The Structure of Multi-Neuron Firing Patterns in Primate Retina

Shlens, Jonathon; Field, Greg D.; Gauthier, Jeffrey; Grivich, Matthew I.; Petrusca, Dumitru; Sher, Alexander; Litke, A. M.; Chichilnisky, E. J.

doi:10.1523/jneurosci.1282-06.2006

Cited by 457 publications

(747 citation statements)

References 64 publications

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“…Previous studies have also used pairwise approximations in other contexts, but the underlying variables represented the dynamics of specific cellular components or other physical entities such as proteins or neurons (24)(25)(26)(27)(28)(29)(30). Most notably, a recent study in cancer cells demonstrated that the expression of some proteins in response to combinations of drugs can be predicted from their responses to smaller drug combinations (24).…”

Section: Discussionmentioning

confidence: 99%

Mechanism-independent method for predicting response to multidrug combinations in bacteria

Wood

Nishida

Sontag

et al. 2012

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

139

177

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Drugs are commonly used in combinations larger than two for treating bacterial infection. However, it is generally impossible to infer directly from the effects of individual drugs the net effect of a multidrug combination. Here we develop a mechanism-independent method for predicting the microbial growth response to combinations of more than two drugs. Performing experiments in both Gram-negative ( Escherichia coli) and Gram-positive ( Staphylococcus aureus ) bacteria, we demonstrate that for a wide range of drugs, the bacterial responses to drug pairs are sufficient to infer the effects of larger drug combinations. To experimentally establish the broad applicability of the method, we use drug combinations comprising protein synthesis inhibitors (macrolides, aminoglycosides, tetracyclines, lincosamides, and chloramphenicol), DNA synthesis inhibitors (fluoroquinolones and quinolones), folic acid synthesis inhibitors (sulfonamides and diaminopyrimidines), cell wall synthesis inhibitors, polypeptide antibiotics, preservatives, and analgesics. Moreover, we show that the microbial responses to these drug combinations can be predicted using a simple formula that should be widely applicable in pharmacology. These findings offer a powerful, readily accessible method for the rational design of candidate therapies using combinations of more than two drugs. In addition, the accurate predictions of this framework raise the question of whether the multidrug response in bacteria obeys statistical, rather than chemical, laws for combinations larger than two.

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Section: Discussionmentioning

confidence: 99%

Mechanism-independent method for predicting response to multidrug combinations in bacteria

Wood

Nishida

Sontag

et al. 2012

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

139

177

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“…The analog signal from each electrode was sampled at 20 kHz. This system has been used previously to study the encoding of visual motion and multineuron firing patterns in mosaics of parasol cells in the primate retina (Frechette et al, 2005;Shlens et al, 2006).…”

Section: Methodsmentioning

confidence: 99%

Identification and Characterization of a Y-Like Primate Retinal Ganglion Cell Type

Petrusca

Grivich²,

Sher³

et al. 2007

J. Neurosci.

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227

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The primate retina communicates visual information to the brain via a set of parallel pathways that originate from at least 22 anatomically distinct types of retinal ganglion cells. Knowledge of the physiological properties of these ganglion cell types is of critical importance for understanding the functioning of the primate visual system. Nonetheless, the physiological properties of only a handful of retinal ganglion cell types have been studied in detail. Here we show, using a newly developed multielectrode array system for the large-scale recording of neural activity, the existence of a physiologically distinct population of ganglion cells in the primate retina with distinctive visual response properties. These cells, which we will refer to as upsilon cells, are characterized by large receptive fields, rapid and transient responses to light, and significant nonlinearities in their spatial summation. Based on the measured properties of these cells, we speculate that they correspond to the smooth/large radiate cells recently identified morphologically in the primate retina and may therefore provide visual input to both the lateral geniculate nucleus and the superior colliculus. We further speculate that the upsilon cells may be the primate retina's counterparts of the Y-cells observed in the cat and other mammalian species.

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“…The existence of a low-dimensional parameterization of the retinal activity (8)(9)(10)(11) is an interesting and encouraging result. Naively, one may be tempted to assign to the inferred parameters a simple interpretation: The fields could represent the external stimuli, and the couplings could reflect the physiological interactions between the cells.…”

mentioning

confidence: 98%

Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods

Cocco

Leibler

Monasson

2009

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

197

235

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Complexity of neural systems often makes impracticable explicit measurements of all interactions between their constituents. Inverse statistical physics approaches, which infer effective couplings between neurons from their spiking activity, have been so far hindered by their computational complexity. Here, we present 2 complementary, computationally efficient inverse algorithms based on the Ising and ''leaky integrate-and-fire'' models. We apply those algorithms to reanalyze multielectrode recordings in the salamander retina in darkness and under random visual stimulus. We find strong positive couplings between nearby ganglion cells common to both stimuli, whereas long-range couplings appear under random stimulus only. The uncertainty on the inferred couplings due to limitations in the recordings (duration, small area covered on the retina) is discussed. Our methods will allow realtime evaluation of couplings for large assemblies of neurons.inference and inverse problems ͉ multielectrode recordings ͉ neural couplings A vertebrate retina is a structured, complex network of interacting neurons that process visual input stimuli at the photoreceptors into an output pattern of action potentials of the retinal ganglion cells (1-2). It is now a well-established fact that retinal cells process information in a collective fashion: The firing of one ganglion cell is correlated with the firing pattern of other cells (3-4). Multielectrode recordings have made accessible hours-long, simultaneous spiking activity of tens of retinal ganglion cells and thus have become a powerful tool to investigate the information processing performed by a vertebrate retina (5-7). The analysis of pairwise correlations in the activity has revealed different patterns of synchrony between 2 cells that have been related to different retina circuits (7).Analyzing the concerted activity of all of the recorded cells is, however, a very challenging task. Recently Schneidman et al. (8) and Shlens et al. (9) pointed out that correlations in the firing activity of cell populations can be reconstructed from the average firing rates, f i , and 2-cell correlations, c ij , alone. The theoretical model, which has been used to generate the frequencies of all possible 2 N spiking configurations for a system of N neurons, is the well-known Ising model. It is characterized by a reduced set of ϷN 2 parameters: N ''fields,'' h i , experienced by individual cells, and N(N Ϫ 1)/2 ''couplings,'' J ij , between pairs of cells. Computing the parameters h i and J ij from the firing patterns can be viewed as an example of the inverse statistical physics method.The existence of a low-dimensional parameterization of the retinal activity (8-11) is an interesting and encouraging result. Naively, one may be tempted to assign to the inferred parameters a simple interpretation: The fields could represent the external stimuli, and the couplings could reflect the physiological interactions between the cells. However, because most of the neural circuitry (all cells in intermediat...

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The Structure of Multi-Neuron Firing Patterns in Primate Retina

Cited by 457 publications

References 64 publications

Mechanism-independent method for predicting response to multidrug combinations in bacteria

Mechanism-independent method for predicting response to multidrug combinations in bacteria

Identification and Characterization of a Y-Like Primate Retinal Ganglion Cell Type

Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods

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