AIMC Topic: Neurosciences

Clear Filters Showing 1 to 10 of 149 articles

Bridging Model and Experiment in Systems Neuroscience with Cleo: The Closed-Loop, Electrophysiology, and Optophysiology Simulation Testbed.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Systems neuroscience has experienced an explosion of new tools for reading and writing neural activity, enabling exciting new experiments (e.g., all-optical interrogation, closed-loop control) for interrogating neural circuits. Unfortunately, these a...

Generating synthetic task-based brain fingerprints for population neuroscience using deep learning.

Communications biology
Task-based functional magnetic resonance imaging (fMRI) reveals individual differences in neural correlates of cognition but faces scalability challenges due to cognitive demands, protocol variability, and limited task coverage in large datasets. Her...

Towards a neuroethological approach to consciousness.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Understanding consciousness remains a significant challenge in science. What distinguishes conscious beings from unconscious systems, such as organoids, artificial intelligence or other non-sentient entities? Research on consciousness often focuses o...

From code to archetype: Toward a unified theory of biological, neural, and artificial artifacts.

Bio Systems
Carl Jung's concept of archetypes as innate, universal structures of the human psyche finds surprising resonance with contemporary theories in Code Biology, neuroscience, and artificial intelligence. Archetypes, far from being metaphysical abstractio...

Empowering Data Sharing in Neuroscience: A Deep Learning Deidentification Method for Pediatric Brain MRIs.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging data sets for research. Consequently, pediatric neuroscience research lags adult counterparts,...

Unsupervised alignment in neuroscience: Introducing a toolbox for Gromov-Wasserstein optimal transport.

Journal of neuroscience methods
BACKGROUND: Understanding how sensory stimuli are represented across different brains, species, and artificial neural networks is a critical topic in neuroscience. Traditional methods for comparing these representations typically rely on supervised a...

Letters to the editor generated by AI in neuroscience: The role of neuroethics.

Neuroscience
The letter to the editor (LTE) is a correspondence forum that allows a journal's readers to comment on published research and also publish data and arguments in a brief way. The LTE has vital functions as an accessible comment forum, including holdin...

Leveraging Artificial Intelligence to Reduce Neuroscience ICU Length of Stay.

Journal of healthcare management / American College of Healthcare Executives
GOAL: Efficient patient flow is critical at Tampa General Hospital (TGH), a large academic tertiary care center and safety net hospital with more than 50,000 discharges and 30,000 surgical procedures per year. TGH collaborated with GE HealthCare Comm...

Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification.

Sensors (Basel, Switzerland)
This study explores the link between the emotion "guilt" and human EEG data, and investigates the influence of gender differences on the expression of guilt and neutral emotions in response to visual stimuli. Additionally, the stimuli used in the stu...

Neuroevolution insights into biological neural computation.

Science (New York, N.Y.)
This article reviews existing work and future opportunities in neuroevolution, an area of machine learning in which evolutionary optimization methods such as genetic algorithms are used to construct neural networks to achieve desired behavior. The ar...