Imaging the large-scale and cellular response to focal traumatic brain injury in mouse neocortex.

Traumatic brain injury (TBI) affects neural function at the local injury site and also at distant, connected brain areas. However, the real-time neural dynamics in response to injury and subsequent effects on sensory processing and behaviour are not fully resolved, especially across a range of spatial scales. We used in vivo calcium imaging in awake, head-restrained male and female mice to measure large-scale and cellular resolution neuronal activation, respectively, in response to a mild/moderate TBI induced by focal controlled cortical impact (CCI) injury of the motor cortex (M1).

Imaging the large-scale and cellular response to focal traumatic brain injury in mouse neocortex.

Traumatic brain injury (TBI) affects neural function at the local injury site and also at distant, connected brain areas. However, the real-time neural dynamics in response to injury and subsequent effects on sensory processing and behavior are not fully resolved, especially across a range of spatial scales. We used calcium imaging in awake, head-restrained male and female mice to measure large-scale and cellular resolution neuronal activation, respectively, in response to a mild/moderate TBI induced by focal controlled cortical impact (CCI) injury of the motor cortex (M1).

Identifying mild traumatic brain injury using measures of frequency-specified networks.

. Early diagnosis of mild traumatic brain injury (mTBI) is challenging, yet crucial for providing patients with timely treatments and minimizing the risks of developing injury-related disorders. To tackle this problem, this paper presents a framework based on measures of frequency-specified brain functional networks identifying mTBI.

A Variational Encoder Framework for Decoding Behavior Choices from Neural Data.

In this paper, using an adversarial variational encoder model, we propose a two-step data-driven approach to extract cross-subject feature representations from neural activity in order to decode subjects' behavior choices. First, various characteristics of the recorded behavior are computed and passed as features to a clustering model in order to categorize different behavior choices in each trial and create labels for the data. Then, we utilize a variational encoder to learn the latent space mappings from neural activity.

Detection of Mild Traumatic Brain Injury via Topological Graph Embedding and 2D Convolutional Neural Networks.

Early diagnosis of mild traumatic brain injury (mTBI) is challenging, yet significantly important in order to grant the patients with timely treatment and mitigating the risks of possible long-term psychiatric and neurological disorders. To tackle this problem, in this paper, we develop an mTBI detection framework based on graph embedding features combined with convolutional neural networks (CNN). Cortical activity in transgenic calcium reporter mice expressing Thy1-GCaMP6s is recorded in two sessions, prior to and after inducing injury.

Quantifying Changes in Brain Function Following Injury via Network Measures.

Widefield optical imaging enables longitudinal capturing of the large-scale network activity of the cerebral cortex in awake behaving animals. Utilizing this technique, we investigate how the brain's functional network structure is altered following injury. Cortical activity in transgenic calcium reporter mice expressing GCaMP6s is recorded in two sessions, prior and after inducing the injury.