AUTOMATIC MARKUP OF NEURAL CELL MEMBRANES USING BOOSTED DECISION STUMPS

To better understand the central nervous system, neurobiologists need to reconstruct the underlying neural circuitry from electron microscopy images. One of the necessary tasks is to segment the individual neurons. For this purpose, we propose a supervised learning approach to detect the cell membranes. The classifier was trained using AdaBoost, on local and context features. The features were selected to highlight the line characteristics of cell membranes. It is shown that using features from context positions allows for more information to be utilized in the classification. Together with the nonlinear discrimination ability of the AdaBoost classifier, this results in clearly noticeable improvements over previously used methods. Index Terms — Serial-section TEM, cell membrane detection, AdaBoost, Segmentation, Machine Learning

Hippocampal brain-derived neurotrophic factor determines recruitment of anatomically connected networks after stress in diabetic mice

Diabetes increases adrenal steroids in humans and animal models, but potential interactions with psychological stress remain poorly understood. Diabetic rodents exhibit anxiety and reductions in hippocampal brain-derived neurotrophic factor (BDNF) expression, and these studies investigated whether loss of BDNF-driven hippocampal activity promotes anxiety and disinhibits the HPA axis. Mice with genetic obesity and diabetes (db/db) received intrahippocampal injections of lentivirus for BDNF overexpression (db/db-BDNFOE), and Wt mice received lentiviral constructs for BDNF knockdown (Wt-BDNFKD). Behavioral anxiety, and glucocorticoid responses to acute restraint were compared with mice that received a fluorescent reporter (Wt-GFP, db/db-GFP). These experiments revealed that changes in hippocampal BDNF were necessary and sufficient for behavioral anxiety and HPA axis disinhibition. To examine patterns of stress-induced regional activity, we used algorithmic detection of cFos and automated segmentation of forebrain regions to generate maps of functional covariance, which were subsequently aligned with anatomical connectivity weights from the Brain Architecture Management database. db/db-GFP mice exhibited reduced activation of the hippocampal ventral subiculum (vSub) and anterior bed nucleus of stria terminalis (aBNST), and increases in the paraventricular hypothalamus (PVH), relative to Wt-GFP. BDNFKD recapitulated this pattern in Wt mice, and BDNFOE normalized activation of the vSub>aBNST>PVH pathway in db/db mice. Analysis of forebrain activation revealed largely overlapping patterns of network disruption in db/db-GFP and Wt-BDNFKD mice, implicating BDNF-driven hippocampal activity as a determinant of stress vulnerability in both the intact and diabetic brain. This article is protected by copyright. All rights reserved

Distinct Cortical-Thalamic-Striatal Circuits through the Parafascicular Nucleus

The thalamic parafascicular nucleus (PF), an excitatory input to the basal ganglia, is targeted with deep-brain stimulation to alleviate a range of neuropsychiatric symptoms. Furthermore, PF lesions disrupt the execution of correct motor actions in uncertain environments. Nevertheless, the circuitry of the PF and its contribution to action selection are poorly understood. We find that, in mice, PF has the highest density of striatum-projecting neurons among all sub-cortical structures. This projection arises from transcriptionally and physiologically distinct classes of PF neurons that are also reciprocally connected with functionally distinct cortical regions, differentially innervate striatal neurons, and are not synaptically connected in PF. Thus, mouse PF contains heterogeneous neurons that are organized into parallel and independent associative, limbic, and somatosensory circuits. Furthermore, these subcircuits share motifs of cortical-PF-cortical and cortical-PF-striatum organization that allow each PF subregion, via its precise connectivity with cortex, to coordinate diverse inputs to striatum

Mapping Social Behavior-Induced Brain Activation at Cellular Resolution in the Mouse

Understanding how brain activation mediates behaviors is a central goal of systems neuroscience. Here, we apply an automated method for mapping brain activation in the mouse in order to probe how sex-specific social behaviors are represented in the male brain. Our method uses the immediate-early-gene c-fos, a marker of neuronal activation, visualized by serial two-photon tomography: the c-fos-GFP+ neurons are computationally detected, their distribution is registered to a reference brain and a brain atlas, and their numbers are analyzed by statistical tests. Our results reveal distinct and shared female and male interaction-evoked patterns of male brain activation representing sex discrimination and social recognition. We also identify brain regions whose degree of activity correlates to specific features of social behaviors and estimate the total numbers and the densities of activated neurons per brain areas. Our study opens the door to automated screening of behavior-evoked brain activation in the mouse.Howard Hughes Medical InstituteGatsby Charitable Foundatio

Mapping Social Behavior-Induced Brain Activation at Cellular Resolution in the Mouse

Summary Understanding how brain activation mediates behaviors is a central goal of systems neuroscience. Here, we apply an automated method for mapping brain activation in the mouse in order to probe how sex-specific social behaviors are represented in the male brain. Our method uses the immediate-early-gene c-fos, a marker of neuronal activation, visualized by serial two-photon tomography: the c-fos-GFP+ neurons are computationally detected, their distribution is registered to a reference brain and a brain atlas, and their numbers are analyzed by statistical tests. Our results reveal distinct and shared female and male interaction-evoked patterns of male brain activation representing sex discrimination and social recognition. We also identify brain regions whose degree of activity correlates to specific features of social behaviors and estimate the total numbers and the densities of activated neurons per brain areas. Our study opens the door to automated screening of behavior-evoked brain activation in the mouse