Dr Alekhya Mandali

University position

Research Associate


Department of Psychiatry



Home page

https://sites.google.com/view/al... (personal home page)

Research Themes

Systems and Computational Neuroscience

Cognitive and Behavioural Neuroscience


I study neural mechanisms pertaining to behaviors that are repetitive (compulsive) and impulsive, and factors (mood/external factors) that influence them. Specifically in the context of neuropsychiatric conditions such as Parkinson's disease, OCD, and addiction.

Experimentally, I employ invasive (deep brain stimulation) and non-invasive(Transcranial magnetic stimulation) techniques to modulate the underlying networks that govern these behaviors. Computationally, data-driven and network-based models are utilized to understand and estimate parameters that capture the behavior

I am happy to discuss my research and collaborate.

Research Focus


Computational Neuroscience

Transcranial Magnetic Stimulation

Parkinson's disease

spiking neuron models

compulsivity and impulsivity

Clinical conditions


Cognitive impairment

Movement disorders

Obsessive compulsive disorder

Parkinson's disease


Behavioural analysis

Computational modelling

Neuropsychological testing

Transcranial Magnetic stimulation



Nuria Doñamayor Alonso

Srinivasa Chakravarthy Web: https://biotech.iitm.ac.in/Faculty...

Ahmed Moustafa Web: https://www.westernsydney.edu.au/staff_p...

Ryan Philiphs Thomas

Chenchen Zhang

Associated News Items

Key publications

Mandali A, Weidacker K, Kim SG, Voon V (2019), “ The ease and sureness of a decision: evidence accumulation of conflict and uncertainty” Brain Volume 142, Issue 5, Pages 1471–1482

Mandali A, Rengaswamy M, Chakravarthy VS, Moustafa AA. (2015), “A spiking Basal Ganglia model of synchrony, exploration and decision making. ” Frontiers in Neuroscience. 9:191.



A Mandali, VS Chakravarthy, R Rajan, S Sarma, A Kishore (2016), “Electrode Position and Current Amplitude Modulate Impulsivity after Subthalamic Stimulation in Parkinsons Disease—A Computational Study” Frontiers in Physiology