Undergraduate Institution and Major:
New York Institute of Technology, BA, Computer Science, 2011
Ben Hayden, Ph.D., Department of Neuroscience
I’m interested in understanding the neural correlates of value- based decision-making and executive control. Most of my research involves analysis of single-neuron data recorded in primate prefrontal cortex.
Graduate Level Publications:
- Cash-Padgett T, Azab H, Yoo SBM, Hayden BY. Opposing pupil responses to offered and anticipated reward values. Anim Cogn. 2018 Sep;21(5):671-684.
- Azab H, Hayden BY. Correlates of economic decisions in dorsal and subgenual anterior cingulate cortices. Eur J Neurosci. 2018;47(8):979-993.
- Farashahi S, Azab H, Hayden B, Soltani A. On the flexibility of basic risk attitudes in monkeys. J Neurosci. 2018;38(18):4383-4398.
- Pirrone A, Azab H, Hayden BY, Stafford T, Marshall JAR. Evidence for the speed-value trade-off: human and monkey decision making is magnitude sensitive. Decision (Wash D C ). 2018;5(2):129-142.
- Azab H, Hayden BY. Correlates of decisional dynamics in the dorsal anterior cingulate cortex. PLoS Biol. 2017 Nov 15;15(11):e2003091.
- Strait CE, Sleezer BJ, Blanchard TC, Azab H, Castagno MD, Hayden BY. Neuronal selectivity for spatial position of offers and choices in five reward regions. J Neurophysiol. 2016;115:1098-111.
Thesis Committee Members:
Matthew Johnson, Ph.D., Department of Biomedical Engineering (Chair)
Benjamin Hayden, Ph.D., Department of Neuroscience
David Redish, Ph.D., Department of Neuroscience
Nicola Grissom, Ph.D., Department of Neuroscience
Jocelyn Richard, Ph.D., Department of Neuroscience
Graduated summa cum laude with a Bachelor of Science in Computer Science
What Got You Interested in Research?
My undergraduate background is in computer science, and I’ve had a long-held interest in psychology and philosophy. I was especially interested in concepts of self-control, self-determination and free will, but wanted to tackle these from a primarily scientific perspective. My ultimate goal is to understand the algorithms and biological circuits that enable us to exhibit such complex, motivated behavior.