test sessions before and during the first year of the COVID-19 pandemic. The other component is a rich collection of socio-demographic data collected through a survey from the same participants. This paper introduces the first release of the corpus consisting of 1.3 million tokens and the survey data (CoSoWELL version 1.0). It also presents a series of analyses validating design decisions for creating the corpus of narratives written about personal life events that took place in the distant past, recent past (yesterday) and future, along with control narratives. We report results of computational topic modeling and linguistic analyses of the narratives in the corpus, which track the time-locked impact of the COVID-19 pandemic on the content of autobiographical memories before and during the COVID-19 pandemic. The main findings demonstrate a high validity of our analytical approach to unique narrative data and point to both the locus of topical shifts (narratives about recent past and future) and their detailed timeline. We make the CoSoWELL corpus and survey data available to researchers and discuss implications of our findings in the framework of research on aging and autobiographical memories under stress.Supplementary InformationThe online version contains supplementary material available at 10.3758/s13428-022-01926-0.

Schedulability analysis for 3-phase tasks with partitioned fixed-priority scheduling

Multicore platforms are being increasingly adopted in Cyber-Physical Systems (CPS) due to their advantages over single-core processors, such as raw computing power and energy efficiency. Typically, multicore platforms use a shared memory bus that connects the cores to the off-chip main memory. This sharing of memory bus may cause tasks running on different cores to compete for access to the main memory whenever data/instructions are need to be read/written from/to the main memory. Such competition is problematic, as it may cause variations in the execution time of tasks in a non-deterministic way. To reduce the complexity of analyzing this problem, the 3-phase task model was proposed that divides tasks’ executions into distinct memory and execution phases. The distinctive memory phases are then scheduled to eliminate/minimize main memory contention between concurrently executing tasks. However, 3-phase tasks running on different cores may still compete to access the shared memory bus/main memory in order to execute memory phases. This paper presents a partitioned scheduling-based approach that allows one to derive memory bus contention-aware worst-case response time of tasks that follow the 3-phase task model. In particular, the bus-contention analysis is derived by considering two memory access models, i.e., (i) dedicated memory access model, where a core having allowed to access the main memory via memory bus is permitted to execute more than one memory phase, and (ii) fair memory access model, that restrict each core to execute only one memory phase in its allocated bus access. Both these models represent different system and application requirements, and the resulting bus contention of tasks may vary depending on the considered model. To evaluate the effectiveness of the proposed bus contention analysis, we compare its performance against an existing analysis in the state-of-the-art by performing (i) case-study experiments, using benchmarks from the Mälardalen Benchmark suite, and (ii) empirical evaluation using synthetic task sets. Results show that our proposed analysis can improve task set schedulability of 3-phase tasks by up to 88 percentage points.

Understanding autobiographical memory content using computational text analysis

ABSTRACT Although research on autobiographical memory (AM) continues to grow, there remain few methods to analyze AM content. Past approaches are typically manual, and prohibitively time- and labour-intensive. These methodological limitations are concerning because content may provide insights into the nature and functions of AM. In particular, analyzing content in recurrent involuntary autobiographical memories (IAMs; those that spring to mind unintentionally and repetitively) could resolve controversies about whether these memories typically involve mundane or distressing events. Here, we present computational methods that can analyze content in thousands of participants’ AMs, without needing to hand-code each memory. A sample of 6,187 undergraduates completed surveys about recurrent IAMs, resulting in 3,624 text descriptions. Using frequency analyses, we identified common (e.g., “time”, “friend”) and distinctive words in recurrent IAMs (e.g., “argument” as distinctive to negative recurrent IAMs). Using structural topic modelling, we identified coherent topics (e.g., “Negative past relationships”, “Conversations”, “Experiences with family members”) within recurrent IAMs and found that topic use significantly differed depending on the valence of these memories. Computational methods allowed us to analyze large quantities of AM content with enhanced granularity and reproducibility. We present the means to enable future research on AM content at an unprecedented scope and scale.

Informacionnye faktory formirovaniya istoricheskogo soznaniya molodezhi (na primere izucheniya predstavlenij o Velikoj Otechestvennoj vojne)

The article is devoted to the analysis of patterns and factors in the formation of historical ideas of Russian students about the Great Patriotic War under the influence of the information environment. The key components of the information space are considered as factors that have a sustainable impact on the content and structure of the historical memory of young Russian citizens. The basis of empirical data was the materials of three sociological studies conducted by the authors during 2021-2022.

Development of the function of autobiographical memories evoked by odor scale for older Japanese people.

Odor-evoked autobiographical memory and related psychological changes have been evaluated based on several factors, such as emotionality, clarity, and re-experience. We developed the Function of Autobiographical Memories Evoked by Odor Scale (FAMOS) for older Japanese people as a new method for comprehensively evaluating the functions of odor-evoked autobiographical memory. We used the diary method; participants were instructed to record the contents of everyday involuntary autobiographical memories triggered by odor and complete the FAMOS. In Study 1, 600 older adults were surveyed to select items for the FAMOS and examine the factor structure. An exploratory factor analysis with PROMAX rotation using the maximum likelihood method resulted in four factors: (1) Evoking positive emotion, (2) Identity, (3) Facilitating communication, and (4) Coping with negative emotion. Sufficient reliability was demonstrated. In Study 2, the FAMOS's validity was examined in 600 older adults. We found significant correlations (Pearson) with the affective valence of odors, the Odor-evoked Autobiographical Memory Questionnaire, and other scales, confirming the validity of the FAMOS. In Study 3, the FAMOS was administered to 600 younger and 600 older adults; generational differences were compared for further validity. Older adults had higher “Evoking positive emotion,” “Identity,” and “Facilitating communication” scores on the FAMOS than younger adults, suggesting a fair degree of reliability and validity of the FAMOS.

The eyes don't have it: Eye movements are unlikely to reflect refreshing in working memory.

There is a growing interest in specifying the mechanisms underlying refreshing, i.e., the use of attention to keep working memory (WM) contents accessible. Here, we examined whether participants' visual fixations during the retention interval of a WM task indicate the current focus of internal attention, thereby serving as an online measure of refreshing. Eye movements were recorded while participants studied and maintained an array of colored dots followed by probed recall of one (Experiments 1A and 1B) or all (Experiment 2) of the memoranda via a continuous color wheel. Experiments 1A and 2 entailed an unfilled retention interval in which refreshing is assumed to occur spontaneously, and Experiment 1B entailed a retention interval embedded with cues prompting the sequential refreshment of a subset of the memoranda. During the retention interval, fixations revisited the locations occupied by the memoranda, consistent with a looking-at-nothing phenomenon in WM, but the pattern was only evident when placeholders were onscreen in Experiment 2, indicating that most of these fixations may largely reflect random gaze. Furthermore, spontaneous fixations did not predict recall precision (Experiments 1A and 2), even when ensuring that they did not reflect random gaze (Experiment 2). In Experiment 1B, refreshing cues increased fixations to the eventually tested target and predicted better recall precision, which interacted with an overall benefit of target fixations, such that the benefit of fixations decreased as the number of refreshing cues increased. Thus, fixations under spontaneous conditions had no credible effect on recall precision, whereas the beneficial effect of fixations under instructed refreshing conditions may indicate situations in which cues were disregarded. Consequently, we conclude that eye movements do not seem suitable as an online measure of refreshing.

Energy-Efficient Stream Compaction Through Filtering and Coalescing Accesses in GPGPU Memory Partitions

Graph-based applications are essential in emerging domains such as data analytics or machine learning. Data gathering in a knowledge-based society requires great data processing efficiency. High-throughput GPGPU architectures are key to enable efficient graph processing. Nonetheless, irregular and sparse memory access patterns present in graph-based applications induce high memory divergence and contention, which result in poor GPGPU efficiency for graph processing. Recent work has pointed out the importance of stream compaction operations, and has proposed a Stream Compaction Unit (SCU) to offload them to a specialized hardware. On the other hand, memory contention caused by high divergence has been tackled with the Irregular accesses Reorder Unit (IRU), delivering improved memory coalescing. In this paper, we propose a new unit, the IRU-enhanced SCU (ISCU), that leverages the strengths of both approaches. The ISCU employs the efficient mechanisms of the IRU to improve SCU stream compaction efficiency and throughput limitations, achieving a synergistic effect for graph processing. We evaluate the ISCU for a wide variety of state-of-the-art graph-based algorithms and applications. Results show that the ISCU achieves a performance speedup of 2.2x and 90 percent energy savings derived from a high reduction of 78 percent memory accesses, while incurring in 8.5 percent area overhead.

Artificial neural network performance based on correlation analysis qualitatively comparable with human performance in behavioral signal detection experiments.

Standard Gaussian signal detection theory (SDT) is a widely used approach to assess the detection performance of living organisms or technical systems without looking at the inner workings of these systems like neural or electronic mechanisms. Nevertheless, a consideration of the inner mechanisms of a system and how they produce observed behaviors should help to better understand the functioning. It might even offer the possibility to demonstrate isolated pattern separation processes directly in the model. To do so, modeling the interaction between the entorhinal cortex (EC) and the hippocampal subnetwork dentate gyrus (DG) via the perforant path reveals the decorrelation network's mode of operation. We show that the ability to do pattern separation is crucial for high-performance pattern recognition, but also for lure discrimination, and depends on the proportionality between input and output network. NEW & NOTEWORTHY We elucidate the interplay of the entorhinal cortex and the hippocampal dentate gyrus during pattern separation tasks by providing a new simulation model. Functional memory formation and processing of similar memory content is illuminated from within the system. For the first time orthogonalized spiking patterns are evaluated with signal detection theory methods, and the results are applied to clinically established and novel tests.

Media Memory: Theoretical Aspect

The article is devoted to the study of the theory of media memory and its role in the construction of collectively shared ideas about the past. The author proceeds in his work from McLuhan’s expansive interpretation of media. The processes of mediatization of communicative and cultural memory are being analyzed. Considering the views of Y. M. Lotman and J. Assman on cultural and communicative memory, the author comes to the conclusion that their theories explaining the functioning of collective memory in the era of oral and written communication, cease to work when describing the mechanisms of memory reproduction in the digital environment. Theories of mediatization of memory regard communicative memory are limited to J. Assman’s understanding of, that is, as a memory of the recent past covered by the time of the existence of contemporary digital media. Based on the works of J. Garde-Hansen, E. Hopkins and others, the author considered the theory of digital memory showing its difference from mediamemory. The processes of mediatization of collective memory in the digital environment lead to the emergence of media memory as a special virtual mechanism for constructing ideas about the past. Media memory possesses the characteristics of communicative, cultural and digital memory simultaneously, being a phenomenon of the digital era, where the change in the means of communication has led to the transformation of the content of memories and ways of their reproduction.

Altered alpha/beta desynchronization during item-context binding contributes to the associative deficit in older age.

It is proposed that older adults have difficulties to bind item and context and to recruit deep, elaborative processing during encoding. Senescent changes in the oscillatory foundations of these processes are currently unclear. We recorded electroencephalography during item-context memory formation in younger (n= 57) and older (n= 55) adults. At test, we assessed memory for the items and the item-context pairs and examined encoding-related activity based on how much information was recovered at retrieval (miss < item-only < pair). Item memory was comparable between age groups while pair memory was reduced in the older adults. Theta synchronization and alpha/beta desynchronization increased linearly with the amount of information available. Single-trial theta power could not predict subsequent item memory, but predicted pair memory in an age-invariant manner, in line with a mechanism supporting associative memory. In contrast, single-trial alpha/beta power predicted both item and pair memory, in line with a mechanism reflecting the depth of information processing, and predicted pair memory less well in the older than the younger adults. Thus, theta and alpha/beta oscillations contribute differently in shaping the contents of memories and reduced processing capacity contributes to episodic memory decline in older age.

Episodic Memories Among Irritable Bowel Syndrome (IBS) Patients: An Important Aspect of the IBS Symptom Experience.

Objective:Some IBS patients possess detailed memories of the events surrounding their bowel symptom onset (“episodic memories”). In this exploratory study we sought to: (1) examine memory relationship with gastrointestinal (GI) symptom severity, extraintestinal symptoms, and mood; (2) qualitatively explore memory valence and content in IBS patients with or without episodic memories.MethodsReferral IBS patients n = 29; age 47.0± 2.2 years, 79.3% female) enrolled in this cross-sectional, mixed methods research study. Participants completed validated specific memory instruments [Autobiographical Memory Test (AMT), Sentence Completion for Events from the Past Test (SCEPT)] and relevant questionnaires [IBS symptoms 10-cm visual analog scale); SF-36 Health-related quality of life (HRQOL); Perley-Guze and PHQ-15/12: somatization; Beck Depression/Anxiety Inventories). Qualitative analysis examined the content and valence of general memories.Results14/29 (48.3%) of IBS subjects endorsed episodic memories of IBS symptom onset, often GI infections/enteritis (35.7%). Recall of the exact year (69%) and month (60%) of symptom onset were common. Episodic memories were associated with greater IBS symptom severity/bother, higher anxiety/depression, and poorer HRQOL. Though AMT and SCEPT memory specificity were not different based on episodic memories, overgeneralization to negatively-valenced cues in the AMT was associated with more severe IBS in those without episodic memory. Qualitative analysis revealed no observable differences in topic focus of IBS patients with and without episodic memories.ConclusionsIBS patients often endorse episodic memories associated with symptom onset, and this recall seems to associate with more severe symptoms. Overgeneralization responses to negative stimuli may lead to worse bowel symptoms in those without episodic memories. IBS memory specificity may associate with qualitative differences in processing psychosocial experiences and might be important to IBS pathophysiology.

A Predictive Processing Model of Episodic Memory and Time Perception

Human perception and experience of time are strongly influenced by ongoing stimulation, memory of past experiences, and required task context. When paying attention to time, time experience seems to expand; when distracted, it seems to contract. When considering time based on memory, the experience may be different than what is in the moment, exemplified by sayings like "time flies when you're having fun." Experience of time also depends on the content of perceptual experience-rapidly changing or complex perceptual scenes seem longer in duration than less dynamic ones. The complexity of interactions among attention, memory, and perceptual stimulation is a likely reason that an overarching theory of time perception has been difficult to achieve. Here, we introduce a model of perceptual processing and episodic memory that makes use of hierarchical predictive coding, short-term plasticity, spatiotemporal attention, and episodic memory formation and recall, and apply this model to the problem of human time perception. In an experiment with approximately 13,000 human participants, we investigated the effects of memory, cognitive load, and stimulus content on duration reports of dynamic natural scenes up to about 1 minute long. Using our model to generate duration estimates, we compared human and model performance. Model-based estimates replicated key qualitative biases, including differences by cognitive load (attention), scene type (stimulation), and whether the judgment was made based on current or remembered experience (memory). Our work provides a comprehensive model of human time perception and a foundation for exploring the computational basis of episodic memory within a hierarchical predictive coding framework.

Complexity of symbolic representation in working memory of Transformer correlates with the complexity of a task

Even though Transformers are extensively used for Natural Language Processing tasks, especially for machine translation, they lack an explicit memory to store key concepts of processed texts. This paper explores the properties of the content of symbolic working memory added to the Transformer model decoder. Such working memory enhances the quality of model predictions in machine translation task and works as a neural-symbolic representation of information that is important for the model to make correct translations. The study of memory content revealed that translated text keywords are stored in the working memory, pointing to the relevance of memory content to the processed text. Also, the diversity of tokens and parts of speech stored in memory correlates with the complexity of the corpora for machine translation task.

Optimizing UniFrac with OpenACC Yields Greater Than One Thousand Times Speed Increase.

ABSTRACTUniFrac is an important tool in microbiome research that is used for phylogenetically comparing microbiome profiles to one another (beta diversity). Striped UniFrac recently added the ability to split the problem into many independent subproblems, exhibiting nearly linear scaling but suffering from memory contention. Here, we adapt UniFrac to graphics processing units using OpenACC, enabling greater than 1,000× computational improvement, and apply it to 307,237 samples, the largest 16S rRNA V4 uniformly preprocessed microbiome data set analyzed to date.IMPORTANCE UniFrac is an important tool in microbiome research that is used for phylogenetically comparing microbiome profiles to one another. Here, we adapt UniFrac to operate on graphics processing units, enabling a 1,000× computational improvement. To highlight this advance, we perform what may be the largest microbiome analysis to date, applying UniFrac to 307,237 16S rRNA V4 microbiome samples preprocessed with Deblur. These scaling improvements turn UniFrac into a real-time tool for common data sets and unlock new research questions as more microbiome data are collected.