The big picture
Recent articles
Researchers ask colleagues to weigh in on important topics in the field.
Accepting “the bitter lesson” and embracing the brain’s complexity
To gain insight into complex neural data, we must move toward a data-driven regime, training large models on vast amounts of information. We asked nine experts on computational neuroscience and neural data analysis to weigh in.
Accepting “the bitter lesson” and embracing the brain’s complexity
To gain insight into complex neural data, we must move toward a data-driven regime, training large models on vast amounts of information. We asked nine experts on computational neuroscience and neural data analysis to weigh in.
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.
What makes memories last—dynamic ensembles or static synapses?
Teasing out how different subfields conceptualize central terms might help move this long-standing debate forward. I asked eight scientists to weigh in.
What makes memories last—dynamic ensembles or static synapses?
Teasing out how different subfields conceptualize central terms might help move this long-standing debate forward. I asked eight scientists to weigh in.
What are mechanisms? Unpacking the term is key to progress in neuroscience
Mechanism is a common and powerful concept, invoked in grant calls and publication guidelines. But scientists use it in different ways, making it difficult to clarify standards in the field. We asked nine scientists to weigh in.
What are mechanisms? Unpacking the term is key to progress in neuroscience
Mechanism is a common and powerful concept, invoked in grant calls and publication guidelines. But scientists use it in different ways, making it difficult to clarify standards in the field. We asked nine scientists to weigh in.
What, if anything, makes mood fundamentally different from memory?
To better understand mood disorders—and to develop more effective treatments—should we target the brain, the mind, the environment or all three?
What, if anything, makes mood fundamentally different from memory?
To better understand mood disorders—and to develop more effective treatments—should we target the brain, the mind, the environment or all three?
Is the brain uncontrollable, like the weather?
The brain may be chaotic. Does that mean our efforts to control it are doomed?
Is the brain uncontrollable, like the weather?
The brain may be chaotic. Does that mean our efforts to control it are doomed?
Explore more from The Transmitter
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.