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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.A stimulus-locked Late Positive Complex (LPC) associated with explicit memory updating was modulated by accuracy in the RB, but not the II task.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.


Related in: MedlinePlus

Schematic of a single trial. A fixation cross was followed by the to-be-categorized-stimulus for a fixed duration, followed by a short visual mask, followed by auditory feedback and a brief ISI before the next trial. The subject responded “category A” or “category B” during the 2 s the stimulus was on the screen by pressing one of two buttons on a hand-held response box. EEG was recorded continuously, and stimulus- and feedback-locked ERPs were calculated from each trial.
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Figure 2: Schematic of a single trial. A fixation cross was followed by the to-be-categorized-stimulus for a fixed duration, followed by a short visual mask, followed by auditory feedback and a brief ISI before the next trial. The subject responded “category A” or “category B” during the 2 s the stimulus was on the screen by pressing one of two buttons on a hand-held response box. EEG was recorded continuously, and stimulus- and feedback-locked ERPs were calculated from each trial.

Mentions: We used a visual category-learning paradigm (Maddox et al., 2003) in which subjects learned to categorize visual stimuli into two categories via feedback given at the conclusion of each trial. Stimuli were circular sine-wave gratings that varied in spatial frequency (number of lines per patch, also perceived as thickness of lines) and spatial orientation (tilt of lines). For the RB distribution, the stimuli were divided into two categories based on a vertical decision boundary such that category membership depended only on the spatial frequency of the sine-wave grating (Figure 1A). For the II group, the categories were defined by a diagonal decision boundary that required II of frequency and orientation information (Figure 1B). Trial timing was similar to that used by Nomura et al. (2007a) in their fMRI study (Figure 2).


Dissociation of category-learning systems via brain potentials.

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

Schematic of a single trial. A fixation cross was followed by the to-be-categorized-stimulus for a fixed duration, followed by a short visual mask, followed by auditory feedback and a brief ISI before the next trial. The subject responded “category A” or “category B” during the 2 s the stimulus was on the screen by pressing one of two buttons on a hand-held response box. EEG was recorded continuously, and stimulus- and feedback-locked ERPs were calculated from each trial.
© Copyright Policy
Related In: Results  -  Collection

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

Figure 2: Schematic of a single trial. A fixation cross was followed by the to-be-categorized-stimulus for a fixed duration, followed by a short visual mask, followed by auditory feedback and a brief ISI before the next trial. The subject responded “category A” or “category B” during the 2 s the stimulus was on the screen by pressing one of two buttons on a hand-held response box. EEG was recorded continuously, and stimulus- and feedback-locked ERPs were calculated from each trial.
Mentions: We used a visual category-learning paradigm (Maddox et al., 2003) in which subjects learned to categorize visual stimuli into two categories via feedback given at the conclusion of each trial. Stimuli were circular sine-wave gratings that varied in spatial frequency (number of lines per patch, also perceived as thickness of lines) and spatial orientation (tilt of lines). For the RB distribution, the stimuli were divided into two categories based on a vertical decision boundary such that category membership depended only on the spatial frequency of the sine-wave grating (Figure 1A). For the II group, the categories were defined by a diagonal decision boundary that required II of frequency and orientation information (Figure 1B). Trial timing was similar to that used by Nomura et al. (2007a) in their fMRI study (Figure 2).

Bottom Line: Categorization accuracy was similar for the two distributions.A stimulus-locked Late Positive Complex (LPC) associated with explicit memory updating was modulated by accuracy in the RB, but not the II task.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.


Related in: MedlinePlus