Erick J. Paul

Architecture of fluid intelligence and working memory revealed by lesion mapping

Although cognitive neuroscience has made valuable progress in understanding the role of the prefrontal cortex in human intelligence, the functional networks that support adaptive behavior and novel problem solving remain to be well characterized. Here, we studied 158 human brain lesion patients to investigate the cognitive and neural foundations of key competencies for fluid intelligence and working memory. We administered a battery of neuropsychological tests, including the Wechsler Adult Intelligence Scale (WAIS) and the N-Back task. Latent variable modeling was applied to obtain error-free scores of fluid intelligence and working memory, followed by voxel-based lesion-symptom mapping to elucidate their neural substrates. The observed latent variable modeling and lesion results support an integrative framework for understanding the architecture of fluid intelligence and working memory and make specific recommendations for the interpretation and application of the WAIS and N-Back task to the study of fluid intelligence in health and disease.

Preservation of general intelligence following traumatic brain injury: contributions of the Met66 brain-derived neurotrophic factor.

Brain-derived neurotrophic factor (BDNF) promotes survival and synaptic plasticity in the human brain. The Val66Met polymorphism of the BDNF gene interferes with intracellular trafficking, packaging, and regulated secretion of this neurotrophin. The human prefrontal cortex (PFC) shows lifelong neuroplastic adaption implicating the Val66Met BDNF polymorphism in the recovery of higher-order executive functions after traumatic brain injury (TBI). In this study, we examined the effect of this BDNF polymorphism on the preservation of general intelligence following TBI. We genotyped a sample of male Vietnam combat veterans (n = 156) consisting of a frontal lobe lesion group with focal penetrating head injuries for the Val66Met BDNF polymorphism. Val/Met did not differ from Val/Val genotypes in general cognitive ability before TBI. However, we found substantial average differences between these groups in general intelligence (≈ half a standard deviation or 8 IQ points), verbal comprehension (6 IQ points), perceptual organization (6 IQ points), working memory (8 IQ points), and processing speed (8 IQ points) after TBI. These results support the conclusion that Val/Met genotypes preserve general cognitive functioning, whereas Val/Val genotypes are largely susceptible to TBI.

A neurocomputational account of cognitive deficits in Parkinson's disease.

Parkinsons disease (PD) is caused by the accelerated death of dopamine (DA) producing neurons. Numerous studies documenting cognitive deficits of PD patients have revealed impairments in a variety of tasks related to memory, learning, visuospatial skills, and attention. While there have been several studies documenting cognitive deficits of PD patients, very few computational models have been proposed. In this article, we use the COVIS model of category learning to simulate DA depletion and show that the model suffers from cognitive symptoms similar to those of human participants affected by PD. Specifically, DA depletion in COVIS produced deficits in rule-based categorization, non-linear information-integration categorization, probabilistic classification, rule maintenance, and rule switching. These were observed by simulating results from younger controls, older controls, PD patients, and severe PD patients in five well-known tasks. Differential performance among the different age groups and clinical populations was modeled simply by changing the amount of DA available in the model. This suggests that COVIS may not only be an adequate model of the simulated tasks and phenomena but also more generally of the role of DA in these tasks and phenomena.

Lesion mapping of social problem solving

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease.

Simulating category learning and set shifting deficits in patients weight-restored from anorexia nervosa.

OBJECTIVE To examine set shifting in a group of women previously diagnosed with anorexia nervosa who are now weight-restored (AN-WR) and then apply a biologically based computational model (Competition between Verbal and Implicit Systems [COVIS]) to simulate the pattern of category learning and set shifting performances observed. METHOD Nineteen AN-WR women and 35 control women (CW) were administered an explicit category learning task that required rule acquisition and then a set shift following a rule change. COVIS was first fit to the behavioral results of the controls and then parameters of the model theoretically relevant to AN were altered to mimic the behavioral results. RESULTS Relative to CW, the AN-WR group displayed steeper learning curves (i.e., hyper learning) before the rule shift, but greater difficulty in learning the new categories after the rule shift (i.e., a deficit in set shifting). Hyper learning and set shifting deficits in the AN-WR group were not associated and differentially correlated with clinical measures. Hyper learning in the AN-WR group was simulated by increasing the model parameter that represents sensitivity to negative feedback (δ parameter), whereas the deficit in set shifting was simulated by altering the parameters that represent changes in rule selection and flexibility (λ and γ parameters, respectively). CONCLUSIONS These simulations suggest that multiple factors can impact category learning and set shifting in AN-WR individuals (e.g., alterations in sensitivity to negative feedback, rule selection deficits, and inflexibility) and provide an important starting point to further investigate this pervasive deficit in adult AN.

Anterior cingulate cortex mediates the relationship between O3PUFAs and executive functions in APOE e4 carriers

Introduction: Although diet has a substantial influence on the aging brain, the relationship between biomarkers of diet and aspects of brain health remains unclear. This study examines the neural mechanisms that mediate the relationship between omega-3 polyunsaturated fatty acids (O3PUFAs) and executive functions in at-risk (APOE e4 carriers), cognitively intact older adults. We hypothesized that higher levels of O3PUFAs are associated with better performance in a particular component of the executive functions, namely cognitive flexibility, and that this relationship is mediated by gray matter volume of a specific region thought to be important for cognitive flexibility, the anterior cingulate cortex. Methods: We examined 40 cognitively intact adults between the ages of 65 and 75 with the APOE e4 polymorphism to investigate the relationship between biomarkers of O3PUFAs, tests of cognitive flexibility (measured by the Delis-Kaplan Executive Function System Trail Making Test), and gray matter volume within regions of the prefrontal cortex (PFC). Results: A mediation analysis revealed that gray matter volume within the left rostral anterior cingulate cortex partially mediates the relationship between O3PUFA biomarkers and cognitive flexibility. Conclusion: These results suggest that the anterior cingulate cortex acts as a mediator of the relationship between O3PUFAs and cognitive flexibility in cognitively intact adults thought to be at risk for cognitive decline. Through their link to executive functions and neuronal measures of PFC volume, O3PUFAs show potential as a nutritional therapy to prevent dysfunction in the aging brain.

A neurocomputational theory of how explicit learning bootstraps early procedural learning

It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative) system depending largely on the prefrontal cortex, and a procedural (non-declarative) system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categorization tasks. However, it remains unknown precisely how these systems interact to produce optimal learning and behavior. In order to investigate this issue, the present research evaluated the progression of learning through simulation of categorization tasks using COVIS, a well-known model of human category learning that includes both explicit and procedural learning systems. Specifically, the models parameter space was thoroughly explored in procedurally learned categorization tasks across a variety of conditions and architectures to identify plausible interaction architectures. The simulation results support the hypothesis that one-way interaction between the systems occurs such that the explicit system “bootstraps” learning early on in the procedural system. Thus, the procedural system initially learns a suboptimal strategy employed by the explicit system and later refines its strategy. This bootstrapping could be from cortical-striatal projections that originate in premotor or motor regions of cortex, or possibly by the explicit systems control of motor responses through basal ganglia-mediated loops

Parahippocampal Cortex Mediates the Relationship between Lutein and Crystallized Intelligence in Healthy, Older Adults

Introduction: Although, diet has a substantial influence on the aging brain, the relationship between dietary nutrients and aspects of brain health remains unclear. This study examines the neural mechanisms that mediate the relationship between a carotenoid important for brain health across the lifespan, lutein, and crystallized intelligence in cognitively intact older adults. We hypothesized that higher serum levels of lutein are associated with better performance on a task of crystallized intelligence, and that this relationship is mediated by gray matter structure of regions within the temporal cortex. This investigation aims to contribute to a growing line of evidence, which suggests that particular nutrients may slow or prevent aspects of cognitive decline by targeting specific features of brain aging. Methods: We examined 76 cognitively intact adults between the ages of 65 and 75 to investigate the relationship between serum lutein, tests of crystallized intelligence (measured by the Wechsler Abbreviated Scale of Intelligence), and gray matter volume of regions within the temporal cortex. A three-step mediation analysis was implemented using multivariate linear regressions to control for age, sex, education, income, depression status, and body mass index. Results: The mediation analysis revealed that gray matter thickness of one region within the temporal cortex, the right parahippocampal cortex (Brodmanns Area 34), partially mediates the relationship between serum lutein and crystallized intelligence. Conclusion: These results suggest that the parahippocampal cortex acts as a mediator of the relationship between serum lutein and crystallized intelligence in cognitively intact older adults. Prior findings substantiate the individual relationships reported within the mediation, specifically the links between (i) serum lutein and temporal cortex structure, (ii) serum lutein and crystallized intelligence, and (iii) parahippocampal cortex structure and crystallized intelligence. This report demonstrates a novel structural mediation between lutein status and crystallized intelligence, and therefore provides further evidence that specific nutrients may slow or prevent features of cognitive decline by hindering particular aspects of brain aging. Future work should examine the potential mechanisms underlying this mediation, including the antioxidant, anti-inflammatory, and membrane modulating properties of lutein.

Information–integration category learning and the human uncertainty response

The human response to uncertainty has been well studied in tasks requiring attention and declarative memory systems. However, uncertainty monitoring and control have not been studied in multi-dimensional, information-integration categorization tasks that rely on non-declarative procedural memory. Three experiments are described that investigated the human uncertainty response in such tasks. Experiment 1 showed that following standard categorization training, uncertainty responding was similar in information-integration tasks and rule-based tasks requiring declarative memory. In Experiment 2, however, uncertainty responding in untrained information-integration tasks impaired the ability of many participants to master those tasks. Finally, Experiment 3 showed that the deficit observed in Experiment 2 was not because of the uncertainty response option per se, but rather because the uncertainty response provided participants a mechanism via which to eliminate stimuli that were inconsistent with a simple declarative response strategy. These results are considered in the light of recent models of category learning and metacognition.

Lesion Mapping the Four-Factor Structure of Emotional Intelligence

Emotional intelligence (EI) refers to an individual’s ability to process and respond to emotions, including recognizing the expression of emotions in others, using emotions to enhance thought and decision making, and regulating emotions to drive effective behaviors. Despite their importance for goal-directed social behavior, little is known about the neural mechanisms underlying specific facets of EI. Here, we report findings from a study investigating the neural bases of these specific components for EI in a sample of 130 combat veterans with penetrating traumatic brain injury. We examined the neural mechanisms underlying experiential (perceiving and using emotional information) and strategic (understanding and managing emotions) facets of EI. Factor scores were submitted to voxel-based lesion symptom mapping to elucidate their neural substrates. The results indicate that two facets of EI (perceiving and managing emotions) engage common and distinctive neural systems, with shared dependence on the social knowledge network, and selective engagement of the orbitofrontal and parietal cortex for strategic aspects of emotional information processing. The observed pattern of findings suggests that sub-facets of experiential and strategic EI can be characterized as separable but related processes that depend upon a core network of brain structures within frontal, temporal and parietal cortex.