Jul 27, 2026
Dr. Jin Hyung Lee is an associate professor at Stanford and founder of LVIS, a company translating years of brain circuit research into clinical software for neurological care. In this episode, we discuss how her team thinks about the brain as a circuit system, why neurological disorders can be difficult to diagnose with today’s tools, and how LVIS’s NeuroMatch platform aims to use EEG data to visualize brain network function in a more accessible way.
We also talk about why EEG remains clinically useful despite its limitations, how software can help clean and interpret noisy brain signals, and why Dr. Lee believes brain health should become something we monitor and maintain rather than only address after major disability occurs. The conversation touches on epilepsy, memory problems, traumatic brain injury, anxiety, depression, sleep, clinical access bottlenecks, and the broader future of brain health clinics.
1.
Brain disorders may be better understood as circuit
problems.
Dr. Lee frames neurological disease
around how signals flow through the brain, rather than only around
symptoms or broad diagnostic categories. Her goal is to visualize
brain network function so clinicians can better understand where
communication may be disrupted.
2. EEG
is imperfect, but accessible.
EEG is noisy and spatially limited,
but it is far easier to deploy than MRI or invasive recordings.
LVIS chose EEG because a 19-channel clinical EEG system could
potentially make brain network analysis more accessible to patients
and clinicians.
3.
Software may help extract more useful information from traditional
brain recordings.
Dr. Lee explains that the NeuroMatch
approach combines signal processing, machine learning for data
cleaning, and years of circuit neuroscience insight to extract
meaningful patterns from EEG. The claim is not simply “AI finds
everything,” but that software can help make noisy clinical data
more interpretable.
4.
Access to neurological testing is a major
bottleneck.
Although EEG may seem simple from an
engineering perspective, clinical EEG requires trained technicians,
physicians, interpretation time, and infrastructure. Dr. Lee argues
that automation and cloud-based software could reduce delays and
make neurological evaluation more available.
5. Dr.
Lee’s long-term vision is preventive brain
health.
Rather than waiting until someone is
severely impaired, she imagines a future where people monitor brain
function the way they monitor blood pressure, glucose, weight, or
car maintenance. That is the central philosophical shift of the
episode: brain health as something measurable, trackable, and
potentially maintainable.
0:00 Introduction to Dr. Jin Hyung Lee, Stanford,
LVIS, and NeuroMatch
0:50 Translating 15 years of Stanford brain circuit
research into clinical tools
1:30 Why brain disorders require understanding how
signals flow through the brain
2:35 NeuroMatch, EEG, and visualizing individual
brain network status
3:30 Epilepsy, memory problems, TBI, anxiety,
depression, sleep, and other applications
5:00 What a brain network scan might reveal about
symptoms
7:30 Measuring brain performance like glucose,
weight, or other health metrics
8:10 Why use EEG despite its noisy and
low-resolution nature?
9:20 Standard 19-channel clinical EEG and
extracting more information from limited data
12:25 Why this was not possible before: hardware,
signal processing, and circuit knowledge
15:00 Novera Brain Health Institute and a new model
for brain health clinics
18:40 Why clinical EEG is less accessible than it
seems
21:30 Software as a medical device and keeping
physicians in the loop
23:30 Dr. Lee’s origin story: electrical
engineering, her grandmother’s stroke, and brain
circuits
27:00 The five-year vision: maintaining brain
health before disability occurs
29:00 Early clinical use and the hope for changing
the future of brain disorders