Publications by authors named "Carol Seger"

Category learning is usually better supported by interleaved training (alternating between exemplars from different categories) than by blocked training (studying all exemplars within a category sequentially), yet when asked to choose between the two strategies most people endorse blocking as superior. We used a prototype category-learning task to examine the effects of between- and within-category similarity and knowledge of the number of stimuli to be studied on study sequencing choices during self-regulated learning. Across three experiments (including a complete replication), participants who viewed the number of stimuli in each category showed more interleaving in comparison with those who did not, indicating that participants adjusted their strategy based on the projected length of the study phase.

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Article Synopsis
  • The study investigates how neural representations involved in learning categories evolve as individuals gain experience through a prototype learning task.
  • It finds that while activity in brain regions tied to habitual learning remains stable, regions related to goal-directed learning decrease in activation over time, indicating a shift in processing.
  • Advanced training enhances the ability to decode category information in the intraparietal sulcus and develops category representations in the motor cortex and ventromedial prefrontal cortex, reflecting improved decision-making and memory for category structures.
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  • Children and adults engage in different learning strategies with feedback-based and observational training when categorizing new information.
  • Adults excel in feedback training for rule-based tasks, while children show no significant difference in performance between training types.
  • The study's results highlight that children can effectively learn through observational methods, suggesting educational interventions should be tailored to their strengths.
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  • Theories of category learning have mainly examined how category structures influence what learners grasp, with less focus on other factors affecting their learned representations.
  • A new "5/5" categorization task was developed to clarify previous ambiguities in the "5/4" task, and various methods, including computational modeling, were used to determine if participants relied on exemplar or prototype representations.
  • Results indicated that learners predominantly used prototypes for categorization, with a noticeable shift over time towards increased reliance on prototype representations and decreased reliance on exemplars.
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  • The study examined how people use feedback during categorization tasks, specifically focusing on conditions where participants earn or lose points based on their answers.
  • The researchers found that the tail of the caudate, a brain region, showed the most activity when participants experienced both gains and losses, suggesting a heightened sensitivity to feedback type.
  • Additionally, brain activity varied based on the difficulty of the task, with higher activity for stimuli near the decision boundary that yielded more points, indicating that both reward and loss influence decision-making in categorization.
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In a dynamic environment, expectations of the future constantly change based on updated evidence and affect the dynamic allocation of attention. To further investigate the neural mechanisms underlying attentional expectancies, we employed a modified Central Cue Posner Paradigm in which the probability of cues being valid (that is, accurately indicated the upcoming target location) was manipulated. Attentional deployment to the cued location (α), which was governed by precision of predictions on previous trials, was estimated using a hierarchical Bayesian model and was included as a regressor in the analyses of electrophysiological (EEG) data.

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Higher executive control capacity allows people to appropriately evaluate risk and avoid both excessive risk aversion and excessive risk-taking. The neural mechanisms underlying this relationship between executive function and risk taking are still unknown. We used voxel-based morphometry (VBM) analysis combined with resting-state functional connectivity (rs-FC) to evaluate how one component of executive function, model-based learning, relates to risk taking.

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Global effects of feature-based attention (FBA) are generally limited to stimuli sharing the same or similar features, as hypothesized in the "feature-similarity gain model." Visual perception, however, often reflects categories acquired via experience/learning; whether the global-FBA effect can be induced by the categorized features remains unclear. Here, human subjects were trained to classify motion directions into two discrete categories and perform a classical motion-based attention task.

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Background: Obsessive-compulsive disorder (OCD) is a classic disorder on the compulsivity spectrum, with diverse comorbidities. In the current study, we sought to understand OCD from a dimensional perspective by identifying multimodal neuroimaging patterns correlated with multiple phenotypic characteristics within the striatum-based circuits known to be affected by OCD.

Methods: Neuroimaging measurements of local functional and structural features and clinical information were collected from 110 subjects, including 51 patients with OCD and 59 healthy control subjects.

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Introduction: Obsessive-compulsive disorder (OCD) is characterized by an imbalance between goal-directed and habitual learning systems in behavioral control, but it is unclear whether these impairments are due to a single system abnormality of the goal-directed system or due to an impairment in a separate arbitration mechanism that selects which system controls behavior at each point in time.

Methods: A total of 30 OCD patients and 120 healthy controls performed a 2-choice, 3-stage Markov decision-making paradigm. Reinforcement learning models were used to estimate goal-directed learning (as model-based reinforcement learning) and habitual learning (as model-free reinforcement learning).

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Background: The relationship between cognitive function and psychopathological symptoms has been an important research field in recent years. Previous studies have typically applied case-control designs to explore differences in certain cognitive variables. Multivariate analyses are needed to deepen our understanding of the intercorrelations among cognitive and symptom phenotypes in OCD.

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  • The study investigated how the brain processes new information using two methods: applying general rules versus recognizing specific examples.
  • Participants learned a categorization task and then categorized new stimuli without feedback, using either rule-based or example-based methods.
  • Results showed that using rules activated a specific brain network linked to memory, while using examples involved different brain areas related to mapping stimuli and memory recall, supporting theories that categorize learning as a blend of these two strategies.
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Obsessive-compulsive disorder (OCD) is characterized by uncontrollable repetitive actions thought to rely on abnormalities within fundamental instrumental learning systems. We investigated cognitive and computational mechanisms underlying Pavlovian biases on instrumental behavior in both clinical OCD patients and healthy controls using a Pavlovian-Instrumental Transfer (PIT) task. PIT is typically evidenced by increased responding in the presence of a positive (previously rewarded) Pavlovian cue, and reduced responding in the presence of a negative cue.

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Procrastination is defined as putting off an intended course of action voluntarily despite the harmful consequences. Previous studies have suggested that procrastination is associated with punishment sensitivity in that high punishment sensitivity results in increased negative utility for task performance. We hypothesized the effects of punishment sensitivity on procrastination would be mediated by a network connecting the caudate nucleus and prefrontal cortex, both of which have been previously associated with self-control and emotional control during procrastination.

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Compulsion is one of core symptoms of obsessive-compulsive disorder (OCD). Although many studies have investigated the neural mechanism of compulsion, no study has used brain-based measures to predict compulsion. Here, we used connectome-based predictive modeling (CPM) to identify networks that could predict the levels of compulsion based on whole-brain functional connectivity in 57 OCD patients.

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Background: Bipolar disorder (BD) is a mental disorder with severe implications for those affected and their families. Previous studies detected brain structural and functional alterations in BD patients. However, very few studies conducted a multimodal MRI fusion analysis, and little is known about the role of common anomalies in the connectivity of BD.

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An imbalance between the goal-directed and habitual learning systems has been proposed to underlie compulsivity in obsessive-compulsive disorder (OCD). In addition, the overall balance between these systems may be influenced by stress hormones. We examined the multimodal networks underlying these dual learning systems.

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We utilized dynamic functional network connectivity (dFNC) analysis to compare participants with obsessive-compulsive disorder (OCD) with their unaffected first-degree relative (UFDR) and healthy controls (HC). Resting state fMRI was performed on 46 OCD, 24 UFDR, and 49 HCs, along with clinical assessments. dFNC analyses revealed two distinct connectivity states: a less frequent, integrated state characterized by the predominance of between-network connections (State I), and a more frequent, segregated state with strong within-network connections (State II).

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In the last decade, research has reported that items at the beginning of a memorized sequence are responded to faster with the left hand, whereas items at the end are responded to faster with the right hand. This Spatial-Positional Associations of Response Codes effect has been extensively studied using behavioral methods. However, the neural networks underlying it remain unclear.

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Article Synopsis
  • The study explores how feedback value and its framing (gains vs. losses) affect category learning, comparing rule-based (RB) and information-integration (II) categories.
  • In experiments with point-valued feedback, results showed that overall, participants learned better with feedback compared to a control group, but the effectiveness varied between the two learning types.
  • For II tasks, participants learned quickest with both gains and losses, highlighting reinforcement-based learning, while for RB tasks, performance was best with either gains or losses alone, suggesting the potential overload of processing conflicting feedback.
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Behavioral research has found that trait anxiety is associated with a lower propensity for risk-taking. However, the neural mechanisms underlying this relation are still unknown. To address this question, we employed voxel-based morphometry (VBM) analysis and resting-state functional connectivity (rs-FC) to examine the influence of trait anxiety on risk-taking.

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Humans are able to categorize things they encounter in the world (e.g., a cat) by integrating multisensory information from the auditory and visual modalities with ease and speed.

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We used voxel-based morphometry and resting-state functional magnetic resonance imaging (rs-fMRI) to investigate whether the regulatory mode orientation of assessment (the tendency of each individual to self-regulate by critically evaluating alternatives) interacts with neural systems underlying risk-taking. Across a sample of 112 participants, propensity for risk-taking (measured using the Wheel of Fortune task) was negatively correlated with assessment orientation, such that a greater tendency to critically evaluate alternatives was associated with a lower tendency for risk-taking. VBM revealed a negative correlation between assessment orientation and right inferior parietal lobe (RIPL) gray matter volume.

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Article Synopsis
  • The study investigated the role of working memory (WM) in category learning, specifically comparing interleaved and blocked presentation methods.
  • Results showed that interleaved presentations were more effective for learning regardless of whether participants were using their WM due to a dual task or had high WM capacity.
  • Participants often believed that blocked presentations were superior for learning, despite evidence that interleaving produced better performance, suggesting a disconnect between metacognitive beliefs and actual learning outcomes.
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