Topological Features of Electroencephalography are Robust to Re-referencing and Preprocessing.

Electroencephalography (EEG) is among the most widely diffused, inexpensive, and adopted neuroimaging techniques. Nonetheless, EEG requires measurements against a reference site(s), which is typically chosen by the experimenter, and specific pre-processing steps precede analyses. It is therefore valuable to obtain quantities that are minimally affected by reference and pre-processing choices.

Simplicial and topological descriptions of human brain dynamics.

While brain imaging tools like functional magnetic resonance imaging (fMRI) afford measurements of whole-brain activity, it remains unclear how best to interpret patterns found amid the data's apparent self-organization. To clarify how patterns of brain activity support brain function, one might identify metric spaces that optimally distinguish brain states across experimentally defined conditions. Therefore, the present study considers the relative capacities of several metric spaces to disambiguate experimentally defined brain states.

Resting Brain Fluctuations Are Intrinsically Coupled to Visual Response Dynamics.

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation.

A black esophagus as a result of treatment of inferior vena cava occlusion by a massive pelvic schwannoma.

This case presentation involves a 57-year-old-male who suffered multiple adverse sequels from the delayed diagnosis of a large presacral mass. He initially presented with lower extremity deep vein thrombosis (DVT). Several months later, he had developed a pulmonary embolus.

Quasi-periodic patterns contribute to functional connectivity in the brain.

Functional connectivity is widely used to study the coordination of activity between brain regions over time. Functional connectivity in the default mode and task positive networks is particularly important for normal brain function. However, the processes that give rise to functional connectivity in the brain are not fully understood.

Disentangling Multispectral Functional Connectivity With Wavelets.

The field of brain connectomics develops our understanding of the brain's intrinsic organization by characterizing trends in spontaneous brain activity. Linear correlations in spontaneous blood-oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) fluctuations are often used as measures of functional connectivity (FC), that is, as a quantity describing how similarly two brain regions behave over time. Given the natural spectral scaling of BOLD-fMRI signals, it may be useful to represent BOLD-fMRI as multiple processes occurring over multiple scales.

Resting State fMRI in Rodents.

Resting state functional MRI (fMRI) and functional connectivity are widely applied in humans to examine the role of brain networks in normal function and dysfunction. A similar approach can be taken in rodents, either to obtain translational measures in models of brain disorders or to more carefully examine the neurophysiological underpinnings of the networks. A protocol for resting state functional connectivity in the anesthetized rat, from animal setup to data acquisition to possible pipelines for data analysis, is described.

Detection of neural light-scattering activity in vivo: optical transmittance studies in the rat brain.

Optical studies of ex vivo brain slices where blood is absent show that neural activity is accompanied by significant intrinsic optical signals (IOS) related to activity-dependent scattering changes in neural tissue. However, the neural scattering signals have been largely ignored in vivo in widely-used IOS methods where absorption contrast from hemoglobin was employed. Changes in scattering were observed on a time scale of seconds in previous brain slice IOS studies, similar to the time scale for the hemodynamic response.

The Not-So-Global Blood Oxygen Level-Dependent Signal.

Global signal regression is a controversial processing step for resting-state functional magnetic resonance imaging, partly because the source of the global blood oxygen level-dependent (BOLD) signal remains unclear. On the one hand, nuisance factors such as motion can readily introduce coherent BOLD changes across the whole brain. On the other hand, the global signal has been linked to neural activity and vigilance levels, suggesting that it contains important neurophysiological information and should not be discarded.

Parametric Dependencies of Sliding Window Correlation.

Objective: In this paper, we explore the dependence of sliding window correlation (SWC) results on different parameters of correlating signals. The SWC is extensively used to explore the dynamics of functional connectivity (FC) networks using resting-state functional MRI (rsfMRI) scans. These scanned signals often contain multiple amplitudes, frequencies, and phases.

Instantaneous brain dynamics mapped to a continuous state space.

Measures of whole-brain activity, from techniques such as functional Magnetic Resonance Imaging, provide a means to observe the brain's dynamical operations. However, interpretation of whole-brain dynamics has been stymied by the inherently high-dimensional structure of brain activity. The present research addresses this challenge through a series of scale transformations in the spectral, spatial, and relational domains.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously.

Multiscale network activity in resting state fMRI.

The brain is inherently multiscalar in both space and time. We argue that this multiscalar nature is reflected in the blood oxygenation level dependent (BOLD) fluctuations used to map functional connectivity. We present evidence that global fluctuations in activity, quasiperiodic spatiotemporal patterns, and aperiodic time-varying activity coexist within the BOLD signal.

Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies.

The BOLD signal reflects hemodynamic events within the brain, which in turn are driven by metabolic changes and neural activity. However, the link between BOLD changes and neural activity is indirect and can be influenced by a number of non-neuronal processes. Motion and physiological cycles have long been known to affect the BOLD signal and are present in both humans and animal models.

Considerations for resting state functional MRI and functional connectivity studies in rodents.

Resting state functional MRI (rs-fMRI) and functional connectivity mapping have become widely used tools in the human neuroimaging community and their use is rapidly spreading into the realm of rodent research as well. One of the many attractive features of rs-fMRI is that it is readily translatable from humans to animals and back again. Changes in functional connectivity observed in human studies can be followed by more invasive animal experiments to determine the neurophysiological basis for the alterations, while exploratory work in animal models can identify possible biomarkers for further investigation in human studies.

Phase-amplitude coupling and infraslow (<1 Hz) frequencies in the rat brain: relationship to resting state fMRI.

Resting state functional magnetic resonance imaging (fMRI) can identify network alterations that occur in complex psychiatric diseases and behaviors, but its interpretation is difficult because the neural basis of the infraslow BOLD fluctuations is poorly understood. Previous results link dynamic activity during the resting state to both infraslow frequencies in local field potentials (LFP) (<1 Hz) and band-limited power in higher frequency LFP (>1 Hz). To investigate the relationship between these frequencies, LFPs were recorded from rats under two anesthetics: isoflurane and dexmedetomidine.