scholarly journals Event segmentation reveals working memory forgetting rate

2019 ◽  
Author(s):  
Anna Jafarpour ◽  
Elizabeth A Buffalo ◽  
Robert T Knight ◽  
Anne GE Collins
Keyword(s):  
Working Memory ◽  
Working Memory Capacity ◽  
Recognition Task ◽  
Learning Task ◽  
Individual Variability ◽  
Event Perception ◽  
Event Segmentation ◽  
Association Learning ◽  
Sequence Of Events ◽  
Salient Event

1.AbstractWe perceive the world as a series of events and fluidly segment them into episodes. Although individuals generally agree on the segmentation at the occurrence of a salient event, the number of determined segments is variable. Working memory plays a key role in tracking and segmenting a sequence of events; however, it is unclear which aspect of working memory is related to individual variability in event segmentation. We used computational modeling to extract the working memory capacity and forgetting rate of healthy adults (n=36) from an association learning task, and we studied a link between individuals’ working memory limitations and the subjective number of determined events in three movies with different storylines. We found that memory decay, measured in the learning task, is related to event segmentation: Participants who perceived either a very low (under-segmenters) or a very high (over-segmenters) number of events had a higher forgetting rate. We observed that under-segmenters performed better on a temporal recognition task for the movie with a linear storyline and an overarching story, benefiting from the schema. In contrast, the over-segmenters performed better at free recall than under-segmenters for all the movies. The results provide evidence that variability in forgetting rate is linked to the variability in event perception.

scholarly journals Reviewing the Role of Cognitive Load, Expertise Level, Motivation, and Unconscious Processing in Working Memory Performance

2015 ◽  
Vol 4 (2) ◽  
pp. 142 ◽  
Author(s):  
Seffetullah Kuldas ◽  
Shahabuddin Hashim ◽  
Hairul Nizam Ismail ◽  
Zainudin Abu Bakar
Keyword(s):  
Working Memory ◽  
Emotional Processing ◽  
Memory Performance ◽  
Working Memory Capacity ◽  
Cognitive Learning ◽  
Learning Task ◽  
Cognitive Capacity ◽  
Unconscious Processing ◽  
Expertise Level

<p class="p1">Human cognitive capacity is unavailable for conscious processing of every amount of instructional messages. Aligning an instructional design with learner expertise level would allow better use of available working memory capacity in a cognitive learning task. Motivating students to learn consciously is also an essential determinant of the capacity usage. However, motivational factors are often subject to unconscious rather than conscious emotional processing. This review sets out the need for further studies to elucidate the role of motivation and unconscious processing in the use of cognitive capacity<span class="s1">. </span></p>

scholarly journals Effects of methylphenidate on reversal learning depend on working memory capacity

2020 ◽  
Author(s):  
Mojtaba Rostami Kandroodi ◽  
Jennifer Cook ◽  
Jennifer Swart ◽  
Monja Isabel Froböse ◽  
Dirk Geurts ◽  
...  
Keyword(s):  
Working Memory ◽  
Reversal Learning ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Individual Variability ◽  
Large Individual ◽  
Learning Rates ◽  
Trait Impulsivity ◽  
Reversal Phase ◽  
Probabilistic Reversal Learning

Brain catecholamines have long been implicated in cognitive flexibility, exemplified by catecholamine drug and genetic effects on probabilistic reversal learning. However, the mechanisms underlying such effects are unclear. Here we investigated effects of an acute catecholamine challenge with methylphenidate (20 mg, oral) on a novel probabilistic reversal learning paradigm with three options, which was designed to disentangle effects on punishment avoidance from effects on reward perseveration. Given the known large individual variability in methylphenidate’s effects, we stratified our effects by working memory capacity and trait impulsivity, putative proxies of baseline dopamine, in a large sample (n = 102) of healthy volunteers. Contrary to our prediction, methylphenidate did not alter performance in the reversal phase of the task. However, learning rates during the initial acquisition phase of the task were altered by methylphenidate, in a manner that depended on baseline working memory capacity. Participants with greater capacity exhibited greater adaptive reduction of the learning rate in this initial phase, in which outcome contingencies were stable. We hypothesize that the addition of a third choice option in this novel paradigm increased the demands for reinforcement learning, uncovering an effect of methylphenidate on initial learning rather than flexibility to reverse what was learnt.

Neural Mechanisms of Individual Differences in Working Memory Capacity: Observations From Functional Neuroimaging Studies

2017 ◽  
Vol 26 (4) ◽  
pp. 335-345 ◽  
Author(s):  
Takehiro Minamoto ◽  
Hiroyuki Tsubomi ◽  
Naoyuki Osaka
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Fluid Intelligence ◽  
Functional Neuroimaging ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Individual Variability ◽  
Neural Mechanisms ◽  
Related Activity ◽  
Intrinsic Connectivity

Working memory capacity (WMC) indicates an individual’s capability of executive attentional control, which is thought to be critical for general fluid intelligence. Individual variability in WMC has been attributed to the function of the lateral prefrontal cortex (lPFC); however, it is still less clear how the lPFC contributes to individual differences in WMC. Referring to functional neuroimaging studies, we consider three possible neural mechanisms. First, greater task-related activity of the lPFC predicts higher WMC across tasks. Second, a specific task-related functional connectivity also predicts higher WMC. The lPFC consistently forms a part of the connectivity while the coupled region varies depending on tasks. Thus, WMC is reflected by not a fixed but flexible connectivity regulated by the lPFC. Third, distinctive intrinsic connectivity even during resting state is also responsible for individual differences in WMC, with the lPFC seated at a critical hub within the network. These three neural mechanisms differentially contribute to WMC, and therefore, complementarily explain individual differences in WMC.

scholarly journals The Dynamics of Feedback-based Learning is Modulated by Working Memory Capacity

2020 ◽  
Author(s):  
Jil Humann ◽  
Adrian Georg Fischer ◽  
Markus Ullsperger
Keyword(s):  
Working Memory ◽  
Reversal Learning ◽  
Working Memory Capacity ◽  
Instrumental Learning ◽  
Memory Capacity ◽  
Learning Task ◽  
Learning Performance ◽  
Prediction Errors ◽  
Dependent Manner ◽  
Learning Rates

Research suggests that working memory (WM) has an important role in instrumental learning in changeable environments when reinforcement histories of multiple options must be tracked. Working memory capacity (WMC) not only reflects the ability to maintain items, but also to update and shield items against interference in a context-dependent manner; functions conceivably also essential to instrumental learning. To address the relationship of WMC and instrumental learning, we studied choice behavior and EEG of participants performing a probabilistic reversal learning task. Their separately measured WMC positively correlated with reversal learning performance. Computational modeling revealed that low-capacity participants modulated learning rates less dynamically around value reversals. Their choices were more stochastic and less guided by learnt values, resulting in less stable performance and higher susceptibility to misleading probabilistic feedback. Single-trial model-based EEG analysis revealed that prediction errors and learning rates were less strongly represented in cortical activity of low-capacity participants, while the centroparietal positivity, a general correlate of adaptation, was independent of WMC. In conclusion, cognitive functions tackled by WMC tasks are also necessary in instrumental learning. We suggest that noisier representations render items held in WM as well as tracked values in instrumental learning less stable and more susceptible to distractors.

scholarly journals Effects of methylphenidate on reinforcement learning depend on working memory capacity

2021 ◽  
Author(s):  
Mojtaba Rostami Kandroodi ◽  
Jennifer L. Cook ◽  
Jennifer C. Swart ◽  
Monja I. Froböse ◽  
Dirk E. M. Geurts ◽  
...  
Keyword(s):  
Working Memory ◽  
Reinforcement Learning ◽  
Reversal Learning ◽  
Memory Span ◽  
Working Memory Capacity ◽  
Computational Modelling ◽  
Memory Capacity ◽  
Individual Variability ◽  
Large Individual ◽  
Probabilistic Reversal Learning

Abstract Rationale Brain catecholamines have long been implicated in reinforcement learning, exemplified by catecholamine drug and genetic effects on probabilistic reversal learning. However, the mechanisms underlying such effects are unclear. Objectives and methods Here we investigated effects of an acute catecholamine challenge with methylphenidate (20 mg, oral) on a novel probabilistic reversal learning paradigm in a within-subject, double-blind randomised design. The paradigm was designed to disentangle effects on punishment avoidance from effects on reward perseveration. Given the known large individual variability in methylphenidate’s effects, we stratified our effects by working memory capacity and trait impulsivity, putatively modulating the effects of methylphenidate, in a large sample (n = 102) of healthy volunteers. Results Contrary to our prediction, methylphenidate did not alter performance in the reversal phase of the task. Our key finding is that methylphenidate altered learning of choice-outcome contingencies in a manner that depended on individual variability in working memory span. Specifically, methylphenidate improved performance by adaptively reducing the effective learning rate in participants with higher working memory capacity. Conclusions This finding emphasises the important role of working memory in reinforcement learning, as reported in influential recent computational modelling and behavioural work, and highlights the dependence of this interplay on catecholaminergic function.

The role of working memory in the comprehension of unfamiliar and familiar metaphors

2013 ◽  
Vol 5 (4) ◽  
pp. 409-436 ◽  
Author(s):  
Nira Mashal
Keyword(s):  
Working Memory ◽  
Semantic Processing ◽  
Digit Span ◽  
Working Memory Capacity ◽  
Recognition Task ◽  
Phonological Loop ◽  
Free Recall Task ◽  
Long Term Storage ◽  
Semantic Errors ◽  
Phonological Errors

AbstractComprehension of unfamiliar metaphors (mercy blanket) is an effortful cognitive process that requires the formation of a novel metaphoric mapping between two disparate domains during which irrelevant properties have to be suppressed. The present study aims to examine the relationship between the comprehension of both unfamiliar and familiar metaphors and working memory. Three experiments were conducted: a comprehension task (Experiment 1), a recognition task (Experiments 2a and 2b), and a free recall task (Experiment 3). In the first experiment comprehension of both unfamiliar and familiar metaphors correlated with digit span backward but not with digit span forward. Results of the second experiment revealed that unfamiliar metaphors induced a higher rate of semantic errors relative to phonological errors, whereas familiar metaphors induced the same number of phonological and semantic errors. The third experiment confirmed that unfamiliar metaphors were harder to recall than were familiar metaphors. These findings show that working memory capacity may be involved in the computation of unfamiliar metaphoric interpretations, and more specifically in the process of suppressing irrelevant information via the central executive. Familiar metaphor recognition may rely on either phonological codes that are maintained in the phonological loop or on semantic processing that involves long term storage.

Differential Effects of Executive Processes on Working Memory

2016 ◽  
Vol 37 (4) ◽  
pp. 239-249
Author(s):  
Xuezhu Ren ◽  
Tengfei Wang ◽  
Karl Schweizer ◽  
Jing Guo
Keyword(s):  
Working Memory ◽  
Cognitive Processes ◽  
Latent Variable ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Executive Processes ◽  
Differential Effects ◽  
Prepotent Response ◽  
Two Measures

Abstract. Although attention control accounts for a unique portion of the variance in working memory capacity (WMC), the way in which attention control contributes to WMC has not been thoroughly specified. The current work focused on fractionating attention control into distinctly different executive processes and examined to what extent key processes of attention control including updating, shifting, and prepotent response inhibition were related to WMC and whether these relations were different. A number of 216 university students completed experimental tasks of attention control and two measures of WMC. Latent variable analyses were employed for separating and modeling each process and their effects on WMC. The results showed that both the accuracy of updating and shifting were substantially related to WMC while the link from the accuracy of inhibition to WMC was insignificant; on the other hand, only the speed of shifting had a moderate effect on WMC while neither the speed of updating nor the speed of inhibition showed significant effect on WMC. The results suggest that these key processes of attention control exhibit differential effects on individual differences in WMC. The approach that combined experimental manipulations and statistical modeling constitutes a promising way of investigating cognitive processes.

Working Memory Capacity and a Notorious Brain Teaser

2006 ◽  
Vol 53 (2) ◽  
pp. 123-131 ◽  
Author(s):  
Wim De Neys ◽  
Niki Verschueren
Keyword(s):  
Working Memory ◽  
Secondary Task ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Task Load ◽  
Normative Reasoning ◽  
Monty Hall Dilemma ◽  
Monty Hall ◽  
Memory Resources

Abstract. The Monty Hall Dilemma (MHD) is an intriguing example of the discrepancy between people’s intuitions and normative reasoning. This study examines whether the notorious difficulty of the MHD is associated with limitations in working memory resources. Experiment 1 and 2 examined the link between MHD reasoning and working memory capacity. Experiment 3 tested the role of working memory experimentally by burdening the executive resources with a secondary task. Results showed that participants who solved the MHD correctly had a significantly higher working memory capacity than erroneous responders. Correct responding also decreased under secondary task load. Findings indicate that working memory capacity plays a key role in overcoming salient intuitions and selecting the correct switching response during MHD reasoning.

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