Memory Content Research Articles

Control of working memory by phase–amplitude coupling of human hippocampal neurons

Retaining information in working memory is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference1,2. However, how cognitive control regulates working memory storage is unclear. Here we show that interactions of frontal control and hippocampal persistent activity are coordinated by theta–gamma phase–amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in their working memory. In the hippocampus, TG-PAC was indicative of working memory load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. The spike timing of these PAC neurons was coordinated with frontal theta activity when cognitive control demand was high. By introducing noise correlations with persistently active neurons in the hippocampus, PAC neurons shaped the geometry of the population code. This led to higher-fidelity representations of working memory content that were associated with improved behaviour. Our results support a multicomponent architecture of working memory1,2, with frontal control managing maintenance of working memory content in storage-related areas3–5. Within this framework, hippocampal TG-PAC integrates cognitive control and working memory storage across brain areas, thereby suggesting a potential mechanism for top-down control over sensory-driven processes.

Differential effects of high-definition transcranial direct current stimulation (HD-tDCS) on attentional guidance by working memory in males with substance use disorder according to memory modality

Information stored in working memory can guide perception selection, and this process is modulated by cognitive control. Although previous studies have demonstrated that neurostimulation over the left dorsolateral prefrontal cortex (lDLPFC) contributes to restore cognitive control among individuals with substance use disorder (SUD), there remains an open question about the potential stimulation effects on memory-driven attention. To address this issue, the present study adopted a combined working memory/attention paradigm while employing high-definition transcranial direct current stimulation (HD-tDCS) to stimulate the lDLPFC. Observers were asked to maintain visual or audiovisual information in memory while executing a search task, while the validity of the memory contents for the subsequent search task could be either invalid or neutral. The results showed a faint memory-driven attentional suppression effect in sham stimulation only under the audiovisual condition. Moreover, anodal HD-tDCS facilitated attentional suppression effect in both the strength and temporal dynamics under the visual-only condition, whereas the effect was impaired or unchanged under the audiovisual condition. Surprisingly, cathodal HD-tDCS selectively improved temporal dynamics of the attentional suppression effect under the audiovisual condition. The present study revealed the differential enhancement of HD-tDCS on cognitive control over visual and audiovisual memory-driven attention among individuals with SUD.

Sfântul Augustin despre memoria lucrurilor și memoria spirituală

Augustine is fascinated by the domains that memory dominates, as well as by the mystery that envelops them. Their classification cannot lead to the inclusion of what it represents in the soul, but you can be surprised by the faculties that it can coordinate or stimulate in one way or another. More precisely, it surprises you to discover contents in your memory that we believe come from outside, from an objective reality that our senses probe and offer us. From the life of consciousness ‒ which, at every investigation, meets us as a mystery, which constitutes the originality of Augustine's thinking ‒ memory is also a part, but not only it is lived in this way, but also time, like any faculty or aspect over which consciousness falls in its movement of self-absorption.

It's not a lie … If you believe it: Narrative analysis of autobiographical memories reveals over-confidence disposition in patients who confabulate

Humans perceive their personal memories as fundamentally true, and although memory is prone to inaccuracies, flagrant memory errors are rare. Some patients with damage to the ventromedial prefrontal cortex (vmPFC) recall and act upon patently erroneous memories (spontaneous confabulations). Clinical observations suggest these memories carry a strong sense of confidence, a function ascribed to vmPFC in studies of memory and decision making. However, most studies of the underlying mechanisms of memory overconfidence do not directly probe personal recollections and resort instead to laboratory-based tasks and contrived rating scales. We analyzed naturalistic word use of patients with focal vmPFC damage (N = 18) and matched healthy controls (N = 23) while they recalled autobiographical memories using the Linguistic Inquiry and Word Count (LIWC) method. We found that patients with spontaneous confabulation (N = 7) tended to over-use words related to the categories of ‘certainty’ and of ‘swearwords’ compared to both non-confabulating vmPFC patients (N = 11) and control participants. Certainty related expressions among confabulating patients were at normal levels during erroneous memories and were over-expressed during accurate memories, contrary to our predictions. We found no elevation in expressions of affect (positive or negative), temporality or drive as would be predicted by some models of confabulation. Thus, erroneous memories may be associated with subjectively lower certainty, but still exceed patients' report criterion because of a global proclivity for overconfidence. This may be compounded by disinhibition reflected by elevated use of swearwords. These findings demonstrate that analysis of naturalistic expressions of memory content can illuminate global meta-mnemonic contributions to memory accuracy complementing indirect laboratory-based correlates of behavior. Memory accuracy is the result of complex interactions among multiple meta-mnemonic processes such as monitoring, report criteria, and control processes which may be shared across decision-making domains.

A Neural Decision Signal during Internal Sampling from Working Memory in Humans.

How humans transform sensory information into decisions that steer purposeful behavior is a central question in psychology and neuroscience that is traditionally investigated during the sampling of external environmental signals. The decision-making framework of gradual information sampling toward a decision has also been proposed to apply when sampling internal sensory evidence from working memory. However, neural evidence for this proposal remains scarce. Here we show (using scalp EEG in male and female human volunteers) that sampling internal visual representations from working memory elicits a scalp EEG potential associated with gradual evidence accumulation-the central parietal positivity. Consistent with an evolving decision process, we show how this signal (1) scales with the time participants require to reach a decision about the cued memory content and (2) is amplified when having to decide among multiple contents in working memory. These results bring the electrophysiology of decision-making into the domain of working memory and suggest that variability in memory-guided behavior may be driven (at least in part) by variations in the sampling of our inner mental contents.

Computerized cognitive control training to reduce rumination in major depression: A randomized controlled trial

ObjectiveRumination is a major risk factor for the onset and recurrence of depressive episodes and has been associated with deficits in updating working memory content. This randomized controlled trial examines whether training updating-specific cognitive control processes reduces daily ruminative thoughts in clinically depressed individuals. MethodsSixty-five individuals with a current major depressive episode were randomized to 10 sessions of either cognitive control training (N = 31) or placebo training (N = 34). The frequency and negativity of individuals’ daily ruminative thoughts were assessed for seven days before training, after training, and at a 3-month follow-up using experience sampling methodology. Secondary outcomes were depressive symptoms, depressed mood, and level of disability. ResultsCognitive control training led to stronger improvements in the trained task than placebo training. However, cognitive control training did not lead to greater reductions in the frequency or negativity of daily ruminative thoughts than placebo training. There were no training-specific effects on participants' depressive symptoms or level of disability. ConclusionsThe robustness of the present null-findings, combined with the methodological strengths of the study, suggest that training currently depressed individuals to update emotional content in working memory does not affect the frequency or negativity of their daily ruminative thoughts.

Electrophysiological Mechanisms of Memory Consolidation in Human Non-rapid Eye Movement Sleep

Abstract Purpose of Review Pioneering work in rodents has shown that the reactivation of recently acquired memories during sleep is a key mechanism underlying the beneficial effect of sleep on memory consolidation. In this review, we consider recent evidence of memory reactivation processes in human sleep. Recent Findings The precise temporal coupling of sleep spindles to slow oscillations during non-rapid eye movement sleep plays a central role in sleep-associated memory consolidation. Both correlational studies and studies directly manipulating oscillatory activity in the sleeping brain have confirmed that spindles coupled to slow oscillations are better predictors of memory than uncoupled spindles and that the greatest memory benefit comes when spindles are tightly coupled to the up-state of the slow oscillation. Recent evidence suggests that memory content is reactivated during sleep, with a functional benefit for memory performance after sleep. Reactivation events are time-locked around slow oscillation-spindle coupling events, as well as sharp-wave ripples in hippocampus. Summary Memory reactivation, which is facilitated by slow oscillation-spindle coupling events, can be observed during human sleep and shows promise as a prime mechanism underlying sleep’s beneficial effects on memory.

Current Effect of Mother-Child Memory Talk on Emotion Regulation, Self-Esteem, and Memory

Children talking to their parents more frequently about past experiences tend to have higher emotion regulation skills and self-esteem in their future lives, which may lead to higher volume and richer emotional content in future memories. Previous research also indicated that self-esteem has a strong bond with emotion regulation skills. This study’s aim is to measure the mediator roles of emotion regulation difficulty and self-esteem on the relationship between childhood maternal reminiscing frequency and the volume and emotional content of the current memory experienced with the mother. Additionally, mediator roles of self-esteem in the connection between past maternal reminiscing and emotion regulation difficulty, and emotion regulation difficulty in the relationship between self-esteem and the current memory variables (i.e., total words, total emotion and unique emotion words) are examined. Participants (N=124, the age range was 22-39) filled out Rosenberg Self-Esteem, Emotion Regulation Difficulty, and Family Reminiscence Scales and wrote down one negatively-charged recent memory about their mothers. Path analysis revealed significant positive associations between past maternal reminiscing and self-esteem, emotion regulation difficulty, and total and unique emotion words in recent memory, and negative association between self-esteem and emotion regulation difficulty, supporting half of the mediation hypotheses. Results supported the notion that the frequency of parent-child reminiscing conversations in childhood is a parameter of child development since it can show its prospective effect via improving self-esteem and emotional functioning. Gender differences were not evident for current memory variables but more research on this issue is needed to reach more precise conclusions.

Memory identification and its failures

When we remember, we often know that we do. How does this memory identification proceed? After having articulated some constraints on an attractive account of memory identification, this paper explores three types of accounts that respectively appeal to features of memory content, of memory as an activity, and of memory as an attitude. It offers reasons to favour an attitudinal account giving pride of place to the feeling of familiarity.

Enhancing Heterogeneous Network Performance: Advanced Content Popularity Prediction and Efficient Caching

With the popularity of smart devices and the growth of high-bandwidth applications, the wireless industry is facing an increased surge in data traffic. This challenge highlights the limitations of traditional edge-caching solutions, especially in terms of content-caching effectiveness and network-communication latency. To address this problem, we investigated efficient caching strategies in heterogeneous network environments. The caching decision process becomes more complex due to the heterogeneity of the network environment, as well as due to the diversity of user behaviors and content requests. To address the problem of increased system latency due to the dynamically changing nature of content popularity and limited cache capacity, we propose a novel content placement strategy, the long-short-term-memory–content-population-prediction model, to capture the correlation of request patterns between different contents and the periodicity in the time domain, in order to improve the accuracy of the prediction of content popularity. Then, to address the heterogeneity of heterogeneous network environments, we propose an efficient content delivery strategy: the multi-intelligent critical collaborative caching policy. This strategy models the edge-caching problem in heterogeneous scenarios as a Markov decision process using multi-base-station-environment information. In order to fully utilize the multi-intelligence information, we have improved the actor–critic approach by integrating the attention mechanism into a neural network. Whereas the actor network is responsible for making decisions based on local information, the critic network evaluates and enhances the actor’s performance. We conducted extensive simulations, and the results showed that the Long Short Term Memory content population prediction model was more advantageous, in terms of content-popularity-prediction accuracy, with a 28.61% improvement in prediction error, compared to several other existing methods. The proposed multi-intelligence actor–critic collaborative caching policy algorithm improved the cache-hit-rate metric by up to 32.3% and reduced the system latency by 1.6%, demonstrating the feasibility and effectiveness of the algorithm.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall of stimulus features and categories.

Here, we demonstrate the first successful use of static neural stimulation patterns for specific information content. These static patterns were derived by a model that was applied to a subject's own hippocampal spatiotemporal neural codes for memory. We constructed a new model of processes by which the hippocampus encodes specific memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of targeted content into short-term memory. A memory decoding model (MDM) of hippocampal CA3 and CA1 neural firing was computed which derives a stimulation pattern for CA1 and CA3 neurons to be applied during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. MDM electrical stimulation delivered to the CA1 and CA3 locations in the hippocampus during the sample phase of DMS trials facilitated memory of images from the DMS task during a delayed recognition (DR) task that also included control images that were not from the DMS task. Across all subjects, the stimulated trials exhibited significant changes in performance in 22.4% of patient and category combinations. Changes in performance were a combination of both increased memory performance and decreased memory performance, with increases in performance occurring at almost 2 to 1 relative to decreases in performance. Across patients with impaired memory that received bilateral stimulation, significant changes in over 37.9% of patient and category combinations was seen with the changes in memory performance show a ratio of increased to decreased performance of over 4 to 1. Modification of memory performance was dependent on whether memory function was intact or impaired, and if stimulation was applied bilaterally or unilaterally, with nearly all increase in performance seen in subjects with impaired memory receiving bilateral stimulation. These results demonstrate that memory encoding in patients with impaired memory function can be facilitated for specific memory content, which offers a stimulation method for a future implantable neural prosthetic to improve human memory.

The representation of agreement features in memory is updated during sentence processing: Evidence from verb-reflexive interactions

The formation of linguistic dependencies is subject to memory interference. In this study, we ask whether memory representations are fixed, or whether they can be distorted and updated after their initial encoding. Models of Cue-Based Retrieval assume that memory representations are fixed. However, representational interference and rational inference models assume that memory contents can be edited. To examine this, we test how reflexive attraction is affected by preceding verbal agreement in Hebrew. Cue-Based Retrieval suggests that agreement on the verb can exaggerate the reflexive’s sensitivity to the distractor. In contrast, we propose that if memory representations can be edited, verbal agreement can alter the representation of the subject. This process would reduce vulnerability to distortions originating from the distractor. In two self-paced reading experiments and one forced-choice completion we find (i) decreased reflexive attraction when (grammatical or ungrammatical) agreement cues were available on the preceding verb; and (ii) a preference for reflexive forms matching the verb over forms matching the subject when the sentence included ungrammatical verbal agreement. These results suggest that comprehenders use featural information from the verb to recover properties of the subject. The findings are therefore consistent with a memory model where representations can be distorted and updated, as well as with rational inference about memory disruption.

Differences in the content and coherence of autobiographical memories between younger and older adults: Insights from text analysis.

Several studies have shown that older adults generate autobiographical memories with fewer specific details than younger adults, a pattern typically attributed to age-relate declines in episodic memory. A relatively unexplored question is how aging affects the content used to represent and recall these memories. We recently proposed that older adults may predominately represent and recall autobiographical memories at the gist level. Emerging from this proposal is the hypothesis that older adults represent memories with a wider array of content topics and recall memories with a distinct narrative style when compared to younger adults. We tested this hypothesis by applying natural language processing approaches to a data set of autobiographical memories described by healthy younger and older adults. We used topic modeling to estimate the distribution (i.e., diversity) of content topics used to represent a memory, and sentence embedding to derive an internal similarity score to estimate the shifts in content when narrating a memory. First, we found that older adults referenced a wider array of content topics (higher content diversity) than younger adults when recalling their autobiographical memories. Second, we found older adults were included more content shifts when narrating their memories than younger adults, suggesting a reduced reliance on choronology to form a coherent memory. Third, we found that the content diversity measures were positively related to specific detail generation for older adults, potentially reflecting age-related compensation for episodic memory difficulties. We discuss how our results shed light on how younger and older adults differ in the way they remember and describe the past. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Saccadic selection in visual working memory is robust across the visual field and linked to saccade metrics: Evidence from nine experiments and more than 100,000 trials.

Visual working memory and actions are closely intertwined. Memory can guide our actions, but actions also impact what we remember. Even during memory maintenance, actions such as saccadic eye movements select content in visual working memory, resulting in better memory at locations that are congruent with the action goal as compared to incongruent locations. Here, we further substantiate the claim that saccadic eye movements are fundamentally linked to visual working memory by analyzing a large data set (> 100k trials) of nine experiments (eight of them previously published). Using Bayesian hierarchical models, we demonstrate robust saccadic selection across the full range of probed saccade directions, manifesting as better memory performance at the saccade goal irrespective of its location in the visual field. By inspecting individual differences in saccadic selection, we show that saccadic selection was highly prevalent in the population. Moreover, both saccade metrics and visual working memory performance varied considerably across the visual field. Crucially, however, both idiosyncratic and systematic visual field anisotropies were not correlated between visual working memory and the oculomotor system, suggesting that they resulted from different sources (e.g., rely on separate spatial maps). In stark contrast, trial-by-trial variations in saccade metrics were strongly associated with memory performance: At any given location, shorter saccade latencies and more accurate saccades were associated with better memory performance, undergirding a robust link between action selection and visual memory. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Remembering our darkest moments: Reminiscence bumps for highly negative life events.

Prior research has shown that the lifetime age distribution of adults' personal memories peaks in late adolescence and early adulthood, and that this reminiscence bump is apparent primarily for positive rather than negative events. Inspired by sociological research on the crime-age curve, four new studies tested the idea that adults' negative memories of moral transgressions and behavioral missteps also would show a reminiscence bump. A secondary goal was to determine if the ages and content of actual memories recounted by older adults aligned closely with people's expectations for memories provided by an imaginary "typical" older adult. In Study 1, college students were asked to estimate the ages at which people are most likely to have committed crimes and minor moral transgressions; estimated ages peaked sharply during adolescence and early adulthood. Participants also listed emotions that they thought would accompany these misdeeds. In Study 2, college students were asked to describe memories that they expected a typical older adult to recall in response to distinctive emotion cues, including the negative emotions identified in Study 1. Study 3 was a replication of Study 2 using middle-aged participants. In Study 4, older adults provided their own personal memories in response to the emotion cues used in Study 2 and Study 3. The studies identified, for the first time, prominent reminiscence bumps for both expected and actual memories cued by negative emotions. Implications for new research on autobiographical memory functions and age-related memory declines are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The effects of eye movements on the content and characteristics of unpleasant autobiographical memories: an extended replication study

ABSTRACT Experimental studies show that vividness and emotionality of aversive memories decrease after recall with eye movements. We aimed at replicating this finding. Relatedly, consistent with Conway’s view that memory retrieval is constructive, we examined changes in the content of the memories. If eye movements render a memory less aversive, it may be avoided less, stimulating recall and increasing the opportunity to infer (contextual) details. Two experiments (N = 97 and N = 250) examined whether eye movements affect the number of central and peripheral memory details and characteristics. Female undergraduate students were randomly allocated to either eye movements with recall (EM) or recall only (RO). Before and after the experimental task, participants rated the vividness and emotionality, provided a detailed description and evaluated other memory characteristics. We replicated earlier findings that vividness (both experiments) and emotionality (experiment 2) were reduced more after EM compared to RO. However, conditions did not statistically significantly differ with respect to content details and other memory characteristics. Overall, findings support the idea that eye movements decrease the experience of the memory as vivid and emotional. Results are inconclusive regarding the idea that eye movements alter the number of recalled central and peripheral memory details.

Mitigating Debugger-based Attacks to Java Applications with Self-Debugging

Java bytecode is a quite high-level language and, as such, it is fairly easy to analyze and decompile with malicious intents, e.g., to tamper with code and skip license checks. Code obfuscation was a first attempt to mitigate malicious reverse engineering based on static analysis. However, obfuscated code can still be dynamically analyzed with standard debuggers to perform step-wise execution and to inspect (or change) memory content at important execution points, e.g., to alter the verdict of license validity checks. Although some approaches have been proposed to mitigate debugger-based attacks, they are only applicable to binary compiled code and none address the challenge of protecting Java bytecode. In this paper, we propose a novel approach to protect Java bytecode from malicious debugging. Our approach is based on automated program transformation to manipulate Java bytecode and split it into two binary processes that debug each other (i.e., a self-debugging solution). In fact, when the debugging interface is already engaged, an additional malicious debugger cannot attach. To be resilient against typical attacks, our approach adopts a series of technical solutions, e.g., an encoded channel is shared by the two processes to avoid leaking information, an authentication protocol is established to avoid Man-in-the-Middle attacks and the computation is spread between the two processes to prevent the attacker to replace or terminate either of them. We test our solution on 18 real-world Java applications, showing that our approach can effectively block the most common debugging tasks (either with the Java debugger or the GNU debugger) while preserving the functional correctness of the protected programs. While the final decision on when to activate this protection is still up to the developers, the observed performance overhead was acceptable for common desktop application domains.

Disentangling boredom from depression using the phenomenology and content of involuntary autobiographical memories

Recurrent involuntary autobiographical memories (IAMs) are memories retrieved unintentionally and repetitively. We examined whether the phenomenology and content of recurrent IAMs could differentiate boredom and depression, both of which are characterized by affective dysregulation and spontaneous thought. Participants (n = 2484) described their most frequent IAM and rated its phenomenological properties (e.g., valence). Structural topic modeling, a method of unsupervised machine learning, identified coherent content within the described memories. Boredom proneness was positively correlated with depressive symptoms, and both boredom proneness and depressive symptoms were correlated with more negative recurrent IAMs. Boredom proneness predicted less vivid recurrent IAMs, whereas depressive symptoms predicted more vivid, negative, and emotionally intense ones. Memory content also diverged: topics such as relationship conflicts were positively predicted by depressive symptoms, but negatively predicted by boredom proneness. Phenomenology and content in recurrent IAMs can effectively disambiguate boredom proneness from depressive symptoms in a large sample of undergraduate students from a racially diverse university.

Automated scoring of the autobiographical interview with natural language processing.

The autobiographical interview has been used in more than 200 studies to assess the content of autobiographical memories. In a typical experiment, participants recall memories, which are then scored manually for internal details (episodic details from the central event) and external details (largely non-episodic details). Scoring these narratives requires a significant amount of time. As a result, large studies with this procedure are often impractical, and even conducting small studies is time-consuming. To reduce scoring burden and enable larger studies, we developed an approach to automatically score responses with natural language processing. We fine-tuned an existing language model (distilBERT) to identify the amount of internal and external content in each sentence. These predictions were aggregated to obtain internal and external content estimates for each narrative. We evaluated our model by comparing manual scores with automated scores in five datasets. We found that our model performed well across datasets. In four datasets, we found a strong correlation between internal detail counts and the amount of predicted internal content. In these datasets, manual and automated external scores were also strongly correlated, and we found minimal misclassification of content. In a fifth dataset, our model performed well after additional preprocessing. To make automated scoring available to other researchers, we provide a Colab notebook that is intended to be used without additional coding.

HyLAC: Hybrid linear assignment solver in CUDA

The Linear Assignment Problem (LAP) is a fundamental combinatorial optimization problem with a wide range of applications. Over the years, significant progress has been made in developing efficient algorithms to solve the LAP, particularly in the realm of high-performance computing, leading to remarkable reductions in computation time. In recent years, hardware improvements in General Purpose Graphics Processing Units (GPGPUs) have shown promise in meeting the ever-increasing compute bandwidth requirements. This has attracted researchers to develop GPU-accelerated algorithms to solve the LAP.Recent work in the GPU domain has uncovered parallelism available in the problem structure to achieve significant performance improvements. However, each solution presented so far targets either sparse or dense instances of the problem and has some scope for improvement. The Hungarian algorithm is one of the most famous approaches to solving the LAP in polynomial time. Hungarian algorithm has classical O(N4) (Munkres') and tree based O(N3) (Lawler's) implementations. It is well established that the Munkres' implementation is faster for sparse LAP instances while the Lawler's implementation is faster for dense instances. In this work, we blend the GPU implementations of Munkres' and Lawler's to develop a Hybrid GPU-accelerated solver for LAP that switches between the two implementations based on available sparsity. Also, we improve the existing GPU implementations to reduce memory contention, minimize CPU-GPU synchronizations, and coalesced memory access. The resulting solver (HyLAC) works faster than existing CPU/GPU LAP solvers for sparse as well as dense problem instances. HyLAC achieves a speedup of up to 6.14× over existing state-of-the-art GPU implementation when run on the same hardware. We also develop an implementation to solve a list of small LAPs (tiled LAP), which is particularly useful in the optimization domain. This tiled LAP solver performs 22.59× faster than the existing implementation.