Response properties of visual neurons in the turtle nucleus isthmi

Saha, Diganta; Morton, David; Ariel, Michael; Weßel, Ralf

doi:10.1007/s00359-010-0596-3

Cited by 20 publications

(16 citation statements)

References 55 publications

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“…We suddenly switched from no visual input (darkness) to a movie projected onto the retina of the ex vivo turtle eye-attached whole-brain preparation [16,25] (Fig 2A). Using a microelectrode array we recorded local field potential (LFP) and multi-unit activity (MUA) from visual cortex (Fig 2B).…”

Section: Resultsmentioning

confidence: 99%

Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection

Clawson

Weßel

et al. 2017

PLoS Comput Biol

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Fundamental to the function of nervous systems is the ability to reorganize to cope with changing sensory input. Although well-studied in single neurons, how such adaptive versatility manifests in the collective population dynamics and function of cerebral cortex remains unknown. Here we measured population neural activity with microelectrode arrays in turtle visual cortex while visually stimulating the retina. First, we found that, following the onset of stimulation, adaptation tunes the collective population dynamics towards a special regime with scale-free spatiotemporal activity, after an initial large-scale transient response. Concurrently, we observed an adaptive tradeoff between two important aspects of population coding–sensory detection and discrimination. As adaptation tuned the cortex toward scale-free dynamics, stimulus discrimination was enhanced, while stimulus detection was reduced. Finally, we used a network-level computational model to show that short-term synaptic depression was sufficient to mechanistically explain our experimental results. In the model, scale-free dynamics emerge only when the model operates near a special regime called criticality. Together our model and experimental results suggest unanticipated functional benefits and costs of adaptation near criticality in visual cortex.

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Section: Resultsmentioning

confidence: 99%

Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection

Clawson

Weßel

et al. 2017

PLoS Comput Biol

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“…Turtles were anesthetized with propofol (2 mg of propofol/kg) then decapitated. Dissection proceeded as described previously (Saha et al, 2011;Crockett et al, 2015;Wright et al, 2017a).…”

Section: Surgery and Visual Cortexmentioning

confidence: 99%

Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality

Johnson

Xià

et al. 2019

J. Neurosci.

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What information single neurons receive about general neural circuit activity is a fundamental question for neuroscience. Somatic membrane potential (V m ) fluctuations are driven by the convergence of synaptic inputs from a diverse cross-section of upstream neurons. Furthermore, neural activity is often scale-free, implying that some measurements should be the same, whether taken at large or small scales. Together, convergence and scale-freeness support the hypothesis that single V m recordings carry useful information about high-dimensional cortical activity. Conveniently, the theory of "critical branching networks" (one purported explanation for scale-freeness) provides testable predictions about scale-free measurements that are readily applied to V m fluctuations. To investigate, we obtained whole-cell current-clamp recordings of pyramidal neurons in visual cortex of turtles with unknown genders. We isolated fluctuations in V m below the firing threshold and analyzed them by adapting the definition of "neuronal avalanches" (i.e., spurts of population spiking). The V m fluctuations which we analyzed were scale-free and consistent with critical branching. These findings recapitulated results from large-scale cortical population data obtained separately in complementary experiments using microelectrode arrays described previously (Shew et al., 2015). Simultaneously recorded single-unit local field potential did not provide a good match, demonstrating the specific utility of V m . Modeling shows that estimation of dynamical network properties from neuronal inputs is most accurate when networks are structured as critical branching networks. In conclusion, these findings extend evidence of critical phenomena while also establishing subthreshold pyramidal neuron V m fluctuations as an informative gauge of high-dimensional cortical population activity. The relationship between membrane potential (V m ) dynamics of single neurons and population dynamics is indispensable tounderstanding cortical circuits. Just as important to the biophysics of computation are emergent properties such as scale-freeness, where critical branching networks offer insight. This report makes progress on both fronts by comparing statistics from singleneuron whole-cell recordings with population statistics obtained with microelectrode arrays. Not only are fluctuations of somatic V m scale-free, they match fluctuations of population activity. Thus, our results demonstrate appropriation of the brain's own subsampling method (convergence of synaptic inputs) while extending the range of fundamental evidence for critical phenomena in neural systems from the previously observed mesoscale (fMRI, LFP, population spiking) to the microscale, namely, V m fluctuations.

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“…Turtles were anesthetized with Propofol (2 mg Propofol/kg), then decapitated. Dissection proceeded as described previously (Saha et al, 2011;Crockett et al, 2015;Wright et al, 2017a).…”

Section: Surgery and Visual Cortexmentioning

confidence: 99%

Single-cell membrane potential fluctuations evince network scale-freeness and quasicriticality

Johnson

Xià

et al. 2018

Preprint

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What information single neurons receive about general neural circuit activity is a fundamental question for neuroscience. Somatic membrane potential fluctuations are driven by the convergence of synaptic inputs from a diverse cross section of upstream neurons. Furthermore, neural activity is often scale-free implying that some measurements should be the same, whether taken at large or small scales. Together, convergence and scalefreeness support the hypothesis that single membrane potential recordings carry useful information about highdimensional cortical activity. Conveniently, the theory of "critical branching networks" (a purported explanation for scale-freeness) provides testable predictions about scale-free measurements which are readily applied to membrane potential fluctuations. To investigate, we obtained whole-cell current clamp recordings of pyramidal neurons in visual cortex of turtles with unknown genders. We isolated fluctuations in membrane potential below the firing threshold and analyzed them by adapting the definition of "neuronal avalanches" (spurts of population spiking). The membrane potential fluctuations we analyzed were scale-free and consistent with critical branching. These findings recapitulated results from large-scale cortical population data obtained separately in complementary experiments using microelectrode arrays (previously published (Shew et al., 2015)). Simultaneously recorded single-unit local field potential did not provide a good match; demonstrating the specific utility of membrane potential. Modeling shows that estimation of dynamical network properties from neuronal inputs is most accurate when networks are structured as critical branching networks. In conclusion, these findings extend evidence for critical branching while also establishing subthreshold pyramidal neuron membrane potential fluctuations as an informative gauge of high-dimensional cortical population activity. Significance StatementThe relationship between membrane potential dynamics of single neurons and population dynamics is indispensable to understanding cortical circuits. Just as important to the biophysics of computation are emergent properties such as scale-freeness, where critical branching networks offer insight. This report makes progress on both fronts by comparing statistics from single-neuron whole-cell recordings to population statistics obtained with microelectrode arrays. Not only are fluctuations of somatic membrane potential scale-free, they match fluctuations of population activity. Thus, our results demonstrate appropriation of the brain's own subsampling method (convergence of synaptic inputs), while extending the range of fundamental evidence for critical branching in neural systems from the previously observed mesoscale (fMRI, LFP, population spiking) to the microscale, namely, membrane potential fluctuations.

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Response properties of visual neurons in the turtle nucleus isthmi

Cited by 20 publications

References 55 publications

Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection

Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection

Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality

Single-cell membrane potential fluctuations evince network scale-freeness and quasicriticality

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