Best Place To BuildWorld’s largest fetal-brain mapping dataset is being built here in India! | Dr Richa Verma on S2E10
CHAPTERS
- 0:00 – 0:31
Cold open: Mapping the brain down to cell-level detail
The episode begins with punchy highlights: achieving “house-level” (cellular) resolution across the whole brain, and why that’s far from straightforward. Dr. Richa Verma frames the Dharani effort as a world-leading, high-detail map of the developing human brain.
- •Cell-level resolution across the entire brain is the goal
- •Imaging a human brain sounds simple but is a major engineering challenge
- •Dharani is positioned as the largest, most detailed second-trimester developing brain map
- •The work aims to make brain structure navigable like a map
- 0:31 – 1:34
Podcast setup + introducing Dr. Richa Verma and the Brain Centre’s scale
Host Amrit introduces IIT Madras and the show’s premise—meeting builders and understanding what they’re creating. Dr. Richa Verma is introduced as CSO of the Sudha Gopalakrishnan Brain Centre, emphasizing the multidisciplinary team and 0.5-micron imaging capability.
- •Show mission: what’s being built at IIT Madras and what it takes to build it
- •Dr. Richa Verma’s role as CSO at the Sudha Gopalakrishnan Brain Centre
- •0.5-micron (cellular-scale) imaging is highlighted upfront
- •Brain Centre spans wet lab, engineering, optics, imaging, software, and analytics
- 1:34 – 6:29
What brain mapping means—and why resolution changes everything
Dr. Verma explains brain mapping via a geography analogy: maps of regions combine into an atlas. She connects higher resolution (like Google Maps street/house level) to the ability to understand organization, cell types, and ultimately disease-relevant differences.
- •Brain is heterogeneous: many cell types and distinct regions
- •Brain atlases are built by mapping regions and assembling them into a unified reference
- •Resolution leap: from coarse regional views to cell-level detail across the whole brain
- •Reference “normal” maps are essential to interpret disorders and disease
- 6:29 – 8:15
What the IITM Brain Centre is building: lifespan atlases + the Dharani release
The Brain Centre’s overarching goal is to map the human brain from prenatal stages up to 100 years. Dr. Verma introduces Dharani—an open-access, second-trimester developing brain dataset—and explains how the centre also studies conditions like developmental disorders, stroke/ischemia, neurodegeneration, and aging.
- •Mission: map brains across the full lifespan (prenatal to 100 years)
- •Dharani (second trimester) released as open-source/open-access atlas
- •Largest and most detailed dataset of its kind for that developmental stage
- •Parallel disease-oriented work: developmental disorders, stroke/ischemia, neurodegeneration, aging
- 8:15 – 13:05
Why whole-brain cellular imaging is hard: bridging volume and resolution
Dr. Verma contrasts clinical imaging (MRI/CT) with cellular-level needs: MRI can cover the whole brain but not at neuron-level resolution. The Brain Centre’s core innovation is closing the gap between imaging an entire large organ and seeing microscopic cellular detail—primarily using post-mortem brains with proper consent and clinical partnerships.
- •Clinical MRI provides whole-brain views but typically ~1 mm best resolution
- •Cell-level histology exists but usually only for small regions, not whole brains
- •Goal: bridge whole-organ volume with cellular resolution
- •Post-mortem brains enable detailed mapping not possible in living humans today
- •Clinical partners and consent are central to acquiring high-quality tissue
- 13:05 – 15:01
The end-to-end pipeline: MRI → cryoprotection → freezing → ultra-thin slicing
The conversation breaks down the Brain Centre’s workflow step-by-step, from post-mortem structural MRI to preparing tissue for sectioning. Dr. Verma explains why water-rich brain tissue must be cryoprotected and carefully frozen at -80°C before slicing into extremely thin sections (10–50 microns).
- •Post-mortem structural MRI provides a whole-brain reference
- •Cryoprotection replaces water to enable controlled freezing
- •Freezing large brains is non-trivial due to cracking and freezing artifacts
- •Ultra-thin sectioning targets ~10–20 microns (or thicker depending on goals)
- •Process has been standardized through repeated execution (100+ brains)
- 15:01 – 18:02
Key engineering innovation: tape-transfer section handling at large scale
Dr. Verma details a major bottleneck: lifting and transferring huge, ultra-thin sections (e.g., ~6×8 inches at ~20 microns). The centre developed a tape-transfer method using specialized adhesive and UV-assisted transfer to move fragile sections onto glass slides reliably.
- •Traditional brush/float methods become fragile at large human-brain section sizes
- •Tape-transfer technique helps lift large, thin sections without tearing
- •Special glue + UV uncure enables precise slide transfer
- •Engineering and process optimization are required at multiple steps
- •Quality control becomes evident during slicing if freezing/handling failed
- 18:02 – 23:35
From transparent slices to usable data: staining, scanning, digitization, and a web viewer
Once sectioned, tissue must be chemically stained to reveal cell types and protein markers. Slides are then scanned with light microscopy at 0.5-micron resolution, producing massive datasets that the team organizes into digital inventory systems and interactive viewers so researchers can zoom, navigate slices, and view 3D reconstructions.
- •Staining protocols make cell types/markers visible and queryable
- •Different stains/markers support different scientific questions
- •High-resolution scanners digitize large sections at ~0.5 microns
- •Researchers can navigate 2D slice series and reconstructed 3D views
- •The Dharani Atlas is open-access, with contact pathways for deeper collaboration
- 23:35 – 26:07
Who can build this? The interdisciplinary team + the critical role of hospitals
Dr. Verma outlines the breadth of expertise required: engineers, life scientists, radiology, image processing, technicians, and more. She emphasizes that clinical partners are indispensable, especially because post-mortem interval and timely extraction/processing determine tissue quality and downstream usability.
- •120+ people across mechanical/electrical/computational engineering and life sciences
- •Radiology and image processing expertise supports multimodal integration
- •Technicians and scanning specialists enable consistent, high-throughput workflows
- •Hospital partners ensure consented acquisition and short post-mortem intervals
- •Clinical context and tissue preservation steps prevent deterioration artifacts
- 26:07 – 28:21
Global collaborators and the ‘largest in the world’ claim—why Dharani draws attention
The host probes whether the dataset is “largest in India,” and Dr. Verma clarifies it’s the largest of its kind globally for that stage. She describes rapid international interest and a growing collaborator network spanning Indian institutes and overseas universities.
- •Dharani is described as the largest such second-trimester atlas worldwide
- •The atlas is new yet already attracting significant attention
- •Collaboration spans India (e.g., inStem) and global institutions (e.g., UCSF, Canada)
- •Collaboration list is extensive (20+), reflecting broad scientific pull
- •Reference datasets enable diverse labs to test long-standing hypotheses
- 28:21 – 29:46
Can we ever do this in living humans? Limits of MRI and the promise of predictive overlays
The discussion turns to whether in-vivo imaging could reach similar detail. Dr. Verma explains the limits of clinical MRI field strength (e.g., 3T in India) and safety/practical constraints, while proposing a realistic path forward: using post-mortem cellular atlases to inform and interpret what clinical MRI implies at cell level via models.
- •Clinical MRI is limited in field strength and resolution relative to cellular needs
- •Higher-field systems exist for animals but aren’t feasible for routine human use
- •Future strategy: overlay cellular atlas knowledge onto MRI space
- •Use computational models to infer cell-level changes from in-vivo imaging signals
- •Atlases become a bridge between clinical imaging and cellular pathology
- 29:46 – 31:44
The economics of mapping brains: cost per specimen and who funds open access
Dr. Verma shares the startling consumables cost per brain and distinguishes that from equipment and staffing. She then explains the project’s funding mix—government support and major philanthropy—enabling the centre to release datasets openly despite high costs.
- •Consumables alone can reach ~₹2 crores per brain (varies by markers/protocols)
- •Equipment, centre operations, and people costs are separate additional burdens
- •Funding includes the Principal Scientific Adviser’s office and major philanthropy
- •Support from Pratiksha Trust (Kris Gopalakrishnan) and others is highlighted
- •Open-access release is enabled by multi-source funding and long-term vision
- 31:44 – 38:37
Why neuroscience is booming: foundational datasets, AI, and faster translation to medicine
Dr. Verma argues that brain science is expanding because our understanding of the human brain lags behind other organs and animal models don’t fully capture human complexity. She positions whole-brain, high-resolution datasets as foundational infrastructure—akin to the genome era—especially powerful when paired with modern AI and broad collaboration to accelerate translational impact.
- •Human brain remains less understood due to heterogeneity and limited in-vivo experimentation
- •Animal models dominate, creating gaps when translating to humans
- •Large open datasets demand AI to detect patterns beyond human visual capacity
- •Foundational mapping strengthens downstream translational/clinical research robustness
- •Genome-project analogy: shared reference resources catalyze decades of innovation
- 38:37 – 43:29
Dr. Richa Verma’s path: optometry → retina electrophysiology → primate brain research → IITM
Dr. Verma narrates a non-linear career trajectory across countries and disciplines: undergrad optometry in Chennai, PhD and postdoc work in Australia, primate brain research, and eventually moving back to India. She also notes the Brain Centre’s rapid scale-up from a handful of people to over 120.
- •Started in optometry; PhD in retinal electrophysiology (University of Melbourne)
- •Retina as neural tissue became a gateway into brain research interests
- •Postdoc and research experience included monkey brain electrophysiology and anatomy
- •Moved to India in 2017; Brain Centre work began in 2020 with a small founding team
- •Growth story: from ~5 people to 120+ in a few years
- 43:29 – 50:12
Interdisciplinary reality check: degrees don’t define careers—and labs need adaptable learners
The host and Dr. Verma discuss why rigid “degree lanes” don’t match real research work. She advocates training in critical thinking and problem solving so students can switch fields, and describes how team members often discover new strengths after joining—provided they stay open and learn how the whole system works.
- •Interdisciplinary work is not optional in complex science problems
- •Students should be trained to move across fields (biology ↔ coding ↔ engineering)
- •Critical thinking/problem solving matter more than narrow early specialization
- •New hires often shift roles after 3–6 months as strengths become clear
- •Mindset shift takes time, especially for early-career researchers focused on “a project”
- 50:12 – 55:52
NVIDIA collaboration, Neurovoyager, and managing petabyte-scale brain data (closing)
The episode closes by connecting biology and engineering to the next bottleneck: petabyte-scale data management, visualization, and analytics. Dr. Verma explains why NVIDIA’s compute/visualization tools matter and describes Neurovoyager as a way to explore datasets and query brain-condition-related information, before final reflections and outreach to young researchers.
- •Whole adult-brain digitization can reach multiple petabytes
- •Core challenges: data management, visualization speed, and scalable analytics
- •NVIDIA collaboration supports tooling for compute-heavy workflows
- •Neurovoyager: explore datasets and query brain-condition-related information
- •Closing message: attract young minds; contact via Brain Centre website/email
