Determination of the transfer ratio of cat's geniculate neurons through quasi-intracellular recordings and the relation with the level of alertness

Coenen, A.M.L.; Vendrik, A. J. H.

doi:10.1007/bf00816160

Cited by 172 publications

(81 citation statements)

References 18 publications

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“…This number aligns well with that of investigators dependent on S-potential records to infer numbers of retinal inputs (e.g. Coenen and Vendrik, 1972;Kaplan and Shapley, 1984;Wang et al, 1985;Weyand, 2007). The degree to which retinal ganglion cells converge on LGN neurons is not without controversy (see Comments, below), but there seems to be reasonable agreement that few Y-cells are driven by a single input, and many, if not most, X-cells are driven by a single input.…”

Section: Amplification/integration Of Retinal Signalssupporting

confidence: 79%

“…Reality has efficacy closer to 50%, a striking departure from Coenen and Vendrik's (1972) assertion that wakefulness would normally yield efficacy near 100%. Weyand (2007) observed an overall level of efficacy of 50% in the awake cat, curiously the same level of efficacy observed by Sincich and colleagues (2007) in the anesthetized monkey.…”

Section: Efficacy In Wakefulness Is Often Well Below 100%mentioning

confidence: 85%

“…While indicting, it was also true that stimulus size increased burst probability, an observation that the increase was as likely associated with manipulating on/off polarity as issuing a wake-up call (e.g. Coenen and Vendrik, 1972, show an obvious burst associated with on/ off polarity reversal in their Figure 2). It is significant that McAlonan and colleagues (2008) showed robust enhancement with attention yet do not mention any link to bursting, even though Crick's (1984) paper is cited.…”

Section: Long Interspike Intervals From Retina Succeed At Much Highermentioning

confidence: 99%

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The multifunctional lateral geniculate nucleus

Weyand

2016

Reviews in the Neurosciences

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AbstractProviding the critical link between the retina and visual cortex, the well-studied lateral geniculate nucleus (LGN) has stood out as a structure in search of a function exceeding the mundane ‘relay’. For many mammals, it is structurally impressive: Exquisite lamination, sophisticated microcircuits, and blending of multiple inputs suggest some fundamental transform. This impression is bolstered by the fact that numerically, the retina accounts for a small fraction of its input. Despite such promise, the extent to which an LGN neuron separates itself from its retinal brethren has proven difficult to appreciate. Here, I argue that whereas retinogeniculate coupling is strong, what occurs in the LGN is judicious pruning of a retinal drive by nonretinal inputs. These nonretinal inputs reshape a receptive field that under the right conditions departs significantly from its retinal drive, even if transiently. I first review design features of the LGN and follow with evidence for 10 putative functions. Only two of these tend to surface in textbooks: parsing retinal axons by eye and functional group and gating by state. Among the remaining putative functions, implementation of the principle of graceful degradation and temporal decorrelation are at least as interesting but much less promoted. The retina solves formidable problems imposed by physics to yield multiple efficient and sensitive representations of the world. The LGN applies context, increasing content, and gates several of these representations. Even if the basic concentric receptive field remains, information transmitted for each LGN spike relative to each retinal spike is measurably increased.

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Section: Amplification/integration Of Retinal Signalssupporting

confidence: 79%

Section: Efficacy In Wakefulness Is Often Well Below 100%mentioning

confidence: 85%

Section: Long Interspike Intervals From Retina Succeed At Much Highermentioning

confidence: 99%

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The multifunctional lateral geniculate nucleus

Weyand

2016

Reviews in the Neurosciences

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“…It was originally thought that the tonic mode was associated with behavioral states, such as wakefulness and sleep, during which afferent stimuli are readily relayed by the thalamus (3,(6)(7)(8). In contrast, the bursting mode was thought to occur only during times when no afferent information was, in theory, transmitted by the thalamus (refs.…”

mentioning

confidence: 99%

Thalamic bursting in rats during different awake behavioral states

Fanselow

Sameshima²,

Baccalá³

et al. 2001

Proc. Natl. Acad. Sci. U.S.A.

221

174

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Thalamic neurons have two firing modes: tonic and bursting. It was originally suggested that bursting occurs only during states such as slow-wave sleep, when little or no information is relayed by the thalamus. However, bursting occurs during wakefulness in the visual and somatosensory thalamus, and could theoretically influence sensory processing. Here we used chronically implanted electrodes to record from the ventroposterior medial thalamic nucleus (VPM) and primary somatosensory cortex (SI) of awake, freely moving rats during different behaviors. These behaviors included quiet immobility, exploratory whisking (large-amplitude whisker movements), and whisker twitching (small-amplitude, 7-to 12-Hz whisker movements). We demonstrated that thalamic bursting appeared during the oscillatory activity occurring before whisker twitching movements, and continued throughout the whisker twitching. Further, thalamic bursting occurred during whisker twitching substantially more often than during the other behaviors, and a neuron was most likely to respond to a stimulus if a burst occurred Ϸ120 ms before the stimulation. In addition, the amount of cortical area activated was similar to that during whisking. However, when SI was inactivated by muscimol infusion, whisker twitching was never observed. Finally, we used a statistical technique called partial directed coherence to identify the direction of influence of neural activity between VPM and SI, and observed that there was more directional coherence from SI to VPM during whisker twitching than during the other behaviors. Based on these findings, we propose that during whisker twitching, a descending signal from SI triggers thalamic bursting that primes the thalamocortical loop for enhanced signal detection during the whisker twitching behavior. I t has been demonstrated that thalamic relay neurons have two distinct modes of firing. These are the tonic firing mode, in which neurons fire single action potentials, and the bursting mode, in which cells fire bursts of two to seven action potentials (1, 2). During the tonic firing mode, cells respond to stimuli with individual spikes that can closely follow incoming activity (3-5). In contrast, during the burst mode, cells respond to incoming stimuli with bursts that do not directly resemble the afferent activity because the bursts are all-or-nothing events, and there is a long refractory period between bursts (4, 5).It was originally thought that the tonic mode was associated with behavioral states, such as wakefulness and sleep, during which afferent stimuli are readily relayed by the thalamus (3, 6-8). In contrast, the bursting mode was thought to occur only during times when no afferent information was, in theory, transmitted by the thalamus (refs. 1, 9, and 10; see ref. 11 for review), such as during slow-wave sleep, barbiturate anesthesia, and pathological conditions such as seizure activity. However, it has recently been demonstrated that thalamic bursting can occur during awake states as well, in multiple species (12-...

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“…The apparent similarity between anesthetized and alert preparations is misleading, however, if variability in the two cases is generated by different sources. Uncontrolled fluctuations in responsiveness can be caused by sleep or anesthesia for neurons in the LGN (Maffei and Rizzolatti, 1965;Coenen and Vendric, 1972) and visual cortex (Bartlett and Doty, 1974;Ikeda and Wright, 1974;Livingstone and Hubel, 1981), and prolonged paralysis has similar effects (Mountcastle et al, 1969). In contrast, using alert animals has the advantage that a relatively steady physiological state may be assumed.…”

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confidence: 99%

Response Variability of Neurons in Primary Visual Cortex (V1) of Alert Monkeys

1997

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Response variability of neurons limits the reliability and resolution of sensory systems. It is generally thought that response variability in the visual system increases at cortical levels, but the causes of the variability have not been identified. We have measured the response variability of neurons in primary visual cortex (V1) of alert monkeys. We recorded from 80 single cells distributed over all V1 layers and from 8 parvocellular cells of the lateral geniculate nucleus. All cells were stimulated with a bar of near-optimal orientation, color, and dimensions while continuously monitoring the eye movements of fixation. To minimize the effects of eye movements, responses that occurred while the eye was relatively steady were selected for analysis. The impulses elicited by each stimulus presentation were counted, and the variance and coefficient of variation were computed. Both measures of response variability were much lower than reported previously for V1 cells of both alert and anesthetized monkeys. Our data show that fixational eye movements cause a large component of response variance in alert monkeys. Moreover, the reliability of V1 neurons is not obviously degraded compared with lateral geniculate nucleus cells. The high reliability of neurons in alert monkeys is consistent with expectations from conventional biophysical models, and it suggests that activity in a modest number of neurons may suffice to form a perceptual decision.

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Determination of the transfer ratio of cat's geniculate neurons through quasi-intracellular recordings and the relation with the level of alertness

Cited by 172 publications

References 18 publications

The multifunctional lateral geniculate nucleus

The multifunctional lateral geniculate nucleus

Thalamic bursting in rats during different awake behavioral states

Response Variability of Neurons in Primary Visual Cortex (V1) of Alert Monkeys

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