Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons DOI
Salvador Durá-Bernal, Beatriz Herrera, Carmen Alina Lupaşcu

и другие.

Journal of Neuroscience, Год журнала: 2024, Номер 44(40), С. e1236242024 - e1236242024

Опубликована: Окт. 2, 2024

Understanding the brain requires studying its multiscale interactions from molecules to networks. The increasing availability of large-scale datasets detailing circuit composition, connectivity, and activity is transforming neuroscience. However, integrating interpreting this data remains challenging. Concurrently, advances in supercomputing sophisticated modeling tools now enable development highly detailed, biophysical models. These mechanistic models offer a method systematically integrate experimental data, facilitating investigations into structure, function, disease. This review, based on Society for Neuroscience 2024 MiniSymposium, aims disseminate recent broader community. It highlights (1) examples current various regions developed through integration; (2) their predictive capabilities regarding cellular mechanisms underlying recordings (e.g., membrane voltage, spikes, local-field potential, electroencephalography/magnetoencephalography) function; (3) use simulating biomarkers diseases like epilepsy, depression, schizophrenia, Parkinson's, aiding understanding underpinnings developing novel treatments. review showcases state-of-the-art covering hippocampus, somatosensory, visual, motor, auditory cortical, thalamic circuits across species. predict neural at multiple scales provide insights sensation, motor behavior, signals, coding, disease, pharmacological interventions, stimulation. Collaboration with neuroscientists clinicians essential validation these models, particularly as grow. Hence, foster interest detailed leading cross-disciplinary collaborations that accelerate research.

Язык: Английский

Integrating multimodal data to understand cortical circuit architecture and function DOI
Anton Arkhipov, Nuno Maçarico da Costa, Saskia de Vries

и другие.

Nature Neuroscience, Год журнала: 2025, Номер unknown

Опубликована: Март 24, 2025

Язык: Английский

Процитировано

1
Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons DOI
Salvador Durá-Bernal, Beatriz Herrera, Carmen Alina Lupaşcu

и другие.

Journal of Neuroscience, Год журнала: 2024, Номер 44(40), С. e1236242024 - e1236242024

Опубликована: Окт. 2, 2024

Understanding the brain requires studying its multiscale interactions from molecules to networks. The increasing availability of large-scale datasets detailing circuit composition, connectivity, and activity is transforming neuroscience. However, integrating interpreting this data remains challenging. Concurrently, advances in supercomputing sophisticated modeling tools now enable development highly detailed, biophysical models. These mechanistic models offer a method systematically integrate experimental data, facilitating investigations into structure, function, disease. This review, based on Society for Neuroscience 2024 MiniSymposium, aims disseminate recent broader community. It highlights (1) examples current various regions developed through integration; (2) their predictive capabilities regarding cellular mechanisms underlying recordings (e.g., membrane voltage, spikes, local-field potential, electroencephalography/magnetoencephalography) function; (3) use simulating biomarkers diseases like epilepsy, depression, schizophrenia, Parkinson's, aiding understanding underpinnings developing novel treatments. review showcases state-of-the-art covering hippocampus, somatosensory, visual, motor, auditory cortical, thalamic circuits across species. predict neural at multiple scales provide insights sensation, motor behavior, signals, coding, disease, pharmacological interventions, stimulation. Collaboration with neuroscientists clinicians essential validation these models, particularly as grow. Hence, foster interest detailed leading cross-disciplinary collaborations that accelerate research.

Язык: Английский

Процитировано

1