Optical reconstruction of cortical connectivity

One of the greatest challenges in computational neuroscience is to reconstruct the connectivity of large, complex neuronal networks. The ability to decipher circuit connectivity would have a fundamental impact on our understanding of the dynamical properties and the functional organization of the nervous system. Knowledge of prevalent connectivity patterns will also shed light on the developmental constraints and learning rules under which the network might be operating.

Recent developments open new possibilities for collaborative efforts to tackle this basic problem. First, advances in two-photon imaging and photostimulation methods make it possible to observe the simultaneous activity of large ensembles of neurons, while stimulating neurons in arbitrary spatiotemporal patterns. Second, new statistical methods for extracting action potential timing information from calcium imaging data, and for modeling the response properties of small collections of neurons, are now efficient enough that they may be implemented on-line and scaled up to understand the function of large networks.

The investigators will combine these new experimental and analytical methods to estimate, for the first time, the connectivity diagram of large neocortical circuits, using two-photon calcium imaging of spontaneous and evoked activity in thalamocortical slices. A key novel step here is to directly verify the estimated circuit model with two-photon glutamate uncaging, which allows any neuron in the circuit to be activated (with single-cell resolution) while the evoked postsynaptic responses are monitored.

This interdisciplinary project has three complementary specific aims: (1) Develop statistically-optimal methods for real-time inference of spike timing from calcium imaging data. (2) Use these spike timing inference methods to estimate the network connectivity from large-scale multineuronal calcium-imaging of cortical slices. (3) Confirm the derived connectivity maps with glutamate uncaging and patch clamping, by photoactivating putative presynaptic neurons while recording intracellularly from postsynaptic cells. The proposed methods should also prove applicable to study other central and peripheral regions of the nervous system; data analysis software will be made publicly available online, to enhance the infrastructure for research and education in computational neuroscience.