title: Neural networks supporting switching, hypothesis testing, and rule application.
abstract: We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example "choose the blue letter". Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest learning speed late in the time course of learning. As subjects shifted from hypothesis testing to rule application, activity in this network decreased and activity in the somatomotor and default mode networks increased.
authors.affiliation: South China Normal University, School of Psychology, Center for Studies of Psychological Application, Guangzhou, China. Electronic address: zhiyaliu@scnu.edu.cn.
authors.forename: Zhiya
authors.initials: Z
authors.lastname: Liu
authors.affiliation: Colorado State University, Department of Psychology, Colorado, United States; Colorado State University, Molecular, Cellular and Integrative Neurosciences Program, Colorado, United States.
authors.forename: Kurt
authors.initials: K
authors.lastname: Braunlich
authors.affiliation: Colorado State University, Department of Psychology, Colorado, United States; Colorado State University, Molecular, Cellular and Integrative Neurosciences Program, Colorado, United States.
authors.forename: Hillary S
authors.initials: HS
authors.lastname: Wehe
authors.affiliation: South China Normal University, School of Psychology, Center for Studies of Psychological Application, Guangzhou, China; Colorado State University, Department of Psychology, Colorado, United States; Colorado State University, Molecular, Cellular and Integrative Neurosciences Program, Colorado, United States. Electronic address: Carol.Seger@colostate.edu.
authors.forename: Carol A
authors.initials: CA
authors.lastname: Seger
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D030141:Feedback, Psychological / Q000502:physiology; D005260:Female; D006801:Humans; D007858:Learning / Q000502:physiology*; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D015999:Multivariate Analysis; D009434:Neural Pathways / Q000502:physiology; D009483:Neuropsychological Tests; D025341:Principal Component Analysis; D055815:Young Adult
keywords: Cognitive control network; Functional connectivity; Functional networks; Hypothesis testing; Reversal learning; Salience network; Shifting; Ventral striatum