OM DENNE EPISODE
Starting with the work of pioneers like Wilson and Cowan in the 1970s, mean‑field models have become a dominant tool for modeling neural activity at the level of neuronal populations.
Despite their popularity, most mean‑field models have been heuristic and not systematically derived from the underlying 'microscopic' dynamics of individual neurons.
Today's guest has made important contributions towards remedying this situation.
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ANDRE EPISODE I DENNE PODCAST
An important discovery that has come out of computational neuroscience, is that cortical neurons in vivo appear to receive so-called balanced inputs.
In the balanced state the excitatory and inhibitory synaptic inputs to a neuron are about equal, and action potentials occur when a fluctuation temp…
How can computational neuroscience contribute to developing neurotechnology to help people with brain disorders and disabilities?
This was the topic of a panel debate I hosted at the 34th Annual Computational Neuroscience Meeting in Florence in July this year.
Electric or magnetic recording and/o…
Reproducibility is key for scientific progress. If research results cannot be reproduced and trusted, other researchers cannot build on them.
Reproducibility is a challenge also in computational neuroscience, and today's guest has worked on how this can be remedied, for example, through standardiz…
Neurons need particular sodium and potassium concentration gradients across their membranes to function. These gradients are set up by so-called ion pumps which require energy stored in ATP molecules to run.
ATP is the common energy currency in the brain and is produced from nutrients delivered by…
Historically, the analysis of neural recordings focused on responses of single neurons recorded by single-contact electrodes. Modern electrodes with multiple electrode contacts can instead record spikes (action potentials) from hundreds of neurons simultaneously.
Manifold analysis of the overall p…
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