Decoding Cortical Brain States from Widefield Calcium Imaging Data Using Visibility Graph
Posted on 2018-06-07 - 16:21
Widefield optical imaging of neuronal populations over large portions of the cerebral cortex in awake behaving animals, provides a unique opportunity for investigating the relationship between brain function and behavior. In this paper,we demonstrate that the temporal characteristics of calcium dynamics obtained through widefield imaging can be utilized to infer the corresponding
behavior. Cortical activity in six new generation transgenic calcium reporter mice expressing GCaMP6f in neocortical pyramidal neurons, are recorded during active whisking (AW) and no whisking (NW). To extract features related to temporal characteristics of calcium recordings, a method based on visibility graph (VG) is introduced. An extensive study considering different choice of features and classifiers is conducted to find the best model capable of predicting AW and NW from calcium recordings. Our experimental results show that temporal characteristics of calcium recordings identified by the proposed method, carry discriminatory information that are powerful enough for decoding behavior.
CITE THIS COLLECTION
DataCite
3 Biotech
3D Printing in Medicine
3D Research
3D-Printed Materials and Systems
4OR
AAPG Bulletin
AAPS Open
AAPS PharmSciTech
Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg
ABI Technik (German)
Academic Medicine
Academic Pediatrics
Academic Psychiatry
Academic Questions
Academy of Management Discoveries
Academy of Management Journal
Academy of Management Learning and Education
Academy of Management Perspectives
Academy of Management Proceedings
Academy of Management Review
Zhu, Li; Lee, Christian; Margolis, David; Najafizadeh, Laleh (2018). Decoding Cortical Brain States from Widefield Calcium Imaging Data Using Visibility Graph. Optica Publishing Group. Collection. https://doi.org/10.6084/m9.figshare.c.3986253.v1
or
Select your citation style and then place your mouse over the citation text to select it.
Resource Link
SHARE
Usage metrics
Read the peer-reviewed publication
AUTHORS (4)
LZ
Li Zhu
CL
Christian Lee
DM
David Margolis
LN
Laleh Najafizadeh