Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity
The ongoing exponential rise in recording capacity calls for new approaches for analysing
and interpreting neural data. Effective dimensionality has emerged as an important property …
and interpreting neural data. Effective dimensionality has emerged as an important property …
Analysis methods for large-scale neuronal recordings
Simultaneous recordings from hundreds or thousands of neurons are becoming routine
because of innovations in instrumentation, molecular tools, and data processing software …
because of innovations in instrumentation, molecular tools, and data processing software …
Climate crisis and ecological emergency: Why they concern (neuro) scientists, and what we can do
Our planet is experiencing severe and accelerating climate and ecological breakdown
caused by human activity. As professional scientists, we are better placed than most to …
caused by human activity. As professional scientists, we are better placed than most to …
Data science and its future in large neuroscience collaborations
Collaborative neuroscience requires systematic data management and analysis. How this is
best done in practice remains unclear. Based on a survey across collaborative neuroscience …
best done in practice remains unclear. Based on a survey across collaborative neuroscience …
[PDF][PDF] Centering inclusivity in the design of online conferences—An OHBM–Open Science perspective
As the global health crisis unfolded, many academic conferences moved online in 2020.
This move has been hailed as a positive step towards inclusivity in its attenuation of …
This move has been hailed as a positive step towards inclusivity in its attenuation of …
Reporting checklists in neuroimaging: promoting transparency, replicability, and reproducibility
Neuroimaging plays a crucial role in understanding brain structure and function, but the lack
of transparency, reproducibility, and reliability of findings is a significant obstacle for the field …
of transparency, reproducibility, and reliability of findings is a significant obstacle for the field …
Deep social neuroscience: The promise and peril of using artificial neural networks to study the social brain
This review offers an accessible primer to social neuroscientists interested in neural
networks. It begins by providing an overview of key concepts in deep learning. It then …
networks. It begins by providing an overview of key concepts in deep learning. It then …
The future of data analysis is now: integrating generative AI in neuroimaging methods development
E DuPre, RA Poldrack - Imaging Neuroscience, 2024 - direct.mit.edu
In this perspective, we highlight how emerging artificial intelligence tools are likely to impact
the experiences of researchers conducting computational fMRI analyses. While calls for the …
the experiences of researchers conducting computational fMRI analyses. While calls for the …
A perspective on neuroscience data standardization with Neurodata Without Borders
Neuroscience research has evolved to generate increasingly large and complex
experimental data sets, and advanced data science tools are taking on central roles in …
experimental data sets, and advanced data science tools are taking on central roles in …
Trainees' perspectives and recommendations for catalyzing the next generation of NeuroAI researchers
Trainees’ perspectives and recommendations for catalyzing the next generation of NeuroAI
researchers | Nature Communications Skip to main content Thank you for visiting nature.com …
researchers | Nature Communications Skip to main content Thank you for visiting nature.com …