James N. Lee

Bio: James N. Lee is an academic researcher from University of Utah. The author has contributed to research in topics: Functional magnetic resonance imaging & Tensor. The author has an hindex of 21, co-authored 37 publications receiving 2471 citations. Previous affiliations of James N. Lee include United States Department of Veterans Affairs & Veterans Health Administration.

Putamen coactivation during motor task execution.

Abstract: Models of corticostriatal motor circuitry have focused on the role of the circuit in the hemisphere of the motor cortex providing primary control (contralateral to the movement). We used functional magnetic resonance imaging and functional connectivity analyses to study circuit function in both the controlling and noncontrolling hemispheres. During the completion of a unilateral motor task with either hand, each putamen nucleus demonstrated strong coactivation with structures in both hemispheres. The putamen in the noncontrolling hemisphere (ipsilateral to the movement) coactivated more strongly with the controlling motor cortex than with the noncontrolling cortex. These findings suggest that the two corticostriatal circuits are functionally integrated. New circuit models based on functional connectivity may need to be developed.

Striatal and cortical midline circuits in major depression: implications for suicide and symptom expression.

Abstract: Background In major depression, the neural mechanisms underlying suicide related thoughts and behaviors as well as the expression of other depressive symptoms are incompletely characterized. Evidence indicates that both the striatum and cortical midline structures (CMS) may be involved with both suicide and emotional dysregulation in unipolar illness. The aim of this study was to identify striatal–CMS circuits associated with current depression severity and suicidal ideation (SI) as well as a history of self-harm. Methods Twenty-two male subjects with recurrent unipolar depression were studied using functional MRI. All subjects were unmedicated and without current psychiatric comorbidity. Correlational analyses were used to determine whether striatal–CMS functional connectivity was associated with any of the three clinical variables. Results A network involving the bilateral striatum and anterior CMS was found to be associated with depressive symptom severity. Current SI was associated with a similar but less extensive circuit in the left hemisphere. A distinct striatal motor/sensory network was associated with self-harm behaviors, but not current SI or depression severity. Conclusions The striatal–anterior CMS circuit likely plays a significant role in the expression of depressive symptoms and SI. In contrast, a striatum–motor/sensory cortex network may be a trait marker of suicide-related behaviors. If replicated, this result might eventually lead to the development of a biomarker that would be useful for studies of pharmacologic and/or psychotherapeutic suicide prevention interventions.

Where Is the Semantic System? A Critical Review and Meta-Analysis of 120 Functional Neuroimaging Studies

Abstract: Semantic memory refers to knowledge about people, objects, actions, relations, self, and culture acquired through experience. The neural systems that store and retrieve this information have been studied for many years, but a consensus regarding their identity has not been reached. Using strict inclusion criteria, we analyzed 120 functional neuroimaging studies focusing on semantic processing. Reliable areas of activation in these studies were identified using the activation likelihood estimate (ALE) technique. These activations formed a distinct, left-lateralized network comprised of 7 regions: posterior inferior parietal lobe, middle temporal gyrus, fusiform and parahippocampal gyri, dorsomedial prefrontal cortex, inferior frontal gyrus, ventromedial prefrontal cortex, and posterior cingulate gyrus. Secondary analyses showed specific subregions of this network associated with knowledge of actions, manipulable artifacts, abstract concepts, and concrete concepts. The cortical regions involved in semantic processing can be grouped into 3 broad categories: posterior multimodal and heteromodal association cortex, heteromodal prefrontal cortex, and medial limbic regions. The expansion of these regions in the human relative to the nonhuman primate brain may explain uniquely human capacities to use language productively, plan, solve problems, and create cultural and technological artifacts, all of which depend on the fluid and efficient retrieval and manipulation of semantic knowledge.

Functional and effective connectivity: a review.

Abstract: Over the past 20 years, neuroimaging has become a predominant technique in systems neuroscience. One might envisage that over the next 20 years the neuroimaging of distributed processing and connectivity will play a major role in disclosing the brain's functional architecture and operational principles. The inception of this journal has been foreshadowed by an ever-increasing number of publications on functional connectivity, causal modeling, connectomics, and multivariate analyses of distributed patterns of brain responses. I accepted the invitation to write this review with great pleasure and hope to celebrate and critique the achievements to date, while addressing the challenges ahead.

DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

Abstract: Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.

The Representation of Object Concepts in the Brain

Abstract: Evidence from functional neuroimaging of the human brain indicates that information about salient properties of an object—such as what it looks like, how it moves, and how it is used—is stored in sensory and motor systems active when that information was acquired. As a result, object concepts belonging to different categories like animals and tools are represented in partially distinct, sensory- and motor property–based neural networks. This suggests that object concepts are not explicitly represented, but rather emerge from weighted activity within property-based brain regions. However, some property-based regions seem to show a categorical organization, thus providing evidence consistent with category-based, domain-specific formulations as well.

Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity.

Abstract: Importance Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. Objective To investigate network dysfunction in MDD through a meta-analysis of rsFC studies. Data Sources Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data. Study Selection Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis. Data Extraction and Synthesis Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network. Results Major depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions. Conclusions and Relevance Reduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.