Year: 2023
Type: preprint
Abstract: Translational studies benefit from experimental designs where laboratory organisms use human-relevant behaviors. One such behavior is decision-making, however studying complex decision-making in rodents poses many problems. We overcame these limitations by designing a fully automated, inexpensive, high-throughput framework to study decision-making across multiple levels of rewards and costs in rodents: the REward-COst in Rodent Decision-making (RECORD) system. RECORD integrates three components: 1) 3D-printed configurable arenas, 2) custom electronic hardware, and 3) software for databasing, analysis, and computational modeling. RECORD sequentially offers subjects single cost/reward trade-offs that they can approach or avoid. We validated four different behavioral protocols, highlighting the versatility of our system. RECORD enables the execution of a decision-making task battery without requiring food or water deprivation, thus allowing us to characterize a profound and systematic impact of food deprivation on decision-making. We also demonstrate how RECORD enables analysis of heterogeneity in decision-making both within and across individuals and show, for the first time, that this behavioral variability is quantifiably constrained. Using oxycodone self-administration as a test case, we also reveal how analytic approaches that incorporate behavioral heterogeneity are more sensitive to detecting perturbations in decision-making than conventional approaches that average behavior across all individuals. Overall, RECORD is a more powerful and sensitive approach to studying decision-making in animals, with features that facilitate translational studies of DM in psychiatric disorders.
Source: Research Square
Authors: Alexander Friedman, Rodrigo Ibanez-Alcala, Dirk Beck, Alexis Salcido, Luis Davila, Atanu Giri, Cory Heaton, Kryssia Rodriguez, Lara Rakocevic, Safa Hossain, Neftali Reyes, Serina Batson, Andrea Macias, Sabrina Drammis, Kenichiro Negishi, Qingyang Zhang, Shreeya Umashankar Beck, Paulina Vara, Arnav Joshi, Austin Franco, Bianca Hernandez Carbajal, Miguel Ordonez, Felix Ramirez, Johnathan Lopez, Nayeli Lozano, Abigail Ramirez, Linette Legaspy, Paulina Cruz, Abril Armenta, Stephanie Viel, Jessica Aguirre, Odalys Quintanar, Fernanda Medina, Pablo Ordonez, Alfonzo Munoz, Gustavo Martinez Gaudier, Gabriela Naime, Rosalie Powers, Laura O'Dell, Travis Moschak, Ki Goosens
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W4389621212