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Role of the Hippocampus and Orbitofrontal Cortex in Dynamic Decision-Making

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Title:
Role of the Hippocampus and Orbitofrontal Cortex in Dynamic Decision-Making
Series Title:
18th Annual Undergraduate Research Symposium
Creator:
Wasanwala, Huzaifa
Language:
English

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Subjects / Keywords:
Center for Undergraduate Research
Biological Sciences
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Conference papers and proceedings
poster ( aat )

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Abstract:
Decisions often must be made in the face of changing information and dynamic contingencies. This involves constantly updating representations regarding cost versus reward to optimize future decisions (Holmes, Trueblood & Heathcote, 2016). This neural computation likely requires organized communication between the prefrontal cortices and medial temporal lobe. Despite this interconnected dependency, research on the role of the orbitofrontal cortex (OFC) and hippocampus (HPC) in decision-making has continued independently (Wikenheiser & Schoenbaum, 2016). Therefore, this study investigates the role of the OFC-HPC interaction for decision-making in a dynamic spatial delay discounting task, which examines an animal's preference for a large reward preceded by a delay over a small, immediate reward (Papale & Redish, 2012). Rats were implanted with four guide cannulae bilaterally targeting the dorsal HPC and lateral OFC in order to administer muscimol (GABAA agonists), or a saline vehicle control. This allowed for bilateral inactivation of the OFC or HPC as well as an OFC-HPC disconnection condition (contralateral OFC-HPC muscimol infusions). Disrupted communication between these two structures altered performance and behavior in the dynamic spatial delay decision-making task. This study takes a systems-level approach to exploring decision-making and highlights how the OFC and HPC dynamically interact to compose behavior. ( en )
General Note:
Research Authors: Huzaifa Wasanwala, Jack-Morgan Mizell, Deandra Chetram, Margaret Ann Kreher, Sara Rukmini Garcia-Sosa, Sarah A Johnson, Sara N. Burke, Andrew P. Maurer - University of Florida
General Note:
University Scholars Program
General Note:
Faculty Mentor: Andrew Maurer - Neuroscience, University of Florida

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University of Florida
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Copyright Huzaifa Wasanwala. Permission granted to University of Florida to digitize and display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.

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Animals 4 Male Fischer 344 x Brown Norway F1 Hybrid rats from the NIA colony (Taconic), aged 6 months at time of arrival to the animal facility. Decisions are often made in the face of changing information and dynamic contingencies. This process requires constant updating of representations regarding cost versus reward in order to optimize future decisions (Holmes, Trueblood & Heathcote, 2016). This neural computation likely requires orchestrated communication across the medial temporal lobe and prefrontal cortices. Despite this multiregional dependency, research on the role of the orbitofrontal cortex (OFC) and hippocampus (HPC) in decision making has continued independently (Wikenheiser & Schoenbaum, 2016) Wikenheiser &Schoenbaum, 2016 Therefore, we investigated how OFC HPC interaction supports decision making in a dynamic discounting task which tests an animal's preference for a large reward ( Papale & Redish, 2012; Breton, Seeland, and Redish, 2015). xsddd Background xsddd Future Directions xsddd Summary and Conclusions Hippocampal inactivation and Orbitofrontal Inactivation have different impacts on dynamic decision making. We find that an OFC inactivation causes a disruption in deliberation that they compensate for the inability to access representations by automating their behavior later in the trial. Hippocampal inactivations do not cause disruptions in behavior and may be compensated for by some other means. We also find that dampening the communication between the two structures may have an impact on the ability for the rat to stabilize their behavior. References Breton, Y. A., Seeland, K. D., & Redish, A. D. (2015). Aging impairs deliberation and behavioral flexibility in inter temporal choice. Frontiers in aging neuroscience, 7. Bett, D., Murdoch, L. H., Wood, E. R., & Dudchenko, P. A. (2015). Hippocampus, Hippocampus, 25(5), 643 654. Papale, A. E., Scott, J. J., Powell, N. J., Regier, P. S., & Redish, A. D. (2012). Interactions between deliberation and delay discounting in rats. Cognitive, Affective, & Behavioral Neuroscience 12 (3), 513 526. Sharpe, M. J., Wikenheiser, A. M., Niv, Y., & Schoenbaum, G. (2015). The state of the orbitofrontal cortex. Neuron, 88(6), 1075 1077. Wikenheiser, A. M., & Schoenbaum, G. (2016). Over the river, through the woods: cognitive maps in the hippocampus and orbitofrontal cortex. Nature Reviews Neuroscience. Acknowledgments xsddd Thank you to Dylan Guenther, Kaeli Fertal, Sean Turner, and Jack Kennedy for technical assistance in the project. Funding provided bAG049722 McKnight Brain Research Foundation MH109548. and the University Scholars Program, University of Florida xsddd Results xsddd The Spatial Delay Discounting Task This task evaluates the length of time a rat is willing to wait for a large reward (e.g., 20 seconds for 3 pellets) against a small, immediate reward (1 second for 1 pellet) (Papale et. al.,2012). This task naturally creates three distinct behavioral phases. Rodent Surgery and Muscimol Infusion Paradigm Rodents were implanted with four cannulae bilaterally in the orbitofrontal cortex and the dorsal hippocampus. Following recovery from surgery, rodents were retrained on the 3:1 reward ratio, 30 second initial delay. They were either infused 1) bilaterally in the OFC, 2) bilaterally in the Dorsal Hippocampus, 3) Contralaterally, or 4) Ipsilaterally. Order of the infusion was pseudorandomized and every rat received each infusion condition with washout days in between. Figure 5: Investigation Phase Figure 6: Titration Phase Figure 7: Exploitation Phase I making computations, we wish to characterize this behavior across cost modalities. To do this we have developed the Dynamic Effort task Figure 1: Example Sessions Figure 2: Initial Testing 0 5 10 15 20 25 30 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 DELAY TRIAL NUMBER EXAMPLE SESSION large reward small reward Figure 3:Indifference Point By Infusion Figure 2 : Reward Ratio significantly predicted Indifference points, b = 3.0342, t (87) = p < .0001. Reward Ratio also explained a significant proportion of variance in Indifference Points, R 2 = .7608, F (1, 87) = 276.7, p < .0001 Fig. 3: An analysis of variance showed that the effect of Infusion Condition on Indifference Point was not significant, F(4,19) = .79, p =0.541(N.S.) Fig. 5: An analysis of variance showed that the effect of Infusion Condition on Indifference Point was not significant, F(4,19) = 1.295, p =0.307 (N.S.) Fig. 6 : An analysis of variance showed that the effect of Infusion Condition on Indifference Point was not significant, F(4,19) = 1.282, p =0.312(N.S.) Fig. 7 : An analysis of variance showed that the effect of Infusion Condition on Indifference Point was not significant, F(4,19) = 2.292, p <0.097(N.S.) Fig. 4 : An analysis of variance showed that the effect of Infusion Condition on Indifference Point was significant, F(4,19) = 3.937, p <.05 0 5 10 15 20 25 30 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 DELAY TRIAL NUMBER EXAMPLE SESSION large reward small reward Indifference Point Indifference Point Xsdd Figure 4: Total Trials Infusion Conditions ? 1 Hippocampal Inactivation Orbitofrontal Cortex Inactivation Disconnection Ipsilateral Inactivation Vehicle Infusion 0 5 10 15 20 25 30 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 113 117 121 125 129 133 137 141 145 149 153 157 161 165 169 173 177 181 185 189 193 197 201 Effort Pilot Data 2:1 Reward Ratio 1:1 Reward Ratio The Dynamic Effort Maze Methods Fig. 10 : A two way analysis of variance showed a significant main effect of behavioral phase on Reaction Time, F(2,36) = 4.216, p <.05. The effect of infusion condition on Reaction time was not significant, p< .099(N.S.) and neither was the interaction effect, p=.359. Error bars represent SEMs Fig. 8 : An analysis of variance showed that the effect of Infusion Condition on VTE was not significant, F(4,16) = .737, p =.58. Error bars represent SDs. Fig. 9: A two way analysis of variance showed a significant main effect of Phase on VTE amount, F(4,16) = 12.448, p <.05. The effect of condition was also trending towards significance, p=0.0505(N.S). The Interaction Effect could not be analyzed due to too few N. Error bars represent SEMs. The Orbitofrontal cortex and hippocampus contribute to dynamic inter temporal choice Huzaifa Wasanwal a 1 Jack Morgan Mizell 1 Deandra Chetram 1 Margaret Ann Kreher 1 Sara Rukmini Garcia Sosa 1 Sarah A Johnson 1 Sara N. Burke 1 Andrew P. Maurer 1,2 1 Department of Neuroscience 2 McKnight Brain Institute, 2 Department of Biomedical Engineering, University of Florida Correspondence: mxdd8pum3@ufl.edu 400 600 800 1000 1200 1400 1600 1800 1 2 3 Time In Choice Point (msec) Behavioral Phase Hippocampus OFC Contralateral Ipsilater Vehicle Figure 10: Reaction Time At Choice Point Investigation Titration Exploitation 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 1 2 3 Amount of VTE Behavioral Phase Hippocampus OFC Contralateral Ipsilateral Vehicle Investigation Titration Exploitation Figure 8: Total VTE Figure 9: VTE by Behavioral Phase