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
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.