Neurophysiological correlates of short-term recognition of sounds: Insights from magnetoencephalography.

Metacognition enables adaptive behavior through the self-evaluation of our cognitions. An unresolved question is whether metacognition relies on domain-general or domain-specific mechanisms. The domain-general account proposes that shared prefrontal resources support metacognition across all cognitive functions. This predicts that metacognitive abilities should correlate across cognitive tasks and show uniform age-related decline, as aging would affect this shared system. However, behavioral results show inconsistent cross-domain correlations and age-related decline, often confounded by methodological differences between tasks. The neural oscillations supporting metacognition also remain unclear, though electroencephalography (EEG) studies suggest theta oscillations as a potential mechanism in specific domains. No study has compared both behavioral and oscillatory patterns across domains using matched tasks. We addressed this by recording EEG from younger and older-adults during matched perceptual and visual short-term memory tasks. Despite equivalent task performance, aging selectively impaired metacognition in perception and not memory, revealing behavioral decoupling between domains. This dissociation was mirrored in oscillatory dynamics. Younger adults showed stronger occipital theta-synchronization supporting perceptual metacognition, while older adults engaged compensatory frontal beta-desynchronization. During memory, older adults’ metacognition was supported by occipital alpha-desynchronization. These findings reveal the domain-specific oscillatory mechanisms supporting metacognition, each tuned to computational demands of the cognitive domain and age-group.

Video gaming has been shown to improve information processing. Enhanced attention control functions appear to illustrate cognitive substrates thereof. Additionally, attention control functions represent constraints of cognitive capacity—an established predictor of multitasking performance. Thus, cognitive capacity may explain an association between video gaming and enhanced multitasking performance via attention control functions. To investigate this, we assessed the short-term memory and multi-attribute task battery (MATB) task performance of 60 individuals with different levels of video gaming experience; and conducted structural equation modeling to test if video gaming experience predicted multitasking performance; and if this effect was mediated by cognitive capacity. We used two functions of the theory of visual attention computational modeling framework as indicators of cognitive capacity; four MATB performance measures as indictors of multitasking performance; and self-reports on video game play time and expertise to model video gaming experience. Video gaming experience predicted multitasking performance but we found no evidence for cognitive capacity mediating this relationship. Thus, the role of cognitive capacity in the association between video gaming experience and multitasking is inconclusive.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-25260-5.

Because the study of working memory and long-term memory diverged decades ago, views about the diagnostic nature of certain measures within each literature might not be valid. For example, in the study of working memory, it is viewed as critical to show a capacity limit in storage as a way of demonstrating that one is measuring the limited-capacity working memory store and not the unlimited capacity long-term memory store. Although this is a strong logical structure, these hallmarks of working memory might already fall out of existing models of human long-term memory. Here, we show that several of the set size effects often used to validate the assumption that one is studying working memory are also observed as a natural result of the dynamics of contextual models of long-term memory storage and retrieval. Integrating contextual dynamics into a model of visual working memory provides new insight into the nature of interference in short-term visual memory tasks and allows the model to capture the temporal structure of visual experience as it unfolds in time. We discuss how the situation motivates a re-examination of unified models of human memory. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

BackgroundCognitive tasks are foundational tools in psychology and neuroscience for studying attention, perception, and memory. However, they typically employ simple or artificial stimuli and require numerous repetitive trials, which can adversely affect participant engagement and ecological validity.ObjectiveThis study investigated whether gamified versions of 3 established cognitive tasks, namely, the Visual Search task (attention), the Whack-the-Mole task (response inhibition), and the Corsi block-tapping test (visual short-term memory), replicate the typical patterns of results reported for their traditional counterparts. It also examined whether the method of administration—in immersive virtual reality (VR) versus desktop computer, and in the laboratory versus at home—influences performance.MethodsSeventy-five participants (male=24, female=51; age range 18‐35 years; mean 23.15, SD 4.38 years) were randomly assigned to 1 of 3 administration conditions (n=25 each). In the VR-Lab condition, participants completed the tasks in immersive VR within the laboratory; in the Desktop-Lab condition, they completed the tasks on a 2D desktop screen in the laboratory; and in the Desktop-Remote condition, participants completed the tasks on their personal computers at home. All participants completed the same gamified tasks while seated, entering responses with either a mouse or a VR controller, depending on the condition.ResultsThe results obtained from these gamified tasks across all 3 administration conditions replicated the typical performance patterns observed with their traditional counterparts, despite using more ecologically valid stimuli and fewer trials. However, administration modality did influence certain performance measures, particularly reaction times (RTs) and task efficiency. Specifically, in the Visual Search task, RTs were significantly faster in the VR-Lab condition (mean 1.24 seconds) than in the Desktop-Lab (mean 1.49 seconds; P<.001) and Desktop-Remote (mean 1.44 seconds; P=.008) conditions. In the Whack-the-Mole task, no significant group differences emerged in d’ scores (VR-Lab: mean 3.79, Desktop-Remote: mean 3.75, Desktop-Lab: mean 3.62; P=.49), but RTs were slower in the Desktop-Remote condition (mean 0.64 seconds) than in the VR-Lab (mean 0.41 seconds; P<.001) and Desktop-Lab (mean 0.48 seconds; P<.001) conditions. For the Corsi block-tapping test, no significant group differences in span scores were found (VR-Lab: mean 5.48, Desktop-Lab: mean 5.68, and Desktop-Remote: mean 5.24; P=.24). Finally, a significant positive correlation was observed between RTs for Hits in the Whack-the-Mole task and feature search trials in the Visual Search task (r=0.24; P=.04).ConclusionsGamified cognitive tasks administered in VR replicated established behavioral patterns observed with their traditional versions while improving ecological validity and reducing task duration. Administration modality had limited effects on overall outcomes, although RTs were slower in remote settings. These findings support the feasibility of using gamified VR tasks for scalable and ecologically valid cognitive assessment. Overall, the study underscores the potential of VR to increase participant engagement and enrich cognitive research through more immersive and motivating testing environments.

A large body of evidence consistently indicates a relationship between the apolipoprotein E (APOE) ε4 allele and memory decline in later life; however, the influence of the APOE ε4 allele on memory performance during the early stages of life remains poorly understood. Therefore, we explored whether the APOE ε4 allele is associated with cognitive advantages or disadvantages early in life from the perspective of memory function, specifically working memory and short-term memory. Based on a study of 516 university students aged 17–26 who completed short-term memory tasks and 156 students in the same age range who completed working memory tasks, our findings reveal that individuals carrying the APOE ε4 allele exhibited poorer performance in working memory, with no significant impact on short-term memory. Subsequently, employing a connectome-based predictive modeling approach in resting-state functional magnetic resonance imaging data, we defined a functional network model-dominated by default-sensorimotor network interactions that was capable of forecasting fluctuations in working memory among the held-out individuals (i.e., cross-brain prediction). Furthermore, the functional connectivity serves as a mediator in the association between APOE genotypes and working memory performance. Collectively, these findings provide novel insights into the early-life relationship between the APOE ε4 allele and memory performance, as well as its neural underpinnings.

Auditory processing (AP) disorder is underdiagnosed in Australian children due to reduced access to assessments. Mobile health technology (mHealth) tools such as the AP assessment application Feather Squadron (FS) may be a way to overcome barriers of clinical assessments. This study aimed to consider the validity of FS as a remote assessment tool when compared to current Australian clinical assessments of speech recognition in noise, dichotic listening, temporal processing, and auditory short-term memory. This study employed a within-subject, comparative design. Thirty-five normal-hearing children aged between 6.8 and 13.1 years (M = 9.1, SD = 1.8) were tested on the following AP skills: dichotic listening, temporal sequencing, speech recognition in noise, and auditory short-term memory. Participants were tested using traditional clinical tests administered by a qualified audiologist and then completed an mHealth delivered counterpart via the FS application. Results of both clinical and FS tests were converted into age-related z scores or scaled scores for comparison. Significant, positive interclass correlations were found on assessments of dichotic listening in the worse ear and temporal sequencing. However, poor agreement was noted between these assessments using Bland-Altman analysis, which found substantial bias and wide limits of agreement. A moderate significant Pearson correlation was noted when comparing performance on the clinical and FS auditory short-term memory task. mHealth tools like FS may be useful for identifying children at risk of AP disorder and increasing referrals for assessment. The poor limits of agreement and bias recognize that FS assessments cannot directly replace clinical tests of AP skills and that despite significant relations between tasks, clinical assessments of AP skills delivered by specialists in a controlled environment remains preferable.

Clustered protocadherins (cPcdh) are cell adhesion molecules with 58 isoforms, essential for neural circuit formation and higher cognitive functions. This study investigated the impact of reduced cPcdh-α diversity on cognitive function using mutant mice. Behavioral tests revealed that cPcdh-α1-12 mice exhibited specific memory impairments ranging from a few seconds to 2 h short-term memory, while memory from 24 h to 2 weeks long-term memory remained intact. Notably, no abnormalities in appearance or spontaneous behavior were observed in cPcdh-α1-12 mice, suggesting that the deficits were specific to short-term memory. Furthermore, a comprehensive analysis of neural activity during memory recall in 2 h short-term memory and 24 h long-term memory following showed significant reductions in the hippocampus, amygdala, and retrosplenial cortex during short-term memory tasks. No such reductions were observed during long-term memory recall. These results suggest that short-term and long-term memory are supported by partially distinct neural circuits and underscore the critical role of cPcdh-α diversity in establishing the neural pathways necessary for short-term memory retrieval.

Abstract This paper introduces an analog spiking neuron that utilizes time-domain information, i.e. a time interval of two signal transitions and a pulse width, to construct a spiking neural network (SNN) for a hardware-friendly physical reservoir computing (RC) on a complementary metal-oxide-semiconductor platform. A neuron with leaky integrate-and-fire is realized by employing two voltage-controlled oscillators with opposite sensitivities to the internal control voltage, and the neuron connection structure is restricted by the use of only 4 neighboring neurons on a 2-dimensional plane to feasibly construct a regular network topology. Such a system enables us to compose an SNN with a counter-based readout circuit, which simplifies the hardware implementation of the SNN. Moreover, another technical advantage thanks to the bottom–up integration is the capability of dynamically capturing every neuron state in the network, which can significantly contribute to finding guidelines on how to enhance the performance for various computational tasks in temporal information processing. Diverse nonlinear physical dynamics needed for RC can be realized by collective behavior through dynamic interaction between neurons, like coupled oscillators, despite the simple network structure. With behavioral system-level simulations, we demonstrate physical RC through short-term memory and exclusive OR tasks, and the spoken digit recognition task with an accuracy of 97.7% as well. Our system is considerably feasible for practical applications and can also be a useful platform for studying the mechanism of physical RC.

Physical reservoir computing has emerged as a powerful framework for exploiting the inherent nonlinear dynamics of physical systems to perform computational tasks. Recently, we presented the magnon-scattering reservoir, whose internal nodes are given by the fundamental wavelike excitations of ferromagnets called magnons. These excitations can be geometrically quantized and, in response to an external stimulus, show transient nonlinear scattering dynamics that can be harnessed to perform memory and nonlinear transformation tasks. Here, we test a magnon-scattering reservoir in a single magnetic disk in the vortex state against two key performance indicators for physical reservoir computing: the short-term memory and parity-check tasks. Using time-resolved Brillouin light scattering microscopy, we measure the evolution of the reservoir’s spectral response to an input sequence consisting of random binary inputs encoded in microwave pulses with two distinct frequencies. Two different output spaces of the reservoir are defined: one based on the time-averaged frequency spectra and another based on temporal multiplexing. Our results demonstrate that the memory and nonlinear transformation capability do not depend on the chosen readout scheme, provided that the dimension of the output space is large enough to capture all nonlinear features provided by the magnon-magnon interactions. This further shows that it is solely the nonlinear magnons in the physical system—not the readout—that determine the reservoir’s capacity. Published by the American Physical Society 2025

IntroductionOne of the commonly used indices of short-term memory (STM) is the digit span task. Prior studies have proposed pupil dilation as a measure of task engagement and as a promising biomarker of vagal activation. Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel non-invasive brain stimulation technique which might be used to improve cognition and modulate pupil size through its effects on the noradrenergic release in the locus coeruleus. No previous study has investigated the effects of off-line taVNS on a digit span task. With this single-blind, sham-controlled, crossover design trial, we aimed to assess whether taVNS was able to improve the digit span score, as well as to modulate the pupillary response to cognitive load in a sample of 18 elderly Japanese volunteers with no self-reported cognitive impairments.ResultsSubjects were randomized to receive either real or sham taVNS during a digit span task while recording the pupil size, and then switched over to the other treatment group. We found that real stimulation significantly reduced the mean number of errors performed at span length 7, 8, and 9 (–0.83, –0.90, and –0.39, respectively compared to pre-stimulation values, and –0.71, –1.08, and –0.79, respectively, compared to sham stimulation). Additionally, real taVNS stimulation slightly but significantly increased the pupil size at all span lengths during the encoding period of the task, with larger effects for span 7–10 compared to pre-stimulation, and for span 5–10 compared to sham. No effect over the pupil size was found during the recall period.DiscussionOur results suggest that taVNS might selectively improve the cognitive performance during the encoding phase of the task. Although further studies are needed to better clarify the optimal stimulation parameters, findings from this study could support the use of taVNS as a safe neuromodulation technique to improve cognitive function.

Engaging with music while studying can influence academic performance among students. Several studies have shown a negative effect of non-classical genres on short-term memory performance yet still limited to classical background music, especially in the context of Malaysian culture. Therefore, a present study investigated the impact of classical background music on short-term memory performance among undergraduate female participants (N=48) from Sultan Idris Education University (UPSI). The study employed a Randomised Controlled Trial (RCT) design where purposive sampling with inclusion and exclusion criteria was used to recruit the participants, which then randomly assigned into four groups: Solo piano, Orchestral, Operatic, and No music through single-blind method. The short-term memory task consisted of 20 trials of 5-letter nonsense syllables displayed for three seconds, with an 8-second gap between each trial and the scoring ranged from zero to 20. Classical music from the romantic period was selected, featuring five different short pieces looped in each condition. The results of one-way ANOVA and Tukey (HSD) post hoc analysis showed significant mean differences among the groups (F(3, 44) = 15.95, p &lt; .001) with the Operatic group exhibiting the lowest accuracy in short-term memory compared to the other groups (Mdiff = 5.33, p &lt; .001, Mdiff = 3.16, p = .002, Mdiff = –4.08, p &lt; .001, α = .05, SE = .57). Future researchers should address the following improvements: larger and diverse sample size to avoid bias assumptions, suitable experimental design for task variety and cultural acceptance of background music, and alternative psychology analysis methods.

Cognitive offloading refers to using physical actions to reduce cognitive demand by altering a task’s information processing requirements. It enables problem-solving beyond the brain’s capacity. This study introduces subjective trust toward tools as a key factor in cognitive offloading, reflecting the connection between users and the tools they rely on. Participants rated their trust toward three tools before using them in a short-term memory task with four difficulty levels. Task performance and cognitive offloading frequency were recorded. Results showed that cognitive offloading significantly improved performance, with stronger effects when trust toward the tool was high. When faced with tasks of medium difficulty, participants were more inclined to adopt cognitive offloading strategies with tools they trusted than those they trusted less. These findings highlight the importance of trust toward tool selection for cognitive offloading, offering insights into designing and choosing effective tools for enhancing cognitive performance.

Metacognition and facial emotional expressions both play a major role in human social interactions [1, 2] as inner narrative and primary communicational display, and both are limited by self-monitoring, control and their interaction with personal and social reference frames. The study aims to investigate how metacognitive abilities relate to facial emotional expressions, as the inner narrative of a subject might project subconsciously and primes facial emotional expressions in a non-social setting. Subjects were presented online to a set of digitalised short-term memory tasks and attended a screening of artistic and artificial stimuli, where their facial emotional expressions were recorded and analyzed by artificial intelligence. Results show self-assessment bias in association with emotional expressivity – neutrality, saturation, transparency – and the display of anger and hostility as an individually specific trait expressed at modality-dependent degrees. Our results indicate that self-assessment bias interplays in subconscious communication – the expression, control and recognition of facial emotions, especially – with empathetic skills and manipulation.

Functional neuroimaging studies in neurotypical subjects correlate sentence comprehension to a left fronto-temporo-parietal network. Recent voxel-based lesion-symptom mapping (VLSM) studies of aphasia confirm the link between sentence comprehension and a left posterior region including the angular gyrus, the supra-marginal gyrus and the postero-superior division of the temporal lobe but support left pre-frontal involvement inconsistently. However, these studies focus on thematic role assignment without considering morphosyntactic processes. Hence, available VLSM evidence could provide a partial view of the neurofunctional substrate of sentence comprehension. In the present VLSM study, both morphosyntactic and thematic processes were evaluated systematically and in the same sentence types in each participant, to provide a more detailed picture of the sentence comprehension network. Participants (33 patients with post-stroke aphasia and 90 healthy controls) completed a sentence-picture matching task in which active and passive, declarative reversible sentences were paired with morphosyntactic, thematic and lexical-semantic alternatives. Phonological short-term memory tasks were also administered. Aphasic participants were selected from an initial pool of 70 because they scored below norm on thematic foils (n = 18) or on thematic and morphological foils (n = 15), but within the norm on lexical-semantic foils. The neurofunctional correlates of morphosyntactic and thematic processes were starkly distinguishable. Pre-frontal areas including the inferior and middle frontal gyrus were involved directly in processing local morphosyntactic features and only indirectly in thematic processes. When these areas were damaged, morphosyntactic errors always co-occurred with thematic errors, probably because morphosyntactic damage disrupts the assignment of grammatical roles and ultimately that of thematic roles. Morphosyntactic errors were not influenced by word order canonicity. In contrast, selective thematic role reversals were linked to temporal and parietal damage and were significantly influenced by word order, occurring on passive more than on active sentences. An area including the angular and supra-marginal gyrus was critical for processing non-canonical word order. In sentence comprehension, pre-frontal regions are critical for processing local morphosyntactic features (at least in simple declarative sentences). Temporal and parietal regions are critical for thematic processes. Postero-superior temporal areas are involved in retrieving verb argument structure. Parietal areas are critical for assigning morphosyntactically analysed constituents to the appropriate thematic role, thus serving a crucial function in thematic re-analysis. Each area plays a prevailing but not exclusive role in these processes, interacting with other areas in the network and possibly providing both the language-specific and the domain-general resources needed at various stages of sentence comprehension.

Abstract In recent years, there has been growing interest in physical reservoir computing, which operates with low power consumption and low computational cost, utilizing various phenomena for their operations. In this study, we developed a liquid crystal-based reservoir that utilizes dielectric polarization as a new state variable for the physical reservoir operation. Nonlinear polarization change in a liquid crystal film was confirmed both by observation using a polarized optical microscope and by electrical measurements. We also evaluated the performance of the liquid crystal reservoir by basic methods such as short-term memory tasks. In the MNIST classification task, we achieved an accuracy of approximately 88%, suggesting the potential of the liquid crystal reservoir for future applications.

Measuring and interpreting errors in behavioral tasks is critical for understanding cognition. Conventional wisdom assumes that encoding/decoding errors for continuous variables in behavioral tasks should naturally have Gaussian distributions, so that deviations from normality in the empirical data indicate the presence of more complex sources of noise. This line of reasoning has been central for prior research on working memory. Here, we reassess this assumption and find that even in ideal observer models with Gaussian encoding noise, the error distribution is generally non-Gaussian, contrary to the commonly held belief. Critically, we find that the shape of the error distribution is determined by the geometrical structure of the encoding manifold via a simple rule. In the case of a high-dimensional geometry, the error distributions naturally exhibit flat tails. Using this insight, we apply our theory to visual short-term memory tasks, and find that it can account for a large array of experimental data with only two free parameters. Our results challenge the dominant view in the mechanisms and capacity constraints of working memory systems. They instead suggest that the Bayesian framework, which explains various aspects of perceptual behavior, also provides an excellent account of working memory. Overall, our results establish a direct connection between neural manifold geometry and behavior, and call attention to the geometry of the representation as a critically important, yet underappreciated factor in determining the character of errors in human behavior.

Tonal short-term memory has been positively associated with both incidentally acquired absolute pitch memory (e.g., for popular songs) and explicitly learned absolute pitch (AP) categories; however, the relationship between these constructs has not been directly tested within the same individuals. The current study investigated how tonal short-term memory relates to both incidentally and intentionally acquired AP. Participants (n = 192) completed a tonal short-term memory task, an incidental AP task, and an AP categorization task. The tonal short-term assessment involved adjusting a starting tone to match a target tone. The incidental AP task involved judging whether excerpts of popular songs were presented in the correct key. The AP categorization task involved associating six pitch chroma categories with arbitrary labels, including a generalization test that used Shepard tones to discourage pitch height cues. We found that all three pitch measures were positively correlated with one another. Critically, however, we found that tonal short-termmemoryfully mediated the relationship between incidental AP and explicit AP categorization. This finding held even when controlling for musical training and tonal language fluency. Overall, these results suggest that pitch memory is a consistent individual difference measure across different timescales and different measures (e.g., incidental measures, explicit measures). However, tonal short-term memory appears to be foundational to both incidentally acquired and explicitly learned AP categories.

Understanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as measured by the fMRI technique. However, it's essential to match the type of learning method to the problem type, and extracting the information about the most important ROI connections might be challenging. In this contribution, we used machine learning techniques to classify tasks in a working memory experiment and identify the brain areas involved in processing information. We employed classical discriminators and neural networks (convolutional and residual) to differentiate between brain responses to distinct types of visual stimuli (visuospatial and verbal) and different phases of the experiment (information encoding and retrieval). The best performance was achieved by the LGBM classifier with 1-time point input data during memory retrieval and a convolutional neural network during the encoding phase. Additionally, we developed an algorithm that took into account feature correlations to estimate the most important brain regions for the model's accuracy. Our findings suggest that from the perspective of considered models, brain signals related to the resting state have a similar degree of complexity to those related to the encoding phase, which does not improve the model's accuracy. However, during the retrieval phase, the signals were easily distinguished from the resting state, indicating their different structure. The study identified brain regions that are crucial for processing information in working memory, as well as the differences in the dynamics of encoding and retrieval processes. Furthermore, our findings indicate spatiotemporal distinctions related to these processes. The analysis confirmed the importance of the basal ganglia in processing information during the retrieval phase. The presented results reveal the benefits of applying machine learning algorithms to investigate working memory dynamics.

Measuring transient functional connectivity is an important challenge in electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of brain activity offered by high-temporal resolution is confounded by the inherent noise of the medium and the spurious nature of correlations computed over short temporal windows. We propose a methodology to overcome these problems called filter average short-term (FAST) functional connectivity. First, a long-term, stable, functional connectivity is averaged across an entire study cohort for a given pair of visual short-term memory (VSTM) tasks. The resulting average connectivity matrix, containing information on the strongest general connections for the tasks, is used as a filter to analyze the transient high-temporal resolution functional connectivity of individual subjects. In simulations, we show that this method accurately discriminates differences in noisy event-related potentials (ERPs) between two conditions where standard connectivity and other comparable methods fail. We then apply this to analyze an activity related to visual short-term memory binding deficits in two cohorts of familial and sporadic Alzheimer’s disease (AD)-related mild cognitive impairment (MCI). Reproducible significant differences were found in the binding task with no significant difference in the shape task in the P300 ERP range. This allows new sensitive measurements of transient functional connectivity, which can be implemented to obtain results of clinical significance.