I did my undergraduate studies in Biomedical Engineering (BME) at Amirkabir University of Technology (Tehran Polytechnic), followed by a second major in Control Engineering. By the end of my college time, after building a mine detector robot, and also the first EEG-based Brain Computer Interface system of the country, I well knew that what I strive for falls far more in realm of science than engineering. 

Doctoral research: During my graduate work in Alessandro Treves’ group at SISSA (Trieste, Italy), I developed a theoretical framework to evaluate the contributions of attractor dynamics to the perception of ambiguous stimuli, with the purpose of describing data from monkey electrophysiology, human psychophysics and human brain imaging studies. In particular, I developed an autoassociative model to describe neural dynamics in monkey inferotemporal cortex, a brain region involved in learning about complex objects. I showed that the same type of model is also able to describe the transient dynamics involved in some well-known behavioral traits in humans, including the adaptation aftereffect and priming. This suggests that common neural processes may underlie these phenomena, which were previously considered to be distinct.

Postdoctoral research: After my graduate studies, I switched gears into the experimental world when I realized the challenges of understanding cognition without seeing it as a systems neuroscience question. In Mathew Diamond’s lab at SISSA, I first worked on a project addressing a long lasting debate about the involvement of hippocampal oscillations in sensory perception. In rats, the hippocampus and the vibrissal sensorimotor system (whisking) are both characterized by rhythmic oscillation in the theta range (5-12 Hz). Previous work had been divided as to whether the rhythms of the two systems are independent or coherent; the most recent inquiry argued for independence. Our hypothesis was that the sensorimotor system and

hippocampus become coherent selectively in moments when the hippocampus must integrate tactile information into memory networks. Barrel cortex exhibits rhythmic

neuronal activity during vibrissa-based sensation. We showed that this activity transiently locks to ongoing hippocampal theta-rhythmic activity during the sensory-gathering epoch of a discrimination task. These results suggest that, as rats collect touch signals, enhanced coherence between the whisking rhythm, sensory cortex, and hippocampal local field potential (LFP) boosts the efficiency of integration of sensory information into memory and decision making centers.

In parallel, I developed the first Parametric Working Memory (PWM) task in rats. In this task, rats compare two sequential vibratory stimuli on theirs whiskers, separated by a delay. PWM is a unique WM behavioral paradigm in which different stages --sensory processing, memory maintenance, and decision making-- can be precisely parsed out and deconfounded. In addition, using memory items that lie on a quantitative, graded, continuum greatly facilitates both analysis and modeling of the data. Over the past couple of decades, primates have been the focus of research on neural correlates of PWM. Compared to the primate nervous system, that of rodents is more amenable to visualization and external manipulations. Additionally, a larger numbers of subjects can be studied with lower cost. However, PWM paradigms were assumed impossible in rodents due to the difficulty of training protocols. My comparative human psychophysics experiments showed that rats’ PWM capacities are remarkably similar to humans’.

During my postdoctoral research in Brody lab, I expanded the rodent PWM task to the auditory domain, using semi-automated training protocols implemented in high-throughput training facilities. I also developed several computational methods to assay PWM behavior and its interplay with prior sensory history in rats and humans.

Further, I combined formal algorithmic behavioral analysis, optogenetic inactivations, and electrophysiological recordings in rats to show that Posterior Parietal Cortex (PPC) is specifically involved in the representation and use of prior sensory experience in PWM. Earlier proposals that PPC supports working memory predict that optogenetic silencing of the PPC would lead to a behavioral impairment in our working memory task. Contrary to this prediction, silencing PPC produced a significant performance improvement. Quantitative analyses of behavior revealed that this improvement was due to the selective reduction of the effects of prior sensory stimuli. Electrophysiological recordings showed that PPC neurons carried far more information about sensory stimuli of previous trials than about stimuli of the current trial. Furthermore, an increase in the amount of this information was associated with greater behavioral effects of sensory history, suggesting a tight link between behavior and PPC representations of stimulus history. Together, the data reveal the PPC as a causally necessary and important node in the representation and use of prior sensory stimulus information.


October 2005 – December 2009

  • PhD in Computational Neuroscience, International School for Advanced Studies (SISSA/ISAS), with Prof. Alessandro Treves, Thesis title: “Attractors, memory and perception”

October 2000 – October 2004

  • B.Sc. in Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran 

October 2002 – October 2005

  • B.Sc. in Control Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran


December 2012 – present:

  • Post-doctoral research fellow, Brodylab, Howard Hughes Medical Institute & Princeton University, Princeton Neurosci. Inst.   &   Dept. of Molecular Biology, USA

December 2009 – December 2012:

  • December 2009 – December 2012: Post-doctoral researcher, Tactile Perception and Learning Lab, Cognitive Neuroscience Sector, SISSA/ISAS International School for Advanced Studies, Trieste