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J Neurophysiol 96: 2173-2174, 2006. First published July 12, 2006; doi:10.1152/jn.00665.2006
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EDITORIAL FOCUS

Gamma Oscillations, Synaptic Depression, and the Enhancement of Spatiotemporal Processing. Focus on "Global Electrosensory Oscillations Enhance Directional Responses of Midbrain Neurons in Eigenmannia"

Oscillatory brain activity has been observed since the earliest EEG studies and classified by its frequency range. In particular, oscillations in the range of 20–60 Hz (gamma band) have been identified in numerous vertebrate species and brain regions (Bullock and Achimowicz 1994Go); in mammals, cortical {gamma}-band oscillations typically occur in activated brain states (Steriade et al. 1996Go) and they have in general been associated with processing behaviorally relevant information (Bullock and Achimowicz 1994Go; Csibra et al. 2000Go). The precise role of such oscillations and the mechanisms by which they might optimize information processing has remained controversial, in part because of the complexity of cortical circuits. In this issue of the Journal of Neurophysiology (p. 2319–2326) Ramcharitar and colleagues demonstrate that {gamma}-band oscillations, which occur naturally during social interactions of electric fish, enhance the directional selectivity of movement-responsive neurons (Ramcharitar et al. 2006Go). In addition this paper presents strong evidence that {gamma}-band oscillation-induced synaptic depression may be a biophysical mechanism that contributes to this enhancement of directional selectivity.

Eigenmannia virescens, the gymnotiform species studied by Ramacharitar et al. (2006)Go, produces a weak sinusoidal electric organ discharge (EOD) that creates an electric field around the animal. EOD frequencies in this species range from 200 to 700 Hz but isolated individual fish maintain near-constant frequencies. The EOD serves as a carrier that can be modulated by environmental objects such as prey (electrolocation) as well as by the EOD of conspecifics (electrocommunication). Prey—because its conductivity is greater than that of the ambient water—will increase the local EOD amplitude. Thus movement of the fish relative to prey will therefore produce a low-frequency amplitude modulation (AM, <20 Hz) moving across its skin. This AM is sensed by numerous specialized cutaneous electroreceptors (P-units) and the output used for prey capture (Nelson and MacIver 1999Go). Not surprisingly, many midbrain electrosensory neurons are responsive to moving electrosensory images (in the torus semicircularis [TS] this region is analogous to the mammalian inferior colliculus).

When two fish are in proximity their EODs will interfere so as to produce a beat frequency (equal to the difference in the frequencies of their individual EODs). The beat AM is also a very effective stimulus for P-units and beat frequencies <20 Hz will interfere with the detection of prey. Eigenmannia, which are most commonly found in small groups (Tan et al. 2005Go), have developed a specialized electromotor behavior—the jamming avoidance response (JAR)—to prevent its neighbors' EODs from interfering with electrolocation, including prey capture. The JAR shifts the EOD frequencies of neighboring fish away from each other so that the resulting beats increase to the 20- to 50-Hz ({gamma}-band) range and no longer overlap with the AM frequencies of prey; the JAR therefore permits electrolocation in the presence of conspecifics. The neural circuitry of the JAR has been thoroughly explicated by Heiligenberg and colleagues (Fortune and Rose 1997aGo,bGo, 2000Go, 2003Go; Heiligenberg 1991Go; Rose and Call 1992Go; Rose and Fortune 1999Go) who found many neurons in the TS responsive to beat frequencies (2–50 Hz).

Earlier studies from this group (Ramcharitar et al. 2005Go) established that low-frequency beats interfered with the electrosensory detection of moving objects by TS neurons, as might be expected from the earlier literature on the JAR. The paper in this issue reveals a surprising and far more interesting result: the {gamma}-band oscillations induced by the JAR can greatly enhance the directional selectivity of TS neurons to moving objects. The JAR thus serves not only to prevent the deleterious effect of low-frequency beats but actually enhances electrolocation by sharpening directionally selective responses to prey. There have been numerous studies that suggest that {gamma}-band oscillations are induced during perception and might be involved in attention to specific stimulus features (Cardin et al. 2005Go; Fries et al. 2002Go; Ishikane et al. 2005Go; Siegel and Konig 2003Go; Womelsdorf et al. 2006Go). Ramacharitar et al. (2006)Go are the first to convincingly demonstrate that behaviorally induced {gamma}-band oscillations can enhance "attention" to behaviorally relevant spatiotemporal signals. Furthermore, the generality of this effect across species and brain regions suggests that it may be a consequence of conserved neuronal biophysics.

The second major result of this paper is therefore also of general interest: the enhancement of directional selectivity is highly positively correlated with the previously demonstrated synaptic depression of TS input (Fortune and Rose 2000Go; Rose and Fortune 1999Go). Although the causal link between synaptic depression and directional selectivity was not established in this paper, the authors make a plausible connection to models of directional selectivity in visual cortex that use synaptic depression as a key biophysical element (Chance et al. 1998Go; Fortune and Rose 2002Go).

This conclusion is in some ways surprising because the literature on {gamma}-band oscillations typically emphasizes its role as enhancing perceptual processing by promoting neuronal synchrony (Cardin et al. 2005Go; Fries et al. 2002Go; Ishikane et al. 2005Go; Siegel and Konig 2003Go; Womelsdorf et al. 2006Go). More recently, Schaefer et al. (2006)Go suggested that neuronal oscillations enhance stimulus detection by promoting the temporal precision of action potentials. Perhaps these ideas are not as disparate as first appears. Computational analysis has suggested that synaptic depression can allow a neuronal network to better detect synchronous input (Senn et al. 1998Go). There may thus be a deeper link between {gamma}-band oscillations, synaptic depression, the detection of synchronous input, and the enhancement of specific types of time-varying signals. {gamma}-Band oscillations might induce both synchrony (by an increase in spike precision across the oscillating neurons) and synaptic depression; these effects might then synergistically enhance the detection of more localized signals such as prey. Exploring this link experimentally and theoretically and across diverse sensory systems will likely prove a rewarding enterprise.

Leonard Maler

Department of Cell and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada

Address for reprint requests and other correspondence: L. Maler, Dept. of Cell and Molecular Medicine, University of Ottawa, 451 Smyth Rd., Ottawa, ON, Canada K1H 8M5 (E-mail: lmaler{at}uottawa.ca)

REFERENCES

Bullock TH and Achimowicz JZ. A comparative survey of oscillatory brain activity, especially gamma-band rhythms. In: Oscillatory Event-Related Brain Dynamics, edited by Pantev C, Elbert T, and Lutkenhuner B. New York: Plenum Press, 1994, p. 11–26.

Cardin JA, Palmer LA, and Contreras D. Stimulus-dependent gamma (30–50 Hz) oscillations in simple and complex fast rhythmic bursting cells in primary visual cortex. J Neurosci 25: 5339–5350, 2005.[Abstract/Free Full Text]

Chance FS, Nelson SB, and Abbott LF. Synaptic depression and the temporal response characteristics of V1 cells. J Neurosci 18: 4785–4799, 1998.[Abstract/Free Full Text]

Csibra G, Davis G, Spratling MW, and Johnson MH. Gamma oscillations and object processing in the infant brain. Science 290: 1582–1585, 2000.[Abstract/Free Full Text]

Fortune ES and Rose G. Passive and active membrane properties contribute to the temporal filtering properties of midbrain neurons in vivo. J Neurosci 17: 3815–3825, 1997a.[Abstract/Free Full Text]

Fortune ES and Rose GJ. Temporal filtering properties of ampullary electrosensory neurons in the torus semicircularis of Eigenmannia: evolutionary and computational implications. Brain Behav Evol 49: 312–323, 1997b.[ISI][Medline]

Fortune ES and Rose GJ. Short-term synaptic plasticity contributes to the temporal filtering of electrosensory information. J Neurosci 20: 7122–7130, 2000.[Abstract/Free Full Text]

Fortune ES and Rose GJ. Roles for short-term synaptic plasticity in behavior. J Physiol (Paris) 96: 539–545, 2002.

Fortune ES and Rose GJ. Voltage-gated Na+ channels enhance the temporal filtering properties of electrosensory neurons in the torus. J Neurophysiol 90: 924–929, 2003.[Abstract/Free Full Text]

Fries P, Schroder JH, Roelfsema PR, Singer W, and Engel AK. Oscillatory neuronal synchronization in primary visual cortex as a correlate of stimulus selection. J Neurosci 22: 3739–3754, 2002.[Abstract/Free Full Text]

Heiligenberg W. Neural Nets in Electric Fish. Cambridge, MA: MIT Press, 1991.

Ishikane H, Gangi M, Honda S, and Tachibana M. Synchronized retinal oscillations encode essential information for escape behavior in frogs. Nat Neurosci 8: 1087–1095, 2005.[CrossRef][ISI][Medline]

Nelson ME and MacIver MA. Prey capture in the weakly electric fish Apteronotus leptorhynchus: sensory acquisition strategies and electrosensory consequences. J Exp Biol 202: 1195–1203, 1999.[Abstract]

Ramcharitar JU, Tan EW, and Fortune ES. Effects of global electrosensory signals on motion processing in the midbrain of Eigenmannia. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 191: 865–872, 2005.[CrossRef][ISI][Medline]

Ramcharitar JU, Tan EW, and Fortune ES. Global electrosensory oscillations enhance directional responses of midbrain neurons in Eigenmannia. J Neurophysiol 96: 2319–2326, 2006.[Abstract/Free Full Text]

Rose GJ and Call SJ. Evidence for the role of dendritic spines in the temporal filtering properties of neurons: the decoding problem and beyond. Proc Natl Acad Sci USA 89: 9662–9665, 1992.[Abstract/Free Full Text]

Rose GJ and Fortune ES. Frequency-dependent PSP depression contributes to low-pass temporal filtering in Eigenmannia. J Neurosci 19: 7629–7639, 1999.[Abstract/Free Full Text]

Schaefer AT, Angelo K, Spors H, and Margrie TW. Neuronal oscillations enhance stimulus discrimination by ensuring action potential precision. PLoS Biol 4: e163, 2006.[CrossRef][Medline]

Senn W, Segev I, and Tsodyks M. Reading neuronal synchrony with depressing synapses. Neural Comput 10: 815–819, 1998.[Abstract]

Siegel M and Konig P. A functional gamma-band defined by stimulus-dependent synchronization in area 18 of awake behaving cats. J Neurosci 23: 4251–4260, 2003.[Abstract/Free Full Text]

Steriade M, Amzica F, and Contreras D. Synchronization of fast (30–40 Hz) spontaneous cortical rhythms during brain activation. J Neurosci 16: 392–417, 1996.[Abstract/Free Full Text]

Tan EW, Nizar JM, Carrera GE, and Fortune ES. Electrosensory interference in naturally occurring aggregates of a species of weakly electric fish, Eigenmannia virescens. Behav Brain Res 164: 83–92, 2005.[CrossRef][ISI][Medline]

Womelsdorf T, Fries P, Mitra PP, and Desimone R. Gamma-band synchronization in visual cortex predicts speed of change detection. Nature 439: 733–736, 2006.[CrossRef][Medline]





This Article
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96/5/2173    most recent
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