Physical activity improves the visual-spatial working memory of individuals with mild cognitive impairment or Alzheimer's disease: a systematic review and network meta-analysis.

Objective: Our network meta-analysis aimed to ascertain the effect of physical activity on the visual-spatial working memory of individuals with mild cognitive impairment and Alzheimer's disease as well as to propose tailored exercise interventions for each group. Methods: Employing a frequentist approach, we performed a network meta-analysis to compare the effectiveness of different exercise interventions in improving the visual-spatial working memory of individuals with mild cognitive impairment and Alzheimer's disease. Subsequently, we explored the moderating variables influencing the effectiveness of the exercise interventions through a subgroup analysis. Results: We included 34 articles involving 3,074 participants in the meta-analysis, comprised of 1,537 participants from studies on mild cognitive impairment and 1,537 participants from studies on Alzheimer's disease. The articles included exhibited an average quality score of 6.6 (score studies) and 6.75 (reaction time [RT] studies), all passing the inconsistency test (p > 0.05). In the mild cognitive impairment literature, mind-body exercise emerged as the most effective exercise intervention (SMD = 0.61, 95% CI: 0.07-1.14). In Alzheimer's disease research, aerobic exercise was identified as the optimal exercise intervention (SMD = 0.39, 95% CI: 0.06-0.71). Conclusion: The results of the subgroup analysis suggest that the most effective approach to enhancing the visual-spatial working memory of individuals with mild cognitive impairment entails exercising at a frequency of three or more times per week for over 60 min each time and at a moderate intensity for more than 3 months. Suitable exercise options include mind-body exercise, multicomponent exercise, resistance exercise, and aerobic exercise. For individuals with Alzheimer's disease, we recommend moderately intense exercise twice per week for over 90 min per session and for a duration of 3 months or longer, with exercise options encompassing aerobic exercise and resistance exercise.

Correlations between developmental trajectories of brain functional connectivity, neurocognitive functions, and clinical symptoms in patients with attention-deficit hyperactivity disorder.

Several studies on attention-deficit hyperactivity disorder (ADHD) have suggested a developmental sequence of brain changes: subcortico-subcortical connectivity in children, evolving to subcortico-cortical in adolescence, and culminating in cortico-cortical connectivity in young adulthood. This study hypothesized that children with ADHD would exhibit decreased functional connectivity (FC) between the cortex and striatum compared to adults with ADHD, who may show increased FC in these regions. Seventy-six patients with ADHD (26 children, 26 adolescents, and 24 adults) and 74 healthy controls (25 children, 24 adolescents, and 25 adults) participated in the study. Resting state magnetic resonance images were acquired using a 3.0 T Philips Achieva scanner. The results indicated a gradual decrease in the number of subcategories representing intelligence quotient deficits in the ADHD group with age. In adulthood, the ADHD group exhibited lower working memory compared to the healthy control group. The number of regions showing decreased FC from the cortex to striatum between the ADHD and control groups reduced with age, while regions with increased FC from the default mode network and attention network in the ADHD group increased with age. In adolescents and adults, working memory was positively associated with brain activity in the postcentral gyrus and negatively correlated with ADHD clinical symptoms. In conclusion, the findings suggest that intelligence deficits in certain IQ subcategories may diminish as individuals with ADHD age. Additionally, the study indicates an increasing anticorrelation between cortical and subcortical regions with age in individuals with ADHD.

Stochastic attractor models of visual working memory.

This paper investigates models of working memory in which memory traces evolve according to stochastic attractor dynamics. These models have previously been shown to account for response-biases that are manifest across multiple trials of a visual working memory task. Here we adapt this approach by making the stable fixed points correspond to the multiple items to be remembered within a single-trial, in accordance with standard dynamical perspectives of memory, and find evidence that this multi-item model can provide a better account of behavioural data from continuous-report tasks. Additionally, the multi-item model proposes a simple mechanism by which swap-errors arise: memory traces diffuse away from their initial state and are captured by the attractors of other items. Swap-error curves reveal the evolution of this process as a continuous function of time throughout the maintenance interval and can be inferred from experimental data. Consistent with previous findings, we find that empirical memory performance is not well characterised by a purely-diffusive process but rather by a stochastic process that also embodies error-correcting dynamics.

Predictability and Variation in Language Are Differentially Affected by Learning and Production.

General principles of human cognition can help to explain why languages are more likely to have certain characteristics than others: structures that are difficult to process or produce will tend to be lost over time. One aspect of cognition that is implicated in language use is working memory-the component of short-term memory used for temporary storage and manipulation of information. In this study, we consider the relationship between working memory and regularization of linguistic variation. Regularization is a well-documented process whereby languages become less variable (on some dimension) over time. This process has been argued to be driven by the behavior of individual language users, but the specific mechanism is not agreed upon. Here, we use an artificial language learning experiment to investigate whether limitations in working memory during either language learning or language production drive regularization behavior. We find that taxing working memory during production results in the loss of all types of variation, but the process by which random variation becomes more predictable is better explained by learning biases. A computational model offers a potential explanation for the production effect using a simple self-priming mechanism.

Aerobic fitness as a moderator of acute aerobic exercise effects on executive function.

This study aimed to investigate the moderating role of aerobic fitness on the effect of acute exercise on improving executive function from both behavioral and cerebral aspects. Thirty-four young individuals with motor skills were divided into high- and low-fitness groups based on their maximal oxygen uptake. Both groups completed 30 min of moderate-intensity aerobic exercise on a power bike. Executive function tests (Flanker, N-back, More-odd-shifting) were performed before and after exercise and functional near-infrared spectroscopy was used to monitor prefrontal cerebral blood flow changes during the tasks. The results indicated significant differences between the two groups regarding executive function. Participants with lower aerobic fitness performed better than their higher fitness counterparts in inhibitory control and working memory, but not in cognitive flexibility. This finding suggests that the aerobic fitness may moderate the extent of cognitive benefits gained from acute aerobic exercise. Furthermore, the neuroimaging data indicated negative activation in the frontopolar area and dorsolateral prefrontal cortex in response to three complex tasks. These findings underscore the importance of considering individual aerobic fitness when assessing the cognitive benefits of exercise and could have significant implications for tailoring fitness programs to enhance cognitive performance.

Noninvasive brain stimulations modulated brain modular interactions to ameliorate working memory in community-dwelling older adults.

Non-invasive brain stimulations have drawn attention in remediating memory decline in older adults. However, it remains unclear regarding the cognitive and neural mechanisms underpinning the neurostimulation effects on memory rehabilitation. We evaluated the intervention effects of 2-weeks of neurostimulations (high-definition transcranial direct current stimulation, HD-tDCS, and electroacupuncture, EA versus controls, CN) on brain activities and functional connectivity during a working memory task in normally cognitive older adults (age 60+, n = 60). Results showed that HD-tDCS and EA significantly improved the cognitive performance, potentiated the brain activities of overlapping neural substrates (i.e. hippocampus, dlPFC, and lingual gyrus) associated with explicit and implicit memory, and modulated the nodal topological properties and brain modular interactions manifesting as increased intramodular connection of the limbic-system dominated network, decreased intramodular connection of default-mode-like network, as well as stronger intermodular connection between frontal-dominated network and limbic-system-dominated network. Predictive model further identified the neuro-behavioral association between modular connections and working memory. This preliminary study provides evidence that noninvasive neurostimulations can improve older adults' working memory through potentiating the brain activity of working memory-related areas and mediating the modular interactions of related brain networks. These findings have important implication for remediating older adults' working memory and cognitive declines.

Association between poverty, low educational level and smoking with adolescent's working memory: cross lagged analysis from longitudinal data.

Background: Working memory is a crucial element of cognitive function. Previous cross-sectional studies have identified various determinants of working memory in children and adolescents. Nonetheless, no study has yet demonstrated the causal relationship of social determinants with working memory in adolescents. Objective: This study explores the causal link between the level of education, smoking, and other factors with adolescent's working memory. Methods: This study analyzed secondary data from waves 4 and 5 of the Indonesia Family Life Survey (IFLS), utilizing cross-lagged analysis in Jamovi version 2.4.8. The variables included working memory score, maternal education, household income, stress, educational level, smoking, urbanicity, and physical activity. These variables were extracted from IFLS waves 4 and 5, and each dependent variable in IFLS wave four was controlled by the same dependent variables in IFLS 5. Then, we used cross-lagged analysis to assess the causality between each dependent variable and a working memory score in IFLS wave 5. Result: The findings indicate that level of education had a positive impact on working memory in adolescents aged 15-18 years, with a Beta value of 0.18 (95% CI 0.81-0.2; p < 0.001). Smoking and age were negatively associated with working memory, with Beta values of -0.07 (95% CI -0.65 -0.04; p < 0.029) and - 0.10 (95% CI -0.25 -0.05; p < 0.003), respectively. No evidence was found for a significant correlation between poverty and adolescents's working memory. Conclusion: The findings indicate that increased education levels are associated with improved working memory in adolescents aged 15-18. At the same time, smoking has a negative impact on working memory in this age group.

Dysfunctional hippocampal-prefrontal network underlies a multidimensional neuropsychiatric phenotype following early-life seizure.

Brain disturbances during development can have a lasting impact on neural function and behavior. Seizures during this critical period are linked to significant long-term consequences such as neurodevelopmental disorders, cognitive impairments, and psychiatric symptoms, resulting in a complex spectrum of multimorbidity. The hippocampus-prefrontal cortex (HPC-PFC) circuit emerges as a potential common link between such disorders. However, the mechanisms underlying these outcomes and how they relate to specific behavioral alterations are unclear. We hypothesized that specific dysfunctions of hippocampal-cortical communication due to early-life seizure would be associated with distinct behavioral alterations observed in adulthood. Here, we performed a multilevel study to investigate behavioral, electrophysiological, histopathological, and neurochemical long-term consequences of early-life Status epilepticus in male rats. We show that adult animals submitted to early-life seizure (ELS) present working memory impairments and sensorimotor disturbances, such as hyperlocomotion, poor sensorimotor gating, and sensitivity to psychostimulants despite not exhibiting neuronal loss. Surprisingly, cognitive deficits were linked to an aberrant increase in the HPC-PFC long-term potentiation (LTP) in a U-shaped manner, while sensorimotor alterations were associated with heightened neuroinflammation, as verified by glial fibrillary acidic protein (GFAP) expression, and altered dopamine neurotransmission. Furthermore, ELS rats displayed impaired HPC-PFC theta-gamma coordination and an abnormal brain state during active behavior resembling rapid eye movement (REM) sleep oscillatory dynamics. Our results point to impaired HPC-PFC functional connectivity as a possible pathophysiological mechanism by which ELS can cause cognitive deficits and psychiatric-like manifestations even without neuronal loss, bearing translational implications for understanding the spectrum of multidimensional developmental disorders linked to early-life seizures.

Repertoire of timescales in uni - and transmodal regions mediate working memory capacity.

Working memory (WM) describes the dynamic process of maintenance and manipulation of information over a certain time delay. Neuronally, WM recruits a distributed network of cortical regions like the visual and dorsolateral prefrontal cortex as well as the subcortical hippocampus. How the input dynamics and subsequent neural dynamics impact WM remains unclear though. To answer this question, we combined the analysis of behavioral WM capacity with measuring neural dynamics through task-related power spectrum changes, e.g., median frequency (MF) in functional magnetic resonance imaging (fMRI). We show that the processing of the input dynamics, e.g., the task structure's specific timescale, leads to changes in the unimodal visual cortex's corresponding timescale which also relates to working memory capacity. While the more transmodal hippocampus relates to working memory capacity through its balance across multiple timescales or frequencies. In conclusion, we here show the relevance of both input dynamics and different neural timescales for WM capacity in uni - and transmodal regions like visual cortex and hippocampus for the subject's WM performance.

Alpha desynchronization during the filtering initiation phase reflects active processing of distractors.

The ability to select task-relevant information and filter out task-irrelevant information is critical to our success in daily goal-directed behavior. Researchers call this ability filtering efficiency and divide it into three cognitive processing stages: detection of distractors, initiation of filtering, and unnecessary storage. Although researchers have conducted more studies on ERP components related to filtration efficiency, there are few studies related to neural oscillations. Alpha oscillation activity is related to the active processing of information and the suppression of distractors. In the current EEG study, we used the change detection task with distracted items to examine whether alpha activity during filtering initiation reflects reactive suppression of distractors by manipulating memory load levels and the presence or absence of distractors. Results showed that, the presence of the distractors caused an increase in the degree of desynchronization of the alpha oscillations, and in the subsequent time, the alpha activity level returned to a level consistent with the absence of interference conditions. Phase synchronization between frontal and posterior brain regions in the upper alpha oscillations found no effects associated with distractors. Based on these results, we believed that the alpha activity during the filtering initiation phase reflected the active processing of distractors, but this may also be due to lower perceptual load of the target items. In addition, we observed a dominance effect of the right hemisphere in both time-frequency results and connectivity results. We speculate that this effect is related to the activation of the right ventral frontoparietal network.

The multi-strategy hybrid forecasting base on SSA-VMD-WST for complex system.

In view of the strong randomness and non-stationarity of complex system, this study suggests a hybrid multi-strategy prediction technique based on optimized hybrid denoising and deep learning. Firstly, the Sparrow search algorithm (SSA) is used to optimize Variational mode decomposition (VMD) which can decompose the original signal into several Intrinsic mode functions (IMF). Secondly, calculating the Pearson correlation coefficient (PCC) between each IMF component and the original signal, the subsequences with low correlation are eliminated, and the remaining subsequence are denoised by Wavelet soft threshold (WST) method to obtain effective signals. Thirdly, on the basis of the above data noise reduction and reconstruction, our proposal combines Convolutional neural network (CNN) and Bidirectional short-term memory (BiLSTM) model, which is used to analyze the evolution trend of real time sequence data. Finally, we applied the CNN-BiLSTM-SSA-VMD-WST to predict the real time sequence data together with the other methods in order to prove it's effectiveness. The results show that SNR and CC of the SSA-VMD-WST are the largest (the values are 20.2383 and 0.9342). The performance of the CNN-BiLSTM-SSA-VMD-WST are the best, MAE and RMSE are the smallest (which are 0.150 and 0.188), the goodness of fit R2 is the highest(its value is 0.9364). In contrast with other methods, CNN-BiLSTM-SSA-VMD-WST method is more suitable for denoising and prediction of real time series data than the traditional and singular deep learning methods. The proposed method may provide a reliable way for related prediction in various industries.

Improving mental arithmetic ability of primary school students with schema teaching method: An experimental study.

Skillful utilization of mental arithmetic can significantly improve students' mathematical computation ability. However, it was observed that primary school students often resort to reiterating the process of written arithmetic in their minds during mental arithmetic, which is not conducive to their numerical ability improvement. This paper devises a set of graphic teaching aids for primary school students' mental arithmetic improvement based on mental arithmetic strategies, schema theory, and working memory. To validate the effectiveness of schema teaching in enhancing mental arithmetic ability among primary school students, a controlled experiment was conducted with two groups of third-grade students randomly selected from a primary school in Jingshan City. The results, obtained through descriptive statistical analysis and the multitrait-multimethod approach (MTMM), indicated that the experimental group (n = 52) demonstrated significant improvements in speed, accuracy, and stability in mental addition and subtraction after a 14-day instruction period in schema teaching. This study offers a potent mental arithmetic teaching strategy for elementary mathematics education, which can lead to a comprehensive enhancement of students' mental calculation abilities. It also holds promise for inspiring innovative teaching methodologies in primary and secondary mathematics education in the future.

A design for life: Predicting cognitive performance from lifestyle choices.

Maintaining cognitive capacity through adulthood has been the target of many recent studies that have examined the influence of lifestyle choices such as exercise, diet, and sleeping habits. Many of these studies have focused on a single factor (e.g., diet) and its effect on cognitive abilities; however, humans make numerous lifestyle choices every single day, many of which interact and influence each other. Here, we investigated whether combinations of lifestyle choices can predict better or worse cognitive performance in the general population, and whether optimal combinations of choices existed depending on the cognitive domain. Specifically, we examined 20 self-reported lifestyle choices, such as playing video games, drinking alcohol, and amount of exercise taken, in a sample of almost 10,000 participants. All participants also completed 12 cognitive tests that have been shown to generate three composite cognitive domain scores pertaining to short-term memory, verbal abilities, and reasoning. Using recursive feature elimination and random forest regression, we were able to explain 9% of the variance in short-term memory scores, 8% of the variance in reasoning scores, and 7% of the variance in verbal ability scores. While the regression model provided predictive power in all three domains, these levels indicate that even when considering a large number of lifestyle choices, there remains a considerable degree of variability in predicting short-term memory, reasoning and verbal abilities. Thus, while some modifiable lifestyle factors may have an impact on cognitive capacity, there likely exists no single optimal design for life.

Event-related theta and gamma band oscillatory dynamics during visuo-spatial sequence memory in younger and older adults.

Visuo-spatial working memory (VSWM) for sequences is thought to be crucial for daily behaviors. Decades of research indicate that oscillations in the gamma and theta bands play important functional roles in the support of visuo-spatial working memory, but the vast majority of that research emphasizes measures of neural activity during memory retention. The primary aims of the present study were (1) to determine whether oscillatory dynamics in the Theta and Gamma ranges would reflect item-level sequence encoding during a computerized spatial span task, (2) to determine whether item-level sequence recall is also related to these neural oscillations, and (3) to determine the nature of potential changes to these processes in healthy cognitive aging. Results indicate that VSWM sequence encoding is related to later (∼700 ms) gamma band oscillatory dynamics and may be preserved in healthy older adults; high gamma power over midline frontal and posterior sites increased monotonically as items were added to the spatial sequence in both age groups. Item-level oscillatory dynamics during the recall of VSWM sequences were related only to theta-gamma phase amplitude coupling (PAC), which increased monotonically with serial position in both age groups. Results suggest that, despite a general decrease in frontal theta power during VSWM sequence recall in older adults, gamma band dynamics during encoding and theta-gamma PAC during retrieval play unique roles in VSWM and that the processes they reflect may be spared in healthy aging.

Evidence and sources of placebo effects in transcranial direct current stimulation during a single session of visuospatial working memory practice.

Transcranial direct current stimulation (tDCS) can be used to non-invasively augment cognitive training. However, the benefits of tDCS may be due in part to placebo effects, which have not been well-characterized. The purpose of this study was to determine whether tDCS can have a measurable placebo effect on cognitive training and to identify potential sources of this effect. Eighty-three right-handed adults were randomly assigned to one of three groups: control (no exposure to tDCS), sham tDCS, or active tDCS. The sham and active tDCS groups were double-blinded. Each group performed 20 min of an adapted Corsi Block Tapping Task (CBTT), a visuospatial working memory task. Anodal or sham tDCS was applied during CBTT training in a right parietal-left supraorbital montage. After training, active and sham tDCS groups were surveyed on expectations about tDCS efficacy. Linear mixed effects models showed that the tDCS groups (active and sham combined) improved more on the CBTT with training than the control group, suggesting a placebo effect of tDCS. Participants' tDCS expectations were significantly related to the placebo effect, as was the belief of receiving active stimulation. This placebo effect shows that the benefits of tDCS on cognitive training can occur even in absence of active stimulation. Future tDCS studies should consider how treatment expectations may be a source of the placebo effect in tDCS research, and identify ways to potentially leverage them to maximize treatment benefit.

The voluntary utilization of visual working memory.

While a vast amount of research has focused on understanding the capacity limits of visual working memory (VWM), little is known about how VWM resources are employed in unforced behavior and how they correlate with individual capacity constraints. We present a novel, openly available, and easy-to-administer paradigm enabling participants to freely utilize their VWM capacity. Participants had to reconstruct an array of colored squares. In each trial, they were allowed to alternate between the memory array and the reconstruction screen as many times as they wished, each time choosing how many items to reconstruct. This approach allowed us to estimate the number of utilized items, as well as the accuracy of the reconstruction. In addition, VWM capacity was measured using a change detection task. In two experiments, we show that participants tend to under-utilize their VWM resources, performing well below their capacity limits. Surprisingly, while the extent to which participants utilized their VWM was highly reliable, it was uncorrelated with VWM capacity, suggesting that VWM utilization is limited due to strategic considerations rather than capacity limits.

Cross-frequency coupling in cortico-hippocampal networks supports the maintenance of sequential auditory information in short-term memory.

It has been suggested that cross-frequency coupling in cortico-hippocampal networks enables the maintenance of multiple visuo-spatial items in working memory. However, whether this mechanism acts as a global neural code for memory retention across sensory modalities remains to be demonstrated. Intracranial EEG data were recorded while drug-resistant patients with epilepsy performed a delayed matched-to-sample task with tone sequences. We manipulated task difficulty by varying the memory load and the duration of the silent retention period between the to-be-compared sequences. We show that the strength of theta-gamma phase amplitude coupling in the superior temporal sulcus, the inferior frontal gyrus, the inferior temporal gyrus, and the hippocampus (i) supports the short-term retention of auditory sequences; (ii) decodes correct and incorrect memory trials as revealed by machine learning analysis; and (iii) is positively correlated with individual short-term memory performance. Specifically, we show that successful task performance is associated with consistent phase coupling in these regions across participants, with gamma bursts restricted to specific theta phase ranges corresponding to higher levels of neural excitability. These findings highlight the role of cortico-hippocampal activity in auditory short-term memory and expand our knowledge about the role of cross-frequency coupling as a global biological mechanism for information processing, integration, and memory in the human brain.

Memory-specific encoding activities of the ventral tegmental area dopamine and GABA neurons.

Although the midbrain dopamine (DA) system plays a crucial role in higher cognitive functions, including updating and maintaining short-term memory, the encoding properties of the somatic spiking activity of ventral tegmental area (VTA) DA neurons for short-term memory computations have not yet been identified. Here, we probed and analyzed the activity of optogenetically identified DA and GABA neurons while mice engaged in short-term memory-dependent behavior in a T-maze task. Single-neuron analysis revealed that significant subpopulations of DA and GABA neurons responded differently between left and right trials in the memory delay. With a series of control behavioral tasks and regression analysis tools, we show that firing rate differences are linked to short-term memory-dependent decisions and cannot be explained by reward-related processes, motivated behavior, or motor-related activities. This evidence provides novel insights into the mnemonic encoding activities of midbrain DA and GABA neurons.

Using unsupervised capsule neural network reveal spatial representations in the human brain.

Humans can extract high-level spatial features from visual signals, but spatial representations in the brain are complex and remain unclear. The unsupervised capsule neural network (U-CapsNet) is sensitive to the spatial location and relationship of the object, contains a special recurrent mechanism and uses a self-supervised generation strategy to represent images, which is similar to the computational principle in the human brain. Therefore, we hypothesized that U-CapsNet can help us understand how the human brain processes spatial information. First, brain activities were studied using functional magnetic resonance imaging during spatial working memory in which participants had to remember the locations of circles for a short time. Then, U-CapsNet served as a computational model of the brain to perform tasks that are identical to those performed by humans. Finally, the representational models were used to compare the U-CapsNet with the brain. The results showed that some human-defined spatial features naturally emerged in the latent space of U-CapsNet. Moreover, representations in U-CapsNet captured the response structure of two types of brain regions during different activity patterns, as well as important factors associated with human behavior. Together, our study not only provides a computationally feasible framework for modeling how the human brain encodes spatial features but also provides insights into the representational format and goals of the human brain.

Role of GLR-1 in Age-Dependent Short-Term Memory Decline.

As the global elderly population grows, age-related cognitive decline is becoming an increasingly significant healthcare issue, often leading to various neuropsychiatric disorders. Among the many molecular players involved in memory, AMPA-type glutamate receptors are known to regulate learning and memory, but how their dynamics change with age and affect memory decline is not well understood. Here, we examined the in vivo properties of the AMPA-type glutamate receptor GLR-1 in the AVA interneuron of the Caenorhabditis elegans nervous system during physiological aging. We found that both total and membrane-bound GLR-1 receptor levels decrease with age in wild-type worms, regardless of their location along the axon. Using fluorescence recovery after photobleaching, we also demonstrated that a reduction in GLR-1 abundance correlates with decreased local, synaptic GLR-1 receptor dynamics. Importantly, we found that reduced GLR-1 levels strongly correlate with the age-related decline in short-term associative memory. Genetic manipulation of GLR-1 stability, by either deleting msi-1 or expressing a ubiquitination-defective GLR-1 (4KR) variant, prevented this age-related reduction in receptor abundance and improved the short-term memory performance in older animals, which reached performance levels similar to those of young animals. Overall, our data indicate that AMPA-type glutamate receptor abundance and dynamics are key factors in maintaining memory function and that changes in these parameters are linked to age-dependent short-term memory decline.