In this Historical Perspective, we ask what information is needed beyond connectivity diagrams to understand the function of nervous systems. Informed by invertebrate circuits whose connectivities are known, we highlight the importance of neuronal dynamics and neuromodulation, and the existence of parallel circuits. The vertebrate retina has these features in common with invertebrate circuits, suggesting that they are general across animals. Comparisons across these systems suggest approaches to study the functional organization of large circuits based on existing knowledge of small circuits.
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References
Bock, D.D. et al. Network anatomy and in vivo physiology of visual cortical neurons. Nature 471, 177–182 (2011).
Briggman, K.L. & Bock, D.D. Volume electron microscopy for neuronal circuit reconstruction. Curr. Opin. Neurobiol. 22, 154–161 (2012).
Briggman, K.L., Helmstaedter, M. & Denk, W. Wiring specificity in the direction-selectivity circuit of the retina. Nature 471, 183–188 (2011).
Kleinfeld, D. et al. Large-scale automated histology in the pursuit of connectomes. J. Neurosci. 31, 16125–16138 (2011).
Burrows, M. Monosynaptic connexions between wing stretch receptors and flight motoneurones of the locust. J. Exp. Biol. 62, 189–219 (1975).
Fentress, J.C. Simpler Networks and Behavior (Sinauer Associates, 1976).
Getting, P.A., Lennard, P.R. & Hume, R.I. Central pattern generator mediating swimming in Tritonia. I. Identification and synaptic interactions. J. Neurophysiol. 44, 151–164 (1980).
Stretton, A.O. & Kravitz, E.A. Neuronal geometry: determination with a technique of intracellular dye injection. Science 162, 132–134 (1968).
Remler, M., Selverston, A. & Kennedy, D. Lateral giant fibers of cray fish: location of somata by dye injection. Science 162, 281–283 (1968).
Goodman, C.S. Isogenic grasshoppers: genetic variability in the morphology of identified neurons. J. Comp. Neurol. 182, 681–705 (1978).
Maynard, E.A. Electron microscopy of the stomatogastric ganglion in the lobster, Homarus americanus. Tissue Cell 3, 137–160 (1971).
King, D.G. Organization of crustacean neuropil. I. Patterns of synaptic connections in lobster stomatogastric ganglion. J. Neurocytol. 5, 207–237 (1976).
King, D.G. Organization of crustacean neuropil. II. Distribution of synaptic contacts on identified motor neurons in lobster stomatogastric ganglion. J. Neurocytol. 5, 239–266 (1976).
White, J.G., Southgate, E., Thomson, J.N. & Brenner, S. The structure of the nervous system of the nematode Caenorhabditis elegans. Phil. Trans. R. Soc. Lond. B 314, 1–340 (1986).
Seung, H.S. Reading the book of memory: sparse sampling versus dense mapping of connectomes. Neuron 62, 17–29 (2009).
Meinertzhagen, I.A. & Lee, C.H. The genetic analysis of functional connectomics in Drosophila. Adv. Genet. 80, 99–151 (2012).
Anderson, J.R. et al. Exploring the retinal connectome. Mol. Vis. 17, 355–379 (2011).
Lu, J., Tapia, J.C., White, O.L. & Lichtman, J.W. The interscutularis muscle connectome. PLoS Biol. 7, e32 (2009).
Marder, E. & Bucher, D. Understanding circuit dynamics using the stomatogastric nervous system of lobsters and crabs. Annu. Rev. Physiol. 69, 291–316 (2007).
Nusbaum, M.P. & Beenhakker, M.P. A small-systems approach to motor pattern generation. Nature 417, 343–350 (2002).
Thirumalai, V., Prinz, A.A., Johnson, C.D. & Marder, E. Red pigment concentrating hormone strongly enhances the strength of the feedback to the pyloric rhythm oscillator but has little effect on pyloric rhythm period. J. Neurophysiol. 95, 1762–1770 (2006).
Chalfie, M. et al. The neural circuit for touch sensitivity in Caenorhabditis elegans. J. Neurosci. 5, 956–964 (1985).
Gutierrez, G.J., O'Leary, T. & Marder, E. Multiple mechanisms switch an electrically coupled, synaptically inhibited neuron between competing rhythmic oscillators. Neuron 77, 845–858 (2013).
Sharp, A.A., Skinner, F.K. & Marder, E. Mechanisms of oscillation in dynamic clamp constructed two-cell half-center circuits. J. Neurophysiol. 76, 867–883 (1996).
Jang, H. et al. Neuromodulatory state and sex specify alternative behaviors through antagonistic synaptic pathways in C. elegans. Neuron 75, 585–592 (2012).
Pereda, A.E. et al. Gap junction-mediated electrical transmission: regulatory mechanisms and plasticity. Biochim. Biophys. Acta 1828, 134–146 (2013).
Neyton, J. & Trautmann, A. Physiological modulation of gap junction permeability. J. Exp. Biol. 124, 93–114 (1986).
Guo, Y.M. et al. Imaging dynamic cell-cell junctional coupling in vivo using Trojan-LAMP. Nat. Methods 5, 835–841 (2008).
Marder, E. Neuromodulation of neuronal circuits: back to the future. Neuron 76, 1–11 (2012).
Macosko, E.Z. et al. A hub-and-spoke circuit drives pheromone attraction and social behaviour in C. elegans. Nature 458, 1171–1175 (2009).
Inagaki, H.K. et al. Visualizing neuromodulation in vivo: TANGO-mapping of dopamine signaling reveals appetite control of sugar sensing. Cell 148, 583–595 (2012).
Sharp, A.A., O'Neil, M.B., Abbott, L.F. & Marder, E. Dynamic clamp: computer-generated conductances in real neurons. J. Neurophysiol. 69, 992–995 (1993).
Kawaguchi, Y. & Kondo, S. Parvalbumin, somatostatin and cholecystokinin as chemical markers for specific GABAergic interneuron types in the rat frontal cortex. J. Neurocytol. 31, 277–287 (2002).
Egorov, A.V., Hamam, B.N., Fransen, E., Hasselmo, M.E. & Alonso, A.A. Graded persistent activity in entorhinal cortex neurons. Nature 420, 173–178 (2002).
Aston-Jones, G. & Cohen, J.D. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu. Rev. Neurosci. 28, 403–450 (2005).
Zucker, R.S. & Regehr, W.G. Short-term synaptic plasticity. Annu. Rev. Physiol. 64, 355–405 (2002).
Masland, R.H. The neuronal organization of the retina. Neuron 76, 266–280 (2012).
Grimes, W.N., Zhang, J., Graydon, C.W., Kachar, B. & Diamond, J.S. Retinal parallel processors: more than 100 independent microcircuits operate within a single interneuron. Neuron 65, 873–885 (2010).
Hosoya, T., Baccus, S.A. & Meister, M. Dynamic predictive coding by the retina. Nature 436, 71–77 (2005).
Farrow, K. et al. Ambient illumination toggles a neuronal circuit switch in the retina and visual perception at cone threshold. Neuron 78, 325–338 (2013).
Rivlin-Etzion, M., Wei, W. & Feller, M.B. Visual stimulation reverses the directional preference of direction-selective retinal ganglion cells. Neuron 76, 518–525 (2012).
Witkovsky, P. Dopamine and retinal function. Doc. Ophthalmol. 108, 17–40 (2004).
Ciocchi, S. et al. Encoding of conditioned fear in central amygdala inhibitory circuits. Nature 468, 277–282 (2010).
Marder, E. & Taylor, A.L. Multiple models to capture the variability in biological neurons and networks. Nat. Neurosci. 14, 133–138 (2011).
Milo, R. et al. Network motifs: simple building blocks of complex networks. Science 298, 824–827 (2002).
Markram, H. The blue brain project. Nat. Rev. Neurosci. 7, 153–160 (2006).
Koch, C. & Reid, R.C. Neuroscience: Observatories of the mind. Nature 483, 397–398 (2012).
Alivisatos, A.P. et al. The brain activity map project and the challenge of functional connectomics. Neuron 74, 970–974 (2012).
Koch, C. Systems biology. Modular biological complexity. Science 337, 531–532 (2012).
Varshney, L.R., Chen, B.L., Paniagua, E., Hall, D.H. & Chklovskii, D.B. Structural properties of the Caenorhabditis elegans neuronal network. PLoS Comput. Biol. 7, e1001066 (2011).
Acknowledgements
We thank M. Meister for sharing his knowledge of the retina. C.I.B. is funded by the Howard Hughes Medical Institute. Research in the Marder laboratory relevant to this piece is funded by the US National Institutes of Health (NS17813, NS 81013 and MH46742).
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Bargmann, C., Marder, E. From the connectome to brain function. Nat Methods 10, 483–490 (2013). https://doi.org/10.1038/nmeth.2451
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DOI: https://doi.org/10.1038/nmeth.2451
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