Decoding of in vivo two-photon imaging data in mouse motor cortex

• Applicant: Takashi Sato, Ph.D.
• Subject Area: Cognitive, Systems and Behavioural Neurobiology
• Term: from 2014 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 258000007

Purposeful movements are produced more effectively if preceded by preparation. This process of motor preparation is considered to be mediated, at least partially, by the motor cortex. Supporting this view is that the neurons in the motor cortex modulate discharge rate as animals prepare and execute movements. However, we do not know how circuits of neurons in the motor cortex operate to convert preparation into action. In the current proposal, we will investigate the neural activity of motor cortex in mice that prepare and execute forearm movements using in vivo two-photon calcium imaging. This method will allow us to image the activity of neural circuits in the motor cortex. To extract much information out of the rich imaging data, we will use machine learning based linear decoder. First, we will decode the imaging data to predict the reaction time and other movement related parameters. Through this process, the decoder identifies the neurons that encode the relevant information by determining the weight factors for each neuron. By examining the weight factors at different time-points during the preparatory and execution period, we will reveal the temporal dynamics of the neural representation of the motor preparation and movement commands. Second, we aim to uncover how the activity states of the circuits change moment by moment until the execution of the forearm movements. To reveal this dynamics of the activity state, we will train the decoder with the input variables as the imaging data of a particular frame, and predict the activity of a target neuron in the following frame. By determining the weight factors for each neuron, we will identify the neurons that contribute in predicting the activity of the target neuron. Through these projects, we will link the dynamic change of the neural circuit activity and the animal¿s behavior in a quantitative fashion, which will lead to the better understanding of the computational processes that underlie our actions.

• DFG Programme: Research Grants
• International Connection: Japan
• Participating Person: Professor Yukiyasu Kamitani, Ph.D.