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e that SI/SP-T includes very specific and identifiable procedures and materials, so it is reasonable to expect high treatment fidelity when testing the approach. AZD9291 nmr A patient case is presented that illustrates this confound with a known facilitator (recast intervention) and a method for controlling potential confounds in order to conduct unbiased studies of the effects of SI/SP-T approaches that accurately represent SI/SP-T theories of change.Cortical neural circuits display highly irregular spiking in individual neurons but variably sized collective firing, oscillations and critical avalanches at the population level, all of which have functional importance for information processing. Theoretically, the balance of excitation and inhibition inputs is thought to account for spiking irregularity and critical avalanches may originate from an underlying phase transition. However, the theoretical reconciliation of these multilevel dynamic aspects in neural circuits remains an open question. Herein, we study excitation-inhibition (E-I) balanced neuronal network with biologically realistic synaptic kinetics. It can maintain irregular spiking dynamics with different levels of synchrony and critical avalanches emerge near the synchronous transition point. We propose a novel semi-analytical mean-field theory to derive the field equations governing the network macroscopic dynamics. It reveals that the E-I balanced state of the network manifesting irregular individual spiking is characterized by a macroscopic stable state, which can be either a fixed point or a periodic motion and the transition is predicted by a Hopf bifurcation in the macroscopic field. Furthermore, by analyzing public data, we find the coexistence of irregular spiking and critical avalanches in the spontaneous spiking activities of mouse cortical slice in vitro, indicating the universality of the observed phenomena. Our theory unveils the mechanism that permits complex neural activities in different spatiotemporal scales to coexist and elucidates a possible origin of the criticality of neural systems. It also provides a novel tool for analyzing the macroscopic dynamics of E-I balanced networks and its relationship to the microscopic counterparts, which can be useful for large-scale modeling and computation of cortical dynamics.Sparse time series models have shown promise in estimating contemporaneous and ongoing brain connectivity. This paper was motivated by a neuroscience experiment using EEG signals as the outcome of our established interventional protocol, a new method in neurorehabilitation toward developing a treatment for visual verticality disorder in post-stroke patients. To analyze the [complex outcome measure (EEG)] that reflects neural-network functioning and processing in more specific ways regarding traditional analyses, we make a comparison among sparse time series models (classic VAR, GLASSO, TSCGM, and TSCGM-modified with non-linear and iterative optimizations) combined with a graphical approach, such as a Dynamic Chain Graph Model (DCGM). These dynamic graphical models were useful in assessing the role of estimating the brain network structure and describing its causal relationship. In addition, the class of DCGM was able to visualize and compare experimental conditions and brain frequency domains [using finite impulse response (FIR) filter]. Moreover, using multilayer networks, the results corroborate with the susceptibility of sparse dynamic models, bypassing the false positives problem in estimation algorithms. We conclude that applying sparse dynamic models to EEG data may be useful for describing intervention-relocated changes in brain connectivity.Axonopathy is a pathological feature observed in both Alzheimer's disease (AD) patients and animal models. However, identifying the temporal and regional progression of axonopathy during AD development remains elusive. Using the fluorescence micro-optical sectioning tomography system, we acquired whole-brain datasets in the early stage of 5xFAD/Thy1-GFP-M mice. We reported that among GFP labeled axons, GFP-positive axonopathy first formed in the lateral septal nucleus, subiculum, and medial mammillary nucleus. The axonopathy further increased in most brain regions during aging. However, most of the axonopathic varicosities disappeared significantly in the medial mammillary nucleus after 8 weeks old. Continuous three-dimensional datasets showed that axonopathy in the medial mammillary nucleus was mainly located on axons from hippocampal GFP-positive neurons. Using the rabies viral tracer in combination with immunohistochemistry, we found that axons in the medial mammillary nucleus from the subiculum were susceptible to lesions that prior to the occurrence of behavioral disorders. In conclusion, we created an early-stage spatiotemporal map of axonopathy in 5xFAD/Thy1-GFP-M mice and identified specific neural circuits which are vulnerable to axon lesions in an AD mouse model. These findings underline the importance of early interventions for AD, and may contribute to the understanding of its progression and its early symptom treatment.The hypothalamus is a heterogeneous rostral forebrain region that regulates physiological processes essential for survival, energy metabolism, and reproduction, mainly mediated by the pituitary gland. In the updated prosomeric model, the hypothalamus represents the rostralmost forebrain, composed of two segmental regions (terminal and peduncular hypothalamus), which extend respectively into the non-evaginated preoptic telencephalon and the evaginated pallio-subpallial telencephalon. Complex genetic cascades of transcription factors and signaling molecules rule their development. Alterations of some of these molecular mechanisms acting during forebrain development are associated with more or less severe hypothalamic and pituitary dysfunctions, which may be associated with brain malformations such as holoprosencephaly or septo-optic dysplasia. Studies on transgenic mice with mutated genes encoding critical transcription factors implicated in hypothalamic-pituitary development are contributing to understanding the high clinical complexity of these pathologies.
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