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The Transmitter’s favorite podcasts of 2024
Our picks include a deep dive into dopamine, the role of PKMzeta in memory, and studying the stomatogastric ganglion.
The Transmitter’s favorite podcasts of 2024
Our picks include a deep dive into dopamine, the role of PKMzeta in memory, and studying the stomatogastric ganglion.
Seen and heard: The Transmitter’s top multimedia stories in 2023
Our audio, video and photo highlights from the past year help to transport readers into scientists’ lives and research, and the lives of their study participants.
Seen and heard: The Transmitter’s top multimedia stories in 2023
Our audio, video and photo highlights from the past year help to transport readers into scientists’ lives and research, and the lives of their study participants.
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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.