Dr. Al Hamood

Graduate Student (graduated August 2015)

Volen Center for Complex Systems
Brandeis University,
Mailstop 013
415 South Street
Waltham MA 02454

Tel: (781) 736-3134
Fax: (781) 736-3142



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Hamood AW, Marder E (2015). Consequences of acute and long-term removal of neuromodulatory input on the episodic gastric rhythm of the crab, Cancer borealis. J Neurophysiol, in press. Web PDF

Hamood AW, & Marder E (2015). Animal-to-Animal Variability in Neuromodulation and Circuit Function. Cold Spring Harbor Symposia on Quantitative Biology. doi:10.1101/sqb.2014.79.024828  Web PDF

Hamood AW, Haddad SA, Otopalik AG, Rosenbaum P, & Marder E (2015). Quantitative Reevaluation of the Effects of Short- and Long-Term Removal of Descending Modulatory Inputs on the Pyloric Rhythm of the Crab, Cancer borealis. eNeuro, 2(1). doi:10.1523/ENEURO.0058-14.2015 Web PDF

Williams AH, Hamood AW, & Marder E. (2014). Neuromodulation in Small Networks. In Encyclopedia of Computational Neuroscience (pp. 1–15). New York, NY: Springer New York. doi:10.1007/978-1-4614-7320-6_26-2 Web PDF

Marder E, Goeritz ML, Gutierrez GJ, Hamood A, Brookings T, Haddad S, Kispersky T, and Shruti, S (2014) The Crustacean Stomatogastric Nervous System. In: Derby, C.D. and Thiel, M. eds. Crustacean Nervous Systems and their Control of Behavior. Oxford University Press.

Hamood AW, Goeritz MG. (2012) Correlated voltage dependences of ion channels revealed. J. Neurosci 32(21): 7106-08; Pubmed ID: 22623655 Web PDF

After spending five years working on sheet metal for Ford Motor, I returned to school in Ann Arbor, MI in 2007 to complete my undergraduate degree in neuroscience and psychology.  Following my graduation in 2009 I came to Brandeis to join the neuroscience Ph.D. program, and the Marder lab in the summer of 2010.
I am interested in how neuromodulation and neuronal variability across animals interact to produce networks that are functional and robust to perturbations. While significant variability exists in all measured properties across neurons, central pattern-generating (CPG) networks are nonetheless able to tune themselves to produce appropriate output. I am working on extending our knowledge of this variability to neuromodulatory influences, which are also ubiquitous in nervous systems. Specifically, I am interested in how much these modulatory influences themselves vary, and how they may be able to compensate for variable underlying structures in CPG networks.