How ELDA Is Bringing EEG-fMRI to the Clinic
- Dominic Borkelmans
- Aug 18
- 6 min read
In 1791, Luigi Galvani discovered that the nervous system is orchestrated through a series of electrical pulses. Roughly 130 years later, Hans Berger used his galvanometer to record the first of these signals from the human brain. For a long time, electricity was our primary means of listening to the brain’s inner workings. In recent decades, however, the rise of advanced imaging has increasingly sidelined EEG, its millisecond-level precision eclipsed by the spatial dominance of MRI.
Gilad Peleg joined Dan Shaham to cofound ELDA BrainTech in a bid to bring EEG back to the center of clinical neuroimaging. The Israeli startup is reconnecting the brain’s electrical signals with structural imaging, combining EEG’s unrivaled timing with the spatial depth of fMRI. At ELDA, there’s a belief that only through a synchronous and simultaneous approach can we capture the full complexity of brain disorders. Multimodal imaging has long been described as the future. ELDA is the startup working to make that long-promised vision a clinical reality.
ELDA’s patented imaging approach
Born at the Sagol Brain Institute, headed by professor Talma Hendler, ELDA has developed one of the first clinical tools capable of capturing clean EEG signals from inside an active fMRI scanner. Earlier attempts, mostly within academic research, have struggled with signal accuracy and reproducibility, limiting their clinical utility. The main challenge lies in synchronizing and smoothing data from two fundamentally different modalities: one electrical, the other hemodynamic.
ELDA’s, soon-to-be FDA-approved, commercial platform is an all-in-one software/hardware solution, built around a patented dual-array system. The setup separates the EEG electrodes and amplifier components into two synchronized arrays, minimizing MRI-induced magnetic interference and enabling clean signal acquisition even during active scanning. In doing so, ELDA overcomes two of the key challenges that have long limited multimodal imaging: interference and synchronization.
The resulting data is denoised using Independent Component Analysis, a technique that separates meaningful brain signals from noise caused by muscle activity, eye blinks, and scanner-induced artifacts. The cleaned signal is then processed using flow analysis, an approach that traces how neural activity propagates through networks over time, offering a dynamic alternative to static snapshots. The result is a 3D visualization of brain activity across regions and time, delivered at the highest temporal and spatial resolution currently achievable in a clinical setting.
The promise of multimodal diagnostics
Gilad Peleg explains why a multimodal approach may be essential to understanding the brain. “At the end of the day, most neurological activities and disorders are not single-spot or focal, but they are network presentations. So, combining spatial and temporal, you can really see the entire network disorder within the 3D environment.”
These kinds of 3D presentations have already shown promise in diagnosing several common neurological disorders. ELDA’s approach has been tested in over 300 patients with drug-resistant epilepsy (DRE). Most DRE patients have poor therapeutic outcomes because clinicians struggle to localize the epileptic zone that triggers the seizures. They are currently diagnosed using a range of imaging modalities, from non-invasive EEG to highly invasive intracranial electrode implantation.
Despite this array of tools, the current approach remains trial and error, and a major challenge for clinicians worldwide. According to Peleg, ELDA’s approach “could either totally eliminate that multi-imaging process or, at least from day one, substantially reduce it and identify the epileptic zone.”
One of ELDA’s key innovations is the use of flow analysis not just for localization but for mapping network-level dynamics. Rather than isolating a seizure onset zone in static space, the system reconstructs how signals move across regions, capturing directionality, timing, and connectivity. This can reveal secondary nodes or hidden propagation pathways that wouldn’t appear in standard imaging. For patients with ambiguous or multifocal activity, this could be the difference between inconclusive scans and actionable insights.
So far, ELDA’s approach has been well received by both clinicians and key opinion leaders, including advisory board member Dawn S. Eliashiv, MD, professor of neurology and co-director of the UCLA Seizure Disorders Center. ELDA is now launching testing in Europe and the US, as part of its effort to secure regulatory approval for broad clinical use. The initial focus is on DRE, but the goal is to build a central tool for imaging neural networks across a range of conditions, from dementia to Parkinson’s.
In the future, ELDA may also expand its platform to support additional combinations of imaging modalities. “I think we would really want to first validate and establish this dual combination as a well-known, recognized system,” Peleg cautions. “And thereafter, hey, why not? If we can add and improve it further, absolutely.”
A venture born from expertise
Gilad Peleg is a seasoned health tech professional with over 30 years of experience; 15 years spent on the corporate and startup side as a manager, followed by 15 years as an investor and entrepreneur. Before cofounding ELDA, he spent seven years leading an investment vehicle called Joy Ventures, which focused on neural wellness from a consumer perspective.
Peleg explains they focused on “not clinically ill people, but rather the vast majority of people who are not clinically diseased, but would benefit from some sort of science-based neurological intervention that could improve brainwave activity and well-being at large.” The experience of evaluating marketable interventions through a scientific lens taught Peleg the value of both strong intellectual property and hands-on company building.
Building on those years of experience, Peleg decided to return his focus to clinical applications. ELDA emerged from the Sagol Brain Institute, where neurologists and radiologists were struggling with the limitations of EEG. In search of deeper data, they turned to fMRI, and after years of refinement, arrived at a method for producing simultaneous clean readings from both modalities.
Peleg and his partner recognized their approach as highly valuable IP. They quickly assembled a small team, raised initial funding, and set the venture in motion toward product development. Rather than taking personal credit, Peleg emphasizes the strength of the science. Still, it was in part his background in commercializing health technologies that helped turn an academic finding into a viable product.
A vision for the future
Health tech is everywhere. Increasingly, traditional big tech companies like Apple and Amazon are moving into the space. To Peleg, this isn’t a threat to ELDA but an exciting shift, one that will unlock an unprecedented volume of health data that won’t just improve treatment, but will enhance prediction and, more importantly, prevention.
The growing wealth of health data has turned diagnostics into a far more compelling field than it once was. “When I was younger, diagnostics was less attractive from an investor’s perspective,” Peleg says. “Today, diagnostics and prediction are super exciting. Economically, and in terms of quality of life, there's a huge impact.”
Peleg believes that prediction and prevention will become increasingly efficient and precise as AI matures and gets integrated across clinical workflows. And so, ELDA is betting heavily on machine learning and has already begun integrating it into its imaging platform. Their multimodal system has opened up a rich stream of data which, when paired with the right models, can be used to uncover predictive patterns and aid in diagnostics.
The goal is not to replace the clinician; rather, it is to augment their work. In fields like radiology, AI relieves clinicians by handling 99.9 percent of the work, leaving only the final decision to the expert. As Peleg puts it, “It’s not saying, ‘Hey, you’re a doctor, you know nothing, the AI is better.’ It’s preparing, analyzing, and feeding the doctor with something that’s much more refined, so they can make the expert call.”
In the coming years, these developments could bring much-needed relief to overworked healthcare systems around the world. “With the right integration of AI, I see a continuous win-win, where suddenly, expert doctors can spend 15 or even 30 minutes with patients, instead of being limited to 10,” Peleg says. ELDA is committed to this vision, aiming to offer clinicians not only more data, but more time.
About the founder
Gilad Peleg, MBA, is a health tech entrepreneur and investor with over 30 years of experience across medtech startups, venture capital, and corporate innovation. He co-founded Joy Ventures and Corundum Open Innovation, and held leadership roles at Teva Pharmaceuticals and Rainbow Medical. His strength lies in Healthtech business strategies and development, and building ventures thereof, an approach that led to the founding of ELDA.
About the firm
ELDA BrainTech is an Israeli neurotechnology startup developing a patented EEG-fMRI platform for next-generation brain diagnostics. Spun out of the Sagol Brain Institute at the Tel Aviv Souraski Medical Center, ELDA combines the temporal precision of EEG with the spatial depth of fMRI to map network-level brain activity in real time. Its first clinical focus is drug-resistant epilepsy, with broader applications envisioned in dementia, Parkinson’s disease, and other neurological disorders. ELDA is currently preparing for Beta site studies in the EU and US.
Visit ELDA’s website: https://www.elda-ai.com/
Visit the Sagol Brain Institute: https://www.cbf-tlv.com/contact-us
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