NEATmap: a high-efficiency deep learning approach for whole mouse brain neuronal activity trace mapping.
Natl Sci Rev
; 11(5): nwae109, 2024 May.
Article
en En
| MEDLINE
| ID: mdl-38831937
ABSTRACT
Quantitative analysis of activated neurons in mouse brains by a specific stimulation is usually a primary step to locate the responsive neurons throughout the brain. However, it is challenging to comprehensively and consistently analyze the neuronal activity trace in whole brains of a large cohort of mice from many terabytes of volumetric imaging data. Here, we introduce NEATmap, a deep learning-based high-efficiency, high-precision and user-friendly software for whole-brain neuronal activity trace mapping by automated segmentation and quantitative analysis of immunofluorescence labeled c-Fos+ neurons. We applied NEATmap to study the brain-wide differentiated neuronal activation in response to physical and psychological stressors in cohorts of mice.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Natl Sci Rev
Año:
2024
Tipo del documento:
Article
País de afiliación:
China