Dataset Information

Inferring learning rules from distributions of firing rates in cortical neurons.

ABSTRACT: Information about external stimuli is thought to be stored in cortical circuits through experience-dependent modifications of synaptic connectivity. These modifications of network connectivity should lead to changes in neuronal activity as a particular stimulus is repeatedly encountered. Here we ask what plasticity rules are consistent with the differences in the statistics of the visual response to novel and familiar stimuli in inferior temporal cortex, an area underlying visual object recognition. We introduce a method that allows one to infer the dependence of the presumptive learning rule on postsynaptic firing rate, and we show that the inferred learning rule exhibits depression for low postsynaptic rates and potentiation for high rates. The threshold separating depression from potentiation is strongly correlated with both mean and s.d. of the firing rate distribution. Finally, we show that network models implementing a rule extracted from data show stable learning dynamics and lead to sparser representations of stimuli.

SUBMITTER: Lim S

PROVIDER: S-EPMC4666720 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Inferring learning rules from distributions of firing rates in cortical neurons.

Lim Sukbin S McKee Jillian L JL Woloszyn Luke L Amit Yali Y Freedman David J DJ Sheinberg David L DL Brunel Nicolas N

Nature neuroscience 20151102 12

Information about external stimuli is thought to be stored in cortical circuits through experience-dependent modifications of synaptic connectivity. These modifications of network connectivity should lead to changes in neuronal activity as a particular stimulus is repeatedly encountered. Here we ask what plasticity rules are consistent with the differences in the statistics of the visual response to novel and familiar stimuli in inferior temporal cortex, an area underlying visual object recognit ...[more]

PMID: 26523643

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Project description:BackgroundFragile X syndrome (FXS), a neurodevelopmental disorder, is a leading monogenetic cause of intellectual disability and autism spectrum disorder. Notwithstanding the extensive studies using rodent and other pre-clinical models of FXS, which have provided detailed mechanistic insights into the pathophysiology of this disorder, it is only relatively recently that human stem cell-derived neurons have been employed as a model system to further our understanding of the pathophysiological events that may underlie FXS. Our study assesses the physiological properties of human pluripotent stem cell-derived cortical neurons lacking fragile X mental retardation protein (FMRP).MethodsElectrophysiological whole-cell voltage- and current-clamp recordings were performed on two control and three FXS patient lines of human cortical neurons derived from induced pluripotent stem cells. In addition, we also describe the properties of an isogenic pair of lines in one of which FMR1 gene expression has been silenced.ResultsNeurons lacking FMRP displayed bursts of spontaneous action potential firing that were more frequent but shorter in duration compared to those recorded from neurons expressing FMRP. Inhibition of large conductance Ca2+-activated K+ currents and the persistent Na+ current in control neurons phenocopies action potential bursting observed in neurons lacking FMRP, while in neurons lacking FMRP pharmacological potentiation of voltage-dependent Na+ channels phenocopies action potential bursting observed in control neurons. Notwithstanding the changes in spontaneous action potential firing, we did not observe any differences in the intrinsic properties of neurons in any of the lines examined. Moreover, we did not detect any differences in the properties of miniature excitatory postsynaptic currents in any of the lines.ConclusionsPharmacological manipulations can alter the action potential burst profiles in both control and FMRP-null human cortical neurons, making them appear like their genetic counterpart. Our studies indicate that FMRP targets that have been found in rodent models of FXS are also potential targets in a human-based model system, and we suggest potential mechanisms by which activity is altered.

Dataset Information

Inferring learning rules from distributions of firing rates in cortical neurons.

Publications

Inferring learning rules from distributions of firing rates in cortical neurons.

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