Predicting executive functioning from walking features in Parkinson's disease using machine learning.

Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and executive functioning in patients with Parkinson's disease using state-of-the-art machine learning approaches.

Coordinated changes in a cortical circuit sculpt effects of novelty on neural dynamics.

Recent studies have found dramatic cell-type-specific responses to stimulus novelty, highlighting the importance of analyzing the cortical circuitry at this granularity to understand brain function. Although initial work characterized activity by cell type, the alterations in cortical circuitry due to interacting novelty effects remain unclear. We investigated circuit mechanisms underlying the observed neural dynamics in response to novel stimuli using a large-scale public dataset of electrophysiological recordings in behaving mice and a population network model.

A cognitive process model captures near-optimal confidence-guided waiting in rats.

Rational decision-makers invest more time pursuing rewards they are more confident they will eventually receive. A series of studies have therefore used willingness to wait for delayed rewards as a proxy for decision confidence. However, interpretation of waiting behavior is limited because it is unclear how environmental statistics influence optimal waiting, and how sources of internal variability influence subjects' behavior.

Behavioral strategy shapes activation of the Vip-Sst disinhibitory circuit in visual cortex.

In complex environments, animals can adopt diverse strategies to find rewards. How distinct strategies differentially engage brain circuits is not well understood. Here, we investigate this question, focusing on the cortical Vip-Sst disinhibitory circuit between vasoactive intestinal peptide-postive (Vip) interneurons and somatostatin-positive (Sst) interneurons.

Non-Invasive Wearable Devices for Monitoring Vital Signs in Patients with Type 2 Diabetes Mellitus: A Systematic Review.

Type 2 diabetes mellitus (T2D) poses a significant global health challenge and demands effective self-management strategies, including continuous blood glucose monitoring (CGM) and lifestyle adaptations. While CGM offers real-time glucose level assessment, the quest for minimizing trauma and enhancing convenience has spurred the need to explore non-invasive alternatives for monitoring vital signs in patients with T2D. This systematic review is the first that explores the current literature and critically evaluates the use and reporting of non-invasive wearable devices for monitoring vital signs in patients with T2D.

Coordinated changes in a cortical circuit sculpt effects of novelty on neural dynamics.

Recent studies have found dramatic cell-type specific responses to stimulus novelty, highlighting the importance of analyzing the cortical circuitry at the cell-type specific level of granularity to understand brain function. Although initial work classified and characterized activity for each cell type, the specific alterations in cortical circuitry-particularly when multiple novelty effects interact-remain unclear. To address this gap, we employed a large-scale public dataset of electrophysiological recordings in the visual cortex of awake, behaving mice using Neuropixels probes and designed population network models to investigate the observed changes in neural dynamics in response to a combination of distinct forms of novelty.

Optimizing sleep staging on multimodal time series: Leveraging borderline synthetic minority oversampling technique and supervised convolutional contrastive learning.

Sleep is an important research area in nutritional medicine that plays a crucial role in human physical and mental health restoration. It can influence diet, metabolism, and hormone regulation, which can affect overall health and well-being. As an essential tool in the sleep study, the sleep stage classification provides a parsing of sleep architecture and a comprehensive understanding of sleep patterns to identify sleep disorders and facilitate the formulation of targeted sleep interventions.

Sensor-Based Classification of Primary and Secondary Car Driver Activities Using Convolutional Neural Networks.

To drive safely, the driver must be aware of the surroundings, pay attention to the road traffic, and be ready to adapt to new circumstances. Most studies on driving safety focus on detecting anomalies in driver behavior and monitoring cognitive capabilities in drivers. In our study, we proposed a classifier for basic activities in driving a car, based on a similar approach that could be applied to the recognition of basic activities in daily life, that is, using electrooculographic (EOG) signals and a one-dimensional convolutional neural network (1D CNN).

SenseHunger: Machine Learning Approach to Hunger Detection Using Wearable Sensors.

The perception of hunger and satiety is of great importance to maintaining a healthy body weight and avoiding chronic diseases such as obesity, underweight, or deficiency syndromes due to malnutrition. There are a number of disease patterns, characterized by a chronic loss of this perception. To our best knowledge, hunger and satiety cannot be classified using non-invasive measurements.

Stable choice coding in rat frontal orienting fields across model-predicted changes of mind.

During decision making in a changing environment, evidence that may guide the decision accumulates until the point of action. In the rat, provisional choice is thought to be represented in frontal orienting fields (FOF), but this has only been tested in static environments where provisional and final decisions are not easily dissociated. Here, we characterize the representation of accumulated evidence in the FOF of rats performing a recently developed dynamic evidence accumulation task, which induces changes in the provisional decision, referred to as "changes of mind".

Proximity Ligation Mapping of Microcephaly Associated SMPD4 Shows Association with Components of the Nuclear Pore Membrane.

SMPD4 is a neutral sphingomyelinase implicated in a specific type of congenital microcephaly. Although not intensively studied, SMPD4 deficiency has also been found to cause cell division defects. This suggests a role for SMPD4 in cell-cycle and differentiation.

Generating Membrane Curvature at the Nuclear Pore: A Lipid Point of View.

In addition to its structural role in enclosing and protecting the genome, the nuclear envelope (NE) forms a highly adaptive communication interface between the cytoplasm and the nuclear interior in eukaryotic cells. The double membrane of the NE is perforated by nuclear pores lined with large multi-protein structures, called nuclear-pore complexes (NPCs), which selectively allow the bi-directional transport of ions and macromolecular cargo. In order to nucleate a pore, the inner and outer nuclear membrane have to fuse at the site of NPC insertion, a process requiring both lipid bilayers to be deformed into highly curved structures.

Interrogating theoretical models of neural computation with emergent property inference.

A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or a pattern of neural activity -- and thus can offer insights into neural computation. The operation of these circuits, like all models, critically depends on the choice of model parameters.

Collicular circuits for flexible sensorimotor routing.

Context-based sensorimotor routing is a hallmark of executive control. Pharmacological inactivations in rats have implicated the midbrain superior colliculus (SC) in this process. But what specific role is this, and what circuit mechanisms support it? Here we report a subset of rat SC neurons that instantiate a specific link between the representations of context and motor choice.

Ten-Year Outcome of Neoadjuvant Chemoradiotherapy Plus Surgery for Esophageal Cancer: The Randomized Controlled CROSS Trial.

Purpose: Preoperative chemoradiotherapy according to the chemoradiotherapy for esophageal cancer followed by surgery study (CROSS) has become a standard of care for patients with locally advanced resectable esophageal or junctional cancer. We aimed to assess long-term outcome of this regimen.

Methods: From 2004 through 2008, we randomly assigned 366 patients to either five weekly cycles of carboplatin and paclitaxel with concurrent radiotherapy (41.

Lateral orbitofrontal cortex promotes trial-by-trial learning of risky, but not spatial, biases.

Individual choices are not made in isolation but are embedded in a series of past experiences, decisions, and outcomes. The effects of past experiences on choices, often called sequential biases, are ubiquitous in perceptual and value-based decision-making, but their neural substrates are unclear. We trained rats to choose between cued guaranteed and probabilistic rewards in a task in which outcomes on each trial were independent.

An Analysis of Decision under Risk in Rats.

In 1979, Daniel Kahneman and Amos Tversky published a ground-breaking paper titled "Prospect Theory: An Analysis of Decision under Risk," which presented a behavioral economic theory that accounted for the ways in which humans deviate from economists' normative workhorse model, Expected Utility Theory [1, 2]. For example, people exhibit probability distortion (they overweight low probabilities), loss aversion (losses loom larger than gains), and reference dependence (outcomes are evaluated as gains or losses relative to an internal reference point). We found that rats exhibited many of these same biases, using a task in which rats chose between guaranteed and probabilistic rewards.

Rats adopt the optimal timescale for evidence integration in a dynamic environment.

Decision making in dynamic environments requires discounting old evidence that may no longer inform the current state of the world. Previous work found that humans discount old evidence in a dynamic environment, but do not discount at the optimal rate. Here we investigated whether rats can optimally discount evidence in a dynamic environment by adapting the timescale over which they accumulate evidence.

Effect of Neoadjuvant Chemoradiotherapy on Health-Related Quality of Life in Esophageal or Junctional Cancer: Results From the Randomized CROSS Trial.

Purpose To compare pre-agreed health-related quality of life (HRQOL) domains in patients with esophageal or junctional cancer who received neoadjuvant chemoradiotherapy (nCRT) followed by surgery or surgery alone. Secondary aims were to examine the effect of nCRT on HRQOL before surgery and the effect of surgery on HRQOL. Patients and Methods Patients were randomly assigned to nCRT (carboplatin plus paclitaxel with concurrent 41.

Rat Prefrontal Cortex Inactivations during Decision Making Are Explained by Bistable Attractor Dynamics.

Two-node attractor networks are flexible models for neural activity during decision making. Depending on the network configuration, these networks can model distinct aspects of decisions including evidence integration, evidence categorization, and decision memory. Here, we use attractor networks to model recent causal perturbations of the frontal orienting fields (FOF) in rat cortex during a perceptual decision-making task (Erlich, Brunton, Duan, Hanks, & Brody, 2015 ).