The Physics & Astronomy Colloquium Series presents alumnus Suhita Nadkarni of Indian Institute of Science Education and Research (IISER), Pune, India on “Energy-Information Prescription for Synapses” on Friday, March 12, at 4:10 p.m. at an Online Departmental Colloquium.
- Join on your computer or mobile app
- Or call in (audio only)
- +1 614-706-6572,,971522522# United States, Columbus Phone Conference ID: 971 522 522#
Abstract: Synapses are hotspots for learning and memory and can be extremely complex. They possess diverse morphologies, receptor types, ion channels, and second messengers. The differences between synaptic designs across brain areas suggest a link between synaptic form and function. Additionally, several brain disorders have a synaptic basis. However, direct measurements at a synapse are often difficult. Motivated by the synapses’ vital role in brain function and the experimental constraints that may pose a barrier to a complete understanding of brain function, we construct ‘in silico’ models of synapses with unprecedented detail. This modeling framework lets us address fundamental questions about information processing at synapses and make quantitative predictions.
The human brain makes up about 2% of the bodyweight but uses about 25% of the body’s total energy budget. Within that, signal transmission at synapses alone is an energetically expensive process and consumes more than 50% of the brain’s total energy. If every electrical impulse generated in the brain is transmitted to the connected synapses, the brain will need at least five times more energy than it already consumes. The CA3-CA1 synapse in the hippocampus is a crucial component of the neural circuit associated with learning. This synapse has a curiously low fidelity — Only 1 in 5 impulses are transmitted. The low transmission rate suggests a synaptic design that lowers energy consumption is favored. However, unreliable transmission can lead to a massive loss of information. We used information transmission and energy utilization, fundamental constraints that govern the neural organization, to gain insights into the relationship between form and function of this synapse. We show that unreliable neurotransmitter release and its activity-dependent enhancement (short-term plasticity), a characterizing attribute of this synapse, maximizes information transmitted in an energetically cost-effective manner. Remarkably, our analysis reveals that synapse-specific quirks ensure information rate is independent of the release probability. Thus, even as ongoing long-term memory storage continues to fuel heterogeneity in synaptic strengths, individual synapses maintain robust information transmission.
Comments