Voxel scale complex networks of functional connectivity in the rat brain: neurochemical state dependence of global and local topological properties

Top-Down Network Effective Connectivity in Abstinent Substance Dependent Individuals

Objective

We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls.

Methods

50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI. fMRI results were analyzed using group independent component analysis; 14 networks-of-interest (NOI) were selected using template matching to a canonical set of resting state networks. The number, direction, and strength of connections between NOI were analyzed with Granger Causality. Within-group thresholds were p<0.005 using a bootstrap permutation. Between group thresholds were p<0.05, FDR-corrected for multiple comparisons. NOI were correlated with behavioral measures, and group-level graph theory measures were compared.

Results

Compared to controls, SDI showed significantly greater Granger causal connectivity from right executive control network (RECN) to dorsal default mode network (dDMN) and from dDMN to basal ganglia network (BGN). RECN was negatively correlated with impulsivity, behavioral approach, and negative affect; dDMN was positively correlated with impulsivity. Among the 14 NOI, SDI showed greater bidirectional connectivity; controls showed more unidirectional connectivity. SDI demonstrated greater global efficiency and lower local efficiency.

Conclusions

Increased effective connectivity in long-term abstinent drug users may reflect improved cognitive control over habit and reward processes. Higher global and lower local efficiency across all networks in SDI compared to controls may reflect connectivity changes associated with drug dependence or remission and requires future, longitudinal studies to confirm.

Local Patterns to Global Architectures: Influences of Network Topology on Human Learning

A core question in cognitive science concerns how humans acquire and represent knowledge about their environments. To this end, quantitative theories of learning processes have been formalized in an attempt to explain and predict changes in brain and behavior. We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties. We focus on innovative work that describes how learning is influenced by the topological properties underlying sensory input. The confluence of these theoretical approaches and this recent empirical evidence motivate the importance of scaling-up quantitative approaches to learning at both the behavioral and neural levels.

Considerations for resting state functional MRI and functional connectivity studies in rodents

Resting state functional MRI (rs-fMRI) and functional connectivity mapping have become widely used tools in the human neuroimaging community and their use is rapidly spreading into the realm of rodent research as well. One of the many attractive features of rs-fMRI is that it is readily translatable from humans to animals and back again. Changes in functional connectivity observed in human studies can be followed by more invasive animal experiments to determine the neurophysiological basis for the alterations, while exploratory work in animal models can identify possible biomarkers for further investigation in human studies. These types of interwoven human and animal experiments have a potentially large impact on neuroscience and clinical practice. However, impediments exist to the optimal application of rs-fMRI in small animals, some similar to those encountered in humans and some quite different. In this review we identify the most prominent of these barriers, discuss differences between rs-fMRI in rodents and in humans, highlight best practices for animal studies, and review selected applications of rs-fMRI in rodents. Our goal is to facilitate the integration of human and animal work to the benefit of both fields.

Neuromapping techniques in drug discovery: pharmacological MRI for the assessment of novel antipsychotics

INTRODUCTION

Treatment of psychiatric and neurological diseases represents a substantial unmet medical need, but the development of novel, effective and safe drugs is proving difficult. While substantial improvement over existing pharmacological agents is expected from new molecular targets emerging in the genomic era, the validation and exploitation of novel mechanisms of action is a lengthy and costly process. The use of neuroimaging techniques, and more specifically of functional and pharmacological magnetic resonance imaging (MRI), has been advocated as a powerful approach to this problem, providing translational biomarkers for the objective assessment of drug activity on brain function, and possibly surrogate markers of clinical response.

AREAS COVERED

The authors review the recent application of functional and pharmacological MRI (phMRI) in the study of novel treatments of psychosis based on glutamatergic mechanisms. Furthermore, they review contribution of functional imaging in the target validation and early assessment of drugs exploiting glutamatergic mechanisms as an example of potentially impactful exploitation of neuroimaging methods in drug discovery.

EXPERT OPINION

While functional neuroimaging methods may provide useful markers of drug activity and response to treatment, their translational potential, that is, their use to bridge animal and human investigations is seldom exploited. The application of phMRI in the study of novel antipsychotics based on glutamatergic mechanisms represents an example of functional neuroimaging as a powerful means to link preclinical and clinical research, thus providing a paradigm that may help expedite progression into the clinical phase of novel mechanisms for the treatment of psychiatric and neurological diseases.