Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise

Marcoux, Curtis M.; Clarke, Stephen E.; Nesse, William H.; Longtin, André; Maler, Leonard

doi:10.1152/jn.00786.2015

Cited by 14 publications

(23 citation statements)

References 67 publications

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“…A direct effect of AP5 on granule cells in these experiments is unlikely because of their remote location in an external granule cell mass overlying the ELL molecular layer (Figure 7A). To rule out the possibility that NMDA receptor blockade interferes with electrosensory encoding in the ELL independent of its effects on synaptic plasticity (Marcoux et al, 2016), we analyzed preylike stimulus detection performance in time windows far from the EOD command. Detection performance was unaffected away from the command (Figure 7E, right), consistent with effects of AP5 being exerted mainly or entirely through the elevated firing induced by non-associative potentiation of corollary discharge inputs.…”

Section: Resultsmentioning

confidence: 99%

Internally Generated Predictions Enhance Neural and Behavioral Detection of Sensory Stimuli in an Electric Fish

Enikolopov

Abbott

Sawtell

2018

Neuron

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Studies of cerebellum-like circuits in fish have demonstrated that synaptic plasticity shapes the motor corollary discharge responses of granule cells into highly-specific predictions of self-generated sensory input. However, the functional significance of such predictions, known as negative images, has not been directly tested. Here we provide evidence for improvements in neural coding and behavioral detection of prey-like stimuli due to negative images. In addition, we find that manipulating synaptic plasticity leads to specific changes in circuit output that disrupt neural coding and detection of prey-like stimuli. These results link synaptic plasticity, neural coding, and behavior and also provide a circuit-level account of how combining external sensory input with internally generated predictions enhances sensory processing.

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Section: Resultsmentioning

confidence: 99%

Internally Generated Predictions Enhance Neural and Behavioral Detection of Sensory Stimuli in an Electric Fish

Enikolopov

Abbott

Sawtell

2018

Neuron

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“…2F). The intrinsic membrane noise of ELL 138 pyramidal cells was shown to unaffected by 10 mM kynurenic acid, an AMPA/NMDA receptor 139 antagonist (Marcoux et al, 2016); this is expected given the lack of recurrent connections in ELL 140 (Maler, 1979;Maler et al, 1981). In contrast, kynurenic acid application (10 mM) completely 141 blocked the membrane potential fluctuations of Apteronotus DL cells (N = 2, data not shown).…”

mentioning

confidence: 87%

Cellular and network mechanisms may generate sparse coding of sequential object encounters in hippocampal-like circuits

Trinh

Clarke

Harvey‐Girard

et al. 2019

Preprint

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15In mammals, the localization of distinct landmarks is performed by hippocampal neurons 16 that sparsely encode an animal's location relative to surrounding objects. Similarly, the dorsal 17 lateral pallium (DL) is essential for spatial learning in teleost fish. The DL of weakly electric 18 gymnotiform fish receives sensory inputs from the preglomerular nucleus (PG), which has been 19 hypothesized to encode the temporal sequence of electrosensory or visual landmark/food 20 encounters. Here, we show that DL neurons have a hyperpolarized resting membrane potential 21 combined with a high and dynamic spike threshold that increases following each spike. Current-22 evoked spikes in DL cells are followed by a strong small-conductance calcium-activated 23 potassium channel (SK) mediated after-hyperpolarizing potential (AHP). Together, these 24 properties prevent high frequency and continuous spiking. The resulting sparseness of discharge 25 and dynamic threshold suggest that DL neurons meet theoretical requirements for generating 26 spatial memory engrams by decoding the landmark/

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“…Noise reduces the precision with which spikes lock to the stimulus (1). In populations of neurons that share a common input, for example by having overlapping receptive fields, noise as well as population heterogeneity has the advantage to decorrelate the responses (8,9). That is, only those stimulus features that drive the population strongest could synchronize the response across neurons and thereby signal the presence of a particularly important stimulus.…”

mentioning

confidence: 99%

Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons

Grewe

Kruscha

Lindner

et al. 2017

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

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Synchronous activity in populations of neurons potentially encodes special stimulus features. Selective readout of either synchronous or asynchronous activity allows formation of two streams of information processing. Theoretical work predicts that such a synchrony code is a fundamental feature of populations of spiking neurons if they operate in specific noise and stimulus regimes. Here we experimentally test the theoretical predictions by quantifying and comparing neuronal response properties in tuberous and ampullary electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus. These related systems show similar levels of synchronous activity, but only in the more irregularly firing tuberous afferents a synchrony code is established, whereas in the more regularly firing ampullary afferents it is not. The mere existence of synchronous activity is thus not sufficient for a synchrony code. Single-cell features such as the irregularity of spiking and the frequency dependence of the neuron's transfer function determine whether synchronous spikes possess a distinct meaning for the encoding of time-dependent signals. Because of the strong nonlinearity of the spiking threshold, neural noise can be beneficial by improving the representation of stimuli in populations of spiking neurons (3-7). Noise reduces the precision with which spikes lock to the stimulus (1). In populations of neurons that share a common input, for example by having overlapping receptive fields, noise as well as population heterogeneity has the advantage to decorrelate the responses (8, 9). That is, only those stimulus features that drive the population strongest could synchronize the response across neurons and thereby signal the presence of a particularly important stimulus.The role of synchronous activity in the cortex is widely discussed (6, 10-12), e.g., as a possible solution for the binding problem (for review see, e.g., refs. 13 and 14), as a separate information channel to relay visual information from thalamus to visual cortex (15), as a mechanism for gain control in visual cortex (16), or as a code for odor categories in zebrafish olfactory bulb (17).A synchrony code requires that asynchronously firing populations are synchronized or, vice versa, synchronization is escaped under certain conditions or by specific stimuli. In weakly electric fish, changes in the level of synchronization are considered an important cue for the detection of communication signals on the level of the receptor afferents (18-21) and subsequent processing in hind-and midbrain neurons (22,23). Middleton et al. (24) demonstrated that reading out population activity of electrosensory neurons with either integrators or coincidence detectors results in two distinct representations of sensory stimuli. Integrators encode low stimulus frequencies, approximately matching frequencies characteristic of prey detection and navigation. Coincidence detectors discard low-frequency information and encode predominantly higher frequencies matching the ones of c...

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Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise

Abstract: Marcoux CM, Clarke SE, Nesse WH, Longtin A, Maler L. Balanced ionotropic receptor dynamics support signal estimation via voltagedependent membrane noise.

Cited by 14 publications

References 67 publications

Internally Generated Predictions Enhance Neural and Behavioral Detection of Sensory Stimuli in an Electric Fish

Internally Generated Predictions Enhance Neural and Behavioral Detection of Sensory Stimuli in an Electric Fish

Cellular and network mechanisms may generate sparse coding of sequential object encounters in hippocampal-like circuits

Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons

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