Limits...
Dissociation of category-learning systems via brain potentials.

Morrison RG, Reber PJ, Bharani KL, Paller KA - Front Hum Neurosci (2015)

Bottom Line: Categorization accuracy was similar for the two distributions.Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the RB, but not the II condition.These results provide additional evidence for distinct brain mechanisms supporting RB vs. implicit II category learning and use.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Neuroscience Institute, Loyola University Chicago Chicago, IL, USA.

ABSTRACT
Behavioral, neuropsychological, and neuroimaging evidence has suggested that categories can often be learned via either an explicit rule-based (RB) mechanism critically dependent on medial temporal and prefrontal brain regions, or via an implicit information-integration (II) mechanism relying on the basal ganglia. In this study, participants viewed sine-wave gratings (Gabor patches) that varied on two dimensions and learned to categorize them via trial-by-trial feedback. Two different stimulus distributions were used; one was intended to encourage an explicit RB process and the other an implicit II process. We monitored brain activity with scalp electroencephalography (EEG) while each participant: (1) passively observed stimuli represented of both distributions; (2) categorized stimuli from one distribution, and, 1 week later; (3) categorized stimuli from the other distribution. Categorization accuracy was similar for the two distributions. Subtractions of Event-Related Potentials (ERPs) for correct and incorrect trials were used to identify neural differences in RB and II categorization processes. We identified an occipital brain potential that was differentially modulated by categorization condition accuracy at an early latency (150-250 ms), likely reflecting the degree of holistic processing. A stimulus-locked Late Positive Complex (LPC) associated with explicit memory updating was modulated by accuracy in the RB, but not the II task. Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the RB, but not the II condition. These results provide additional evidence for distinct brain mechanisms supporting RB vs. implicit II category learning and use.

No MeSH data available.


(A) II distribution used in the experiment. (B) II distribution category responses from a participant whose responses were best fit by a RB decision-bound theory (DBT) model and who was excluded from further analysis. (C) II distribution category responses from a participant whose responses were best fit by an II DBT model and who was kept for further analysis.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4493768&req=5

Figure 4: (A) II distribution used in the experiment. (B) II distribution category responses from a participant whose responses were best fit by a RB decision-bound theory (DBT) model and who was excluded from further analysis. (C) II distribution category responses from a participant whose responses were best fit by an II DBT model and who was kept for further analysis.

Mentions: All 28 participants exhibited an RB distribution response best fit by an RB-F DBT model. For II, only 15 participants comprised the Model-Conforming Group because they exhibited an II distribution response profile best fit by an II DBT model. In contrast, 13 participants comprised the Model-Nonconforming Group because they exhibited an II distribution response profile best fit by an RB-F or RB-O DBT model (see Figure 4 for distribution profiles from representative participants). Likewise, when the fits for these two groups were compared directly, the first group of participants exhibited better II model fits than did the second (t (26) = 2.7, p = 0.01). However, these two groups did not differ in the quality of their RB model fits with the RD distribution (t (26) = 0.02, ns). DBT model fitting thus allowed data from participants who were likely using a unidimensional RB strategy with the II category distributions to be excluded from subsequent analyses.


Dissociation of category-learning systems via brain potentials.

Morrison RG, Reber PJ, Bharani KL, Paller KA - Front Hum Neurosci (2015)

(A) II distribution used in the experiment. (B) II distribution category responses from a participant whose responses were best fit by a RB decision-bound theory (DBT) model and who was excluded from further analysis. (C) II distribution category responses from a participant whose responses were best fit by an II DBT model and who was kept for further analysis.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493768&req=5

Figure 4: (A) II distribution used in the experiment. (B) II distribution category responses from a participant whose responses were best fit by a RB decision-bound theory (DBT) model and who was excluded from further analysis. (C) II distribution category responses from a participant whose responses were best fit by an II DBT model and who was kept for further analysis.
Mentions: All 28 participants exhibited an RB distribution response best fit by an RB-F DBT model. For II, only 15 participants comprised the Model-Conforming Group because they exhibited an II distribution response profile best fit by an II DBT model. In contrast, 13 participants comprised the Model-Nonconforming Group because they exhibited an II distribution response profile best fit by an RB-F or RB-O DBT model (see Figure 4 for distribution profiles from representative participants). Likewise, when the fits for these two groups were compared directly, the first group of participants exhibited better II model fits than did the second (t (26) = 2.7, p = 0.01). However, these two groups did not differ in the quality of their RB model fits with the RD distribution (t (26) = 0.02, ns). DBT model fitting thus allowed data from participants who were likely using a unidimensional RB strategy with the II category distributions to be excluded from subsequent analyses.

Bottom Line: Categorization accuracy was similar for the two distributions.Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the RB, but not the II condition.These results provide additional evidence for distinct brain mechanisms supporting RB vs. implicit II category learning and use.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Neuroscience Institute, Loyola University Chicago Chicago, IL, USA.

ABSTRACT
Behavioral, neuropsychological, and neuroimaging evidence has suggested that categories can often be learned via either an explicit rule-based (RB) mechanism critically dependent on medial temporal and prefrontal brain regions, or via an implicit information-integration (II) mechanism relying on the basal ganglia. In this study, participants viewed sine-wave gratings (Gabor patches) that varied on two dimensions and learned to categorize them via trial-by-trial feedback. Two different stimulus distributions were used; one was intended to encourage an explicit RB process and the other an implicit II process. We monitored brain activity with scalp electroencephalography (EEG) while each participant: (1) passively observed stimuli represented of both distributions; (2) categorized stimuli from one distribution, and, 1 week later; (3) categorized stimuli from the other distribution. Categorization accuracy was similar for the two distributions. Subtractions of Event-Related Potentials (ERPs) for correct and incorrect trials were used to identify neural differences in RB and II categorization processes. We identified an occipital brain potential that was differentially modulated by categorization condition accuracy at an early latency (150-250 ms), likely reflecting the degree of holistic processing. A stimulus-locked Late Positive Complex (LPC) associated with explicit memory updating was modulated by accuracy in the RB, but not the II task. Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the RB, but not the II condition. These results provide additional evidence for distinct brain mechanisms supporting RB vs. implicit II category learning and use.

No MeSH data available.