Failure in a population: Tauopathy disrupts homeostatic set-points in emergent dynamics despite stability in the constituent neurons.

Homeostatic regulation of neuronal activity is essential for robust computation; set-points, such as firing rate, are actively stabilized to compensate for perturbations. The disruption of brain function central to neurodegenerative disease likely arises from impairments of computationally essential set-points. Here, we systematically investigated the effects of tau-mediated neurodegeneration on all known set-points in neuronal activity.

A nonoscillatory, millisecond-scale embedding of brain state provides insight into behavior.

The most robust and reliable signatures of brain states are enriched in rhythms between 0.1 and 20 Hz. Here we address the possibility that the fundamental unit of brain state could be at the scale of milliseconds and micrometers.

Sleep restores an optimal computational regime in cortical networks.

Sleep is assumed to subserve homeostatic processes in the brain; however, the set point around which sleep tunes circuit computations is unknown. Slow-wave activity (SWA) is commonly used to reflect the homeostatic aspect of sleep; although it can indicate sleep pressure, it does not explain why animals need sleep. This study aimed to assess whether criticality may be the computational set point of sleep.

Detecting change points in neural population activity with contrastive metric learning.

Finding points in time where the distribution of neural responses changes (change points) is an important step in many neural data analysis pipelines. However, in complex and free behaviors, where we see different types of shifts occurring at different rates, it can be difficult to use existing methods for change point (CP) detection because they can't necessarily handle different types of changes that may occur in the underlying neural distribution. Additionally, response changes are often sparse in high dimensional neural recordings, which can make existing methods detect spurious changes.

Tauopathy severely disrupts homeostatic set-points in emergent neural dynamics but not in the activity of individual neurons.

The homeostatic regulation of neuronal activity is essential for robust computation; key set-points, such as firing rate, are actively stabilized to compensate for perturbations. From this perspective, the disruption of brain function central to neurodegenerative disease should reflect impairments of computationally essential set-points. Despite connecting neurodegeneration to functional outcomes, the impact of disease on set-points in neuronal activity is unknown.

A non-oscillatory, millisecond-scale embedding of brain state provides insight into behavior.

Sleep and wake are understood to be slow, long-lasting processes that span the entire brain. Brain states correlate with many neurophysiological changes, yet the most robust and reliable signature of state is enriched in rhythms between 0.1 and 20 Hz.

Transcriptomic cell type structures in vivo neuronal activity across multiple timescales.

Cell type is hypothesized to be a key determinant of a neuron's role within a circuit. Here, we examine whether a neuron's transcriptomic type influences the timing of its activity. We develop a deep-learning architecture that learns features of interevent intervals across timescales (ms to >30 min).

Directed evolution of Zymomonas mobilis sugar facilitator Glf to overcome glucose inhibition.

Cellular import of D-xylose, the second most abundant sugar in typical lignocellulosic biomass, has been evidenced to be an energy-depriving process in bacterial biocatalysts. The sugar facilitator of Zymomonas mobilis, Glf, is capable of importing xylose at high rates without extra energy input, but is inhibited by D-glucose (the primary biomass sugar), potentially limiting the utility of this transporter for fermentation of sugar mixtures derived from lignocellulose. In this work we developed an Escherichia coli platform strain deficient in glucose and xylose transport to facilitate directed evolution of Glf to overcome glucose inhibition.

Identification of major malate export systems in an engineered malate-producing Escherichia coli aided by substrate similarity search.

Optimization of export mechanisms for valuable extracellular products is important for the development of efficient microbial production processes. Identification of the relevant export mechanism is the prerequisite step for product export optimization. In this work, we identified transporters involved in malate export in an engineered L-malate-producing Escherichia coli strain using cheminformatics-guided genetics tests.

Parallel experimental evolution reveals a novel repressive control of GalP on xylose fermentation in Escherichia coli.

Efficient xylose utilization will facilitate microbial conversion of lignocellulosic sugar mixtures into valuable products. In Escherichia coli, xylose catabolism is controlled by carbon catabolite repression (CCR). However, in E.