Plasticity of inhibitory synaptic transmission in the hippocampus

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The building blocks of the brain are nerves cells, also called neurons, connected to each other by synapses. Neurons form two categories: excitatory neurons promote activity in their connected neurons, whereas inhibitory neurons depress activity. Even though inhibitory neurons are less numerous than excitatory neurons (20%), they play a central role in brain function and computation. Disruption of inhibitory neurons leads to an imbalance in excitation and inhibition that can, in turn, lead to diseases such as epilepsy, schizophrenia and autism spectrum disorders. Thus, understanding what regulates the strength of excitatory and inhibitory synapses is an important research goal. Interestingly, although there has been much focus on plasticity of excitatory synapses, plasticity of inhibitory synapses has been largely neglected. In this BBSRC project, we aim to investigate the phenomenology and function of inhibitory synaptic plasticity. The hippocampus is a brain area that plays an important role in episodic memory and spatial navigation. Neuronal network activity in the hippocampus exhibits multiple discrete states that are identified by rhythmic oscillations and perform distinct computational functions. Memories are initially encoded during exploration when theta (5-12Hz) and gamma (30-120Hz) frequency oscillations are prevalent whereas consolidation of memories occurs offline in periods of transient sharp wave ripple (~200Hz) activity during rest or sleep. Specific subtypes of inhibitory neurons have been found to be active in these distinct behavioural states and, intriguingly, inhibitory plasticity has been shown to depend on the precise co-ordination of inhibitory and excitatory neuron firing and on the state of the neural network. This indicates that different behavioural states are likely to trigger distinct forms of inhibitory plasticity at specific inhibitory synapses. However, there is very limited evidence for the role of inhibitory plasticity in the hippocampus.Our hypotheses are that plasticity of inhibitory synapses: a) can regulate network computations, b) is specific to the inhibitory neurons subtypes and c) determines input selectivity for excitatory neurons in a behavioural state dependent manner. We propose a joint effort from an experimental team, which has expertise in synaptic plasticity in the hippocampus, with a computational team that recently proposed a theoretical model of inhibitory plasticity. By a tight interaction allowing the computational model to be informed by and to guide experiments and experiments to refine the model, we aim to investigate how neural activity engages inhibitory plasticity depending on the inhibitory neuron subtype, and how inhibitory plasticity shapes network computations in the hippocampus. This work will provide important information on the mechanisms and function of inhibitory plasticity that will ultimately improve our understanding of how inhibition may be modified in disease states potentially leading to new therapies.