Fundamental Questions Surrounding Efforts to Improve Cognitive Function Through Video Game Training

2019 ◽  
pp. 432-454
Author(s):  
Adam Eichenbaum ◽  
Daphne Bavelier ◽  
C. Shawn Green
Keyword(s):  
Working Memory ◽  
Video Game ◽  
Neural Plasticity ◽  
Large Scale ◽  
Memory Task ◽  
Learning Gains ◽  
Critical Importance ◽  
Action Video Game ◽  
The Brain ◽  
Structure And Activity

Neural plasticity, or the ability of the brain to reorganize its structure and activity, is of critical importance. For nearly 50 years, the dominant framework in the field of learning and neural plasticity held that the brain was capable of truly large-scale changes only early in life. However, emerging evidence suggests that plasticity that had assumed to be “lost” due to age, injury, or disease may be at least partially re-established via genetic, pharmacological, and/or behavioral means. Yet, while it is true that humans retain a significant capacity to learn throughout the life span, a second roadblock frequently stands in the way of translating learning gains into practical real-world benefits. This obstacle is the “curse of specificity.” While it is true that, given appropriate training, humans will tend to improve on almost any task, the improvements that are observed are often confined to the exact training task, with little to no benefits of the training being observed for even seemingly very similar tasks. This chapter discusses the trend toward task-specific training on one working memory task, as well as the finding that action video game training does appear to lead to more generalizable improvements in cognitive performance.

scholarly journals Action Video Game Experience Related to Altered Large-Scale White Matter Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Diankun Gong ◽  
Weiyi Ma ◽  
Jinnan Gong ◽  
Hui He ◽  
Li Dong ◽  
...  
Keyword(s):  
White Matter ◽  
Cognitive Deficits ◽  
Video Game ◽  
Neural Plasticity ◽  
Action Potentials ◽  
Large Scale ◽  
Brain Regions ◽  
Research Attention ◽  
Cognitive Benefits ◽  
The Brain

With action video games (AVGs) becoming increasingly popular worldwide, the cognitive benefits of AVG experience have attracted continuous research attention over the past two decades. Research has repeatedly shown that AVG experience can causally enhance cognitive ability and is related to neural plasticity in gray matter and functional networks in the brain. However, the relation between AVG experience and the plasticity of white matter (WM) network still remains unclear. WM network modulates the distribution of action potentials, coordinating the communication between brain regions and acting as the framework of neural networks. And various types of cognitive deficits are usually accompanied by impairments of WM networks. Thus, understanding this relation is essential in assessing the influence of AVG experience on neural plasticity and using AVG experience as an interventional tool for impairments of WM networks. Using graph theory, this study analyzed WM networks in AVG experts and amateurs. Results showed that AVG experience is related to altered WM networks in prefrontal networks, limbic system, and sensorimotor networks, which are related to cognitive control and sensorimotor functions. These results shed new light on the influence of AVG experience on the plasticity of WM networks and suggested the clinical applicability of AVG experience.

Converging Evidence That Neural Plasticity Underlies Transcranial Direct-Current Stimulation

2021 ◽  
Vol 33 (1) ◽  
pp. 146-157
Author(s):  
Chong Zhao ◽  
Geoffrey F. Woodman
Keyword(s):  
Visual Search ◽  
Direct Current ◽  
Neural Plasticity ◽  
Transcranial Direct Current Stimulation ◽  
Time Course ◽  
Memory Task ◽  
Long Term Memory ◽  
Visual Stream ◽  
Direct Current Stimulation ◽  
The Brain

It is not definitely known how direct-current stimulation causes its long-lasting effects. Here, we tested the hypothesis that the long time course of transcranial direct-current stimulation (tDCS) is because of the electrical field increasing the plasticity of the brain tissue. If this is the case, then we should see tDCS effects when humans need to encode information into long-term memory, but not at other times. We tested this hypothesis by delivering tDCS to the ventral visual stream of human participants during different tasks (i.e., recognition memory vs. visual search) and at different times during a memory task. We found that tDCS improved memory encoding, and the neural correlates thereof, but not retrieval. We also found that tDCS did not change the efficiency of information processing during visual search for a certain target object, a task that does not require the formation of new connections in the brain but instead relies on attention and object recognition mechanisms. Thus, our findings support the hypothesis that direct-current stimulation modulates brain activity by changing the underlying plasticity of the tissue.

scholarly journals Acute Ketamine Administration Alters the Brain Responses to Executive Demands in a Verbal Working Memory Task: an fMRI Study

2004 ◽  
Vol 29 (6) ◽  
pp. 1203-1214 ◽  
Author(s):  
R A E Honey ◽  
G D Honey ◽  
C O'Loughlin ◽  
S R Sharar ◽  
D Kumaran ◽  
...  
Keyword(s):  
Working Memory ◽  
Memory Task ◽  
Verbal Working Memory ◽  
Brain Responses ◽  
Fmri Study ◽  
The Brain

scholarly journals Exploring the Inner Workings of Neuron Circuits That Exhibit Persistent Activity To Explain How Working Memory and Executive Function Are Implemented in The Brain

2021 ◽  
Author(s):  
Paul Gomez
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Prefrontal Cortex ◽  
Executive Function ◽  
Memory Task ◽  
Persistent Activity ◽  
Storage Mechanism ◽  
Minimum Number ◽  
Task Processing ◽  
The Brain

In this research we explore in detail how a phenomenon called sustained persistent activity is achieved by circuits of interconnected neurons. Persistent activity is a phenomenon that has been extensively studied (Papoutsi et al. 2013; Kaminski et. al. 2017; McCormick et al. 2003; Rahman, and Berger, 2011). Persistent activity consists in neuron circuits whose spiking activity remains even after the initial stimuli are removed. Persistent activity has been found in the prefrontal cortex (PFC) and has been correlated to working memory and decision making (Clayton E. Curtis and Daeyeol Lee, 2010). We go beyond the explanation of how persistent activity happens and show how arrangements of those basic circuits encode and store data and are used to perform more elaborated tasks and computations. The purpose of the model we propose here is to describe the minimum number of neurons and their interconnections required to explain persistent activity and how this phenomenon is actually a fast storage mechanism required for implementing working memory, task processing and decision making.

scholarly journals Multimethod Investigation of the Neurobiological Basis of ADHD Symptomatology in Children Aged 9-10: Baseline Data from the ABCD Study

2020 ◽  
Author(s):  
Max Michael Owens ◽  
Nicholas Allgaier ◽  
Sage Hahn ◽  
Dekang Yuan ◽  
Matthew Albaugh ◽  
...  
Keyword(s):  
Working Memory ◽  
Inhibitory Control ◽  
Internalizing Symptoms ◽  
Memory Task ◽  
Reward Processing ◽  
Continuous Measure ◽  
Neurocognitive Deficits ◽  
Brain Morphometry ◽  
The Brain ◽  
Adhd Symptomatology

Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.

scholarly journals Differences in working memory coding of biological motion attributed to oneself and others

2021 ◽  
Author(s):  
Mateusz Woźniak ◽  
Timo Torsten Schmidt ◽  
Yuan-hao Wu ◽  
Felix Blankenburg ◽  
Jakob Hohwy
Keyword(s):  
Working Memory ◽  
Inferior Frontal Gyrus ◽  
Body Movement ◽  
Univariate Analysis ◽  
Memory Task ◽  
Brain Network ◽  
Temporoparietal Junction ◽  
Ventral Medial Prefrontal Cortex ◽  
The Brain ◽  
Full Body

AbstractThe question how the brain distinguishes between information about oneself and the rest of the world is of fundamental interest to both philosophy and neuroscience. This question can be approached empirically by investigating how associating stimuli with oneself leads to differences in neurocognitive processing. However, little is known about the brain network involved in forming such self-associations for, specifically, bodily stimuli. In this fMRI study, we sought to distinguish the neural substrates of representing a full-body movement as one’s movement and as someone else’s movement. Participants performed a delayed match-to-sample working memory task where a retained full-body movement (displayed using point-light walkers) was arbitrarily labelled as one’s own movement or as performed by someone else. By using arbitrary associations we aimed to address a limitation of previous studies, namely that our own movements are more familiar to us than movements of other people. A searchlight multivariate decoding analysis was used to test where information about types of movement and about self-association was coded. Movement specific activation patterns was found in a network of regions also involved in perceptual processing of movement stimuli, however not in early sensory regions. Information about whether a memorized movement was associated with the self or with another person was found to be coded by activity in the left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), bilateral supplementary motor area, and (at reduced threshold) in the left temporoparietal junction (TPJ). These areas are frequently reported as involved in action understanding (IFG, MFG) and domain-general self/other distinction (TPJ). Finally, in univariate analysis we found that selecting a self-associated movement for retention was related to increased activity in the ventral medial prefrontal cortex.

A Large-scale Neurocomputational Model of Task-oriented Behavior Selection and Working Memory in Prefrontal Cortex

2006 ◽  
Vol 18 (2) ◽  
pp. 242-257 ◽  
Author(s):  
George L. Chadderdon ◽  
Olaf Sporns
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Large Scale ◽  
Memory Task ◽  
Brain Regions ◽  
Synaptic Activity ◽  
Dynamic State ◽  
Memory Representation ◽  
Behavioral Repertoire ◽  
Behavior Selection

The prefrontal cortex (PFC) is crucially involved in the executive component of working memory, representation of task state, and behavior selection. This article presents a large-scale computational model of the PFC and associated brain regions designed to investigate the mechanisms by which working memory and task state interact to select adaptive behaviors from a behavioral repertoire. The model consists of multiple brain regions containing neuronal populations with realistic physiological and anatomical properties, including extrastriate visual cortical regions, the inferotemporal cortex, the PFC, the striatum, and midbrain dopamine (DA) neurons. The onset of a delayed match-to-sample or delayed nonmatch-to-sample task triggers tonic DA release in the PFC causing a switch into a persistent, stimulus-insensitive dynamic state that promotes the maintenance of stimulus representations within prefrontal networks. Other modeled prefrontal and striatal units select cognitive acceptance or rejection behaviors according to which task is active and whether prefrontal working memory representations match the current stimulus. Working memory task performance and memory fields of prefrontal delay units are degraded by extreme elevation or depletion of tonic DA levels. Analyses of cellular and synaptic activity suggest that hyponormal DA levels result in increased prefrontal activation, whereas hypernormal DA levels lead to decreased activation. Our simulation results suggest a range of predictions for behavioral, single-cell, and neuroimaging response data under the proposed task set and under manipulations of DA concentration.

scholarly journals Working memory networks and activation patterns in schizophrenia and bipolar disorder: comparison with healthy controls

2014 ◽  
Vol 204 (4) ◽  
pp. 290-298 ◽  
Author(s):  
Christine Lycke Brandt ◽  
Tom Eichele ◽  
Ingrid Melle ◽  
Kjetil Sundet ◽  
Andrés Server ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Working Memory ◽  
Large Scale ◽  
Psychotic Disorders ◽  
Brain Networks ◽  
Memory Task ◽  
Control Group ◽  
Healthy Controls ◽  
Activation Patterns ◽  
Patient Groups

BackgroundSchizophrenia and bipolar disorder are severe mental disorders with overlapping genetic and clinical characteristics, including cognitive impairments. An important question is whether these disorders also have overlapping neuronal deficits.AimsTo determine whether large-scale brain networks associated with working memory, as measured with functional magnetic resonance imaging (fMRI), are the same in both schizophrenia and bipolar disorder, and how they differ from those in healthy individuals.MethodPatients with schizophrenia (n = 100) and bipolar disorder (n = 100) and a healthy control group (n = 100) performed a 2-back working memory task while fMRI data were acquired. The imaging data were analysed using independent component analysis to extract large-scale networks of task-related activations.ResultsSimilar working memory networks were activated in all groups. However, in three out of nine networks related to the experimental task there was a graded response difference in fMRI signal amplitudes, where patients with schizophrenia showed greater activation than those with bipolar disorder, who in turn showed more activation than healthy controls. Secondary analysis of the patient groups showed that these activation patterns were associated with history of psychosis and current elevated mood in bipolar disorder.ConclusionsThe same brain networks were related to working memory in schizophrenia, bipolar disorder and controls. However, some key networks showed a graded hyperactivation in the two patient groups, in line with a continuum of neuronal abnormalities across psychotic disorders.

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