(@kvossel) kudos icon 4

2020 Epilepsy Research Benchmarks

Understanding the etiology of late-onset epilepsy trending idea

One third of late-onset epilepsy have no known etiology. Cognitive symptoms are common with LOE and a third of these patients have mild cognitive impairment. Some patients with LOE have transient epileptic amnesia (TEA), while others develop neurodegenerative diseases such as Alzheimer's disease or dementia with Lewy bodies. Autoimmune causes have variable clinical presentations.

Voting

Awaiting Votes
Benchmark Feedback
(@muotri) kudos icon 1

2020 Epilepsy Research Benchmarks

Human Brain Organoid Models

Brain organoids, a new class of brain surrogate, have gained traction as a model for studying the intricacies of the human brain by using advancements in stem cell biology to recapitulate aspects of the developing human brain in vitro. Brain organoids generated from human pluripotent stem cells (hPSCs) offer a means to study human disease. Recent observation of nested EEG-like signals spontaneously emerge from these organoids... more »

Voting

Awaiting Votes
Benchmark Feedback
(@jeffrey.loeb) kudos icon 5

2020 Epilepsy Research Benchmarks

Focus on Networks trending idea

Epilepsy is a disease of multi-layered networks including electrical networks that we record on surface and intracranial EEG down to synaptic networks; spatial networks seen with advanced imaging and the presence or absence of developmental or acquired lesions; and the underlying cellular, genetic, and metabolic network. I would argue a research priority to develop ways to understand these individual networks as well... more »

Voting

Awaiting Votes
Benchmark Feedback
(@gerryn) kudos icon 3

2020 Epilepsy Research Benchmarks

Epilepsy-related "training" datasets for machine learning

Most epilepsy-related Machine Learning (ML) tools tend to focus on seizure detection using readily available EEG "training" datasets. ML has potentially many other epilepsy-related use cases beyond seizure detection that are yet to be discovered, but the lack of "training" data is likely hindering its use. If tools could be developed to help identify and generate new "training" data from existing epilepsy datasets, ML... more »

Voting

Awaiting Votes
Benchmark Feedback
(@annapurna.poduri) kudos icon 8

Transformative Research Priorities for the Epilepsies

Accelerating precision diagnosis to precision treatment trending idea

This priority will transform epilepsy research by integrating modern science into modern care for patients with epilepsy.

For example, a patient with as yet unexplained non-acquired epilepsy should be considered to have genetic epilepsy until proven otherwise and appropriately evaluated. If the first line of evaluation is unrevealing he or she should have an iterative re-analysis of cause in tandem with empiric therapy.... more »

Voting

Awaiting Votes
Ideate
(@steve) kudos icon 1

2020 Epilepsy Research Benchmarks

Strategically integrating the benchmarks for clarity

Few benchmarks will have large clinical impact if accomplished alone. Most benchmarks, specifically those relating to integrating large data sets and developing models, depend upon integrating knowledge gained from progress toward other benchmarks. In Area II, for example, benchmarks A, B, and C could be addressed separately, by a variety of innovative research approaches large and small. However, benchmark F needs input... more »

Voting

Awaiting Votes
Benchmark Feedback