Prof. Idan Segev, together with 5 colleagues from top US universities (MIT, Harvard, NYU, Columbia, and Stanford), was awarded a $13M grant for 5 years from the inaugural Collaborative Opportunities for Multidisciplinary, Bold, and Innovative Neuroscience (COMBINE) program by the National Institute of Neurological Disorders and Stroke (NINDS). The mission of this team is to develop a “Rosetta Stone” model of pyramidal neurons from the mouse neocortex, based on its complete 3D electron-microscope (EM) reconstruction, including a full map of its ~10,000 synaptic inputs and the dendritic spines that serve as the sites for synaptic inputs (see example in the Figure above). This will provide a new high-resolution understanding of neurons as input/output plastic (learning) devices and will shed light on information processing in cortical neurons. This knowledge could be used for future studies of neurons and neuronal networks in both normal and pathological states.

The traditional paradigm of how neurons work assumes the excitatory and inhibitory synaptic inputs that they receive on the tree-like (dendritic) structure are summed up linearly at the cell body where an output is generated. However, dendrites are electrically-active nonlinear structures that could mediate and control which of the many thousands of its synaptic inputs are integrated and which are not. Furthermore, recent data suggests that local clusters of excitatory synaptic inputs may affect each other plastically – serving as local memory “hubs” of neurons, and that often the neuron’s output is generated when these clusters of synapses are activated together, triggering large local “dendritic spikes”.

For this mission, an interdisciplinary consortium of laboratories was assembled and will use state-of-the-art experimental and computational methods, including genetically-encoded voltage indicators (GEVIs), volumetric two-photon imaging, holographic optogenetics and optochemistry, dendritic patching, EM connectomics, super-resolution synaptic mapping, and computational models. The team will examine with unprecedented detail the structure, in vivo function, and computational function of dendrites of pyramidal neurons in the visual cortex. This work will elucidate the principles underlying the the operation of the main processing unit of the cortex – and generate a series of complete morphological, connectivity, functional, and computational datasets that could be used as “Rosetta Stones” by the field for future studies.