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Cognitive psychology for dummies
\"Written specifically for psychology students and professionals, this hands-on guide provides an accessible and entertaining introduction to the field of cognitive psychology. Unlike the dense and jargon-laden content found in most psychology textbooks, it offers easy-to-understand explanations of the fundamental elements of cognitive psychology, giving you a firm grasp of the material.\"-- Back cover.
Book
Association between Early Life Exposure to Air Pollution and Working Memory and Attention
Although previous studies have reported negative associations between exposure to air pollution and cognition, studies of the effects of prenatal and postnatal exposures in early childhood have been limited.
We sought to assess the role exposure to fine particulate matter ([Formula: see text]) during different prenatal and postnatal windows may play in children's cognitive development at school age.
Within the Brain Development and Air Pollution Ultrafine Particles in School Children (BREATHE) Project, we estimated residential [Formula: see text] exposures by land use regression for the prenatal period and first seven postnatal years of 2,221 children from Barcelona, Spain. The participants ([Formula: see text]) completed computerized tests assessing working memory, attentiveness, and conflict network during four visits in 2012–2013. We used linear mixed effects and distributed lag models to assess the period of exposure to [Formula: see text] in association with cognitive development.
Inverse associations were identified between [Formula: see text] exposure during the fifth and sixth postnatal years and working memory, with boys showing much higher vulnerability. Regarding attention functions, exposure to higher [Formula: see text] levels during the prenatal period and from the fourth postnatal year were associated with a reduction in conflict network performance, though we found no association with attentiveness. The overall estimated cumulative effect of a [Formula: see text] increase in [Formula: see text] resulted in a reduction in the working memory [Formula: see text] score of [Formula: see text] [95% confidence interval (CI): [Formula: see text], [Formula: see text]] points and an increase in the conflict attentional network of 11.31 (95% CI: 6.05, 16.57) milliseconds, indicating a poorer performance.
Early life exposure to [Formula: see text] was associated with a reduction in fundamental cognitive abilities, including working memory and conflict attentional network. https://doi.org/10.1289/EHP3169.
Journal Article
Working memory and clinical developmental disorders : theories, debates and interventions
This comprehensive volume brings together international experts involved in applying and developing understanding of Working Memory in the context of a variety of neurodevelopmental disorders, neurocognitive disorders, and depressive disorders. Each chapter provides a description of the disorder and investigates the Working Memory and related Executive Function deficits. It goes on to provide a neurological profile, before exploring the impact of the disorder in daily functions, the current debates related to this disorder, and the potential effects of medication and intervention. Through combining coverage of theoretical understanding, methods of assessment, and different evidence-based intervention programs, the book supports clinical assessment and management of poor Working Memory. It is essential reading for students in neurodevelopmental disorders, atypical development and developmental psychopathology as well as allied health professionals, clinicians and those working with children in education and healthcare settings.
Book
Circuit mechanisms for the maintenance and manipulation of information in working memory
Recently it has been proposed that information in working memory (WM) may not always be stored in persistent neuronal activity but can be maintained in ‘activity-silent’ hidden states, such as synaptic efficacies endowed with short-term synaptic plasticity. To test this idea computationally, we investigated recurrent neural network models trained to perform several WM-dependent tasks, in which WM representation emerges from learning and is not a priori assumed to depend on self-sustained persistent activity. We found that short-term synaptic plasticity can support the short-term maintenance of information, provided that the memory delay period is sufficiently short. However, in tasks that require actively manipulating information, persistent activity naturally emerges from learning, and the amount of persistent activity scales with the degree of manipulation required. These results shed insight into the current debate on WM encoding and suggest that persistent activity can vary markedly between short-term memory tasks with different cognitive demands.The role of persistent spiking activity in working memory has recently come under debate. Here the authors use biologically realistic recurrent neural networks to explain why the strength of persistent activity can vary markedly between tasks.
Journal Article
From short-term store to multicomponent working memory: The role of the modal model
The term “modal model” reflects the importance of Atkinson and Shiffrin’s paper in capturing the major developments in the cognitive psychology of memory that were achieved over the previous decade, providing an integrated framework that has formed the basis for many future developments. The fact that it is still the most cited model from that period some 50 years later has, we suggest, implications for the model itself and for theorising in psychology more generally. We review the essential foundations of the model before going on to discuss briefly the way in which one of its components, the short-term store, had influenced our own concept of a multicomponent working memory. This is followed by a discussion of recent claims that the concept of a short-term store be replaced by an interpretation in terms of activated long-term memory. We present several reasons to question these proposals. We conclude with a brief discussion of the implications of the longevity of the modal model for styles of theorising in cognitive psychology.
Journal Article
A review on the long short-term memory model
Long short-term memory (LSTM) has transformed both machine learning and neurocomputing fields. According to several online sources, this model has improved Google’s speech recognition, greatly improved machine translations on Google Translate, and the answers of Amazon’s Alexa. This neural system is also employed by Facebook, reaching over 4 billion LSTM-based translations per day as of 2017. Interestingly, recurrent neural networks had shown a rather discrete performance until LSTM showed up. One reason for the success of this recurrent network lies in its ability to handle the exploding/vanishing gradient problem, which stands as a difficult issue to be circumvented when training recurrent or very deep neural networks. In this paper, we present a comprehensive review that covers LSTM’s formulation and training, relevant applications reported in the literature and code resources implementing this model for a toy example.
Journal Article
Short-Term Load Forecasting Using EMD-LSTM Neural Networks with a Xgboost Algorithm for Feature Importance Evaluation
Accurate load forecasting is an important issue for the reliable and efficient operation of a power system. This study presents a hybrid algorithm that combines similar days (SD) selection, empirical mode decomposition (EMD), and long short-term memory (LSTM) neural networks to construct a prediction model (i.e., SD-EMD-LSTM) for short-term load forecasting. The extreme gradient boosting-based weighted k-means algorithm is used to evaluate the similarity between the forecasting and historical days. The EMD method is employed to decompose the SD load to several intrinsic mode functions (IMFs) and residual. Separated LSTM neural networks were also employed to forecast each IMF and residual. Lastly, the forecasting values from each LSTM model were reconstructed. Numerical testing demonstrates that the SD-EMD-LSTM method can accurately forecast the electric load.
Journal Article
Brain Training Game Boosts Executive Functions, Working Memory and Processing Speed in the Young Adults: A Randomized Controlled Trial
Do brain training games work? The beneficial effects of brain training games are expected to transfer to other cognitive functions. Yet in all honesty, beneficial transfer effects of the commercial brain training games in young adults have little scientific basis. Here we investigated the impact of the brain training game (Brain Age) on a wide range of cognitive functions in young adults.
We conducted a double-blind (de facto masking) randomized controlled trial using a popular brain training game (Brain Age) and a popular puzzle game (Tetris). Thirty-two volunteers were recruited through an advertisement in the local newspaper and randomly assigned to either of two game groups (Brain Age, Tetris). Participants in both the Brain Age and the Tetris groups played their game for about 15 minutes per day, at least 5 days per week, for 4 weeks. Measures of the cognitive functions were conducted before and after training. Measures of the cognitive functions fell into eight categories (fluid intelligence, executive function, working memory, short-term memory, attention, processing speed, visual ability, and reading ability).
Our results showed that commercial brain training game improves executive functions, working memory, and processing speed in young adults. Moreover, the popular puzzle game can engender improvement attention and visuo-spatial ability compared to playing the brain training game. The present study showed the scientific evidence which the brain training game had the beneficial effects on cognitive functions (executive functions, working memory and processing speed) in the healthy young adults.
Our results do not indicate that everyone should play brain training games. However, the commercial brain training game might be a simple and convenient means to improve some cognitive functions. We believe that our findings are highly relevant to applications in educational and clinical fields.
UMIN Clinical Trial Registry 000005618.
Journal Article
The many faces of working memory and short-term storage
The topic of working memory (WM) is ubiquitous in research on cognitive psychology and on individual differences. According to one definition, it is a small amount of information kept in a temporary state of heightened accessibility; it is used in most types of communication and problem solving. Short-term storage has been defined as the passive (i.e., non-attention-based, nonstrategic) component of WM or, alternatively, as a passive store separate from an attention-based WM. Here I note that much confusion has been created by the use by various investigators of many, subtly different definitions of WM and short-term storage. The definitions are sometimes made explicit and sometimes implied. As I explain, the different definitions may have stemmed from the use of a wide variety of techniques to explore WM, along with differences in theoretical orientation. By delineating nine previously used definitions of WM and explaining how additional ones may emerge from combinations of these nine, I hope to improve scientific discourse on WM. The potential advantages of clarity about definitions of WM and short-term storage are illustrated with respect to several ongoing research controversies.
Journal Article
Stability of working memory in continuous attractor networks under the control of short-term plasticity
Continuous attractor models of working-memory store continuous-valued information in continuous state-spaces, but are sensitive to noise processes that degrade memory retention. Short-term synaptic plasticity of recurrent synapses has previously been shown to affect continuous attractor systems: short-term facilitation can stabilize memory retention, while short-term depression possibly increases continuous attractor volatility. Here, we present a comprehensive description of the combined effect of both short-term facilitation and depression on noise-induced memory degradation in one-dimensional continuous attractor models. Our theoretical description, applicable to rate models as well as spiking networks close to a stationary state, accurately describes the slow dynamics of stored memory positions as a combination of two processes: (i) diffusion due to variability caused by spikes; and (ii) drift due to random connectivity and neuronal heterogeneity. We find that facilitation decreases both diffusion and directed drifts, while short-term depression tends to increase both. Using mutual information, we evaluate the combined impact of short-term facilitation and depression on the ability of networks to retain stable working memory. Finally, our theory predicts the sensitivity of continuous working memory to distractor inputs and provides conditions for stability of memory.
Journal Article