William T. Katz

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Animal behaviour arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive.(More)
The aim in high-resolution connectomics is to reconstruct complete neuronal connectivity in a tissue. Currently, the only technology capable of resolving the smallest neuronal processes is electron microscopy (EM). Thus, a common approach to network reconstruction is to perform (error-prone) automatic segmentation of EM images, followed by manual(More)
We reconstructed the synaptic circuits of seven columns in the second neuropil or medulla behind the fly's compound eye. These neurons embody some of the most stereotyped circuits in one of the most miniaturized of animal brains. The reconstructions allow us, for the first time to our knowledge, to study variations between circuits in the medulla's(More)
The promise of extracting connectomes and performing useful analysis on large electron microscopy (EM) datasets has been an elusive dream for many years. Tracing in even the smallest portions of neuropil requires copious human annotation, the rate-limiting step for generating a connectome. While a combination of improved imaging and automatic segmentation(More)
We describe an algorithm for segmentation of 3D nagnetic resonance images into major neuroanatomical tructures with minimal requirement for user interaction. ~his technique incorporates a priori knowledge of ¯ olumes and surfaces present in the head, but permits xtensive deviation from these assumptions to ccommodate the wide morphological variability seen(More)
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