scholarly journals The neural mechanisms of active removal from working memory

2021 ◽  
Author(s):  
Jiangang Shan ◽  
Bradley Postle
Keyword(s):  
Working Memory ◽  
Relevant Information ◽  
Neural Mechanisms ◽  
Fmri Data ◽  
Similarity Analysis ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Flexible Control ◽  
Mental Context ◽  
New Information

The ability to frequently update the contents working memory (WM) is vital for the flexible control of behavior. Whether there even exists a mechanism for the active removal of information from working memory, however, remains poorly understood. In this Registered Report we will test the predictions of models for two different (and not mutually exclusive) mechanisms of active removal: adaptation-hijacking and mental-context shifting. We will collect functional magnetic resonance imaging (fMRI) data while subjects perform a novel “ABC-retrocuing” task designed to elicit two modes of removal, active or passive (Shan & Postle, Registered Report). The adaptation-hijacking model posits an adaptation-like modification of perceptual circuits combined with a weak activation of the to-be-removed item. Its predictions will be assessed by using multivariate inverted encoding modeling (IEM) and photic “pings” to assay the state of feature-selective encoding channels and of activity-silent representations under active-removal versus passive-removal conditions. A second model – “working memory episodic memory” (WMEM) – posits that interference from no-longer-relevant information is minimized by making the mental context associated with new information dissimilar from that associated with the to-be-“removed” information. This will be tested by using representational similarity analysis (RSA) to compare the rate of contextual drift under active-removal versus passive-removal conditions.

scholarly journals Targeting working memory to modify emotional reactivity in adult attention deficit hyperactivity disorder: a functional magnetic resonance imaging study

2021 ◽  
Author(s):  
Antonia Kaiser ◽  
Liesbeth Reneman ◽  
Paul J. Lucassen ◽  
Taco J. de Vries ◽  
Anouk Schrantee ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Attention Deficit Hyperactivity Disorder ◽  
Working Memory ◽  
Adult Adhd ◽  
Emotional Reactivity ◽  
Neural Correlates ◽  
Neural Mechanisms ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Hyperactivity Disorder

AbstractUnderstanding the neural mechanisms of emotional reactivity in Attention-Deficit/Hyperactivity Disorder (ADHD) may help develop more effective treatments that target emotion dysregulation. In adult ADHD, emotion regulation problems cover a range of dimensions, including emotional reactivity (ER). One important process that could underlie an impaired ER in ADHD might be impaired working memory (WM) processing. We recently demonstrated that taxing WM prior to the exposure of emotionally salient stimuli reduced physiological and subjective reactivity to such cues in heavy drinkers, suggesting lasting effects of WM activation on ER. Here, we investigated neural mechanisms that could underlie the interaction between WM and ER in adult ADHD participants. We included 30 male ADHD participants and 30 matched controls. Participants performed a novel functional magnetic resonance imaging paradigm in which active WM-blocks were alternated with passive blocks of negative and neutral images. We demonstrated group-independent significant main effects of negative emotional images on amygdala activation, and WM-load on paracingulate gyrus and dorsolateral prefrontal cortex activation. Contrary to earlier reports in adolescent ADHD, no impairments were found in neural correlates of WM or ER. Moreover, taxing WM did not alter the neural correlates of ER in either ADHD or control participants. While we did find effects on the amygdala, paCG, and dlPFC activation, we did not find interactions between WM and ER, possibly due to the relatively unimpaired ADHD population and a well-matched control group. Whether targeting WM might be effective in participants with ADHD with severe ER impairments remains to be investigated.

scholarly journals Informative Biomarkers for Autism Spectrum Disorder Diagnosis in Functional Magnetic Resonance Imaging Data on the Default Mode Network

2021 ◽  
Vol 11 (13) ◽  
pp. 6216
Author(s):  
Aikaterini S. Karampasi ◽  
Antonis D. Savva ◽  
Vasileios Ch. Korfiatis ◽  
Ioannis Kakkos ◽  
George K. Matsopoulos
Keyword(s):  
Magnetic Resonance Imaging ◽  
Autism Spectrum Disorder ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Default Mode Network ◽  
Autism Spectrum ◽  
Fmri Data ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Dynamic Connectivity

Effective detection of autism spectrum disorder (ASD) is a complicated procedure, due to the hundreds of parameters suggested to be implicated in its etiology. As such, machine learning methods have been consistently applied to facilitate diagnosis, although the scarcity of potent autism-related biomarkers is a bottleneck. More importantly, the variability of the imported attributes among different sites (e.g., acquisition parameters) and different individuals (e.g., demographics, movement, etc.) pose additional challenges, eluding adequate generalization and universal modeling. The present study focuses on a data-driven approach for the identification of efficacious biomarkers for the classification between typically developed (TD) and ASD individuals utilizing functional magnetic resonance imaging (fMRI) data on the default mode network (DMN) and non-physiological parameters. From the fMRI data, static and dynamic connectivity were calculated and fed to a feature selection and classification framework along with the demographic, acquisition and motion information to obtain the most prominent features in regard to autism discrimination. The acquired results provided high classification accuracy of 76.63%, while revealing static and dynamic connectivity as the most prominent indicators. Subsequent analysis illustrated the bilateral parahippocampal gyrus, right precuneus, midline frontal, and paracingulate as the most significant brain regions, in addition to an overall connectivity increment.

scholarly journals Cognitive Control of Working Memory: A Model-Based Approach

2021 ◽  
Vol 11 (6) ◽  
pp. 721
Author(s):  
Russell J. Boag ◽  
Niek Stevenson ◽  
Roel van Dooren ◽  
Anne C. Trutti ◽  
Zsuzsika Sjoerds ◽  
...  
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Cognitive Control ◽  
Relevant Information ◽  
Decision Time ◽  
Control Processes ◽  
Prepotent Response ◽  
New Information ◽  
Empirical Performance ◽  
Flow Of Information

Working memory (WM)-based decision making depends on a number of cognitive control processes that control the flow of information into and out of WM and ensure that only relevant information is held active in WM’s limited-capacity store. Although necessary for successful decision making, recent work has shown that these control processes impose performance costs on both the speed and accuracy of WM-based decisions. Using the reference-back task as a benchmark measure of WM control, we conducted evidence accumulation modeling to test several competing explanations for six benchmark empirical performance costs. Costs were driven by a combination of processes, running outside of the decision stage (longer non-decision time) and showing the inhibition of the prepotent response (lower drift rates) in trials requiring WM control. Individuals also set more cautious response thresholds when expecting to update WM with new information versus maintain existing information. We discuss the promise of this approach for understanding cognitive control in WM-based decision making.

scholarly journals Talent in the taxi: a model system for exploring expertise

2009 ◽  
Vol 364 (1522) ◽  
pp. 1407-1416 ◽  
Author(s):  
Katherine Woollett ◽  
Hugo J. Spiers ◽  
Eleanor A. Maguire
Keyword(s):  
Model System ◽  
Neural Mechanisms ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Taxi Drivers ◽  
The Brain ◽  
Use Of Expertise ◽  
Widespread Interest ◽  
Key Questions ◽  
Extensive Practice

While there is widespread interest in and admiration of individuals with exceptional talents, surprisingly little is known about the cognitive and neural mechanisms underpinning talent, and indeed how talent relates to expertise. Because many talents are first identified and nurtured in childhood, it can be difficult to determine whether talent is innate, can be acquired through extensive practice or can only be acquired in the presence of the developing brain. We sought to address some of these issues by studying healthy adults who acquired expertise in adulthood. We focused on the domain of memory and used licensed London taxi drivers as a model system. Taxi drivers have to learn the layout of 25 000 streets in London and the locations of thousands of places of interest, and pass stringent examinations in order to obtain an operating licence. Using neuropsychological assessment and structural and functional magnetic resonance imaging, we addressed a range of key questions: in the context of a fully developed brain and an average IQ, can people acquire expertise to an exceptional level; what are the neural signatures, both structural and functional, associated with the use of expertise; does expertise change the brain compared with unskilled control participants; does it confer any cognitive advantages, and similarly, does it come at a cost to other functions? By studying retired taxi drivers, we also consider what happens to their brains and behaviour when experts stop using their skill. Finally, we discuss how the expertise of taxi drivers might relate to the issue of talent and innate abilities. We suggest that exploring talent and expertise in this manner could have implications for education, rehabilitation of patients with cognitive impairments, understanding individual differences and possibly conditions such as autism where exceptional abilities can be a feature.

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