Inhibitory plasticity supports replay generalization in the hippocampus.

Memory consolidation assimilates recent experiences into long-term memory. This process requires the replay of learned sequences, although the content of these sequences remains controversial. Recent work has shown that the statistics of replay deviate from those of experience: stimuli that are experientially salient may be either recruited or suppressed from sharp-wave ripples.

Behavioral weight management use in the Veterans Health Administration: Sociodemographic and health correlates.

Introduction: Over 40 % of United States Veterans Health Administration (VHA) primary care patients have obesity. Few patients use VHA's flagship weight management program, MOVE! and there is little information on other behavioral weight management program use.

Methods: The national United States cohort included over 1.

The EMBER trial for weight management engagement: A hybrid type 1 randomized controlled trial protocol.

Background: Almost 40% of Veterans Health Administration (VHA) users have obesity. VHA's national weight management program is associated with weight loss and improved health. However, while 94% of eligible VHA users are offered weight management programs, <8% use them.

Hidden behavioral fingerprints in epilepsy.

Epilepsy is a major disorder affecting millions of people. Although modern electrophysiological and imaging approaches provide high-resolution access to the multi-scale brain circuit malfunctions in epilepsy, our understanding of how behavior changes with epilepsy has remained rudimentary. As a result, screening for new therapies for children and adults with devastating epilepsies still relies on the inherently subjective, semi-quantitative assessment of a handful of pre-selected behavioral signs of epilepsy in animal models.

Peer support and whole health coaching to address the healthcare needs of homeless veterans: a pilot study.

Background: Homelessness is a robust social determinant of acute care service utilization among veterans. Although intensive outpatient programs have been developed for homeless veterans who are high utilizers of acute care ("super utilizers"), few scalable programs have been implemented to address their needs.

Objective: Describe the development and pilot testing of a novel intervention that integrates the roles of a peer and whole health coach ("Peer-WHC") in coordination with primary care teams to reduce homeless veterans' frequent use of acute care.

Maximally selective single-cell target for circuit control in epilepsy models.

Neurological and psychiatric disorders are associated with pathological neural dynamics. The fundamental connectivity patterns of cell-cell communication networks that enable pathological dynamics to emerge remain unknown. Here, we studied epileptic circuits using a newly developed computational pipeline that leveraged single-cell calcium imaging of larval zebrafish and chronically epileptic mice, biologically constrained effective connectivity modeling, and higher-order motif-focused network analysis.

Erratum: Entorhinal mismatch: A model of self-supervised learning in the hippocampus.

[This corrects the article DOI: 10.1016/j.isci.

Entorhinal mismatch: A model of self-supervised learning in the hippocampus.

The hippocampal formation displays a wide range of physiological responses to different spatial manipulations of the environment. However, very few attempts have been made to identify core computational principles underlying those hippocampal responses. Here, we capitalize on the observation that the entorhinal-hippocampal complex (EHC) forms a closed loop and projects inhibitory signals "countercurrent" to the trisynaptic pathway to build a self-supervised model that learns to reconstruct its own inputs by error backpropagation.

Epistemic Autonomy: Self-supervised Learning in the Mammalian Hippocampus.

Biological cognition is based on the ability to autonomously acquire knowledge, or epistemic autonomy. Such self-supervision is largely absent in artificial neural networks (ANN) because they depend on externally set learning criteria. Yet training ANN using error backpropagation has created the current revolution in artificial intelligence, raising the question of whether the epistemic autonomy displayed in biological cognition can be achieved with error backpropagation-based learning.

Correction: Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer.

[This corrects the article DOI: 10.1371/journal.pcbi.

Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer.

The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. Patterned mossy fiber activity induces rhythmic Golgi cell activity that is synchronized by shared parallel fiber input and by gap junctions.

Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit.

The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs.

The layer-oriented approach to declarative languages for biological modeling.

We present a new approach to modeling languages for computational biology, which we call the layer-oriented approach. The approach stems from the observation that many diverse biological phenomena are described using a small set of mathematical formalisms (e.g.

MRCI: a flexible real-time dynamic clamp system for electrophysiology experiments.

We present a real-time simulation system that enables modeled dynamical systems to interact with physical experimental systems, and is specifically aimed towards execution of the dynamic clamp protocol. Model reference current injection (MRCI) operates under Real-Time Linux (RT-Linux or RTL) and provides a simple equation-oriented language for describing dynamical system models. Features include scripting of commands to implement repeatable protocols, the ability to output pre-computed waveforms through any variable or parameter of the model, the means to conduct time measurements and assess the computational performance of the real-time system, and an installation program that installs the software and accompanying device drivers with minimal input from the user.