Josh L. Morgan

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Lichtman Lab

Hi

I am a neuroscientist specializing in imaging the development and synaptic organization of visual circuits.

Current position: Postdoctoral fellow in the lab of Jeff W. Lichtman at Harvard University

Future plans: I hope to continue my research into the organization of synaptic networks and I am in the process of applying for faculty positions.

Why Connections? How do collections of billions of cells organize themselves into the information processing circuitry that generates the mind? Much of this transition from cellular organization to systems organization can be distilled down to the decisions neurons make about who they will form synapses with. The goal of my research is to understand how these decisions are made. My approach has been to use live optical imaging and large scale electron microscopy to study the organization of synaptic connectivity in developing and adult visual systems.

One of the most important lessons I have learned in my studies is that the null hypothesis, the assumption that the default state of a system is random or disconnected is rarely a useful idea in neuroscience. Every neuron has a unique history of interactions with other cells that it leverages to generate its own unique role in the network connectivity of the circuit. By the time neurons are differentiating into circuits they are not a blank slate, but instead reflect organization layered on top of organization layered on top of organization. The fact that this organization can appear random to some analysis speaks only to the fact that the bottom up nature of this organization produces patterns that are not readily apparent from the top down. This fact was apparent when I observed bipolar cells forming axons and dendrites from migratory processes, when I found that synaptic activity plays a role in generating even cell type specific wiring patterns, and when I found that different channels of visual information mix and match in surprisingly complicated patterns within the thalamus.

Why Connectomics? What do biological neural networks look like? It has been more than a hundred years since Ramon y Cajal figured out that cells in the brain were linked together by synapses and more than 70 years since the first computational models of neural networks were developed. Yet in the subsequent years of research it is rare that neuroscientists have been able to directly observe the network organization of neural circuits. Instead, canonical circuits have been constructed by studying one or two neurons at a time in many different subjects and combining these observations together into a composite circuit. While this approach is effective at capturing the most stereotyped features of neural circuits, they fail to capture the interdependency of neurons in real biological circuits. In particular, network properties that emerge only after extended periods of postnatal activity dependent development and learning are unlikely to be successfully inferred by looking at only one or two cells at a time. By imaging every cell and every synapse in a circuit at high resolution, large scale electron microscopy provides an unprecedented view of the synaptic organization of neural circuits. As reconstructing large networks with electron microscopy becomes easier the inferred organization of the nervous system can be replaced with direct observation of the interconnections of hundreds or thousands of neurons. Furthermore, neural networks mapped with electron microscopy reveal much more than which neurons are connected to one another. Large scale electron microscopy also reveals the number, position, size and ultrastructure of each synapse connecting every pair of neurons in a network.