AUTHOR=Fesce Riccardo TITLE=Old innovations and shifted paradigms in cellular neuroscience JOURNAL=Frontiers in Cellular Neuroscience VOLUME=18 YEAR=2024 URL=https://www.frontiersin.org/journals/cellular-neuroscience/articles/10.3389/fncel.2024.1460219 DOI=10.3389/fncel.2024.1460219 ISSN=1662-5102 ABSTRACT=

Once upon a time the statistics of quantal release were fashionable: “n” available vesicles (fusion sites), each with probability “p” of releasing a quantum. The story was not so simple, a nice paradigm to be abandoned. Biophysicists, experimenting with “black films,” explained the astonishing rapidity of spike-induced release: calcium can trigger the fusion of lipidic vesicles with a lipid bilayer, by masking the negative charges of the membranes. The idea passed away, buried by the discovery of NSF, SNAPs, SNARE proteins and synaptotagmin, Munc, RIM, complexin. Electrophysiology used to be a field for few adepts. Then came patch clamp, and multielectrode arrays and everybody became electrophysiologists. Now, optogenetics have blossomed, and the whole field has changed again. Nice surprise for me, when Alvarez de Toledo demonstrated that release of transmitters could occur through the transient opening of a pore between the vesicle and the plasma-membrane, no collapse of the vesicle in the membrane needed: my mentor Bruno Ceccarelli had cherished this idea (“kiss and run”) and tried to prove it for 20 years. The most impressive developments have probably regarded IT, computers and all their applications; machine learning, AI, and the truly spectacular innovations in brain imaging, especially functional ones, have transformed cognitive neurosciences into a new extraordinarily prolific field, and certainly let us imagine that we may finally understand what is going on in our brains. Cellular neuroscience, on the other hand, though the large public has been much less aware of the incredible amount of information the scientific community has acquired on the cellular aspects of neuronal function, may indeed help us to eventually understand the mechanistic detail of how the brain work. But this is no more in the past, this is the future.