Attila Losonczy, MD, PhD
A fundamental capacity of the mammalian cerebral cortex is to process information in a form conducive to encoding, storage and retrieval of memories. A general organizational principle of cortical mnemonic circuits states that these steps all require a precisely orchestrated spatio-temporal interaction among a large number of relatively uniform excitatory and a numerically fewer but richly diverse population of inhibitory and neuromodulatory circuit elements. However, a mechanistic understanding of how these circuit motifs interact during elementary steps of memory processing is lacking. Our general hypothesis is that single neurons perform complex computations by exploiting their multilayered and compartmentalized dendritic arborization. Specifically, we hypothesize that, (1) neuronal dendritic arbor constitutes a backbone for both compartmentalized input integration and plasticity, and (2) dynamic interactions between synaptic and intrinsic forms of neuronal plasticity can expand neuron’s capability to detect, store and recall various features of information.
To test these predictions, we use a variety of techniques: direct electrophysiological recordings from various compartments of neurons, simultaneous patch-clamp recordings from multiple neurons, together with two-photon imaging/photoactivation and optogenetics.
A major focus of our lab will be to understand how dynamic spatio-temporal interactions among excitatory, inhibitory and neuromodulatory inputs in different subcellular domains fundamentally enhance information processing and storage capabilities of single and small networks of neurons in the hippocampal circuit
Another aspect of our work will focus on testing the prediction that intrinsic and synaptic forms of neuronal plasticity bidirectionally interact within dendritic compartments. We also aim to reveal exact mechanisms how these different forms of neuronal plasticity are affected by inhibition and neuromodulation.
The long-term goal of our laboratory is to establish causal links between single cell computations and behavior.