Presynaptic terminals favor intermediate-conductance Ca(V)2.2 (N type) over high-conductance Ca(V)1 (L type) channels for single-channel, Ca(2+) nanodomain-triggered synaptic vesicle fusion. However, the standard Ca(V)1>Ca(V)2>Ca(V)3 conductance hierarchy is based on recordings using nonphysiological divalent ion concentrations. We found that, with physiological Ca(2+) gradients, the hierarchy was Ca(V)2.2>Ca(V)1>Ca(V)3. Mathematical modeling predicts that the Ca(V)2.2 Ca(2+) nanodomain, which is ∼25% more extensive than that generated by Ca(V)1, can activate a calcium-fusion sensor located on the proximal face of the synaptic vesicle.

The DMN has been linked to personal identity and social behavior. As such, our preliminary findings may provide insight into the neuro-functional underpinnings of the cognitive and behavioral changes observed during acute alcohol intoxication. The reduced fractal dimension implies a change in function of small-scale neural networks towards less complex signaling.

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R 2* relaxation provides a semiquantitative method of detecting myelin, iron and white matter fibre orientation angles. Compared with standard histogram-based analyses, angle-resolved analysis of R 2 * has previously been shown to substantially improve the detection of subtle differences in the brain between healthy siblings of subjects with multiple sclerosis and unrelated healthy controls. Neonates, who are born with very little myelin and iron, and an underdeveloped connectome, provide researchers with an opportunity to investigate whether R 2 * is intimately linked with fibre-angle or myelin content as it is in adults, which may in future studies be explored as a potential white matter developmental biomarker. Five healthy adult volunteers (mean age [±SD] = 31.2 [±8.3] years; three males) were recruited from Vancouver, Canada. Eight term neonates (mean age = 38.6 ± 1.2 weeks; five males) were recruited from the Children's Hospital of Chongqing Medical University neonatal ward. All subjects were scanned on identical 3 T Philips Achieva scanners equipped with an eight-channel SENSE head coil and underwent a multiecho gradient echo scan, a 32-direction DTI scan and a myelin water imaging scan. For both neonates and adults, bin-averaged R 2 * variation across the brain's white matter was found to be best explained by fibre orientation. For adults, this represented a difference in R 2 * values of 3.5 Hz from parallel to perpendicular fibres with respect to the main magnetic field. In neonates, the fibre orientation dependency displayed a cosine wave shape, with a small R 2 * range of 0.4 Hz. This minor relationship in neonates provides further evidence for the key role myelin probably plays in creating this fibre orientation dependence later in life, but suggests limited clinical application in newborn populations. Future studies should investigate fibre-orientation dependency in infants in the first 5 years, when substantial myelin development occurs. K E Y W O R D S magnetic susceptibility, myelin water imaging, neonates, R 2 * , white matter development, white matter fibre orientation

The following review will aid readers in providing an overview of scale-free dynamics and monofractal analysis, as well as its applications and potential in functional magnetic resonance imaging (fMRI) neuroscience and clinical research. Like natural phenomena such as the growth of a tree or crashing ocean waves, the brain expresses scale-invariant, or fractal, patterns in neural signals that can be measured. While neural phenomena may represent both monofractal and multifractal processes and can be quantified with many different interrelated parameters, this review will focus on monofractal analysis using the Hurst exponent (H). Monofractal analysis of fMRI data is an advanced analysis technique that measures the complexity of brain signaling by quantifying its degree of scale-invariance. As such, the H value of the blood oxygenation level-dependent (BOLD) signal specifies how the degree of correlation in the signal may mediate brain functions. This review presents a brief overview of the theory of fMRI monofractal analysis followed by notable findings in the field. Through highlighting the advantages and challenges of the technique, the article provides insight into how to best conduct fMRI fractal analysis and properly interpret the findings with physiological relevance. Furthermore, we identify the future directions necessary for its progression towards impactful functional neuroscience discoveries and widespread clinical use. Ultimately, this presenting review aims to build a foundation of knowledge among readers to facilitate greater understanding, discussion, and use of this unique yet powerful imaging analysis technique.