18 research outputs found

    A roadmap to integrate astrocytes into Systems Neuroscience.

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    Systems neuroscience is still mainly a neuronal field, despite the plethora of evidence supporting the fact that astrocytes modulate local neural circuits, networks, and complex behaviors. In this article, we sought to identify which types of studies are necessary to establish whether astrocytes, beyond their well-documented homeostatic and metabolic functions, perform computations implementing mathematical algorithms that sub-serve coding and higher-brain functions. First, we reviewed Systems-like studies that include astrocytes in order to identify computational operations that these cells may perform, using Ca2+ transients as their encoding language. The analysis suggests that astrocytes may carry out canonical computations in a time scale of subseconds to seconds in sensory processing, neuromodulation, brain state, memory formation, fear, and complex homeostatic reflexes. Next, we propose a list of actions to gain insight into the outstanding question of which variables are encoded by such computations. The application of statistical analyses based on machine learning, such as dimensionality reduction and decoding in the context of complex behaviors, combined with connectomics of astrocyte-neuronal circuits, is, in our view, fundamental undertakings. We also discuss technical and analytical approaches to study neuronal and astrocytic populations simultaneously, and the inclusion of astrocytes in advanced modeling of neural circuits, as well as in theories currently under exploration such as predictive coding and energy-efficient coding. Clarifying the relationship between astrocytic Ca2+ and brain coding may represent a leap forward toward novel approaches in the study of astrocytes in health and disease

    A roadmap to integrate astrocytes into Systems Neuroscience

    Get PDF
    Systems Neuroscience is still mainly a neuronal field, despite the plethora of evidence supporting the fact that astrocytes modulate local neural circuits, networks, and complex behaviors. In this article, we sought to identify which types of studies are necessary to establish whether astrocytes, beyond their well-documented homeostatic and metabolic functions, perform computations implementing mathematical algorithms that sub-serve coding and higher-brain functions. First, we reviewed Systems-like studies that include astrocytes in order to identify computational operations that these cells may perform, using Ca2+^{2+} transients as their encoding language. The analysis suggests that astrocytes may carry out canonical computations in time scales of sub-seconds to seconds in sensory processing, neuromodulation, brain state, memory formation, fear, and complex homeostatic reflexes. Next, we propose a list of actions to gain insight into the outstanding question of which variables are encoded by such computations. The application of statistical analyses based on machine learning, such as dimensionality reduction and decoding in the context of complex behaviors, combined with connectomics of astrocyte-neuronal circuits, are, in our view, fundamental undertakings. We also discuss technical and analytical approaches to study neuronal and astrocytic populations simultaneously, and the inclusion of astrocytes in advanced modeling of neural circuits, as well as in theories currently under exploration, such as predictive coding and energy-efficient coding. Clarifying the relationship between astrocytic Ca2+^{2+} and brain coding may represent a leap forward towards novel approaches in the study of astrocytes in health and disease.Junior Leader Fellowhip Program by 'la Caixa' Banking Foundation, LCF/BQ/LI18/11630006 BFU2017-85936-P BFU2016-75107-P BFU2016-79735-P FLAGERA-PCIN-2015-162-C02-02 HHMI 55008742 FPU13/05377 NIH R01NS099254 NSF 1604544 Agència de Gestio d’Ajuts Universitaris i de Recerca, 2017 SGR54

    Decrease in GABA<sub>B</sub> expression in APP mice.

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    <p>GABA<sub>B</sub> immunoreactivity in the somatosensory cortex of a 4 month old wildtype littermate control mouse (<b>A</b>), and a 4 month old APP mouse (<b>B</b>). B represents an extreme case. (<b>C</b>) Bar graph comparing GABA<sub>B</sub> immunoreactivity between conditions as a percentage of wildtype level at 4 months (n = 3–4 mice/group, p≤0.001). (<b>D</b>) Slow oscillation power (normalized to wildtype) and (<b>E</b>) mean slow oscillation frequency before (baseline) and after 50 μM saclofen application to the brain of wildtype mice (n = 4 mice). (<b>F</b>) Slow oscillation power (normalized to wildtype) and (<b>G</b>) mean slow oscillation frequency before (baseline) and after 50 μM saclofen application to the brain of APP mice (n = 6 mice). Scale bar, 30 μm. * p<0.05, *** p≤0.001.</p

    Decrease in GABA<sub>A</sub> immunoreactivity in APP mice.

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    <p>GABA<sub>A</sub> immunoreactivity in the somatosensory cortex of a 4 month old wildtype littermate control mouse (<b>A</b>), and a 4 month old APP mouse (<b>B</b>). (<b>C</b>) Bar graph comparing intensity of GABA<sub>A</sub> immunoreactivity between conditions as a percentage of wildtype level at 4 months (n = 3–4 mice/group). (<b>D</b>) Voltage-sensitive dye traces showing a decrease in power of slow oscillations 60 minutes after topical application of 50 μM picrotoxin to a 4 month old wildtype mouse brain. (<b>E</b>) Slow oscillation power (normalized to wildtype) and (<b>F</b>) mean slow oscillation frequency before (WT baseline) and after picrotoxin (PTX) application to brains of 2–4 month old wildtype mice (n = 4 mice). (<b>G</b>) Slow oscillation power (normalized to APP) and (<b>H</b>) mean slow oscillation frequency before (APP baseline) and after picrotoxin (PTX) application to brains of 2–4 month old APP mice (n = 4 mice). Scale bar, 50 μm. * p<0.05, *** p≤0.001.</p
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