Daniel Liévano
Illustrator
From this contributor
Pooling data points to new potential treatment for spinal cord injury
By gathering raw data from multiple labs, we identified an overlooked predictor of recovery after spinal cord injury. Many more insights remain trapped in scattered data.
We found a major flaw in a scientific reagent used in thousands of neuroscience experiments — and we’re trying to fix it.
As part of that ambition, we launched a public-private partnership to systematically evaluate antibodies used to study neurological disease, and we plan to make all the data freely available.
Simply making data publicly available isn’t enough. We need to make it easy — that requires community buy-in.
I helped create a standard to make it easy to upload, analyze and compare functional MRI data. An ecosystem of tools has since grown up around it, boosting reproducibility and speeding up research.
Incentivizing data-sharing in neuroscience: How about a little customer service?
To make data truly reusable, we need to invest in data curators, who help people enter the information into repositories.
Incentivizing data-sharing in neuroscience: How about a little customer service?
Explore more from The Transmitter
Infant Brain Imaging Study findings, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 23 March.
Infant Brain Imaging Study findings, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 23 March.
Trading places: What happens when neuroscience turns into machine learning, and machine learning turns into neuroscience?
Neuroscience has become increasingly concerned with prediction, and machine learning with causal explanation, with each field adopting methods from the other. I asked eight experts to weigh in on what we stand to learn from this exchange.
Trading places: What happens when neuroscience turns into machine learning, and machine learning turns into neuroscience?
Neuroscience has become increasingly concerned with prediction, and machine learning with causal explanation, with each field adopting methods from the other. I asked eight experts to weigh in on what we stand to learn from this exchange.
Exon-skipping approach boosts levels of key Rett syndrome protein
Deleting a small region of the MECP2 gene partially restored function in neurons derived from people with Rett-associated variants.
Exon-skipping approach boosts levels of key Rett syndrome protein
Deleting a small region of the MECP2 gene partially restored function in neurons derived from people with Rett-associated variants.