Open neuroscience and data-sharing
Recent articles
This series of scientist-written essays explores some of the benefits and challenges of data-sharing.
Deleting data or stopping its collection will erase years of valuable brain research
An explosion in open-neuroscience datasets has created a new generation of researchers with expertise in data science. But new federal restrictions in the United States put their research programs in jeopardy.
Deleting data or stopping its collection will erase years of valuable brain research
An explosion in open-neuroscience datasets has created a new generation of researchers with expertise in data science. But new federal restrictions in the United States put their research programs in jeopardy.
Neuroscience’s open-data revolution is just getting started
Data reuse represents an opportunity to accelerate the pace of science, reduce costs and increase the value of our collective research investments. New tools that make open data easier to use—and new pressures, including funding cuts—may increase uptake.
Neuroscience’s open-data revolution is just getting started
Data reuse represents an opportunity to accelerate the pace of science, reduce costs and increase the value of our collective research investments. New tools that make open data easier to use—and new pressures, including funding cuts—may increase uptake.
To keep or not to keep: Neurophysiology’s data dilemma
An exponential growth in data size presents neuroscientists with a significant challenge: Should we be keeping all raw data or focusing on processed datasets? I asked experimentalists and theorists for their thoughts.
To keep or not to keep: Neurophysiology’s data dilemma
An exponential growth in data size presents neuroscientists with a significant challenge: Should we be keeping all raw data or focusing on processed datasets? I asked experimentalists and theorists for their thoughts.
The S-index Challenge: Develop a metric to quantify data-sharing success
The NIH-sponsored effort aims to help incentivize scientists to share data. But many barriers to the widespread adoption of useful data-sharing remain.
The S-index Challenge: Develop a metric to quantify data-sharing success
The NIH-sponsored effort aims to help incentivize scientists to share data. But many barriers to the widespread adoption of useful data-sharing remain.
A README for open neuroscience
Making data (and code) useful for yourself automatically makes it useful for others.
A README for open neuroscience
Making data (and code) useful for yourself automatically makes it useful for others.
Neuroscience graduate students deserve comprehensive data-literacy education
Despite growing requirements around how to handle and share data, formal training is lacking.
Neuroscience graduate students deserve comprehensive data-literacy education
Despite growing requirements around how to handle and share data, formal training is lacking.
Designing an open-source microscope
Funding for the development of open-source tools is on the rise, but support for their maintenance and dissemination, both crucial for their meaningful uptake, remains a major challenge.
Designing an open-source microscope
Funding for the development of open-source tools is on the rise, but support for their maintenance and dissemination, both crucial for their meaningful uptake, remains a major challenge.
Neuroscience needs a research-video archive
Video data are enormously useful and growing rapidly, but the field lacks a searchable, shareable way to store them.
Neuroscience needs a research-video archive
Video data are enormously useful and growing rapidly, but the field lacks a searchable, shareable way to store them.
Unleashing the power of DIY innovation in behavioral neuroscience
Widespread adoption of open-source tools calls for more support and training.
Unleashing the power of DIY innovation in behavioral neuroscience
Widespread adoption of open-source tools calls for more support and training.
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.
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.
Explore more from The Transmitter
Long-read sequencing unearths overlooked autism-linked variants
Strips that are thousands of base pairs in length offer better resolution of structural variants and tandem repeats, according to two independent preprints.
Long-read sequencing unearths overlooked autism-linked variants
Strips that are thousands of base pairs in length offer better resolution of structural variants and tandem repeats, according to two independent preprints.
This paper changed my life: Dan Goodman on a paper that reignited the field of spiking neural networks
Friedemann Zenke’s 2019 paper, and its related coding tutorial SpyTorch, made it possible to apply modern machine learning to spiking neural networks. The innovation reinvigorated the field.
This paper changed my life: Dan Goodman on a paper that reignited the field of spiking neural networks
Friedemann Zenke’s 2019 paper, and its related coding tutorial SpyTorch, made it possible to apply modern machine learning to spiking neural networks. The innovation reinvigorated the field.
Autism and anxiety insights; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 September.
Autism and anxiety insights; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 September.