Computational algorithm for assessing inter-neuronal connectivity to optimize optogenetic stimulation and neural circuit activity (Conference Presentation)

Carlos Renteria; Shreya M. Santhanam; Yuan-Zhi Liu; Denise Medina; Parijat Sengupta; Stephen A. Boppart

doi:10.1117/12.2291233

14 March 2018 Computational algorithm for assessing inter-neuronal connectivity to optimize optogenetic stimulation and neural circuit activity (Conference Presentation)

Carlos Renteria, Shreya M. Santhanam, Yuan-Zhi Liu, Denise Medina, Parijat Sengupta, Stephen A. Boppart

Author Affiliations +

Proceedings Volume 10482, Optogenetics and Optical Manipulation 2018; 1048210 (2018) https://doi.org/10.1117/12.2291233
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

All-optical systems for stimulating and imaging neuronal activity have served as powerful tools for understanding the underlying circuitry of the brain. Experiments using these setups, however, tend to choose stimulation locations based solely on what brain regions are of interest, and take for granted that stimulation effects may vary even within localized brain regions. We thus have developed an algorithm for acquiring neuronal activity via calcium imaging data to assess network connectivity. These parameters include the signal rise time, decay time, inter-event intervals, and the timing and amplitude of signal peaks. These parameters are then compared between cell clusters for similarities, and used as a basis for establishing interconnectivity. Additionally, we have incorporated both temporal and spatial correlation functions to assess inter-neuronal connectivity based on these parameters. This data is then run through a genetic algorithm, applying weights to cells with similar parameters to learn which are interconnected in a given field-of-view. For this study, hippocampal neurons extracted from 2 day old transgenic mice (GCaMP6s, Jackson Labs), - cultured for 2 weeks and imaged under single and two-photon conditions. Single-photon imaging was performed under a commercial Zeiss microscope, whereas two-photon imaging was performed with an in-house imaging system. Results demonstrate a strong correlation between these parameters and cellular connectivity, making them noteworthy markers for targeted stimulation. This study demonstrates an efficient method of assessing network connectivity for various imaging techniques, and hence directed targeting for optogenetic stimulation.

Conference Presentation

Citation Download Citation

Carlos Renteria, Shreya M. Santhanam, Yuan-Zhi Liu, Denise Medina, Parijat Sengupta, and Stephen A. Boppart "Computational algorithm for assessing inter-neuronal connectivity to optimize optogenetic stimulation and neural circuit activity (Conference Presentation)", Proc. SPIE 10482, Optogenetics and Optical Manipulation 2018, 1048210 (14 March 2018); https://doi.org/10.1117/12.2291233

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
PRESENTATION

WATCH
PRESENTATION SAVE TO MY LIBRARY

GET CITATION

KEYWORDS

Brain

Imaging systems

Optogenetics

Algorithm development

Genetic algorithms

Calcium

Machine learning

Show All Keywords

Keywords/Phrases

Search In:

Publication Years