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The study aimed to evaluate the effects of noninvasive brain stimulation on cognitive function in healthy older adults and patients with Alzheimer's disease. A comprehensive literature search was performed on noninvasive stimulation studies published from January 1990 to November 2014 in Pubmed and Web of Science. Fourteen articles with a total of 331 participants were identified as studies with healthy older adults, and the mean effect size and 95% confidence interval were estimated. A significant effect size of 0.42 was found for the cognitive outcome. Further subgroup analyses demonstrated more prominent effects for studies delivering the stimulation before the execution of the task and studies applying multiple sessions of stimulation. To assess the effects of stimulation on Alzheimer's disease patients, 11 studies with a total of 200 patients were included in the analysis. A significant effect size of 1.35 was found for the cognitive outcomes. Subgroup analyses indicated more pronounced effects for studies applying the stimulation during the execution of the task compared with studies delivering the stimulation before the execution of the task. Noninvasive brain stimulation has a positive effect on cognitive function in physiological and pathological aging. [ABSTRACT FROM AUTHOR]

Abstract: Functional neuroimaging data have shown that mental calculation involves fronto-parietal areas that are composed of different subsystems shared with other cognitive functions such as working memory and language. Event-related potential (ERP) analysis has also indicated sequential information changes during the calculation process. However, little is known about the dynamic properties of oscillatory networks in this process. In the present study, we applied both ERP and event-related (de-)synchronization (ERS/ERD) analyses to EEG data recorded from normal human subjects performing tasks for sequential visual/auditory mental addition. Results in the study indicate that the late positive components (LPCs) can be decomposed into two separate parts. The earlier element LPC1 (around 360ms) reflects the computing attribute and is more prominent in calculation tasks. The later element LPC2 (around 590ms) indicates an effect of number size and appears larger only in a more complex 2-digit addition task. The theta ERS and alpha ERD show modality-independent frontal and parietal differential patterns between the mental addition and control groups, and discrepancies are noted in the beta ERD between the 2-digit and 1-digit mental addition groups. The 2-digit addition (both visual and auditory) results in similar beta ERD patterns to the auditory control, which may indicate a reliance on auditory-related resources in mental arithmetic, especially with increasing task difficulty. These results coincide with the theory of simple calculation relying on the visuospatial process and complex calculation depending on the phonological process. [Copyright &y& Elsevier]

The present study aimed to explore the effect of intermittent theta-burst stimulation (iTBS) on visual working memory for people suffering from methamphetamine use disorder (MUD). Five sessions of iTBS were carried over the left dorsolateral prefrontal cortex (DLPFC) or the vertex as a sham control, with each session in one day. Orientation free-recall tasks were conducted before the iTBS stimulation, after the first and fifth sessions of stimulation. Results showed that when compared with the sham group, a single session of iTBS over the left DLPFC improved participants' working memory performance. Specifically, iTBS over the left DLPFC increased the working memory capacity and such effects enlarged with multiple sessions. The present finding suggested that iTBS over DLPFC could be a promising intervention method to enhance the cognitive function of addicts with MUD. [ABSTRACT FROM AUTHOR]

Working memory (WM) deficits have been widely documented in schizophrenia (SZ), and almost all existing studies attributed the deficits to decreased capacity as compared to healthy control (HC) subjects. Recent developments in WM research suggest that other components, such as precision, also mediate behavioral performance. It remains unclear how different WM components jointly contribute to deficits in schizophrenia. We measured the performance of 60 SZ (31 females) and 61 HC (29 females) in a classical delay-estimation visual working memory (VWM) task and evaluated several influential computational models proposed in basic science of VWM to disentangle the effect of various memory components. We show that the model assuming variable precision (VP) across items and trials is the best model to explain the performance of both groups. According to the VP model, SZ exhibited abnormally larger variability of allocating memory resources rather than resources or capacity per se. Finally, individual differences in the resource allocation variability predicted variation of symptom severity in PSZ, highlighting its functional relevance to schizophrenic pathology. This finding was further verified using distinct visual features and subject cohorts. These results provide an alternative view instead of the widely accepted decreased-capacity theory and highlight the key role of elevated resource allocation variability in generating atypical VWM behavior in schizophrenia. Our findings also shed new light on the utility of Bayesian observer models to characterize mechanisms of mental deficits in clinical neuroscience. Author summary: Working memory is a core cognitive function related to a broad range of cognitive domains such as problem-solving, attention, executive control, and IQ. Although working memory deficits have been well-documented in schizophrenia, the underlying mechanisms remain unclear. Conventional working memory theories attribute working memory deficits in schizophrenia to their reduced memory capacity, overlooking the potential roles of other memory components, such as precision. In this study, we take the approach of computational psychiatry and use computational modeling to uncover the major determinants of working memory deficits. We assess working memory performance of a large cohort of participants (60 schizophrenia patients and 61 demographic matched healthy controls) and evaluate multiple mainstream computational models of visual working memory. The variable precision model turns out to be the best model for both groups. We further find that the poorer performance of schizophrenia patients arises from heterogeneous distribution of memory resources when encoding items in memory. This resource allocation variability can also predict symptom severity in schizophrenia. Our study highlights the use of computational models in psychiatric researches. [ABSTRACT FROM AUTHOR]