Journal of Comparative Physiology A

, Volume 192, Issue 8, pp 777–784 | Cite as

How silent is the brain: is there a “dark matter” problem in neuroscience?

Review

Abstract

Evidence from a variety of recording methods suggests that many areas of the brain are far more sparsely active than commonly thought. Here, we review experimental findings pointing to the existence of neurons which fire action potentials rarely or only to very specific stimuli. Because such neurons would be difficult to detect with the most common method of monitoring neural activity in vivoextracellular electrode recording—they could be referred to as “dark neurons,” in analogy to the astrophysical observation that much of the matter in the universe is undetectable, or dark. In addition to discussing the evidence for largely silent neurons, we review technical advances that will ultimately answer the question: how silent is the brain?

References

  1. Abeles M (1991) Corticonics: neural circuits of the cerebral cortex. Cambridge University Press, CambridgeGoogle Scholar
  2. Abeles M, Gerstein GL (1988) Detecting spatiotemporal firing patterns among simultaneously recorded single neurons. J Neurophysiol 60:909–924PubMedGoogle Scholar
  3. Amassian VE (1953) Evoked single cortical unit activity in the somatic sensory areas. Electroencephalogr Clin Neurophysiol Suppl 5:415–438CrossRefGoogle Scholar
  4. Barlow HB (1972) Single units and sensation: a neuron doctrine for perceptual psychology? Perception 1:371–394PubMedCrossRefGoogle Scholar
  5. Beloozerova IN, Sirota MG, Swadlow HA (2003) Activity of different classes of neurons of the motor cortex during locomotion. J Neurosci 23:1087–1097PubMedGoogle Scholar
  6. Binzegger T, Douglas RJ, Martin KA (2004) A quantitative map of the circuit of cat primary visual cortex. J Neurosci 24:8441–8453PubMedCrossRefGoogle Scholar
  7. Blanche TJ, Spacek MA, Hetke JF, Swindale NV (2005) Polytrodes: high-density silicon electrode arrays for large-scale multiunit recording. J Neurophysiol 93:2987–3000PubMedCrossRefGoogle Scholar
  8. Brecht M, Sakmann B (2002) Dynamic representation of whisker deflection by synaptic potentials in spiny stellate and pyramidal cells in the barrels and septa of layer 4 rat somatosensory cortex. J Physiol 543:49–70PubMedCrossRefGoogle Scholar
  9. Brecht M, Roth A, Sakmann B (2003) Dynamic receptive fields of reconstructed pyramidal cells in layers 3 and 2 of rat somatosensory barrel cortex. J Physiol 553:243–265PubMedCrossRefGoogle Scholar
  10. Brecht M, Fee MS, Garaschuk O, Helmchen F, Margrie TW, Svoboda K, Osten P (2004) Novel approaches to monitor and manipulate single neurons in vivo. J Neurosci 24:9223–9227PubMedCrossRefGoogle Scholar
  11. Chadderton P, Margrie TW, Hausser M (2004) Integration of quanta in cerebellar granule cells during sensory processing. Nature 428:856–860PubMedCrossRefGoogle Scholar
  12. Diamond ME, Armstrong-James M, Ebner FF (1993) Experience-dependent plasticity in adult rat barrel cortex. Proc Natl Acad Sci USA 90(5):2082-2086PubMedCrossRefGoogle Scholar
  13. DeWeese MR, Wehr M, Zador AM (2003) Binary spiking in auditory cortex. J Neurosci 23:7940–7949PubMedGoogle Scholar
  14. Fiete IR, Hahnloser RH, Fee MS, Seung HS (2004) Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong. J Neurophysiol 92:2274–2282PubMedCrossRefGoogle Scholar
  15. Freund TF, Buzsaki G (1996) Interneurons of the hippocampus. Hippocampus 6:347–470PubMedCrossRefGoogle Scholar
  16. Georgopoulos AP, Kalaska JF, Caminiti R, Massey JT (1982) On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex. J Neurosci 2:1527–1537PubMedGoogle Scholar
  17. Georgopoulos AP, Schwartz AB, Kettner RE (1986) Neuronal population coding of movement direction. Science 233:1416–1419PubMedCrossRefGoogle Scholar
  18. Gray CM, Maldonado PE, Wilson M, McNaughton B (1995) Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex. J Neurosci Methods 63:43–54PubMedCrossRefGoogle Scholar
  19. Gross CG (2002) Genealogy of the “grandmother cell”. Neuroscientist 8:512–518PubMedCrossRefGoogle Scholar
  20. Hahnloser RH, Kozhevnikov AA, Fee MS (2002) An ultra-sparse code underlies the generation of neural sequences in a songbird. Nature 419:65–70PubMedCrossRefGoogle Scholar
  21. Hasan MT, Friedrich RW, Euler T, Larkum ME, Giese G, Both M, Duebel J, Waters J, Bujard H, Griesbeck O, Tsien RY, Nagai T, Miyawaki A, Denk W (2004) Functional fluorescent Ca2+ indicator proteins in transgenic mice under TET control. PLoS Biol 2:e163PubMedCrossRefGoogle Scholar
  22. Heeger DJ, Huk AC, Geisler WS, Albrecht DG (2000) Spikes versus BOLD: what does neuroimaging tell us about neuronal activity? Nat Neurosci 3:631–633PubMedCrossRefGoogle Scholar
  23. Henze DA, Borhegyi Z, Csicsvari J, Mamiya A, Harris KD, Buzsaki G (2000) Intracellular features predicted by extracellular recordings in the hippocampus in vivo. J Neurophysiol 84:390–400PubMedGoogle Scholar
  24. Holt GR, Koch C (1999) Electrical interactions via the extracellular potential near cell bodies. J Comput Neurosci 6:169–184PubMedCrossRefGoogle Scholar
  25. Hubel DH (1957) Tungsten microelectrode for recording from single units. Science 125:549–550PubMedCrossRefGoogle Scholar
  26. Lennie P (2003) The cost of cortical computation. Curr Biol 13:493–497PubMedCrossRefGoogle Scholar
  27. Margrie TW, Brecht M, Sakmann B (2002) In vivo, low-resistance, whole-cell recordings from neurons in the anaesthetized and awake mammalian brain. Pflugers Arch 444:491–498PubMedCrossRefGoogle Scholar
  28. Marr D (1969) A theory of cerebellar cortex. J Physiol 202:437–470PubMedGoogle Scholar
  29. Maunsell JH, Van Essen DC (1983) Functional properties of neurons in middle temporal visual area of the macaque monkey. I. Selectivity for stimulus direction, speed, and orientation. J Neurophysiol 49:1127–1147PubMedGoogle Scholar
  30. Mountcastle VB, Davies PW, Berman AL (1957) Response properties of neurons of cat’s somatic sensory cortex to peripheral stimuli. J Neurophysiol 20:374–407PubMedGoogle Scholar
  31. Ohki K, Chung S, Ch’ng YH, Kara P, Reid RC (2005) Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433:597–603PubMedCrossRefGoogle Scholar
  32. O’Keefe J, Dostrovsky J (1971) The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res 34:171–175PubMedCrossRefGoogle Scholar
  33. Olshausen BA, Field DJ (2004) Sparse coding of sensory inputs. Curr Opin Neurobiol 14:481–487PubMedCrossRefGoogle Scholar
  34. Olshausen BA, Field DJ (2005) How close are we to understanding v1? Neural Comput 17:1665–1699PubMedCrossRefGoogle Scholar
  35. Pouget A, Dayan P, Zemel RS (2003) Inference and computation with population codes. Annu Rev Neurosci 26:381–410PubMedCrossRefGoogle Scholar
  36. Quiroga RQ, Reddy L, Kreiman G, Koch C, Fried I (2005) Invariant visual representation by single neurons in the human brain. Nature 435:1102–1107PubMedCrossRefGoogle Scholar
  37. Raichle ME, Gusnard DA (2002) Appraising the brain’s energy budget. Proc Natl Acad Sci USA 99:10237–10239PubMedCrossRefGoogle Scholar
  38. Rall W (1962) Electrophysiology of a dendritic neuron model. Biophys J 2(2Pt 2):145–167PubMedCrossRefGoogle Scholar
  39. Rieke F (1997) Spikes: exploring the neural code. MIT Press, CambridgeGoogle Scholar
  40. Robinson DA (1968) The electrical properties of metal microelectrodes. Proc IEEE 56:1065–1071CrossRefGoogle Scholar
  41. Rosenblatt F (1962) Principles of neurodynamics. Spartan, New YorkGoogle Scholar
  42. Segev R, Shapira Y, Benveniste M, Ben-Jacob E (2001) Observations and modeling of synchronized bursting in two-dimensional neural networks. Phys Rev E Stat Nonlin Soft Matter Phys 64:011920PubMedGoogle Scholar
  43. Segev R, Goodhouse J, Puchalla J, Berry MJ II (2004) Recording spikes from a large fraction of the ganglion cells in a retinal patch. Nat Neurosci 7:1154–1161PubMedCrossRefGoogle Scholar
  44. Sholl DA (1956) The organization of the cerebral cortex. Methuen, LondonGoogle Scholar
  45. Singer W (1999) Neuronal synchrony: a versatile code for the definition of relations? Neuron 24:49–65, 111–125Google Scholar
  46. Song S, Sjostrom PJ, Reigl M, Nelson S, Chklovskii DB (2005) Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biol 3:e68PubMedCrossRefGoogle Scholar
  47. Stepanyants A, Hof PR, Chklovskii DB (2002) Geometry and structural plasticity of synaptic connectivity. Neuron 34:275–288PubMedCrossRefGoogle Scholar
  48. Stosiek C, Garaschuk O, Holthoff K, Konnerth A (2003) In vivo two-photon calcium imaging of neuronal networks. Proc Natl Acad Sci USA 100:7319–7324PubMedCrossRefGoogle Scholar
  49. Sullivan MR, Nimmerjahn A, Sarkisov DV, Helmchen F, Wang SS (2005) In vivo calcium imaging of circuit activity in cerebellar cortex. J Neurophysiol 94:1636–1644PubMedCrossRefGoogle Scholar
  50. Swadlow HA (1998) Neocortical efferent neurons with very slowly conducting axons: strategies for reliable antidromic identification. J Neurosci Methods 79:131–141PubMedCrossRefGoogle Scholar
  51. Swadlow HA, Hicks TP (1996) Somatosensory cortical efferent neurons of the awake rabbit: latencies to activation via supra–and subthreshold receptive fields. J Neurophysiol 75:1753–1759PubMedGoogle Scholar
  52. Thompson LT, Best PJ (1989) Place cells and silent cells in the hippocampus of freely-behaving rats. J Neurosci 9:2382–2390PubMedGoogle Scholar
  53. Towe AL, Harding GW (1970) Extracellular microelectrode sampling bias. Exp Neurol 29:366–381PubMedCrossRefGoogle Scholar
  54. Wang JW, Wong AM, Flores J, Vosshall LB, Axel R (2003) Two-photon calcium imaging reveals an odor-evoked map of activity in the fly brain. Cell 112:271–282PubMedCrossRefGoogle Scholar
  55. Yuste R, Maclean JN, Smith J, Lansner A (2005) Opinion: the cortex as a central pattern generator. Nat Rev Neurosci 6:477–483PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Shy Shoham
    • 1
    • 2
  • Daniel H. O’Connor
    • 2
  • Ronen Segev
    • 2
  1. 1.Faculty of Biomedical EngineeringTechnion-Israel Institute of TechnologyTechnion, HaifaIsrael
  2. 2.Department of Molecular BiologyPrinceton UniversityPrincetonUSA

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