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Neural Dynamics| Behaviour | Computational modelling
My research focuses on understanding how adaptive behaviour emerges from neural dynamics. My work combines neural recordings, behavioural analysis and computational methods to understand how internal states and environmental context shape goal-directed actions. With a background spanning neurophysiology, neuroethology, and modelling, my approach involves extracting structure from complex neural and behavioural data to uncover the mechanisms underlying flexible action control. I am particularly interested in how neural dynamics support adaptive actions in social and interactive contexts.Research
Combining neural recordings during behaviour & computational modelling to understand how neural dynamics shape adaptive behaviour.
Neural circuits & dynamics
I use large-scale neural recordings to study how neural circuit dynamics evolve during behaviour. My work has focussed on identifying neural coding principles underlying learning and plasticity, addressing this at different scales from single neurons to large neuronal population activity. This includes applying signal processing and dynamical systems approaches to understand how internal states and task context shape ongoing neural activity.Publications: Corinna Lorenz*, Anindita Das*, Eduarda Centeno et al. (2025) Sharp waves, bursts, and coherence: Activity in a songbird vocal circuit Is influenced by behavioral state. Journal of Neuroscience. (*equal contribution)Anindita Das, Jesse H. Goldberg. (2022) Songbird subthalamic neurons project to dopaminergic midbrain and exhibit singing-related activity. Journal of Neurophysiology.Anindita Das, Rishikesh Narayanan. (2017) Theta-frequency selectivity in spike triggered average of rat hippocampal pyramidal neurons is dependent on HCN channels. Journal of Neurophysiology.
Behaviour & goal-directed actions
My work is motivated by understanding how behaviour adapts to changing environmental demands and internal needs. I study both naturalistic and task-based behaviours to investigate how goal-directed actions are shaped by different contexts. My experience across songbird and rodent systems informs a broader interest in how behavioural structure emerges and how it can be experimentally probed.Publications:Andrea Roeser*, Vikram Gadagkar*, Anindita Das, et al. (2023) Dopaminergic error signals retune to social feedback during courtship. Nature. (*equal contribution)Anindita Das, Jesse H. Goldberg. (2022) Songbird subthalamic neurons project to dopaminergic midbrain and exhibit singing-related activity. Journal of Neurophysiology.
Computational modelling & theory
My work includes computational modelling to study how neural systems encode behaviourally relevant features. My earlier work focused on how single neurons develop feature selectivity, showing how interactions between intrinsic cellular mechanisms give rise to efficient coding of synaptic inputs. This led to a mathematical framework for capturing neuronal biophysics through a tractable closed-form transfer function, enabling its integration into larger network models. Building on this, I am increasingly interested in using dynamical systems approaches to understand how distributed neural circuits shape behaviour.Publications:Anindita Das, Rishikesh Narayanan. (2014) Active dendrites regulate spectral selectivity in location-dependent spike initiation dynamics of hippocampal model neurons. Journal of Neuroscience.Anindita Das, Rishikesh Narayanan. (2015) Active dendrites mediate stratified gamma-range coincidence detection in hippocampal model neurons.. Journal of Physiology.Anindita Das, Rishikesh Narayanan. (2017) Strings on a violin: Location Dependence of Frequency Tuning in Active Dendrites. Frontiers in Cellular Neuroscience. [Review]
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