The future of fMRI
Recent articles
This series of essays explores new developments and challenges in human brain imaging.
To understand the brain as a network organ, we must image cortical layers
Human neuroscience research has largely overlooked this spatial scale—which bridges cells and brain areas. But new advances in functional MRI technology are changing that.
To understand the brain as a network organ, we must image cortical layers
Human neuroscience research has largely overlooked this spatial scale—which bridges cells and brain areas. But new advances in functional MRI technology are changing that.
To make a meaningful contribution to neuroscience, fMRI must break out of its silo
We need to develop research programs that link phenomena across levels, from genes and molecules to cells, circuits, networks and behavior.
To make a meaningful contribution to neuroscience, fMRI must break out of its silo
We need to develop research programs that link phenomena across levels, from genes and molecules to cells, circuits, networks and behavior.
New tools help make neuroimaging accessible to more researchers
A lack of programming experience can derail experimental aspirations. But custom software packages, web-based applications and video tutorials make functional MRI concepts easier to grasp.
New tools help make neuroimaging accessible to more researchers
A lack of programming experience can derail experimental aspirations. But custom software packages, web-based applications and video tutorials make functional MRI concepts easier to grasp.
Should we use the computational or the network approach to analyze functional brain-imaging data—why not both?
Emerging methods make it possible to combine the two tactics from opposite ends of the analytic spectrum, enabling scientists to have their cake and eat it too.
Should we use the computational or the network approach to analyze functional brain-imaging data—why not both?
Emerging methods make it possible to combine the two tactics from opposite ends of the analytic spectrum, enabling scientists to have their cake and eat it too.
To improve big data, we need small-scale human imaging studies
By insisting that every brain-behavior association study include hundreds or even thousands of participants, we risk stifling innovation. Smaller studies are essential to test new scanning paradigms.
To improve big data, we need small-scale human imaging studies
By insisting that every brain-behavior association study include hundreds or even thousands of participants, we risk stifling innovation. Smaller studies are essential to test new scanning paradigms.
To make fMRI more clinically useful, we need to really get BOLD
A better understanding of the blood oxygen level dependent, or BOLD, signal requires more support for multimodal imaging studies.
To make fMRI more clinically useful, we need to really get BOLD
A better understanding of the blood oxygen level dependent, or BOLD, signal requires more support for multimodal imaging studies.
Explore more from The Transmitter
Neurophysiology data-sharing system faces funding cliff
After the primary grant supporting Neurodata Without Borders ends in March 2026, the platform may no longer be maintained or kept up to date.
Neurophysiology data-sharing system faces funding cliff
After the primary grant supporting Neurodata Without Borders ends in March 2026, the platform may no longer be maintained or kept up to date.
A change at the top of SfN as neuroscientists gather in San Diego
Kevin B. Marvel, longtime head of the American Astronomical Society, will lead the Society for Neuroscience after a year of uncertainty in the neuroscience field.
A change at the top of SfN as neuroscientists gather in San Diego
Kevin B. Marvel, longtime head of the American Astronomical Society, will lead the Society for Neuroscience after a year of uncertainty in the neuroscience field.
How will neuroscience training need to change in the future?
Training in computational neuroscience, data science and statistics will need to expand, say many of the scientists we surveyed. But that must be balanced with a more traditional grounding in the scientific method and critical thinking. Researchers noted that funding concerns will also affect training, especially for people from underrepresented groups.
How will neuroscience training need to change in the future?
Training in computational neuroscience, data science and statistics will need to expand, say many of the scientists we surveyed. But that must be balanced with a more traditional grounding in the scientific method and critical thinking. Researchers noted that funding concerns will also affect training, especially for people from underrepresented groups.