Scientific Understanding of Consciousness
Brain Imaging Challenges
Science 4 November 2011: Vol. 334 no. 6056 pp. 618-623
The Big and the Small: Challenges of Imaging the Brain’s Circuits
Jeff W. Lichtman1, Winfried Denk2
1Molecular and Cellular Biology and Center for Brain Science Harvard University, Cambridge, MA 02138, USA.
2Max-Planck Institute for Medical Research, Department of Biomedical Optics, 69120 Heidelberg, Germany.
The relation between the structure of the nervous system and its function is more poorly understood than the relation between structure and function in any other organ system. We explore why bridging the structure-function divide is uniquely difficult in the brain. These difficulties also explain the thrust behind the enormous amount of innovation centered on microscopy in neuroscience. We highlight some recent progress and the challenges that remain.
A central theme of biology is the relation between the structure and function of things. By structure, we mean the physical form of something, a property that humans can apprehend by touch (if the object is big enough) or by sight. Right now, the leading edge of this effort is the field known by the general name “structural biology” but is focused narrowly on the shapes of molecules in order to provide insights into how proteins such as channels, enzymes, and transcription factors do their jobs. The x-ray crystallography approach commonly used in structural biology does not generate images per se (producing instead diffraction patterns), but with the help of computers humans can change the data into a form that is interpretable intuitively by the visual system. Indeed, all of “imaging” is a means of generating data about an object that depend on location and that are presented so they can be seen and hence interpreted by vision, our most powerful sense.
Here, we will explore why bridging the structure-function divide is uniquely difficult in the brain. These difficulties also explain the thrust behind the enormous amount of innovation centered on microscopy in neuroscience, innovation that has been motivated by the special challenges of understanding how the brain’s functions are related to its especially complicated structure.
Immense Diversity of Cell Types
One unique feature of the brain that frustrates easy understanding of the relation between its structure and function is the immense structural and functional diversity of its cells. The nervous system of Caenorhabditis elegans is miniscule, only ~300 neurons, and yet nearly every single cell is unique in shape and function. In the far larger vertebrate brains, there are certainly structural classes of neurons that, although not having identical morphologies, have enough similarities within a class to be easily identifiable. The retina is a good example. With its iterated tiled structure, its cell classes are easy to recognize because they are repeated at regular intervals and have particular morphologies and molecular properties. Despite this, it is an area of active research to determine the full extent of cell-type diversity in this small part of the nervous system, because the range of cell types continues to grow as the analysis becomes more refined. Moreover, neuronal cellular architecture is so variable from one region to the next that no single area of the brain serves as a guide for anything other than itself. Few believe that learning the full extent of retinal cellular diversity will be of much use in trying to understand the diversity in the cerebral cortex.
Imaging Electrical and Chemical Activity
A second unique feature of the nervous system is that the structural connectivity may ultimately determine function but does not constitute a map of function. The nervous system depends on rapid reversals of membrane potential, known as action potentials, to transmit signals between one part of a neuron and another distant part and depends on smaller, slower changes in member potential at sites of synaptic contact (i.e., synaptic potentials) to mediate the exchange of information between one cell and the next. Action potentials are typically only a few milliseconds in duration, which means direct optical readout of action-potential voltage is a challenge, because, for whatever optical signal one might devise, only relatively few photons would likely be associated with each impulse. Detecting action potentials from many cells in a volume simultaneously would be even more difficult. Synaptic potentials can be orders of magnitude longer in duration than action potentials but are smaller in size, which poses other technical challenges. The development of small-molecule fluorescent calcium indicators, begun in the 1980s, showed that the rise in intracellular calcium, a consequence of neuronal activity, could in many cases serve as a substitute for the direct optical readout of action potential activity. Although in many cases it is only a rough approximation of the number of action potentials, “functional imaging,” as it is called, is a mainstay of linking neural function to individual neurons.
Neurons Extend Over Vast Volumes
Since Cajal’s insight that nerve cells are functionally interconnected in a directional signaling cascade, with axons playing the role of transmitter and dendrites and somata that of receivers, it has been appreciated that neural connectivity holds the key to function. Although neuronal somata are not unusually large, a neuron’s synaptic connections are distributed all through their dendritic and axonal branches. These branches often extend through tissue volumes that are enormous when compared to the actual volume of the cell itself. A pyramidal neuron in the cerebral cortex can have axonal branches that cross to the other hemisphere or go down to the brain stem or even the spinal cord. The dendrites of one pyramidal cell may be circumscribed by a volume of nearly a cubic millimeter. All told, the length of all the branches of one such cell may exceed a centimeter in a mouse and more than a meter in human brain. Thus, fully describing the shape of a single cortical neuron could require sampling a substantial percentage of an entire brain’s volume. But if one wanted to document the sites of all its synaptic connections, the sampling would need to be done at very high resolution to identify all the fine branches containing pre- and postsynaptic sites. Indeed, if one wished to “just” image the complete cell geometry of one neuron along with the complete geometry of the set of all the neurons that are directly pre- and directly postsynaptic to it, that volume would probably require imaging neuronal processes that span nearly the entire brain volume.
The Detailed Structure Cannot Be Resolved by Traditional Light Microscopy
The critical details of neuronal connectivity occur at the level of the synapse. Synapses are densely packed, and in cerebral cortex synapses often connect axons thinner than 100 nm to dendritic spines whose necks are thinner still. The resolution of diffraction-limited light microscopy is insufficient even when used in conjunction with confocal detection, 2P excitation, or—for fast imaging in clear specimens—selective-plane illumination (see above), all so-called optical sectioning techniques that eliminate signals from out-of-focus structures.
Optical super-resolution techniques that truly break the diffraction barrier and rely on the strong nonlinearities of stimulated emission–based deterministic or light activation–based stochastic molecular switching have matured in recent years and are beginning to engage questions about synaptic function and other neurobiological problems. Particularly important problems that are not yet fully overcome include the ability to image multiple colors and to observe dynamic processes at sub-wavelength resolution, even when they are located hundreds of micrometers below the brain’s surface. There are also other serious limitations related to the facts that the overall signal from small structures is proportional to their size and that often labeling densities, especially in vivo, are not high enough to give a sufficiently low noise image of the smallest structures. Moreover, often it is not the physics of the imaging process per se or the label density but rather intrinsic properties of the tissue, especially refractive index inhomogeneities, that distort the wave front and degrade resolution. Adaptive optics, a trick borrowed from astronomy, in which it is used to counteract the effects of Earth’s atmosphere, can improve resolution, signal, and depth penetration, in particular for in vivo imaging. Lastly all these techniques are fluorescence-based, which allows very selective labeling but can make us forget the structural context.
Need for Dense or Saturated Reconstruction
Our present notions of neural circuits are still largely informed by Cajal’s ideas that showed with small arrows the directional flow of information through circuits and pathways. For his insights, the intrinsic inefficiency of the Golgi stain, which labels less than 5% of the neurons, was crucial. This sparse labeling allowed him to propose correctly the law of dynamic polarization, in which axons send signals to dendrites and somata and that information is then passed along to the next neuron by a cell’s axon. But the sparse labeling and his inability to see the signs (inhibitory or excitatory) of connections undermined an understanding of how information was actually processed by the circuits. Such fundamental questions as the number of different inputs a cell receives and the number of target cells a neuron innervates remain unknown even a century later. A small muscle that wiggles the mouse ear is the only place in the mammalian nervous system for which, in some sense, the entire connectivity matrix has been worked out, by complete labeling of all axons using transgenic fluorescent expression. This was possible because the relatively large size and small number of axons allowed a full rendering of all the connections with use of light microscopy and computer-aided manual reconstruction
As circuit analysis finally moves forward, serious questions concerning its utility will be raised. One obvious question concerns the variability in the structure of the brain at the synaptic level. During the study of the mouse ear muscle described above, it became clear that every instantiation of the wiring diagram was different from every other one. Some will take such variability to mean that nothing can be learned from doing this kind of tedious, data-intensive, and highly expensive work. Alternatively, it is likely that one could learn a great deal about the game of chess by watching one game, despite the fact that it is highly unlikely that any two games are identical. It is certainly possible that certain circuit motifs will be recognizable and will be interpretable in a number of contexts. The key may be to make successful use of orthogonal data, such as from functional imaging, to link structure to a cellular or organismal behavior. The links may help decipher the code by which neuronal connections underlie all that we do.
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