Spiking representation learning for associative memories.

Networks of interconnected neurons communicating through spiking signals offer the bedrock of neural computations. Our brain's spiking neural networks have the computational capacity to achieve complex pattern recognition and cognitive functions effortlessly. However, solving real-world problems with artificial spiking neural networks (SNNs) has proved to be difficult for a variety of reasons. Crucially, scaling SNNs to large networks and processing large-scale real-world datasets have been challenging, especially when compared to their non-spiking deep learning counterparts. The critical operation that is needed of SNNs is the ability to learn distributed representations from data and use these representations for perceptual, cognitive and memory operations. In this work, we introduce a novel SNN that performs unsupervised representation learning and associative memory operations leveraging Hebbian synaptic and activity-dependent structural plasticity coupled with neuron-units modelled as Poisson spike generators with sparse firing (~1 Hz mean and ~100 Hz maximum firing rate). Crucially, the architecture of our model derives from the neocortical columnar organization and combines feedforward projections for learning hidden representations and recurrent projections for forming associative memories. We evaluated the model on properties relevant for attractor-based associative memories such as pattern completion, perceptual rivalry, distortion resistance, and prototype extraction.

Associative memory in alcohol-related contexts: An fMRI study with young binge drinkers.

BACKGROUND: Alcohol-related cues are known to influence craving levels, a hallmark of alcohol misuse. Binge drinking (BD), a pattern of heavy alcohol use, has been associated with cognitive and neurofunctional alterations, including alcohol attentional bias, memory impairments, as well as disrupted activity in prefrontal- and reward-related regions. However, literature is yet to explore how memories associated with alcohol-related cues are processed by BDs, and how the recall of this information may influence their reward processing. AIMS: The present functional magnetic resonance imaging (fMRI) study aimed to investigate the neurofunctional signatures of BD during an associative memory task. METHOD: In all, 36 university students, 20 BDs and 16 alcohol abstainers, were asked to memorize neutral objects paired with either alcohol or non-alcohol-related contexts. Subsequently, neutral stimuli were presented, and participants were asked to classify them as being previously paired with alcohol- or non-alcohol-related contexts. RESULTS: While behavioral performance was similar in both groups, during the recall of alcohol-related cues, BDs showed increased brain activation in two clusters including the thalamus, globus pallidus and dorsal striatum, and cerebellum and occipital fusiform gyrus, respectively. CONCLUSION: These findings suggest that BDs display augmented brain activity in areas responsible for mental imagery and reward processing when trying to recall alcohol-related cues, which might ultimately contribute to alcohol craving, even without being directly exposed to an alcohol-related context. These results highlight the importance of considering how alcohol-related contexts may influence alcohol-seeking behavior and, consequently, the maintenance or increase in alcohol use.

Involvement of a lateral entorhinal cortex engram in episodic-like memory recall.

Episodic memory relies on the entorhinal cortex (EC), a crucial hub connecting the hippocampus and sensory processing regions. This study investigates the role of the lateral EC (LEC) in episodic-like memory in mice. Here, we employ the object-place-context-recognition task (OPCRT), a behavioral test used to study episodic-like memory in rodents. Electrophysiology in brain slices reveals that OPCRT specifically induces a shift in the threshold for the induction of synaptic plasticity in LEC superficial layer II. Additionally, a dual viral system is used to express chemogenetic receptors coupled to the c-Fos promoter in neurons recruited during the learning. We demonstrate that the inhibition of LEC neurons impairs the performance of the mice in the memory task, while their stimulation significantly facilitates memory recall. Our findings provide evidence for an episodic-like memory engram in the LEC and emphasize its role in memory processing within the broader network of episodic memory.

EXPRESS: Better face-name recall is associated with better face recognition ability.

Face recognition is a highly developed and specialized human ability, distinct from other cognitive abilities. Previous studies examining individual differences in face recognition have focused on face perception and specialized perceptual mechanisms such as holistic face processing. However, the contribution of specific face memory processes to face recognition ability remains unclear. In 99 neurotypical individuals, we administered validated face perception assessments, three face memory tasks (Old/New task, Face-Scene task, Face-Name/Occupation task), and the Cambridge Face Memory Test (CFMT) to assess face recognition ability. We found that after accounting for face perception ability (which significantly predicted face recognition ability), Face-Name recall and recollection of faces in the Face-Scene task predicted unique variance in face recognition ability, with Face-Name recall being the strongest predictor. This highlights that associative memory mechanisms contribute to face recognition abilities and suggest that the ability to learn and recall proper names is particularly important to face recognition.

Connecting working and long-term memory: Bayesian-hierarchical multinomial model-based analyses reveal storage next to retrieval differences.

Individual differences in working memory capacity (WMC) are correlated with long-term memory (LTM) differences. Whether this is because high-WMC individuals encode more effectively, resulting in better LTM storage, or because they better retrieve information from LTM is debated. In two experiments, we used Bayesian-hierarchical multinomial modeling to correlate participant-level storage and retrieval processes from LTM recall to WMC abilities estimated from operation and symmetry complex span tasks. In Experiment 1, we presented participants with 20 consecutive words, including semantically associated pairs (e.g., knife and fork), to assess LTM processes. Participants received standard (n = 242) or associative-storage instructions (n = 222) and then completed a free recall task. In Experiment 2, we instructed participants (N = 239) to memorize 40 cue-target words as pairs before completing free and cued recall tasks. Correlations with WMC emerged with storage and retrieval processes and only when an associative storage strategy was instructed (Experiment 1). When associative processing was inherent to the task (Experiment 2), only the associative storage, not the retrieval advantage, replicated. The strategy reports suggest that high-WMC individuals use associative encoding strategies more effectively, resulting in better storage in LTM.

Trajectory of associative memory impairment during electroconvulsive therapy in depression.

Memory impairment is a serious cognitive side effect of electroconvulsive therapy (ECT) in the treatment of major depressive episodes (MDEs) and has garnered widespread attention in clinical practice, but its underlying evolution pattern during the course of ECT remains rarely understood in detail. Associative memory (AM) is a core indicator that reflects memory impairment in ECT. This study aimed to identify the dynamic trajectory of AM impairment and explore associated predictive factors. 405 intensive longitudinal AM data from 81 patients with MDE were collected at the baseline, after the first, third, fifth, and eighth ECT using five sets of face-cued word memory paradigms. Changes in AM score over time were analyzed using a linear mixed effects model. Trajectory subgroups and predictive factors were investigated using growth mixture model and logistic regression. AM score during ECT were significantly lower than at baseline, with the lowest scores observed after the eighth ECT session. Two trajectories of rapid (N = 56, 69.14%) and slow (N = 25, 30.86%) AM impairment were differentiated. Older female with lower education level were significant predictors contributing to more rapid memory impairment for ECT. The evolving pattern of associative memory impairment during ECT appears to occur early and worsen with subsequent treatment. This study may provide the important evidence understanding of the number effect of ECT sessions on memory impairment and suggest individual factors for predicting ECT memory outcome.

Short-Term Coupling Associations Between State Loneliness and Cognitive Performance in Daily Life Among Older Adults.

OBJECTIVES: Despite extensive efforts to study individual differences in loneliness and neurocognitive health, little is known about how within-person changes in state loneliness relate to cognitive performance. This study addressed this gap by examining the association between within-person variation in state loneliness and cognitive performance assessed objectively in daily life. METHODS: Participants were 313 community-dwelling older adults (70-90 years) who reported momentary feelings of loneliness and completed smartphone-based cognitive tests 5 times daily for 14 consecutive days. Mobile cognitive tests assess visual associative memory, processing speed, and spatial memory. RESULTS: At the day level, average state loneliness levels were negatively related to cognitive performance on the same day and subsequent day. Consistent with the day-level analysis, momentary assessments of increased loneliness were consistently linked to worse cognitive performance on concurrent assessments. However, moments characterized by lower cognitive performance predicted higher levels of loneliness 3-4 hr later (next occasion), but not vice versa. DISCUSSION: The findings suggest a prospective association between loneliness and cognitive performance, with higher daily loneliness negatively associated with cognitive performance on the same day and predicting worse performance the following day. Notably, within a single day, lower cognitive performance at a given moment predicted elevated loneliness later in the day. This highlights a complex, reciprocal relationship-loneliness predicting and being predicted by cognitive performance depending on timescale.

Examining the role of stimulus complexity in item and associative memory.

Episodic memory comprises memory for individual information units (item memory) and for the connections among them (associative memory). In two experiments using an object pair learning task, we examined the effect of visual stimulus complexity on memory encoding and retrieval mechanisms and on item and associative memory performance. Subjects encoded pairs of black monochrome object images (low complexity, LC condition) or color photographs of objects (high complexity, HC condition) via interactive imagery, and subsequently item and associative recognition were tested. In Experiment 1, event-related potentials (ERPs) revealed an enhanced frontal N2 during encoding and an enhanced late posterior negativity (LPN) during item recognition in the HC condition, suggesting that memory traces containing visually more complex objects elicited a stronger effort in reconstructing the past episode. Item memory was consistently superior in the HC compared to the LC condition. Associative memory was either statistically unaffected by complexity (Experiment 1) or improved (Experiment 2) in the HC condition, speaking against a tradeoff between resources allocated to item versus associative memory, and hence contradicting results of some prior studies. In Experiment 2, in both young and older adults, both item and associative memory benefitted from stimulus complexity, such that the magnitude of the age-related associative deficit was not influenced by stimulus complexity. Together, these results suggest that if familiar objects are presented in a form that exhibits a higher visual complexity, which may support semantic processing, complexity can benefit both item and associative memory. Stimulus properties that enhance item memory can scaffold associative memory in this situation.

Improving associative memory in younger and older adults with unitization: evidence from meta-analysis and behavioral studies.

Introduction: The finding that familiarity can support associative memory by unitizing the to -be-learned items into a novel representation has been widely accepted, but its effects on overall performance of associative memory and recollection are still controversial. Methods: The current study aims to elucidate these discrepancies by identifying potential moderating factors through a combined approach of meta-analysis and behavioral experiment. Results: Results consistently showed that changes in the level of unitization and age groups were two important moderators. Specifically, unitization enhanced younger and older adults' associative memory and its supporting processes (i.e., familiarity and recollection) when the level of unitization between studied and rearranged pairs was changed. However, when this level remained constant, unitization exhibited no impact on associative memory and familiarity in younger adults, but showed an enhanced effect in older adults. Furthermore, results revealed a marked group difference between younger and older adults in associative memory when the unitization level of noncompound words remained unaltered. Upon breaking this condition, the group difference was reduced by enhancing familiarity or recollection. Discussion: These findings not only clarify some of the inconsistencies in the literature concerning the impact of unitization on associative memory, but also suggest that unitization is a beneficial strategy for reducing group difference in associative memory, with its effectiveness varying according to the level of unitization changes.

Are autistic traits associated with a social-emotional memory bias?

Autistic traits are associated with differential processing of emotional and social cues. By contrast little is known about the relationship of autistic traits to socio-emotional memory, though research suggests an integral relationship between episodic memory processes and psychosocial well-being. Using an experimental paradigm, we tested if autistic traits moderate the effects of negative emotion and social cues on episodic memory (i.e. memory for past events). Young adults (N = 706) with varied levels of self-reported autistic traits (24% in clinical range) encoded images stratified by emotion (negative, neutral) and social cues (social, non-social) alongside a neutral object. After 24 h, item memory for images and associative memory for objects was tested. For item memory, after controlling for anxiety, a small effect emerged whereby a memory-enhancing effect of social cues was reduced as autistic traits increased. For associative memory, memory for pairings between neutral, but not negative, images reduced as autistic traits increased. Results suggest autistic traits are associated with reduced ability to bind neutral items together in memory, potentially impeding nuanced appraisals of past experience. This bias toward more negative, less nuanced memories of past experience may represent a cognitive vulnerability to social and mental health challenges commonly associated with autistic traits and a potential intervention target.

LAM Test: A New Cognitive Marker for Early Detection in Preclinical Alzheimer's Disease.

Background: With the arrival of disease-modifying treatments, it is mandatory to find new cognitive markers that are sensitive to Alzheimer's disease (AD) pathology in preclinical stages. Objective: To determine the utility of a newly developed Learning and Associative Memory face test: LAM test. This study examined the relationship between AD cerebrospinal fluid (CSF) biomarkers and performance on LAM test, and assessed its potential clinical applicability to detect subtle changes in cognitively healthy subjects at risk for AD. Methods: We studied eighty cognitively healthy volunteers from the Valdecilla cohort. 61% were women and the mean age was 67.34 years (±6.416). All participants underwent a lumbar puncture for determination of CSF biomarkers and an extensive neuropsychological assessment, including performance on learning and associative memory indices of the LAM-test after 30 min and after 1 week, and two classic word lists to assess verbal episodic memory: the Rey Auditory Verbal Learning Test (RAVLT) and the Free and Cued Selective Reminding Test (FCSRT). We analyzed cognitive performance according to amyloid status (A+ versus A-) and to ATN model (A-T-N-; A+T-N-; A+T+N-/A+T+N+). Results: Performance on the LAM-test was significantly correlated with CSF Aß ratio. A+ participants performed worse on both learning (mean difference = 2.19, p = 0.002) and memory LAM measures than A- (mean difference = 2.19, p = 0.004). A decline in performance was observed along the Alzheimer's continuum, with significant differences between ATN groups. Conclusions: Our findings suggest that LAM test could be a useful tool for the early detection of subjects within the AD continuum, outperforming classical memory tests.

Does theta synchronicity of sensory information enhance associative memory? Replicating the theta-induced memory effect.

The binding of information from different sensory or neural sources is critical for associative memory. Previous research in animals suggested that the timing of theta oscillations in the hippocampus is critical for long-term potentiation, which underlies associative and episodic memory. Studies with human participants showed correlations between theta oscillations in medial temporal lobe and episodic memory. Clouter et al. directly investigated this link by modulating the intensity of the luminance and the sound of the video clips so that they 'flickered' at certain frequencies and with varying synchronicity between the visual and auditory streams. Across several experiments, better memory was found for stimuli that flickered synchronously at theta frequency compared with no-flicker, asynchronous theta, or synchronous alpha and delta frequencies. This effect - which they called the theta-induced memory effect - is consistent with the importance of theta synchronicity for long-term potentiation. In addition, electroencephalography data showed entrainment of cortical regions to the visual and auditory flicker, and that synchronicity was achieved in neuronal oscillations (with a fixed delay between visual and auditory streams). The theoretical importance, large effect size, and potential application to enhance real-world memory mean that a replication of theta-induced memory effect would be highly valuable. The present study aimed to replicate the key differences among synchronous theta, asynchronous theta, synchronous delta, and no-flicker conditions, but within a single experiment. The results do not show evidence of improved memory for theta synchronicity in any of the comparisons. We suggest a reinterpretation of theta-induced memory effect to accommodate this non-replication.

In Search of Dispersed Memories: Generative Diffusion Models Are Associative Memory Networks.

Uncovering the mechanisms behind long-term memory is one of the most fascinating open problems in neuroscience and artificial intelligence. Artificial associative memory networks have been used to formalize important aspects of biological memory. Generative diffusion models are a type of generative machine learning techniques that have shown great performance in many tasks. Similar to associative memory systems, these networks define a dynamical system that converges to a set of target states. In this work, we show that generative diffusion models can be interpreted as energy-based models and that, when trained on discrete patterns, their energy function is (asymptotically) identical to that of modern Hopfield networks. This equivalence allows us to interpret the supervised training of diffusion models as a synaptic learning process that encodes the associative dynamics of a modern Hopfield network in the weight structure of a deep neural network. Leveraging this connection, we formulate a generalized framework for understanding the formation of long-term memory, where creative generation and memory recall can be seen as parts of a unified continuum.

SSTE: Syllable-Specific Temporal Encoding to FORCE-learn audio sequences with an associative memory approach.

The circuitry and pathways in the brains of humans and other species have long inspired researchers and system designers to develop accurate and efficient systems capable of solving real-world problems and responding in real-time. We propose the Syllable-Specific Temporal Encoding (SSTE) to learn vocal sequences in a reservoir of Izhikevich neurons, by forming associations between exclusive input activities and their corresponding syllables in the sequence. Our model converts the audio signals to cochleograms using the CAR-FAC model to simulate a brain-like auditory learning and memorization process. The reservoir is trained using a hardware-friendly approach to FORCE learning. Reservoir computing could yield associative memory dynamics with far less computational complexity compared to RNNs. The SSTE-based learning enables competent accuracy and stable recall of spatiotemporal sequences with fewer reservoir inputs compared with existing encodings in the literature for similar purpose, offering resource savings. The encoding points to syllable onsets and allows recalling from a desired point in the sequence, making it particularly suitable for recalling subsets of long vocal sequences. The SSTE demonstrates the capability of learning new signals without forgetting previously memorized sequences and displays robustness against occasional noise, a characteristic of real-world scenarios. The components of this model are configured to improve resource consumption and computational intensity, addressing some of the cost-efficiency issues that might arise in future implementations aiming for compactness and real-time, low-power operation. Overall, this model proposes a brain-inspired pattern generation network for vocal sequences that can be extended with other bio-inspired computations to explore their potentials for brain-like auditory perception. Future designs could inspire from this model to implement embedded devices that learn vocal sequences and recall them as needed in real-time. Such systems could acquire language and speech, operate as artificial assistants, and transcribe text to speech, in the presence of natural noise and corruption on audio data.

In vivo Effects of Salicornia herbacea and Calystegia soldanella Extracts for Memory Improvement.

The global elderly population, aged 65 and over, reached approximately 10% in 2020, and this proportion is expected to continue rising. Therefore, the prevalence of neurodegenerative diseases such as Parkinson's disease (PD), which are characterized by declining memory capabilities, is anticipated to increase. In a previous study, we successfully restored the diminished memory capabilities in a fruit fly model of PD by administering an omija extract. To identify functional ingredients that can enhance memory akin to the effects of the omija extract, we conducted screenings by administering halophyte extracts to the PD model. Halophytes are plants that thrive in high-salt environments, and given Korea's geographic proximity to the sea on three sides, it serves as an optimal hub for the utilization of these plants. Upon examining the effects of the oral administration of 12 halophyte extracts, Salicornia herbacea and Calystegia soldanella emerged as potential candidates for ameliorating memory loss in PD model flies. Moreover, our findings suggested that C. soldanella, but not S. herbacea, can mitigate oxidative stress in DJ-1ß mutants.

A novel associative memory model based on semi-tensor product (STP).

A good intelligent learning model is the key to complete recognition of scene information and accurate recognition of specific targets in intelligent unmanned system. This study proposes a new associative memory model based on the semi-tensor product (STP) of matrices, to address the problems of information storage capacity and association. First, some preliminaries are introduced to facilitate modeling, and the problem of information storage capacity in the application of discrete Hopfield neural network (DHNN) to associative memory is pointed out. Second, learning modes are equivalently converted into their algebraic forms by using STP. A memory matrix is constructed to accurately remember these learning modes. Furthermore, an algorithm for updating the memory matrix is developed to improve the association ability of the model. And another algorithm is provided to show how our model learns and associates. Finally, some examples are given to demonstrate the effectiveness and advantages of our results. Compared with mainstream DHNNs, our model can remember learning modes more accurately with fewer nodes.

Theta and alpha oscillations in human hippocampus and medial parietal cortex support the formation of location-based representations.

Our ability to navigate in a new environment depends on learning new locations. Mental representations of locations are quickly accessible during navigation and allow us to know where we are regardless of our current viewpoint. Recent functional magnetic resonance imaging (fMRI) research using pattern classification has shown that these location-based representations emerge in the retrosplenial cortex and parahippocampal gyrus, regions theorized to be critically involved in spatial navigation. However, little is currently known about the oscillatory dynamics that support the formation of location-based representations. We used magnetoencephalogram (MEG) recordings to investigate region-specific oscillatory activity in a task where participants could form location-based representations. Participants viewed videos showing that two perceptually distinct scenes (180° apart) belonged to the same location. This "overlap" video allowed participants to bind the two distinct scenes together into a more coherent location-based representation. Participants also viewed control "non-overlap" videos where two distinct scenes from two different locations were shown, where no location-based representation could be formed. In a post-video behavioral task, participants successfully matched the two viewpoints shown in the overlap videos, but not the non-overlap videos, indicating they successfully learned the locations in the overlap condition. Comparing oscillatory activity between the overlap and non-overlap videos, we found greater theta and alpha/beta power during the overlap relative to non-overlap videos, specifically at time-points when we expected scene integration to occur. These oscillations localized to regions in the medial parietal cortex (precuneus and retrosplenial cortex) and the medial temporal lobe, including the hippocampus. Therefore, we find that theta and alpha/beta oscillations in the hippocampus and medial parietal cortex are likely involved in the formation of location-based representations.

Performance on the Latin American version of the Face-Name Associative Memory Exam (LAS-FNAME) distinguishes individuals with Mild Cognitive Impairment from age-matched controls in a sample from Argentina.

INTRODUCTION: The Latin American Spanish version of the Face-Name Associative Memory Exam (LAS-FNAME) has shown promise in identifying cognitive changes in those at risk for Alzheimer's disease (AD). However, its applicability for Mild Cognitive Impairment (MCI) detection in the Latin American population remains unexplored. This study aims to analyze the psychometric properties in terms of validity and reliability and diagnostic performance of the LAS-FNAME for the detection of memory disorders in patients with amnestic MCI (aMCI). MATERIALS AND METHODS: The study included 31 participants with aMCI, diagnosed by a neurologist according to Petersen's criteria, and 19 healthy controls. Inclusion criteria for the aMCI group were to be 60 years of age or older, report cognitive complaints, have a memory test score (Craft Story 21) below a -1.5 z-score and have preserved functioning in activities of daily living. Participants completed LAS-FNAME and a comprehensive neuropsychological assessment. RESULTS: LAS-FNAME showed the ability to discriminate against healthy controls from patients with aMCI (AUC= 75) in comparison with a gold-standard memory test (AUC = 69.1). LAS-FNAME also showed evidence of concurrent and divergent validity with a standard memory test (RAVLT) (r = 0.58, p < .001) and with an attention task (Digit Span) (r = -0.37, p = .06). Finally, the reliability index was very high (α = 0.88). DISCUSSION: LAS-FNAME effectively distinguished aMCI patients from healthy controls, suggesting its potential for detecting early cognitive changes in Alzheimer's prodromal stages among Spanish speakers.

Aging effects on the encoding/retrieval flip in associative memory: fMRI evidence from incidental contingency learning.

Introduction: Associative memory is arguably the most basic memory function and therein constitutes the foundation of all episodic and semantic memory processes. At the same time, the decline of associative memory represents a core feature of age-related cognitive decline in both, healthy and pathological (i.e., dementia-related) aging. The neural mechanisms underlying age-related impairments in associative memory are still not fully understood, especially regarding incidental (i.e., non-intentional) learning. Methods: We investigated the impact of age on the incidental learning and memory retrieval of face-name combinations in a total sample of 46 young (N = 23; mean age = 23.39 years) and elderly (N = 22, mean age = 69.05 years) participants. More specifically, particular interest was placed in age-related changes in encoding/retrieval (E/R) flips, which denote a neural antagonism of opposed activation patterns in the same brain region during memory encoding and retrieval, which were assessed using fMRI. Results: According to our hypothesis, the results showed a significant age-related decline in the retrieval performance in the old group. Additionally, at the neural level, we discovered an abolished E/R flip in the right anterior insula and a joint but reduced E/R flip activation magnitude in the posterior middle cingulate cortex in older subjects. Discussion: In conclusion, the present findings suggest that the impaired neural modulation of the E/R flip in the right aIC might be a sensitive marker in the early detection of neural aging.

Taking time to compose thoughts with prefrontal schemata.

Under what conditions can prefrontal cortex direct the composition of brain states, to generate coherent streams of thoughts? Using a simplified Potts model of cortical dynamics, crudely differentiated into two halves, we show that once activity levels are regulated, so as to disambiguate a single temporal sequence, whether the contents of the sequence are mainly determined by the frontal or by the posterior half, or by neither, depends on statistical parameters that describe its microcircuits. The frontal cortex tends to lead if it has more local attractors, longer lasting and stronger ones, in order of increasing importance. Its guidance is particularly effective to the extent that posterior cortices do not tend to transition from state to state on their own. The result may be related to prefrontal cortex enforcing its temporally-oriented schemata driving coherent sequences of brain states, unlike the atemporal "context" contributed by the hippocampus. Modelling a mild prefrontal (vs. posterior) lesion offers an account of mind-wandering and event construction deficits observed in prefrontal patients.