How do real neural networks, composed of numerous different types of neurons, interconnected by complex arrangements of synapses, process information? Randy M. Bruno, Ph.D., Assistant Professor at the Department of Neuroscience, Columbia University, NY, USA is pursuing this question using the rodent whisker-barrel system. Here, anatomically and functionally distinct networks - barrels and barrel columns - are clearly identifiable, and the sensory transducers that provide input are directly controllable. With a variety of paired-recording techniques he investigates the mechanism for propagating information between thalamus and cortex, to study receptive field generation in excitatory and inhibitory neurons, and to demonstrate micro-organization of inputs to cortical columns. Using imaging techniques such as a broadband confocal system and a custom two-photon microscope, Professor Bruno visualizes neuronal dendritic arborisation of neurons and their synaptic interconnections.

Research Focus

The focus of Professor Bruno's research is on cortical circuitry with the aim of finding out how one circuit, iterated over the entire neocortex, solves tactical, visual, and cognitive problems. Despite their diverse functions, the many distinct areas of neocortex have the same cell types arranged in the same laminar structures, and having the same general connectivity with each other and with other areas of the brain. It is as if nature reiterated this one circuit for many different tasks. His goal is to reverse engineer that circuit.

As a physiologist, Bruno routinely records activity from individual neurons or groups of neurons to assess what the neuronal population is doing. But in the process of doing this he and his team become anatomists because they need to know how the neurons are connected, too. They can use conventional tracers or newer methodologies like viral expression of fluorescence protein, to label large groups of anatomical connections. And, in the course of recording from single cells, they can label individual cells' dendrites and axons. As they start to look at pairs of neurons, they try to figure out the connectivity between individual cell types, or two particular cells, and get back to what the real circuit is.

Model Organisms to Investigate Different Connectivities

To study the barrel cortex they work with rat and mouse.

These two common laboratory species rely heavily on their senses of touch and smell because they are nocturnally active. Rodents have a stereotypical pattern of large facial whiskers which they use for tactile sensation the way humans use finger tips. They swipe their whiskers back and forth over objects and textures as they explore their environments, and they do it with the same frequency of palpation that humans use when we stroke our fingertips across something. They have similar psycho-physical thresholds, so they can discriminate surfaces a little better than humans can, but they are basically very similar. The information from whiskers is processed by the barrel cortex. Barrels are very easily identified anatomical structures in the cortex: each barrel, a group of thousands of neurons, maps on to one whisker. So Bruno and his team now have a discrete sensory organ that they can control - a whisker - and an identifiable network that is listening to it. They can control the input and take apart the network. They perform electrophysiology and imaging on anesthetized, sedated, and conscious head-fixed animals and are now moving to behavioral studies because ultimately sensation is an active process.

Technical Approaches

The Bruno Lab primarily uses "in vivo" (living animal) preparations but also does some "in vitro" work with brain slices. They heavily rely on whole-cell recording in vivo to actually patch into neurons and record intracellular membrane potential as well as action potentials. They value this approach highly for looking at synaptic inputs and consider it key to their research. They also use conventional physiology recording techniques like extracellular recording of single units and local field potentials. Brightfield, epifluorescence, and confocal imaging are extensively used for anatomical studies of dendrites and axons of single cells they have recorded from. For examining large axonal tracks, they employ conventional tracers and viral mediated expression of GFP and many fluorophores.

For anatomical purposes, Bruno and his team use a Leica TCS SP5 broadband confocal. On fixed tissues they image either GFP or dyes like Alexa. A custom two-photon microscope is used for anesthetized and conscious in vivo experiments, in which a variety of synthetic dyes report voltage or calcium levels. The lab is also experimenting with different viruses for expressing different genetically encoded indicators.

Outlook

Although Bruno finds the possibilities offered by today's technology exciting, he points out that scientists are almost insatiable when it comes to technology. When he uses confocal imaging of fixed tissue to map out structures and detailed morphology, for example, he does not image for the purposes of getting nice pictures, but is usually trying to obtain something he can quantify. That often means that he scans large structures (hundreds of microns) in 3D, but has limited resolution due to diffraction limits.

Bruno believes that new technologies such as STED and the OPO laser can contribute toward solving the problems of the diffraction limit and the depth of recording, but he doubts that they will be able to overcome all limitations. One field for new development is better dyes, especially with regard to sensitivity. These are problems that neuroscientists are desperately waiting for molecular biologists and organic chemists to overcome. To do good neuroscience these days, says Bruno, you have to frequently combine incredibly different skill sets. You need computer programming, molecular biology, physiology, anatomy, physics, and chemistry, just to mention the most important ones. Nevertheless, Professor Bruno greatly enjoys his work because of the large number of distinct skill sets involved and people to collaborate with.

References
[1] Bruno R.M. and Sakmann B.: Science 312: 1622-1627, (2006)
[2] Oberlaender M. et al.: J.Biomed.Optics 12: 064029, (2007)
[3] Kuhn B. et al.: Proc.Nat'l.Acad.Sci. 105: 7588-7593, (2008)
[4] Wimmer V.C. et al.: J.Comp.Neurol. 518: 4629-4648, (2010)