2024/05/24 by Iuliia Dmitrieva, Dmitrieva, Iuliia, Sergey Babkin +3 · 1 voice
Biochemistry, Genetics and Molecular Biology · Engineering · Mathematics · Medicine · #Advanced MRI Techniques and Applications #Computation (stat.CO) #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Medical Imaging Techniques and Applications #Neurons and Cognition (q-bio.NC) #Quantitative Methods (q-bio.QM) #eess.IV #electronic engineering #information engineering #q-bio.NC #q-bio.QM #stat.CO
paper · pdf · doi:10.48550/arxiv.2405.15701
openalex publication_date 2024/05/24 · arxiv published 2024/05/24 · arxiv updated 2024/05/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Closed-loop neuroscience experimentation, where recorded neural activity is used to modify the experiment on-the-fly, is critical for deducing causal connections and optimizing experimental time. A critical step in creating a closed-loop experiment is real-time inference of neural activity from streaming recordings. One challenging modality for real-time processing is multi-photon calcium imaging (CI). CI enables the recording of activity in large populations of neurons however, often requires batch processing of the video data to extract single-neuron activity from the fluorescence videos. We use the recently proposed robust time-trace estimator-Sparse Emulation of Unused Dictionary Objects (SEUDO) algorithm-as a basis for a new on-line processing algorithm that simultaneously identifies neurons in the fluorescence video and infers their time traces in a way that is robust to as-yet unidentified neurons. To achieve real-time SEUDO (realSEUDO), we optimize the core estimator via both algorithmic improvements and an fast C-based implementation, and create a new cell finding loop to enable realSEUDO to also identify new cells. We demonstrate comparable performance to offline algorithms (e.g., CNMF), and improved performance over the current on-line approach (OnACID) at speeds of 120 Hz on average.