Propagating patterns of intrinsic activity along macroscale gradients coordinate functional connections across the whole brain.

The intrinsic activity of the human brain, observed with resting-state fMRI (rsfMRI) and functional connectivity, exhibits macroscale spatial organization such as functional networks and gradients. Dynamic analysis techniques have shown that functional connectivity is a mere summary of time-varying patterns with distinct spatial and temporal characteristics. A better understanding of these patterns might provide insight into aspects of the brain's intrinsic activity that cannot be inferred by functional connectivity or the spatial maps derived from it, such as functional networks and gradients. Here, we describe three spatiotemporal patterns of coordinated activity across the whole brain obtained by averaging similar ~20-second-long segments of rsfMRI timeseries. In each of these patterns, activity propagates along a particular macroscale functional gradient, simultaneously across the cerebral cortex and in most other brain regions. In some regions, like the thalamus, the propagation suggests previously-undescribed gradients. The coordinated activity across areas is consistent with known tract-based connections, and nuanced differences in the timing of peak activity between regions point to plausible driving mechanisms. The magnitude of correlation within and particularly between functional networks is remarkably diminished when these patterns are regressed from the rsfMRI timeseries, a quantitative demonstration of their significant role in functional connectivity. Taken together, our results suggest that a few recurring patterns of propagating intrinsic activity along macroscale gradients give rise to and coordinate functional connections across the whole brain.

Quasi-periodic patterns of intrinsic brain activity in individuals and their relationship to global signal.

Quasiperiodic patterns (QPPs) as reported by Majeed et al., 2011 are prominent features of the brain's intrinsic activity that involve important large-scale networks (default mode, DMN; task positive, TPN) and are likely to be major contributors to widely used measures of functional connectivity. We examined the variability of these patterns in 470 individuals from the Human Connectome Project resting state functional MRI dataset. The QPPs from individuals can be coarsely categorized into two types: one where strong anti-correlation between the DMN and TPN is present, and another where most areas are strongly correlated. QPP type could be predicted by an individual's global signal, with lower global signal corresponding to QPPs with strong anti-correlation. After regression of global signal, all QPPs showed strong anti-correlation between DMN and TPN. QPP occurrence and type was similar between a subgroup of individuals with extremely low motion and the rest of the sample, which shows that motion is not a major contributor to the QPPs. After regression of estimates of slow respiratory and cardiac induced signal fluctuations, more QPPs showed strong anti-correlation between DMN and TPN, an indication that while physiological noise influences the QPP type, it is not the primary source of the QPP itself. QPPs were more similar for the same subjects scanned on different days than for different subjects. These results provide the first assessment of the variability in individual QPPs and their relationship to physiological parameters.

QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity.

One prominent brain dynamic process detected in functional neuroimaging data is large-scale quasi-periodic patterns (QPPs) which display spatiotemporal propagations along brain cortical gradients. QPP associates with the infraslow neural activity related to attention and arousal fluctuations and has been identified in both resting and task-evoked brains across various species. Several QPP detection and analysis tools were developed for distinct applications with study-specific parameter methods. This MATLAB package provides a simplified and user-friendly generally applicable toolbox for detecting, analyzing, and visualizing QPPs from fMRI timeseries of the brain. This paper describes the software functions and presents its ease of use on any brain datasets. Metadata: [Table: see text].

Comparison of Resting-State Functional MRI Methods for Characterizing Brain Dynamics.

Resting-state functional MRI (fMRI) exhibits time-varying patterns of functional connectivity. Several different analysis approaches have been developed for examining these resting-state dynamics including sliding window connectivity (SWC), phase synchrony (PS), co-activation pattern (CAP), and quasi-periodic patterns (QPP). Each of these approaches can be used to generate patterns of activity or inter-areal coordination which vary across time. The individual frames can then be clustered to produce temporal groupings commonly referred to as "brain states." Several recent publications have investigated brain state alterations in clinical populations, typically using a single method for quantifying frame-wise functional connectivity. This study directly compares the results of k-means clustering in conjunction with three of these resting-state dynamics methods (SWC, CAP, and PS) and quantifies the brain state dynamics across several metrics using high resolution data from the human connectome project. Additionally, these three dynamics methods are compared by examining how the brain state characterizations vary during the repeated sequences of brain states identified by a fourth dynamic analysis method, QPP. The results indicate that the SWC, PS, and CAP methods differ in the clusters and trajectories they produce. A clear illustration of these differences is given by how each one results in a very different clustering profile for the 24s sequences explicitly identified by the QPP algorithm. PS clustering is sensitive to QPPs with the mid-point of most QPP sequences grouped into the same single cluster. CAPs are also highly sensitive to QPPs, separating each phase of the QPP sequences into different sets of clusters. SWC (60s window) is less sensitive to QPPs. While the QPPs are slightly more likely to occur during specific SWC clusters, the SWC clustering does not vary during the 24s QPP sequences, the goal of this work is to improve both the practical and theoretical understanding of different resting-state dynamics methods, thereby enabling investigators to better conceptualize and implement these tools for characterizing functional brain networks.

Functional Connectivity of the Brain Across Rodents and Humans.

Resting-state functional magnetic resonance imaging (rs-fMRI), which measures the spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, is increasingly utilized for the investigation of the brain's physiological and pathological functional activity. Rodents, as a typical animal model in neuroscience, play an important role in the studies that examine the neuronal processes that underpin the spontaneous fluctuations in the BOLD signal and the functional connectivity that results. Translating this knowledge from rodents to humans requires a basic knowledge of the similarities and differences across species in terms of both the BOLD signal fluctuations and the resulting functional connectivity. This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity. Homologous functional networks are compared across species, and aspects of the BOLD fluctuations such as the topography of the global signal and the relationship between structural and functional connectivity are examined. Time-varying features of functional connectivity, obtained by sliding windowed approaches, quasi-periodic patterns, and coactivation patterns, are compared across species. Applications demonstrating the use of rs-fMRI as a translational tool for cross-species analysis are discussed, with an emphasis on neurological and psychiatric disorders. Finally, open questions are presented to encapsulate the future direction of the field.

Relationship Between Basic Properties of BOLD Fluctuations and Calculated Metrics of Complexity in the Human Connectome Project.

Resting state functional MRI (rs-fMRI) creates a rich four-dimensional data set that can be analyzed in a variety of ways. As more researchers come to view the brain as a complex dynamical system, tools are increasingly being drawn from other fields to characterize the complexity of the brain's activity. However, given that the signal measured with rs-fMRI arises from the hemodynamic response to neural activity, the extent to which complexity metrics reflect neural complexity as compared to signal properties related to image quality remains unknown. To provide some insight into this question, correlation dimension, approximate entropy and Lyapunov exponent were calculated for different rs-fMRI scans from the same subject to examine their reliability. The metrics of complexity were then compared to several properties of the rs-fMRI signal from each brain area to determine if basic signal features could explain differences in the complexity metrics. Differences in complexity across brain areas were highly reliable and were closely linked to differences in the frequency profiles of the rs-fMRI signal. The spatial distributions of the complexity and frequency metrics suggest that they are both influenced by location-dependent signal properties that can obscure changes related to neural activity.

Postnatal changes of steroid receptor coactivator-1 immunoreactivity in rat cerebellar cortex.

Steroid receptor coactivator-1 (SRC-1) interacts with nuclear hormone receptors (NRs) to mediate their action in a ligand-dependent manner. Among such ligands, thyroid hormone (TH) is particularly crucial for brain development. The expression of many TH target genes is regulated by TH only for a limited critical period, although TH receptor (TR) expression is not greatly altered after such period. To alter TH sensitivity, other factors may be involved. We thus examined the changes in SRC-1 expression during postnatal development in the rat cerebellum by immunohistochemistry and Western blotting. Strong SRC-1 immunoreactivity (IR) was constantly seen in Purkinje cell from postnatal days (P) 2 to P30. SRC-1 IR was also constantly observed in the internal granule cell layer. However, it was negative in the external granule cell layer at P2 and P7, whereas a weak IR was detected in the premigratory zone at P15. SRC-1 IR was detected in the molecular layer after P15. These results indicate that although TR is almost ubiquitously expressed in the developing cerebellum, the TH sensitivity could vary in each subset of cells. By Western blotting, SRC-1 protein level was greatest at P15, at which time TH action may be obvious. Taken together, the differential expression of SRC-1 may be crucial in mediating TH action during cerebellar development.

Quantitative and comparative assessment of learning in a tongue-operated computer input device--part II: navigation tasks.

Tongue drive system (TDS) is a novel tongue-operated assistive technology (AT) for the mobility impaired, to empower them to access computers and drive powered wheelchairs (PWC) using their free voluntary tongue motion. We have evaluated the TDS performance in five sessions over 5-8 weeks to study the learning process in different tasks of computer access and PWC navigation on nine able-bodied subjects who already had tongue piercing and used our magnetic tongue studs throughout the trial. Computer access tasks included on-screen maze navigation and issuing random commands to measure the TDS information transfer rate. PWC navigation included driving through a ~50-m obstacle course using three control strategies. Some of the qualitative aspects of using the TDS were also evaluated based on the two Likert scale questionnaires, one of which was short (eight questions) and asked at the end of each session and the other one (46 questions) at the end of the trial. Included in this study was also a task to measure the tongue fatigue as a result of using the TDS continuously for a few hours. All performance measures showed significant improvement from the first to the second session as well as further gradual improvements throughout the rest of the sessions, suggesting a rapid learning process.

Preliminary assessment of Tongue Drive System in medium term usage for computer access and wheelchair control.

Tongue Drive System (TDS) is a wireless, wearable assistive technology that enables individuals with severe motor impairments access computers, drive wheelchairs, and control their environments using tongue motion. In this paper, we have evaluated the TDS performance as a computer input device using ISO9241-9 standard tasks for pointing and selecting, based on the well known Fitts' Law, and as a powered wheelchair controller through an obstacle course navigation task. Nine able-bodied subjects who already had tongue piercing participated in this trial over 5 sessions during 5 weeks, allowing us to study the TDS learning process and its current limiting factors. Subjects worn tongue rings made of titanium in the form of a barbell with a small rare earth magnetic tracer hermetically sealed inside the upper ball. Comparing the results between 1(st) and 5(th) sessions showed that subjects' performance improved in all the measures through 5 sessions, demonstrating the effects of learning.

Quantitative and comparative assessment of learning in a tongue-operated computer input device.

Tongue drive system (TDS) is a wireless, wearable assistive technology that enables individuals with severe motor impairments to access computers, drive wheelchairs, and control their environments using tongue motion. In this paper, we have evaluated the TDS performance as a computer input device in four tasks, commonly known as horizontal, vertical, center-out, and multidirectional rapid tapping, based on Fitts' law and ISO9241-9 Standard. Nine able-bodied subjects, who already had tongue piercing, participated in this trial over five sessions during 5 weeks, allowing us to study the TDS learning process and its current limiting factors. Subjects wore tongue rings made of titanium in the form of a barbell with a small rare-earth magnetic tracer hermetically sealed inside the upper ball. Participants performed the same tasks with a mouse (only in the first session) as a reference as well as a standard keypad for benchmarking. Six performance measures were considered, including throughput, error rate, and reaction time, all of these improved significantly from the first to the last session, and some of these plateaued over the course of the experiment. The comparison between tongue-TDS versus index-finger-keypad provides valuable insights into tongue human factors, which can lead the way in improving the usability of the TDS and similar tongue-operated assistive technologies.

Using Fitts's law for evaluating Tongue Drive System as a pointing device for computer access.

In this paper, the results of a 2-D center-out task in a Fitts's law experiment have been presented for measuring the performance of the Tongue Drive System (TDS). Although the end-user population for TDS is individuals with tetraplegia, in this study, we recruited 6 able-bodied subjects in 3 sessions, conducted in 3 consecutive days. They performed the same task with their right hand using a standard mouse for achieving a baseline as well as a standard keypad with their right index finger. The resulting average throughput for TDS, keypad, and mouse were 1.67, 2.17, and 3.99 bit/s, respectively.