Functional ultrasound and brain connectivity reveal central nervous system compromise in Trembler-J mice model of Charcot-Marie-Tooth disease.

The Charcot-Marie-Tooth-1E (CMT1E) disease is typically described as a peripheral neuropathy in humans, causing decreased nerve conduction, spastic paralysis, and tremor. The Trembler-J (TrJ) mice serve as a high fidelity model of this disease. Here, we use functional ultrasound (fUS) and functional connectivity (FC) to analyze TrJ mice's brain activity during sensory stimulation and resting state experiments against wild type (WT) mice - the healthy counterpart.

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries).

Brain clocks capture diversity and disparity in aging and dementia.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of multimodal diversity (geographical, socioeconomic, sociodemographic, sex, neurodegeneration) on the brain age gap (BAG) is unknown. Here, we analyzed datasets from 5,306 participants across 15 countries (7 Latin American countries -LAC, 8 non-LAC).

Dorsal and median raphe neuronal firing dynamics characterized by nonlinear measures.

The dorsal (DRN) and median (MRN) raphe are important nuclei involved in similar functions, including mood and sleep, but playing distinct roles. These nuclei have a different composition of neuronal types and set of neuronal connections, which among other factors, determine their neuronal dynamics. Most works characterize the neuronal dynamics using classic measures, such as using the average spiking frequency (FR), the coefficient of variation (CV), and action potential duration (APD).

Brain health in diverse settings: How age, demographics and cognition shape brain function.

Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies.

Genetic basis of anatomical asymmetry and aberrant dynamic functional networks in Alzheimer's disease.

Genetic associations with macroscopic brain networks can provide insights into healthy and aberrant cortical connectivity in disease. However, associations specific to dynamic functional connectivity in Alzheimer's disease are still largely unexplored. Understanding the association between gene expression in the brain and functional networks may provide useful information about the molecular processes underlying variations in impaired brain function.

In Vivo Ultrafast Doppler Imaging Combined with Confocal Microscopy and Behavioral Approaches to Gain Insight into the Central Expression of Peripheral Neuropathy in Trembler-J Mice.

The main human hereditary peripheral neuropathy (Charcot-Marie-Tooth, CMT), manifests in progressive sensory and motor deficits. Mutations in the compact myelin protein gene pmp22 cause more than 50% of all CMTs. CMT1E is a subtype of CMT1 myelinopathy carrying micro-mutations in pmp22.

Sleep disrupts complex spiking dynamics in the neocortex and hippocampus.

Neuronal interactions give rise to complex dynamics in cortical networks, often described in terms of the diversity of activity patterns observed in a neural signal. Interestingly, the complexity of spontaneous electroencephalographic signals decreases during slow-wave sleep (SWS); however, the underlying neural mechanisms remain elusive. Here, we analyse in-vivo recordings from neocortical and hippocampal neuronal populations in rats and show that the complexity decrease is due to the emergence of synchronous neuronal DOWN states.

Low frequency oscillations drive EEG's complexity changes during wakefulness and sleep.

Recently, the sleep-wake states have been analysed using novel complexity measures, complementing the classical analysis of EEGs by frequency bands. This new approach consistently shows a decrease in EEG's complexity during slow-wave sleep, yet it is unclear how cortical oscillations shape these complexity variations. In this work, we analyse how the frequency content of brain signals affects the complexity estimates in freely moving rats.

Intensity distribution segmentation in ultrafast Doppler combined with scanning laser confocal microscopy for assessing vascular changes associated with ageing in murine hippocampi.

The hippocampus plays an important role in learning and memory, requiring high-neuronal oxygenation. Understanding the relationship between blood flow and vascular structure-and how it changes with ageing-is physiologically and anatomically relevant. Ultrafast Doppler ([Formula: see text]Doppler) and scanning laser confocal microscopy (SLCM) are powerful imaging modalities that can measure in vivo cerebral blood volume (CBV) and post mortem vascular structure, respectively.

EEG Gamma Band Alterations and REM-like Traits Underpin the Acute Effect of the Atypical Psychedelic Ibogaine in the Rat.

Ibogaine is a psychedelic alkaloid that has attracted large scientific interest because of its antiaddictive properties in observational studies in humans as well as in animal models. Its subjective effect has been described as intense, vivid dream-like experiences occurring while awake; hence, ibogaine is often referred to as an oneirogenic psychedelic. While this unique dream-like profile has been hypothesized to aid the antiaddictive effects, the electrophysiological signatures of this psychedelic state remain unknown.

Communication Through Coherence by Means of Cross-frequency Coupling.

The theory of communication through coherence (CTC) posits the synchronization of brain oscillations as a key mechanism for information sharing and perceptual binding. In a parallel literature, hippocampal theta activity (4-10 Hz) has been shown to modulate the appearance of neocortical fast gamma oscillations (100-150 Hz), a phenomenon known as cross-frequency coupling (CFC). Even though CFC has also been previously associated with information routing, it remains to be determined whether it directly relates to CTC.

Small-worldness favours network inference in synthetic neural networks.

A main goal in the analysis of a complex system is to infer its underlying network structure from time-series observations of its behaviour. The inference process is often done by using bi-variate similarity measures, such as the cross-correlation (CC) or mutual information (MI), however, the main factors favouring or hindering its success are still puzzling. Here, we use synthetic neuron models in order to reveal the main topological properties that frustrate or facilitate inferring the underlying network from CC measurements.

Decreased electrocortical temporal complexity distinguishes sleep from wakefulness.

In most mammals, the sleep-wake cycle is constituted by three behavioral states: wakefulness (W), non-REM (NREM) sleep, and REM sleep. These states are associated with drastic changes in cognitive capacities, mostly determined by the function of the thalamo-cortical system. The intra-cranial electroencephalogram or electocorticogram (ECoG), is an important tool for measuring the changes in the thalamo-cortical activity during W and sleep.

Nasal respiration entrains neocortical long-range gamma coherence during wakefulness.

Recent studies have shown that slow cortical potentials in archi-, paleo- and neocortex can phase-lock with nasal respiration. In some of these areas, gamma activity (γ: 30-100 Hz) is also coupled to the animal's respiration. It has been hypothesized that these functional relationships play a role in coordinating distributed neural activity.

Social learning in large online audiences of health professionals: Improving dialogue with automated tools.

This article was migrated. The article was marked as recommended. Massive open online courses (MOOCs) bring about the opportunity to reach large international audiences of health professionals.

Entropy-based generating Markov partitions for complex systems.

Finding the correct encoding for a generic dynamical system's trajectory is a complicated task: the symbolic sequence needs to preserve the invariant properties from the system's trajectory. In theory, the solution to this problem is found when a Generating Markov Partition (GMP) is obtained, which is only defined once the unstable and stable manifolds are known with infinite precision and for all times. However, these manifolds usually form highly convoluted Euclidean sets, are a priori unknown, and, as it happens in any real-world experiment, measurements are made with finite resolution and over a finite time-span.

Dynamical detection of network communities.

A prominent feature of complex networks is the appearance of communities, also known as modular structures. Specifically, communities are groups of nodes that are densely connected among each other but connect sparsely with others. However, detecting communities in networks is so far a major challenge, in particular, when networks evolve in time.

Approximate solution for frequency synchronization in a finite-size Kuramoto model.

Scientists have been considering the Kuramoto model to understand the mechanism behind the appearance of collective behavior, such as frequency synchronization (FS) as a paradigm, in real-world networks with a finite number of oscillators. A major current challenge is to obtain an analytical solution for the phase angles. Here, we provide an approximate analytical solution for this problem by deriving a master solution for the finite-size Kuramoto model, with arbitrary finite-variance distribution of the natural frequencies of the oscillators.

Resiliently evolving supply-demand networks.

The ability to design a transport network such that commodities are brought from suppliers to consumers in a steady, optimal, and stable way is of great importance for distribution systems nowadays. In this work, by using the circuit laws of Kirchhoff and Ohm, we provide the exact capacities of the edges that an optimal supply-demand network should have to operate stably under perturbations, i.e.

Language organization and temporal correlations in the spiking activity of an excitable laser: experiments and model comparison.

We introduce a method, based on symbolic analysis, to characterize the temporal correlations of the spiking activity exhibited by excitable systems. The technique is applied to the experimentally observed dynamics of a semiconductor laser with optical feedback operating in the low-frequency fluctuations regime, where the laser intensity displays irregular trains of sudden dropouts that can be interpreted as excitable pulses. Symbolic analysis transforms the series of interdropout time intervals into sequences of words, which represent the local ordering of a certain (small) number of those intervals.

Experimental results on synchronization times and stable states in locally coupled light-controlled oscillators.

Recently, a new kind of optically coupled oscillators that behave as relaxation oscillators has been studied experimentally in the case of local coupling. Even though numerical results exist, there are no references about experimental studies concerning the synchronization times with local coupling. In this paper, we study both experimentally and numerically a system of coupled oscillators in different configurations, including local coupling.