Determining the role of correlated firing in large populations of neurons using white noise and natural scene stimuli

Meytlis, Marsha; Nichols, Zachary; Nirenberg, Sheila

doi:10.1016/j.visres.2012.07.007

Cited by 23 publications

(58 citation statements)

References 32 publications

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“…In this study, we observed the changes in information representation throughout the process of adaptation. Our results show that, at the early stage of the adaptation, the firing rates of neurons conveyed the majority (more than 90%) of the stimulus information, which is in agreement with findings reported by other authors (Meytlis et al 2012;Nirenberg et al 2001;Oizumi et al 2010), whereas at the later stage of the adaptation, the contribution of neural correlation increased remarkably and became the dominant factor, which is in accordance with other research (Schneidman et al 2006). Thus our results reconcile the two different views in the literature and reveal that the contribution of neural correlation in conveying the stimulus information can vary with time during adaptation.…”

Section: Discussionsupporting

confidence: 94%

“…However, there is a long-standing debate over the role and significance of concerted activity in neural information processing (Averbeck and Lee 2004). A number of studies have revealed that concerted neuronal activity encodes extra stimulus information which cannot be extracted by the responses of single neurons, and they play important roles in animal behaviors (Dan et al 1998;Ince et al 2010;Ishikane et al 2005), whereas other work suggested that neuronal correlation conveys little information and can be largely neglected (Meytlis et al 2012;Nirenberg et al 2001;Oizumi et al 2010). In this study, we observed the changes in information representation throughout the process of adaptation.…”

Section: Discussionmentioning

confidence: 99%

“…Some studies suggested that the firing rates of neurons conveyed the majority of the stimulus information, and that the contribution of neural correlation could be largely neglected (Meytlis et al 2012;Nirenberg et al 2001;Oizumi et al 2010), whereas others suggested that neural correlation played an indispensable role in neural computation (Dan et al 1998; …”

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Shifted encoding strategy in retinal luminance adaptation: from firing rate to neural correlation

Xiao

Zhang

Xing

et al. 2013

Journal of Neurophysiology

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Neuronal responses to prolonged stimulation attenuate over time. Here, we ask a fundamental question: is adaptation a simple process for the neural system during which sustained input is ignored, or is it actually part of a strategy for the neural system to adjust its encoding properties dynamically? After simultaneously recording the activities of a group of bullfrog's retinal ganglion cells (dimming detectors) in response to sustained dimming stimulation, we applied a combination of information analysis approaches to explore the time-dependent nature of information encoding during the adaptation. We found that at the early stage of the adaptation, the stimulus information was mainly encoded in firing rates, whereas at the late stage of the adaptation, it was more encoded in neural correlations. Such a transition in encoding properties is not a simple consequence of the attenuation of neuronal firing rates, but rather involves an active change in the neural correlation strengths, suggesting that it is a strategy adopted by the neural system for functional purposes. Our results reveal that in encoding a prolonged stimulation, the neural system may utilize concerted, but less active, firings of neurons to encode information.retinal ganglion cell; luminance adaptation; information coding; neural correlation; discrimination ADAPTATION REFERS TO A GENERAL phenomenon in which a neural system adjusts its response property according to the statistics of external inputs (Kohn 2007;Wark et al. 2007). It has been widely suggested that adaptation underlies the strategy for a neural system to utilize its resource efficiently to encode stimulus information (Fairhall et al. 2001;Gutnisky and Dragoi 2008;Lesica et al. 2007;Maravall et al. 2007). For instance, it was found that the tuning functions of sensory neurons are optimized to match the variance of inputs in a natural environment, so that high encoding accuracy for the whole range of stimuli is achieved (Laughlin 1981). In practice, adaptation can also occur very rapidly in response to sudden changes in the input statistics, so that the stimulus information is transmitted with high fidelity (Fairhall et al. 2001;Sharpee et al. 2006). A recent experimental work reported that in addition to enhancing information representation, adaptation can regulate information content transmitted in the sensory pathway (Wang et al. 2010). Thus, to fully understand how the brain processes stimulus information in a natural dynamical environment, it is critical to unveil the computational roles associated with adaptation.Luminance adaptation, in which a neural system is exposed to a sustained stimulation with constant luminance, is a fundamental visual adaptation process whose biophysical mechanisms and potential computational roles have been intensively studied (Wark et al. 2007). However, the detailed time course as to how the stimulus information is encoded dynamically in the varying neural responses during adaptation remains largely unresolved (Kastner and Baccus 2011). In luminance ad...

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Section: Discussionsupporting

confidence: 94%

Section: Discussionmentioning

confidence: 99%

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Shifted encoding strategy in retinal luminance adaptation: from firing rate to neural correlation

Xiao

Zhang

Xing

et al. 2013

Journal of Neurophysiology

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“…Moreover, retinotopic maps show experience-dependent plasticity throughout life, allowing them to accommodate changes in the sensory periphery as well as the brain. Current models of activity-dependent mechanisms of topographic map plasticity are based on coactivity rules (4-7), however information in natural scenes may be encoded in additional temporal properties of neuronal firing other than coactivity (8)(9)(10)(11). For instance, temporal features of RGC spiking have been shown to encode information about the visual stimuli (12).…”

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confidence: 99%

Optic flow instructs retinotopic map formation through a spatial to temporal to spatial transformation of visual information

Hiramoto

Cline

2014

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

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Retinotopic maps are plastic in response to changes in sensory input; however, the experience-dependent instructive cues that organize retinotopy are unclear. In animals with forward-directed locomotion, the predominant anterior to posterior optic flow activates retinal ganglion cells in a stereotyped temporal to nasal sequence. Here we imaged retinotectal axon arbor location and structural plasticity to assess map refinement in vivo while exposing Xenopus tadpoles to visual stimuli. We show that the temporal sequence of retinal activity driven by natural optic flow organizes retinotopy by regulating axon arbor branch dynamics, whereas the opposite sequence of retinal activity prevents map refinement. Our study demonstrates that a spatial to temporal to spatial transformation of visual information controls experience-dependent topographic map plasticity. This organizational principle is likely to apply to other sensory modalities and projections in the brain.temporal code | topographic map | activity-dependent plasticity | STDP | visual system I n the visual system, the sensory world is mapped onto the planar array of retinal ganglion cells (RGCs), and this representation of the visual world is then conveyed to the CNS via the spatial distribution of retinal axons in the target area. It is widely accepted that molecular cues guide retinal axons to approximate regions along the rostrocaudal axis of the target and that activitydependent mechanisms refine this crude map (1-3). Moreover, retinotopic maps show experience-dependent plasticity throughout life, allowing them to accommodate changes in the sensory periphery as well as the brain. Current models of activity-dependent mechanisms of topographic map plasticity are based on coactivity rules (4-7), however information in natural scenes may be encoded in additional temporal properties of neuronal firing other than coactivity (8-11). For instance, temporal features of RGC spiking have been shown to encode information about the visual stimuli (12). Movement of objects through the visual field activates RGCs in a temporal sequence, which corresponds to a progression of spatial locations of the object in the visual scene. This raises the possibility that the temporal sequence of RGC activity might encode spatial information that can be used to organize retinotopic maps.A candidate visual input that shapes retinotopy is optic flow. In most forward-moving animals, the direction of optic flow is biased from anterior to posterior (A→P). For instance, tadpoles always swim forward, and the predominant visual stimulus they experience is A→P motion within the visual scene. This generates an overall correlation between the sequential order of RGC activity from temporal to nasal retina and the retinotopic distribution of axon projections along the rostrocaudal axis of the tectal target (13). However, whether or how the relative sequence of activity induced by optic flow organizes retinotopy is unclear.We tested whether the spatial arrangement of sensory afferents in the retino...

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“…In the visual system, populations of retinal ganglion cells (RGCs)-the brain's sole source of visual information-exhibit activity correlations. Previous work has shown that failing to account for these correlations decreases decoded information by 0-20% (Nirenberg et al, 2001;Pillow et al, 2008;Meytlis et al, 2012).…”

Section: Introductionmentioning

confidence: 98%

Ignoring correlated activity causes a failure of retinal population codes under moonlight conditions

Ruda

Zylberberg

Field

2019

Preprint

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The retina encodes visual stimuli across light intensities spanning 10-12 orders of magnitude from starlight to sunlight. To accommodate this enormous range, adaptation alters retinal output, changing both the signal and noise among populations of retinal ganglion cells (RGCs). Here we determine how these light level-dependent changes in signal and noise impact decoding of retinal output. In particular, we consider the importance of accounting for noise correlations among RGCs to optimally read out retinal activity. We find that at moonlight conditions, correlated noise is greater and assuming independent noise severely diminished decoding performance. In fact, assuming independence among a local population of RGCs produced worse decoding than using a single RGC, demonstrating a failure of population codes when correlated noise is substantial and ignored. We generalize these results with a simple model to determine the signal and noise conditions under which this failure of population processing can occur. This work elucidates the circumstances in which accounting for noise correlations is necessary to take advantage of population-level codes and shows that sensory adaptation can strongly impact decoding requirements on downstream brain areas.

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Determining the role of correlated firing in large populations of neurons using white noise and natural scene stimuli

Cited by 23 publications

References 32 publications

Shifted encoding strategy in retinal luminance adaptation: from firing rate to neural correlation

Shifted encoding strategy in retinal luminance adaptation: from firing rate to neural correlation

Optic flow instructs retinotopic map formation through a spatial to temporal to spatial transformation of visual information

Ignoring correlated activity causes a failure of retinal population codes under moonlight conditions

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