Neurophysiological Mechanisms of Orientation Feature Matching in a Working Memory Task

2020 ◽  
Vol 46 (6) ◽  
pp. 607-620
Author(s):  
E. S. Mikhailova ◽  
N. Yu. Gerasimenko ◽  
K. A. Saltykov
2017 ◽  
Author(s):  
◽  
Kyle O. Hardman

Recent research has examined the how effectively people use the information in working memory (WM) when reasoning about that information is required in a recognition memory task (Chen and Cowan, 2013; Hardman and Cowan, 2016). In the featurematching task, a WM task, deductive reasoning (Deduction) can be used to determine that knowledge of one binding between colors and orientations (blue/left) precludes a different binding (blue/up), given that each color can only be paired with one other orientation. Hardman and Cowan (2016) found that the use of Deduction with the contents of WM is attempted about half of the time. In the reasoning-only task, which is very similar to the feature-matching task but lacks the requirement that items be stored in WM, however, Deduction was used accuracy and often, even by young children (Hardman and Cowan, in prep). Thus, there is a discrepancy in how people use Deduction depending on the task constraints. In this study, we sought the cause of this Deduction Discrepancy. We hypothesized that the Deduction Discrepancy may be due to (a) the requirement of WM maintenance in the feature-matching task, but not the reasoning-only task; (b) incorrect psychometric modeling results; or (c) limits the ability to use Deduction due to WM load. We examined these possibilities with novel tasks and psychometric models. Our results provided partial support for the first and third hypotheses, but not to an extent that we can fully explain the Deduction Discrepancy. New hypotheses and future directions are discussed.


2008 ◽  
Author(s):  
Alexandra S. Atkins ◽  
Marc G. Berman ◽  
John Jonides ◽  
Patricia A. Reuterlorenz

2018 ◽  
Author(s):  
Anthony Paul Zanesco ◽  
Ekaterina Denkova ◽  
Scott L. Rogers ◽  
William K. MacNulty ◽  
Amishi P. Jha

Cognitive ability is a key selection criterion for entry into many elite professions. Herein, we investigate whether mindfulness training (MT) can enhance cognitive performance in elite military forces. The cognitive effects of a short-form 8-hour MT program contextualized for military cohorts, referred to as Mindfulness-Based Attention Training (MBAT), were assessed. Servicemembers received either a 2-week (n = 40) or 4-week (n = 36) version of MBAT, or no training (NTC, n = 44). Sustained attention and working memory task performance along with self-reported cognitive failures were assessed at study onset (T1) and 8-weeks later (T2). In contrast to both the NTC and 2-week MT groups, the 4-week MT group significantly improved over time on attention and working memory outcome measures. Among the 4-week more so than the 2-week MBAT participants, working memory performance improvements were correlated with their amount of out-of-class MT practice. In addition to these group-wise effects, all participants receiving MBAT decreased in their self-reported cognitive failures from T1 to T2. Importantly, none of these improvements were related to self-reported task motivation. Together, these results suggest that short-form MT, when delivered over a 4-week delivery schedule, may be an effective cognitive training tool in elite military cohorts.


Author(s):  
Alberto Quílez-Robres ◽  
Nieves Moyano ◽  
Alejandra Cortés-Pascual

Academic achievement has been linked to executive functions. However, it is necessary to clarify the different predictive role that executive functions have on general and specific academic achievement and to determine the most predictive executive factor of this academic achievement. The relationship and predictive role between executive functions and their components (initiative, working memory, task monitoring, organization of materials, flexibility, emotional control, inhibition, self-monitoring) with academic achievement are analyzed in this study, both globally and specifically in the areas of Language Arts and Mathematics, in 133 students from 6 to 9 years of age. The relationship obtained in Pearson’s correlation analysis does not differ substantially between overall achievement (r = 0.392) and specific achievement (r = 0.361, r = 0.361), but task monitoring (r = 0.531, r = 0.455, r = 0.446) and working memory (r = 0.512, r = 0.475, r = 0.505) had a greater relationship with general and specific achievement. Finally, regression analyses based on correlation results indicate that executive functions predict general academic performance (14.7%) and specific performance (12.3%, 12.2%) for Language Arts and Mathematics, respectively. Furthermore, working memory and task supervision represent 32.5% of general academic performance, 25.5% of performance in Language Arts, and 27.1% of performance in Mathematics. In conclusion, this study yielded exploratory data on the possible executive functions (task supervision and working memory) responsible for good general academic achievements and specific academic achievements in Mathematics and Language Arts.


2021 ◽  
Vol 9 (1) ◽  
pp. 12
Author(s):  
Ming D. Lim ◽  
Damian P. Birney

Emotional intelligence (EI) refers to a set of competencies to process, understand, and reason with affective information. Recent studies suggest ability measures of experiential and strategic EI differentially predict performance on non-emotional and emotionally laden tasks. To explore cognitive processes underlying these abilities further, we varied the affective context of a traditional letter-based n-back working-memory task. In study 1, participants completed 0-, 2-, and 3-back tasks with flanking distractors that were either emotional (fearful or happy faces) or non-emotional (shapes or letters stimuli). Strategic EI, but not experiential EI, significantly influenced participants’ accuracy across all n-back levels, irrespective of flanker type. In Study 2, participants completed 1-, 2-, and 3-back levels. Experiential EI was positively associated with response times for emotional flankers at the 1-back level but not other levels or flanker types, suggesting those higher in experiential EI reacted slower on low-load trials with affective context. In Study 3, flankers were asynchronously presented either 300 ms or 1000 ms before probes. Results mirrored Study 1 for accuracy rates and Study 2 for response times. Our findings (a) provide experimental evidence for the distinctness of experiential and strategic EI and (b) suggest that each are related to different aspects of cognitive processes underlying working memory.


2021 ◽  
Vol 11 (7) ◽  
pp. 935
Author(s):  
Ying Xing Feng ◽  
Masashi Kiguchi ◽  
Wei Chun Ung ◽  
Sarat Chandra Dass ◽  
Ahmad Fadzil Mohd Hani ◽  
...  

The effect of stress on task performance is complex, too much or too little stress negatively affects performance and there exists an optimal level of stress to drive optimal performance. Task difficulty and external affective factors are distinct stressors that impact cognitive performance. Neuroimaging studies showed that mood affects working memory performance and the correlates are changes in haemodynamic activity in the prefrontal cortex (PFC). We investigate the interactive effects of affective states and working memory load (WML) on working memory task performance and haemodynamic activity using functional near-infrared spectroscopy (fNIRS) neuroimaging on the PFC of healthy participants. We seek to understand if haemodynamic responses could tell apart workload-related stress from situational stress arising from external affective distraction. We found that the haemodynamic changes towards affective stressor- and workload-related stress were more dominant in the medial and lateral PFC, respectively. Our study reveals distinct affective state-dependent modulations of haemodynamic activity with increasing WML in n-back tasks, which correlate with decreasing performance. The influence of a negative effect on performance is greater at higher WML, and haemodynamic activity showed evident changes in temporal, and both spatial and strength of activation differently with WML.


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