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Receiver operating characteristic (ROC) analysis of neurons in the cat's lateral geniculate nucleus during tonic and burst response mode

Published online by Cambridge University Press:  02 June 2009

W. Guido ,
S.-M. Lu ,
J.W. Vaughan ,
Dwayne W. Godwin  and
S. Murray Sherman
W. Guido
Affiliation:
Department of Neurobiology, State University of New York, Stony Brook
S.-M. Lu
Affiliation:
Department of Neurobiology, State University of New York, Stony Brook
J.W. Vaughan
Affiliation:
Department of Neurobiology, State University of New York, Stony Brook
Dwayne W. Godwin
Affiliation:
Department of Neurobiology, State University of New York, Stony Brook
S. Murray Sherman
Affiliation:
Department of Neurobiology, State University of New York, Stony Brook
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Abstract

Relay cells of the lateral geniculate nucleus respond to visual stimuli in one of two modes: burst and tonic. The burst mode depends on the activation of a voltage-dependent, Ca2+ conductance underlying the low threshold spike. This conductance is inactivated at depolarized membrane potentials, but when activated from hyperpolarized levels, it leads to a large, triangular, nearly all-or-none depolarization. Typically, riding its crest is a high-frequency barrage of action potentials. Low threshold spikes thus provide a nonlinear amplification allowing hyperpolarized relay neurons to respond to depolarizing inputs, including retinal EPSPs. In contrast, the tonic mode is characterized by a steady stream of unitary action potentials that more linearly reflects the visual stimulus. In this study, we tested possible differences in detection between response modes of 103 geniculate neurons by constructing receiver operating characteristic (ROC) curves for responses to visual stimuli (drifting sine-wave gratings and flashing spots). Detectability was determined from the ROC curves by computing the area under each curve, known as the ROC area. Most cells switched between modes during recording, evidently due to small shifts in membrane potential that affected the activation state of the low threshold spike. We found that the more often a cell responded in burst mode, the larger its ROC area. This was true for responses to optimal and nonoptimal visual stimuli, the latter including nonoptimal spatial frequencies and low stimulus contrasts. The larger ROC areas associated with burst mode were due to a reduced spontaneous activity and roughly equivalent level of visually evoked response when compared to tonic mode. We performed a within-cell analysis on a subset of 22 cells that switched modes during recording. Every cell, whether tested with a low contrast or high contrast visual stimulus exhibited a larger ROC area during its burst response mode than during its tonic mode. We conclude that burst responses better support signal detection than do tonic responses. Thus, burst responses, while less linear and perhaps less useful in providing a detailed analysis of visual stimuli, improve target detection. The tonic mode, with its more linear response, seems better suited for signal analysis rather than signal detection.

Keywords

Visual systemLow threshold Ca2+ conductanceSignal detectionThalamus
Type
Research Articles
Information
Visual Neuroscience , Volume 12 , Issue 4 , July 1995 , pp. 723 - 741
Copyright
Copyright © Cambridge University Press 1995

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References

Barlow, H.B. & Levick, W.R. (1966). Three factors limiting the reliable detection of light by retinal ganglion cells of the cat. Journal of Physiology (London) 200, 1–24.CrossRefGoogle Scholar
Bloomfield, S.A. & Sherman, S.M. (1988). Postsynaptic potentials recorded in neurons of the cat's lateral geniculate nucleus following electrical stimulation of the optic chiasm. Journal of Neurophysiology 60, 1924–1945.CrossRefGoogle ScholarPubMed
Bloomfield, S.A., Hamos, J.E. & Sherman, S.M. (1987). Passive cable properties and morphological correlates of neurones in the lateral geniculate nucleus of the cat. Journal of Physiology (London) 383, 653–692.CrossRefGoogle ScholarPubMed
Britten, K.H., Shadlen, M.N., Newsome, W.T. & Movshon, J.A. (1992). The analysis of visual motion: A comparison of neuronal and psychophysical performance. Journal of Neuroscience 12, 4745–4765.CrossRefGoogle Scholar
Cohn, T.E., Green, D.G. & Tanner, W.P. (1975). Receiver operating characteristic analysis, application to the study of quantum fluctuation effects in optic nerve of Rana pipens. Journal of General Physiology 66, 583–616.CrossRefGoogle Scholar
Crick, F. (1984). Function of the thalamic reticular complex: The searchlight hypothesis. Proceedings of the National Academy of Sciences of the U.S.A. 81, 4586–4590.CrossRefGoogle ScholarPubMed
Crunelli, V., Lightowler, S. & Pollard, C.E. (1989). A T-type Ca2+ current underlies low-threshold Ca2+ potentials in cells of the cat and rat lateral geniculate nucleus. Journal of Physiology (London) 413, 543–561.CrossRefGoogle Scholar
Deschênes, M., Paradis, M., Roy, J.P. & Steriade, M. (1984). Electrophysiology of neurons of lateral thalamic nuclei in cat: Resting properties and burst discharges. Journal of Neurophysiology 51, 1196–1219.CrossRefGoogle ScholarPubMed
Funke, K. & Eysel, U.T. (1992). EEG-dependent modulation of response dynamics of cat dLGN relay cells and the contribution of corticogeniculate feedback. Brain Research 573, 217–227.CrossRefGoogle ScholarPubMed
Green, D.M. & Swets, J.A. (1966). Signal Detection Theory and Psychophysics. New York: Wiley.Google Scholar
Guido, W., Lu, S-M. & Sherman, S.M. (1992). Relative contributions of tonic and burst response modes to the receptive field properties of lateral geniculate neurons in the cat. Journal of Neurophysiology 6, 2199–2211.CrossRefGoogle Scholar
Holdefer, R.N., Norton, T.T. & Godwin, D.W. (1989). Effects of bicuculline on signal detectability in lateral geniculate nucleus relay cells. Brain Research 488, 341–347.CrossRefGoogle ScholarPubMed
Ikeda, H. & Wright, M.J. (1975). Sensitivity of neurones in visual cortex (area 17) under different levels of anesthesia. Experimental Brain Research 20, 417–484.Google Scholar
Jahnsen, H. & Llinás, R. (1984 a). Electrophysiological properties of guinea-pig thalamic neurones: An in vitro study. Journal of Physiology (London) 349, 205–226.CrossRefGoogle ScholarPubMed
Jahnsen, H. & Llinás, R. (1984 b). Ionic basis for the electro-responsiveness and oscillatory properties of guinea-pig thalamic neurones in vitro. Journal of Physiology (London) 349, 227–247.CrossRefGoogle ScholarPubMed
Lo, F.-S., Lu, S.-M. & Sherman, S.M. (1991). Intracellular and extracellular in vivo recording of different response modes for relay cells of the cat's lateral geniculate nucleus. Experimental Brain Research 83, 317–328.CrossRefGoogle ScholarPubMed
Lu, S-M., Guido, W. & Sherman, S.M. (1992). Effects of membrane voltage on receptive field properties of lateral geniculate neurons in the cat: Contributions of the low threshold Ca2+ conductance. Journal of Neurophysiology 6, 2185–2198.CrossRefGoogle Scholar
Lu, S-M., Guido, W. & Sherman, S.M. (1993). The brainstem parabrachial region controls mode of response to visual stimulation of neurons in the cat's lateral geniculate nucleus. Visual Neuroscience 10, 631–642.CrossRefGoogle ScholarPubMed
Macmillan, N.A. & Creelman, C.D. (1991). Detection Theory: A User's Guide. New York: Cambridge University Press.Google Scholar
McCormick, D.A. (1992 a). Cellular mechanisms underlying cholinergic and noradrenergic modulation of neuronal firing mode in the cat and guinea pig dorsal lateral geniculate nucleus. Journal of Neuroscience 12, 278–289.CrossRefGoogle Scholar
McCormick, D.A. (1992 b). Neurotransmitter actions in the thalamus and cerebral cortex and their role in neuromodulation of thalamo-cortical activity. Progress in Neurobiology 39, 337–388.CrossRefGoogle Scholar
Pollack, I. & Hsieh, R. (1969). Sampling variability of the area under the ROC-curve and of d′. Psychological Bulletin 71, 161–173.CrossRefGoogle Scholar
Posner, M.I. & Peterson, S.E. (1990). The attention system of the human brain. Annual Reviews of Neuroscience 13, 25–42.CrossRefGoogle ScholarPubMed
Sherman, S.M. & Koch, C. (1986). The control of retinogeniculate transmission in the mammalian lateral geniculate nucleus. Experimental Brain Research 63, 1–20.CrossRefGoogle ScholarPubMed
Sherman, S.M. & Koch, C. (1990). Thalamus. In Synaptic Organization of the Brain, 3rd edition, ed. Shepherd, G.M., pp. 246–278. New York: Oxford University Press.Google Scholar
Steriade, M. & Deschênes, M. (1984). The thalamus as a neuronal oscillator. Brain Research Reviews 8, 1–63.CrossRefGoogle Scholar
Steriade, M., Jones, E.G. & Llinás, R.R. (1990). Thalamic Oscillations and Signalling. Neuroscience Institute Publ. Series, New York: Wiley and Sons.Google Scholar
Steriade, M. & Llinás, R.R. (1988). The functional states of the thalamus and the associated neuronal interplay. Physiological Reviews 68, 649–742.CrossRefGoogle ScholarPubMed
Steriade, M. & McCarley, R.W. (1990). Brainstem Control of Wakefulness and Sleep. New York: Plenum Press.CrossRefGoogle Scholar
Steriade, M., McCormick, D.A. & Sejnowski, T.J. (1993). Thalamocortical oscillations in the sleeping and aroused brain. Science 262, 679–685.CrossRefGoogle ScholarPubMed
Tolhurst, D.J., Movshon, J.A. & Dean, A.F. (1983). The statistical reliability of signals in single neurons in cat and monkey visual cortex. Vision Research 23, 775–785.CrossRefGoogle Scholar
Wilson, J.R., Bullier, J. & Norton, T.T. (1988). Signal-to-noise comparisons for X and Y cells in the retina and lateral geniculate nucleus of the cat. Experimental Brain Research 70, 399–405.CrossRefGoogle ScholarPubMed