Astrocytes make up about a third of the cells in your brain, and form a second, distinct brain network from the more-studied neuronal network. As neuroscience has discovered in only the last few years, the astrocyte network carries out extremely important computations, integrating information from across different brain networks, and using this information to drive feedback to neurons that controls physiological state and maintains long-term homeostasis.
Open-source software reveals complete 3D architecture of brain cells
The neurons in our brain that underlie thought connect to each other using tiny branch-like structures on their surfaces known as dendritic spines. Now scientists at Columbia's Zuckerman Institute and ...
nubrain - A foundation model for neural decoding
Building the world's largest dataset of human brain activity.
E11 Bio | Moonshot Neuroscience
An FRO building scalable single-cell brain circuit mapping.
Inventing the future: A neuroscience research roadmap
The past decade of transformative advances in neurotechnology portends an exciting future for neuroscience. This NeuroView charts a strategic path to accelerate and integrate research discovery and speed the development of new cures for human brain disorders.
Single-cell multiregion dissection of Alzheimer’s disease
Alzheimer’s disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1–3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer’s disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer’s disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer’s disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer’s disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer’s disease pathology.
CatalystNeuro - Neurophysiology Data & Software Solutions
CatalystNeuro empowers neuroscience labs with data standardization, NWB conversions, spike sorting pipelines, and open-source software tools for neurophysiology research.
Neuropeek — Accelerating the Neuro-AI convergence
Where brain data becomes shared knowledge. A community-driven platform federating neuroscience datasets, models, and tools to accelerate discovery.
The neuron as a direct data-driven controller | PNAS
In the quest to model neuronal function amid gaps in physiological data, a promising strategy is to develop a normative theory that interprets neur...
#digitalbrainproject #neuroscience #artificialintelligence #openscience #callforprojects #research #ai #brain | Fondation Adolphe de Rothschild
The Rothschild Foundation Hospital is excited to launch the Digital Brain Project, a $5M collaborative research initiative to build an open source foundational model of the brain through open-access neural data. Apply by May 15th for up to $500k in funding. Help crack the neural code 👉digitalbrainproject.org Our objective is to develop a standardized, publicly available dataset of human brain recordings to accelerate fundamental research in cognitive neuroscience, AI system development, and clinical health. Our independent, multidisciplinary Scientific Committee oversees data collection, ethical review, privacy, and open science practices of our project — setting standards for large-scale brain research. The Digital Brain Project is conceived as an open collaborative infrastructure, at the intersection of neuroscience, artificial intelligence, and data science. It aims to accelerate data development, a key bottleneck to developing a foundational AI model of the human brain. Key Focus Areas: 1️⃣ Brain recording data related to visual processing, language functions and cognitive actions 2️⃣ Rigorous quality, privacy, and ethical control, along with procedures for standardizing data across sites 3️⃣ Support for teams selected by an international multidisciplinary Scientific Committee Call for applications: Research teams working in neuroscience, neuroimaging, or artificial intelligence are invited to submit their applications by May 15, 2026. Selected teams will receive up to $500k USD funding to support their work. We appreciate our Scientific Committee (Lune Bellec Anne-Marie Kermarrec Arthur Mensch Russell Poldrack Lucia Melloni Jose Alain Sahel) for their independent scientific leadership, and partners Université de Montréal and AI at Meta for collaborating on this exciting project. #DigitalBrainProject #Neuroscience #ArtificialIntelligence #OpenScience #Callforprojects #Research #AI #Brain -------------------------------------------------------------- Pierre Bourdillon Julie Boyle Elisa Cascardi Jean-Rémi King Guillaume Le Hénanff Amélie Yavchitz Julien Gottsmann Fabrice VERRIELE Charlotte Cardin-Taillia
The brain in the machine: How AI could help explain how we think | IBM
Scientists are using large AI models to predict patterns of brain activity at scale, a development that researchers say is pushing neuroscience toward a new kind of digital imaging.
DANDI
DANDI: Distributed Archives for Neurophysiology Data Integration The DANDI platform is supported by the BRAIN Initiative for publishing, sharing, and processing neurophysiology data. The archive accepts cellular neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments. The platform is now available for data upload and distribution. The storage of data in the archive is also supported by the Amazon Opendata program. The data in the archive can be browsed using the Data Portal. For detailed instructions on how to interact (view, upload, download, process) with DANDI click here.
BrainMind
At this important juncture in neuroscience, the BrainMind ecosystem is combining the most talented of these groups in novel ways to collectively shepherd, support, and fund ideas that can be translated from labs into interventions that will benefit humanity.
Learning Outside the Brain: Integrating Cognitive Science and Systems Biology
Learning is commonplace in organisms such as ourselves and even in organisms as far distant as the bee and the octopus. Such learning is implemented by brains, or neuronal networks, and has been extensively studied within ethology, psychology, cognitive science, and neuroscience. Whether learning also takes place in nonneuronal settings has remained a matter of sustained controversy, too often dominated by ideological views. In this survey, I will explain how learning can be rigorously interpreted as a form of information processing and then explore the evidence for whether learning also takes place in organismal contexts outside the brain, such as physiology, development, and individual cells. I will try to explain why it is important to build bridges in this way between cognitive science and systems biology, why concepts and methods from various branches of engineering may be helpful in this task, and what the eventual impact may be on how we think about the organism.
Leading Innovation in Psychiatric Treatment | Alto Neuroscience
We leverage brain biology to develop personalized medicines, helping patients get better faster.
brainlife
The platform allows to analyze Magnetic Resonance Imaging (MRI), electroencephalography (EEG) and magnetoencephalography (MEG) data. Data can either be uploaded from local computers or imported from public archives such as OpenNeuro.org. Over 400+ data processing Apps are available on brainlife.io to build custom data workflows. Thousands of jobs can be submitted using shared clusters or on users' compute resource. Users can perform group-level statistical analysis or apply machine learning methods using Jupyter notebooks. A single record containing the entire data workflow (from raw data to published figures) can be published addressed by with a unique digital object identifier (DOI).
