μ, σ and β in synaptic plasticity A study of synapse organization and plasticity based on variance in synaptic responses

The adult human brain contains over 100 billion neurons, and each neuron is interconnected with other neurons by thousands of contact points called synapses. The strength of these synapses can change, and it is this phenomenon, called synaptic plasticity, that underlies the capacity of experiences to remodel neural circuitry, enabling adaptive behavior, learning and memory. However, for many cases in which synaptic plasticity occurs, the underlying cellular mechanism is still unclear and new tools to study the synaptic changes underlying synaptic plasticity are still required. In this thesis, I validated the variance-to-mean ratio (VMR) as a tool to study the mechanisms underlying synaptic plasticity. The VMR is a statistical tool based on the quantal model of synaptic transmission, and can be used in combination with the conventional quantal measure of the inverse square of the coefficient of variation (1/CV²). I found that calculating both 1/CV² and VMR values of evoked synaptic currents before and after an alteration in synaptic strength allows for a fast and reliable prediction of the source of synaptic plasticity. I then used this variance analysis in combination with other experimental tools to investigate the organization of AMPA-receptor and NMDA-receptor subtypes at synapses onto hippocampal CA1 pyramidal neurons that receive Schaffer collateral input from CA3 neurons, and to investigate multiple types of synaptic plasticity, such as amyloid-β-induced synaptic depression, a phenomenon that is thought to be crucially involved in Alzheimer’s disease, and β-adrenergic activation-induced synaptic potentiation.