Sahil Moza, PhD

Postdoctoral Fellow, Zhang Lab
Harvard University
Boston, USA
sahil.moza AT gmail.com

sahilmoza@fas.harvard.edu CV

I am a postdoctoral researcher at the Zhang Lab at Harvard University, where I investigate how learning reorganizes brain-wide neural dynamics. My research focuses on modeling and analyzing whole-brain neural activity data from C. elegans to understand how distributed neural populations evolve during learning and encode adaptive behavior. I am interested in how memory is instantiated and coordinated across the entire nervous system by combining theory-guided experiment design, computational modeling and machine learning.

A unifying theme of my work is understanding how memory and learning emerge from neural circuits—across scales, substrates, and levels of biological organization.

During my PhD at the National Centre for Biological Sciences (NCBS), Bengaluru, I explored the foundations of memory at microcircuit and molecular levels.

At the neuronal level, we demonstrated using the rodent hippocampus as a model system that a precise EI balance exists in the brain, where random presynaptic inputs are balanced at timescales shorter than the membrane time-constant (\(\lt \tau_m\)). We showed that this precise EI balance enables a subthreshold gain control computation , which allows for a flexible encoding of a wide range of subthreshold inputs and a transformation of input amplitude information into spike times.

At the molecular level, I exhaustively modeled all possible (~3500) small bistable chemical reaction networks capable of storing 1 bit of memory- biochemical flip-flops that may operate at synaptic scales. Our simulations mapped the landscape of motifs that remain robust to perturbations like thermal noise, reaction-rate variability and structural changes, identifying families of reliable molecular architectures for memory storage at femtoliter-scale synaptic compartments.

Currently, I am building CeDNe, a Python-based platform that integrates multi-modal data- anatomical, molecular, and neural activity datasets into cohesive, data-driven models of the nervous system.

news

Jun 11, 2025 Website updated!
Aug 21, 2022 Website updated!
Jan 13, 2021 New website up and running :smiley:!
Jan 1, 2021 Resetting old website to a swanky new one :sparkles:!

selected publications

  1. Precise excitation-inhibition balance controls gain and timing in the hippocampus
    Bhatia, Aanchal, Moza, Sahil, and Bhalla, Upinder Singh
    Elife , eLife Sciences Publications Limited (2019)
  2. Different dimensions of robustness-noise, topology and rates-are nearly independent in chemical switches
    Moza, Sahil, and Bhalla, Upinder S
    BioRxiv , Cold Spring Harbor Laboratory (2020)
  3. SWITCHES: Searchable Web Interface for Topologies of CHEmical Switches.
    HarshaRani, GV, Moza, Sahil, Ramakrishnan, Naren, and Bhalla, Upinder S
    Bionformatics , Oxford University Press (2021)
  4. Action at a Distance: Theoretical Mechanisms of Cross-Dendritic Heterosynaptic Modification
    Moza, Sahil
    eNeuro (2023)
    Abs