Synaptic plasticity underlies several key brain functions including learning, information filtering and homeostatic regulation of overall neural activity.
While several mathematical rules have been developed for plasticity both at excitatory and inhibitory synapses, it has been difficult to make such rules co-exist in network models.
Recently the group of the guest has explored how co-dependent plasticity rules can remedy the situation and, for example, assure that long-term memories can be stored in excitatory synapses while inhibitory synapses assure long-term stability.
Links:
- Vogels et al: “Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks”, Science (2011)
- Bozelos & Vogels: “Talking science, online”, Nature Reviews Neuroscience (2021)
- Agnes & Vogels: “Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks”, Nature Neuroscience (2024)
- Confavreux et al: “Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks”, PLoS Computational Biology (2025)
- World Wide Neuro
- Lab of Tim Vogels
The podcast was recorded on May 23rd, 2025 and lasts 1 hour and 30 minutes.
To become a Patreon supporter of the podcast, go to patreon.com/TheoreticalNeurosciencePodcast .
In addition to the access via the link above, the audio version of the podcast is also available through major podcast providers such as Apple, Spotify, and Amazon Music/Audible.
The video version is available for Patreon supporters via patreon.com/TheoreticalNeurosciencePodcast or at the YouTube channel www.youtube.com/@TheoreticalNeurosciencePodcast .