23 January 2005. Using two-photon microscopy, Clay Reid and colleagues at Harvard Medical School have peered into the brains of rats and cats to see real-time images of neuronal circuitry in action at the single-cell level. Their technique, reported in an advanced online publication in yesterday’s Nature, could potentially be used to dissect the basis for cognitive problems in animal models of neurodegenerative disorders such as Alzheimer disease, according to Bradley Hyman from Massachusetts General Hospital.
Reid and colleagues adopted the microscope to study micro-architecture in the cerebral cortex. It has been known for some time that cortical neurons can be organized into distinct columns of cells that often fire in unison. Because such columns, or clusters, have only been mapped at relatively low resolution, it has been unclear what happens at the borders between them. Take sight, for example. In some animals, clusters of neurons are known to respond to stimuli from a specific direction. Thus, one column fires when an object moves up through the field of vision, another when the object moves down. Are up neurons ever in the down cluster, and vice versa? This has been an outstanding question.
First author Kenichi Ohki and colleagues addressed this by measuring firing patterns as animals respond to visual stimuli. To facilitate the imaging, Ohki loaded the cortical neurons with the calcium-dependent fluorophore OGB-1 AM. This probe fluoresces when the intracellular calcium concentration increases, as it does when the neuron depolarizes and fires. The authors then exposed the animals to bands of moving lines and measured the firing of thousands of neurons in the visual cortex with the two-photon microscope. Focusing the microscope sequentially on several planes, 10-20 μmeters apart, Ohki and colleagues built up a 3-D map of neuronal circuitry at single-cell resolution. Imaging software allowed each flashing neuron to be identified and tracked over time.
The technique confirmed a major difference between the architecture in the visual cortices of rats and cats. Low-resolution mapping using more traditional electrical and optical measurements had indicated that cat visual cortex is highly organized, whereas the rat visual cortex is in disarray. Reid’s work confirms this but also shows that the cat visual cortex is even more highly organized than anyone would have predicted. Clusters of neurons are so tightly integrated in their response to the orientation of a stimulus, that hardly one neuron is out of place (to the fastidious cat, with hardly ever a hair out of place, this would probably come as no surprise). The organization is exquisitely demonstrated in the accompanying short movie files.
In cats, though cells closer to column borders were progressively less directionally sensitive, the authors found that these cells always had a preference and that it was in keeping with the preference of the cluster as a whole. In fact, “the border between cells [clusters] that were biased for opposite directions was so sharp that a straight line perfectly segregated them,” write the authors.
From their data, Reid and colleagues describe three “regimes of functional micro-organization.” First, in the rat, neurons in the visual cortex do have a “direction preference,” though there is no apparent clustering of similarly biased neurons together. Second, in the cat, the opposite is true—neurons with the same direction bias stick together. And third, again in the cat, there are what the authors call “extraordinarily sharp direction discontinuities,” or borders between clusters.
What advantage this fine circuitry may bring to the cat is unclear, but given the well-known evolution of extraordinary visual acuity in felines, facilitated in part by a mirror-like layer behind the retina to increase light capture, the authors wonder if the well-ordered cortical circuits may sharpen their visual responses.—Tom Fagan.
Ohki K, Chung S, Ch’ng YH, Kara P, Reid RC. Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature. January 19, 2005. Advance online publication. Abstract