ArticleNeural computation2020
Efficient Position Decoding Methods Based on Fluorescence Calcium Imaging in the Mouse Hippocampus.
Article in Neural computation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network.Journal of neural engineering · 2024Article
- Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network.bioRxiv : the preprint server for biology · 2024Article
- FPGA-Based In-Vivo Calcium Image Decoding for Closed-Loop Feedback Applications.IEEE transactions on biomedical circuits and systems · 2023Article
- How our understanding of memory replay evolves.Journal of neurophysiology · 2023Review
- Article
- To deconvolve, or not to deconvolve: Inferences of neuronal activities using calcium imaging data.Journal of neuroscience methods · 2022Article
- Uncovering spatial representations from spatiotemporal patterns of rodent hippocampal field potentials.Cell reports methods · 2021Article
- Improving scalability in systems neuroscience.Neuron · 2021Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 3 countries.
Funding
Abstract
Large-scale fluorescence calcium imaging methods have become widely adopted for studies of long-term hippocampal and cortical neuronal dynamics. Pyramidal neurons of the rodent hippocampus show spatial tuning in freely foraging or head-fixed navigation tasks. Development of efficient neural decoding methods for reconstructing the animal's position in real or virtual environments can provide a fast readout of spatial representations in closed-loop neuroscience experiments. Here, we develop an efficient strategy to extract features from fluorescence calcium imaging traces and further decode the animal's position. We validate our spike inference-free decoding methods in multiple in vivo calcium imaging recordings of the mouse hippocampus based on both supervised and unsupervised decoding analyses. We systematically investigate the decoding performance of our proposed methods with respect to the number of neurons, imaging frame rate, and signal-to-noise ratio. Our proposed supervised decoding analysis is ultrafast and robust, and thereby appealing for real-time position decoding applications based on calcium imaging.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.