Conditional and biconditional rule difficulty with attribute identification, rule learning, and complete learning task.

1970 ◽  
Vol 86 (2) ◽  
pp. 250-254 ◽  
Author(s):  
Leonard M. Giambra
Keyword(s):  
Rule Learning ◽  
Learning Task ◽  
Identification Rule ◽  
Attribute Identification

Effects of Display Medium and Luminance Contrast on Concept Formation and EEG Response

2005 ◽  
Vol 100 (3_suppl) ◽  
pp. 943-954 ◽  
Author(s):  
Kong-King Shieh ◽  
Mei-Hsiang Chen
Keyword(s):  
Cognitive Performance ◽  
Cognitive Processes ◽  
Concept Formation ◽  
Rule Learning ◽  
Visual Display ◽  
Luminance Contrast ◽  
Learning Task ◽  
Visual Display Terminal ◽  
Eeg Power ◽  
Learning Concept

Reading from a visual display terminal (VDT) has increased enormously with widespread computer use. Whether such reading affects higher cognitive processes requires study so the effect of display medium (LCD screen vs paper) and luminance contrast (1:3, 1:7, 1:11) on concept-formation performance and EEG responses was investigated. 96 men and 24 women participated in two concept-formation tasks (rule learning vs attribute and rule learning). Concept-formation performance and EEG responses were similar for stimuli displayed on paper or LCD screen. The concern that the screen may be detrimental to conception-formation performance was not confirmed; however, luminance contrast significantly affected time to complete a concept-formation task and EEG response. The middle contrast (1:7) had the smallest mean EEG power, so this contrast might be appropriate for cognitive performance. Participants' performance was significantly faster and EEG power lower for the rule-learning task than for an attribute and rule-learning task.

scholarly journals Electrophysiological Responses to Feedback during the Application of Abstract Rules

2013 ◽  
Vol 25 (11) ◽  
pp. 1986-2002 ◽  
Author(s):  
Matthew M. Walsh ◽  
John R. Anderson
Keyword(s):  
Rule Learning ◽  
Learning Task ◽  
Deviant Stimulus ◽  
Sample Number ◽  
Stimulus Response ◽  
Reward Prediction ◽  
Test Number ◽  
Electrophysiological Responses ◽  
Abstract Rule ◽  
How People Learn

Much research focuses on how people acquire concrete stimulus–response associations from experience; however, few neuroscientific studies have examined how people learn about and select among abstract rules. To address this issue, we recorded ERPs as participants performed an abstract rule-learning task. In each trial, they viewed a sample number and two test numbers. Participants then chose a test number using one of three abstract mathematical rules they freely selected from: greater than the sample number, less than the sample number, or equal to the sample number. No one rule was always rewarded, but some rules were rewarded more frequently than others. To maximize their earnings, participants needed to learn which rules were rewarded most frequently. All participants learned to select the best rules for repeating and novel stimulus sets that obeyed the overall reward probabilities. Participants differed, however, in the extent to which they overgeneralized those rules to repeating stimulus sets that deviated from the overall reward probabilities. The feedback-related negativity (FRN), an ERP component thought to reflect reward prediction error, paralleled behavior. The FRN was sensitive to item-specific reward probabilities in participants who detected the deviant stimulus set, and the FRN was sensitive to overall reward probabilities in participants who did not. These results show that the FRN is sensitive to the utility of abstract rules and that the individual's representation of a task's states and actions shapes behavior as well as the FRN.

P3B and Positive Slow Wave following Real and Dummy Feedback on Arithmetic Rule-Learning and Perceptuomotor Tasks

1997 ◽  
Vol 84 (1) ◽  
pp. 195-216
Author(s):  
Bruce E. McDonough ◽  
Charles A. Warren
Keyword(s):  
Slow Wave ◽  
Green Light ◽  
Rule Learning ◽  
Event Related Potentials ◽  
Learning Task ◽  
Feedback Information ◽  
Feedback Display ◽  
Related Potentials ◽  
Numeric Information

Event-related Potentials (ERPs) were recorded to feedback during a cognitively demanding, arithmetic rule-learning task and a relatively simple, skill-oriented, perceptuomotor task. For both tasks, a compound feedback display was employed. It consisted of numeric feedback information presented simultaneously with a red or green light (50% each) which indicated whether the numeric information was real (valid) or dummy (invalid). The task and feedback-validity manipulations showed a functional dissociation between the P3b (350–450 msec.) and a Positive Slow Wave (600–900 msec.). P3b was larger for real than for dummy feedback; Positive Slow Wave was larger for rule-learning than for perceptuomotor tasks.

scholarly journals Neural correlates of error-related learning deficits in individuals with psychopathy

2009 ◽  
Vol 40 (9) ◽  
pp. 1559-1568 ◽  
Author(s):  
A. K. L. von Borries ◽  
I. A. Brazil ◽  
B. H. Bulten ◽  
J. K. Buitelaar ◽  
R. J. Verkes ◽  
...  
Keyword(s):  
Error Detection ◽  
Rule Learning ◽  
Learning Task ◽  
Error Monitoring ◽  
Learning Deficits ◽  
Stimulus Response ◽  
Error Related Negativity ◽  
Learning Conditions ◽  
The Moment ◽  
Actual Response

BackgroundPsychopathy (PP) is associated with a performance deficit in a variety of stimulus–response and stimulus–reinforcement learning paradigms. We tested the hypothesis that failures in error monitoring underlie these learning deficits.MethodWe measured electrophysiological correlates of error monitoring [error-related negativity (ERN)] during a probabilistic learning task in individuals with PP (n=13) and healthy matched control subjects (n=18). The task consisted of three graded learning conditions in which the amount of learning was manipulated by varying the degree to which the response was predictive of the value of the feedback (50, 80 and 100%).ResultsBehaviourally, we found impaired learning and diminished accuracy in the group of individuals with PP. Amplitudes of the response ERN (rERN) were reduced. No differences in the feedback ERN (fERN) were found.ConclusionsThe results are interpreted in terms of a deficit in initial rule learning and subsequent generalization of these rules to new stimuli. Negative feedback is adequately processed at a neural level but this information is not used to improve behaviour on subsequent trials. As learning is degraded, the process of error detection at the moment of the actual response is diminished. Therefore, the current study demonstrates that disturbed error-monitoring processes play a central role in the often reported learning deficits in individuals with PP.

scholarly journals Applying an exemplar model to an implicit rule-learning task: Implicit learning of semantic structure

2017 ◽  
Vol 70 (1) ◽  
pp. 192-192
Author(s):  
Chrissy M. Chubala ◽  
Brendan T. Johns ◽  
Randall K. Jamieson ◽  
D. J. K. Mewhort
Keyword(s):  
Implicit Learning ◽  
Rule Learning ◽  
Learning Task ◽  
Semantic Structure ◽  
Exemplar Model ◽  
Implicit Rule

Rule learning by zebra finches in an artificial grammar learning task: which rule?

2012 ◽  
Vol 16 (2) ◽  
pp. 165-175 ◽  
Author(s):  
Caroline A. A. van Heijningen ◽  
Jiani Chen ◽  
Irene van Laatum ◽  
Bonnie van der Hulst ◽  
Carel ten Cate
Keyword(s):  
Rule Learning ◽  
Learning Task ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Zebra Finches ◽  
Grammar Learning

scholarly journals Cerebellar and Prefrontal-Cortical Engagement During Higher-Order Rule Learning in Older Adulthood

2020 ◽  
Author(s):  
T. Bryan Jackson ◽  
Ted Maldonado ◽  
Sydney M. Eakin ◽  
Joseph M. Orr ◽  
Jessica A. Bernard
Keyword(s):  
Parietal Lobe ◽  
Rule Learning ◽  
Learning Task ◽  
Anterior Cingulate ◽  
Visual Interpretation ◽  
Aging Research ◽  
Response To Instruction ◽  
Prefrontal Cortical ◽  
Age Related ◽  
Increased Activity

ABSTRACTTo date most aging research has focused on cortical systems and networks, ignoring the cerebellum which has been implicated in both cognitive and motor function. Critically, older adults (OA) show marked differences in cerebellar volume and functional networks, suggesting it may play a key role in the behavioral differences observed in advanced age. OA may be less able to recruit cerebellar resources due to network and structural differences. Here, 26 young adults (YA) and 25 OA performed a second-order learning task, known to activate the cerebellum in the fMRI environment. Behavioral results indicated that YA performed significantly better and learned more quickly compared to OA. Functional imaging detailed robust parietal and cerebellar activity during learning (compared to control) blocks within each group. OA showed increased activity (relative to YA) in the left inferior parietal lobe in response to instruction cues during learning (compared to control); whereas, YA showed increased activity (relative to OA) in the left anterior cingulate to feedback cues during learning, potentially explaining age-related performance differences. Visual interpretation of effect size maps showed more bilateral posterior cerebellar activation in OA compared to YA during learning blocks, but early learning showed widespread cerebellar activation in YA compared to OA. There were qualitatively large age-related differences in cerebellar recruitment in terms of effect sizes, yet no statistical difference. These findings serve to further elucidate age-related differences and similarities in cerebellar and cortical brain function and implicate the cerebellum and its networks as regions of interest in aging research.

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