Dataset Information

Leveraging Optogenetic-Based Neurovascular Circuit Characterization for Repair.

ABSTRACT: Optogenetic techniques are a powerful tool for determining the role of individual functional components within complex neural circuits. By genetically targeting specific cell types, neural mechanisms can be actively manipulated to gain a better understanding of their origin and function, both in health and disease. The potential of optogenetics is not limited to answering biological questions, as it is also a promising therapeutic approach for neurological diseases. An important prerequisite for this approach is to have an identified target with a uniquely defined role within a given neural circuit. Here, we examine the retinal neurovascular unit, a circuit that incorporates neurons and vascular cells to control blood flow in the retina. We highlight the role of a specific cell type, the cholinergic amacrine cell, in modulating vascular cells, and demonstrate how this can be targeted and controlled with optogenetics. A better understanding of these mechanisms will not only extend our understanding of neurovascular interactions in the brain, but ultimately may also provide new targets to treat vision loss in a variety of retinal diseases.

SUBMITTER: Ivanova E

PROVIDER: S-EPMC4824015 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Leveraging Optogenetic-Based Neurovascular Circuit Characterization for Repair.

Ivanova Elena E Yee Christopher W CW Sagdullaev Botir T BT

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics 20160401 2

Optogenetic techniques are a powerful tool for determining the role of individual functional components within complex neural circuits. By genetically targeting specific cell types, neural mechanisms can be actively manipulated to gain a better understanding of their origin and function, both in health and disease. The potential of optogenetics is not limited to answering biological questions, as it is also a promising therapeutic approach for neurological diseases. An important prerequisite for ...[more]

PMID: 26758692

Similar Datasets

Project description:BACKGROUND:Previously, we identified four depression subtypes defined by distinct functional connectivity alterations in depression-related brain networks, which in turn predicted clinical symptoms and treatment response. Optogenetic functional magnetic resonance imaging offers a promising approach for testing how dysfunction in specific circuits gives rise to subtype-specific, depression-related behaviors. However, this approach assumes that there are robust, reproducible correlations between functional connectivity and depressive symptoms-an assumption that was not extensively tested in previous work. METHODS:First, we comprehensively reevaluated the stability of canonical correlations between functional connectivity and symptoms (N = 220 subjects) using optimized approaches for large-scale statistical hypothesis testing, and we validated methods for improving estimation of latent variables driving brain-behavior correlations. Having confirmed this necessary condition, we reviewed recent advances in optogenetic functional magnetic resonance imaging and illustrated one approach to formulating hypotheses regarding latent subtype-specific circuit mechanisms and testing them in animal models. RESULTS:Correlations between connectivity features and clinical symptoms were robustly significant, and canonical correlation analysis solutions tested repeatedly on held-out data generalized. However, they were sensitive to data quality, preprocessing, and clinical heterogeneity, which can reduce effect sizes. Generalization could be markedly improved by adding L2 regularization, which decreased estimator variance, increased canonical correlations in left-out data, and stabilized feature selection. These improvements were useful for identifying candidate circuits for optogenetic interrogation in animal models. CONCLUSIONS:Multiview, latent-variable approaches such as canonical correlation analysis offer a conceptually useful framework for discovering stable patient subtypes by synthesizing multiple clinical and functional measures. Optogenetic functional magnetic resonance imaging holds promise for testing hypotheses regarding latent, subtype-specific mechanisms driving depressive symptoms and behaviors.

Dataset Information

Leveraging Optogenetic-Based Neurovascular Circuit Characterization for Repair.

Publications

Leveraging Optogenetic-Based Neurovascular Circuit Characterization for Repair.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure