NeuroImage
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Neural mass model-based tracking of brain states from electroencephalographic signals holds the promise of simultaneously tracking brain states while inferring underlying physiological changes in various neuroscientific and clinical applications. Here, neural mass model-based tracking of brain states using the unscented Kalman filter applied to estimate parameters of the Jansen-Rit cortical population model is evaluated through the application of propofol-based anesthetic state monitoring. In particular, 15 subjects underwent propofol anesthesia induction from awake to anesthetised while behavioral responsiveness was monitored and frontal electroencephalographic signals were recorded. ⋯ Moreover, it was found that the unscented Kalman filter based parameter estimates of the inhibitory postsynaptic potential amplitude varied in the physiologically expected direction with increases in propofol concentration, while the estimates of the inhibitory postsynaptic potential rate constant did not. These results combined with analysis of monotonicity of parameter estimates, error analysis of parameter estimates, and observability analysis of the Jansen-Rit model, along with considerations of extensions of the Jansen-Rit model, suggests that the Jansen-Rit model combined with unscented Kalman filtering provides a valuable reference point for future real-time brain state tracking studies. This is especially true for studies of more complex, but still computationally efficient, neural models of anesthesia that can more accurately track the anesthetic brain state, while simultaneously inferring underlying physiological changes that can potentially provide useful clinical information.
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The current dogma to explain the extent of injury-related changes following rodent controlled cortical impact (CCI) injury is a focal injury with limited axonal pathology. However, there is in fact good, published histologic evidence to suggest that axonal injury is far more widespread in this model than generally thought. One possibility that might help to explain this is the often-used region-of-interest data analysis approach taken by experimental traumatic brain injury (TBI) diffusion tensor imaging (DTI) or histologic studies that might miss more widespread damage, when compared to the whole brain, statistically robust method of tract-based analysis used more routinely in clinical research. ⋯ However, there was good spatial correspondence between regions of increased FA and areas of increased FTD and mean fiber length. We discuss these widespread changes in DTI parameters in terms of axonal degeneration and potential reorganization, with reference to a resting state fMRI companion paper (Harris et al., 2016, Exp. Neurol. 227:124-138) that demonstrated altered functional connectivity data acquired from the same rats used in this study.
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This paper presents Bingham-NODDI, a clinically-feasible technique for estimating the anisotropic orientation dispersion of neurites. Direct quantification of neurite morphology on clinical scanners was recently realised by a diffusion MRI technique known as neurite orientation dispersion and density imaging (NODDI). However in its current form NODDI cannot estimate anisotropic orientation dispersion, which is widespread in the brain due to common fanning and bending of neurites. ⋯ The results demonstrate that the parameters of the proposed model can be estimated without additional acquisition requirements over the standard NODDI protocol. Thus anisotropic dispersion can be determined and has the potential to be used as a marker for normal brain development and ageing or in pathology. We additionally find that the original NODDI model is robust to the effects of anisotropic orientation dispersion, when the quantification of anisotropic dispersion is not of interest.
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The effects of age on functional connectivity (FC) of intrinsic connectivity networks (ICNs) have largely been derived from cross-sectional studies. Far less is known about longitudinal changes in FC and how they relate to ageing-related cognitive decline. We evaluated intra- and inter-network FC in 78 healthy older adults two or three times over a period of 4years. ⋯ The rate of loss in functional segregation between ECN and DMN was associated with ageing-related decline in processing speed. The observed longitudinal FC changes and their associations with processing speed remained after correcting for longitudinal reduction in gray matter volume. These findings help connect ageing-related changes in FC with ageing-related decline in cognitive performance and underscore the value of collecting concurrent longitudinal imaging and behavioral data.
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Randomized Controlled Trial
From Pavlov to pain: How predictability affects the anticipation and processing of visceral pain in a fear conditioning paradigm.
Conditioned pain-related fear may contribute to hyperalgesia and central sensitization, but this has not been tested for interoceptive, visceral pain. The underlying ability to accurately predict pain is based on predictive cue properties and may alter the sensory processing and cognitive-emotional modulation of pain thus exacerbating the subjective pain experience. In this functional magnetic resonance imaging study using painful rectal distensions as unconditioned stimuli (US), we addressed changes in the neural processing of pain during the acquisition of pain-related fear and subsequently tested if conditioned stimuli (CS) contribute to hyperalgesia and increased neural responses in pain-encoding regions. ⋯ With regard to activation in response to painful stimuli, the unpredictable compared to the predictable group revealed greater activation in pain-encoding (somatosensory cortex, insula) and pain-modulatory (prefrontal and cingulate cortices, periaqueductal grey, parahippocampus) regions. In the test phase, no evidence of hyperalgesia or central sensitization was found, but the predictable group demonstrated enhanced caudate nucleus activation in response to CS(-)-signaled pain. These findings support that during fear conditioning, the ability to predict pain affects neural processing of visceral pain and alters the associative learning processes underlying the acquisition of predictive properties of cues signaling pain, but conditioned pain-related fear does not result in visceral hyperalgesia or central sensitization.