T. Adrian Carpenter

Colored noise and computational inference in neurophysiological (fMRI) time series analysis: resampling methods in time and wavelet domains.

Even in the absence of an experimental effect, functional magnetic resonance imaging (fMRI) time series generally demonstrate serial dependence. This colored noise or endogenous autocorrelation typically has disproportionate spectral power at low frequencies, i.e., its spectrum is  f–1 ‐like. Various pre‐whitening and pre‐coloring strategies have been proposed to make valid inference on standardised test statistics estimated by time series regression in this context of residually autocorrelated errors. Here we introduce a new method based on random permutation after orthogonal transformation of the observed time series to the wavelet domain. This scheme exploits the general whitening or decorrelating property of the discrete wavelet transform and is implemented using a Daubechies wavelet with four vanishing moments to ensure exchangeability of wavelet coefficients within each scale of decomposition. For  f–1 ‐like or fractal noises, e.g., realisations of fractional Brownian motion (fBm) parameterised by Hurst exponent 0 < H < 1, this resampling algorithm exactly preserves wavelet‐based estimates of the second order stochastic properties of the (possibly nonstationary) time series. Performance of the method is assessed empirically using  f–1 ‐like noise simulated by multiple physical relaxation processes, and experimental fMRI data. Nominal type 1 error control in brain activation mapping is demonstrated by analysis of 13 images acquired under null or resting conditions. Compared to autoregressive pre‐whitening methods for computational inference, a key advantage of wavelet resampling seems to be its robustness in activation mapping of experimental fMRI data acquired at 3 Tesla field strength. We conclude that wavelet resampling may be a generally useful method for inference on naturally complex time series. Hum. Brain Mapping 12:61–78, 2001.

Effect of hyperventilation on cerebral blood flow in traumatic head injury: Clinical relevance and monitoring correlates

Objective To investigate the effect of hyperventilation on cerebral blood flow in traumatic brain injury. Design A prospective interventional study. Setting A specialist neurocritical care unit. Patients Fourteen healthy volunteers and 33 patients within 7 days of closed head injury. Interventions All subjects underwent positron emission tomography imaging of cerebral blood flow. In patients, Paco2 was reduced from 36 ± 1 to 29 ± 1 torr (4.8 ± 0.1 to 3.9 ± 0.1 kPa) and measurements repeated. Jugular venous saturation (Sjvo2) and arteriovenous oxygen content differences (AVDO2) were monitored in 25 patients and values related to positron emission tomography variables. Measurements and Main Results The volumes of critically hypoperfused and hyperperfused brain (HypoBV and HyperBV, in milliliters) were calculated based on thresholds of 10 and 55 mL·100g−1·min−1, respectively. Whereas baseline HypoBV was significantly higher in patients (p < .05), baseline HyperBV was similar to values in healthy volunteers. Hyperventilation resulted in increases in cerebral perfusion pressure (p < .0001) and reductions in intracranial pressure (p < .001), whereas Sjvo2 (>50%) and AVDO2 (<9 mL/mL) did not exceed global ischemic thresholds. However, despite these beneficial effects, hyperventilation shifted the cerebral blood flow distribution curve toward the hypoperfused range, with a decrease in global cerebral blood flow (31 ± 1 to 23 ± 1 mL·100g−1·min−1;p < .0001) and an increase in HypoBV (22 [1–141] to 51 [2–428] mL;p < .0001). Hyperventilation-induced increases in HypoBV were apparently nonlinear, with a threshold value between 34 and 38 torr (4.5–5 kPa). Conclusions Hyperventilation increases the volume of severely hypoperfused tissue within the injured brain, despite improvements in cerebral perfusion pressure and intracranial pressure. Significant hyperperfusion is uncommon, even at a time when conventional clinical management includes a role for modest hyperventilation. These reductions in regional cerebral perfusion are not associated with ischemia, as defined by global monitors of oxygenation, but may represent regions of potentially ischemic brain tissue.

Postreceptor insulin resistance contributes to human dyslipidemia and hepatic steatosis.

Metabolic dyslipidemia is characterized by high circulating triglyceride (TG) and low HDL cholesterol levels and is frequently accompanied by hepatic steatosis. Increased hepatic lipogenesis contributes to both of these problems. Because insulin fails to suppress gluconeogenesis but continues to stimulate lipogenesis in both obese and lipodystrophic insulin-resistant mice, it has been proposed that a selective postreceptor defect in hepatic insulin action is central to the pathogenesis of fatty liver and hypertriglyceridemia in these mice. Here we show that humans with generalized insulin resistance caused by either mutations in the insulin receptor gene or inhibitory antibodies specific for the insulin receptor uniformly exhibited low serum TG and normal HDL cholesterol levels. This was due at least in part to surprisingly low rates of de novo lipogenesis and was associated with low liver fat content and the production of TG-depleted VLDL cholesterol particles. In contrast, humans with a selective postreceptor defect in AKT2 manifest increased lipogenesis, elevated liver fat content, TG-enriched VLDL, hypertriglyceridemia, and low HDL cholesterol levels. People with lipodystrophy, a disorder characterized by particularly severe insulin resistance and dyslipidemia, demonstrated similar abnormalities. Collectively these data from humans with molecularly characterized forms of insulin resistance suggest that partial postreceptor hepatic insulin resistance is a key element in the development of metabolic dyslipidemia and hepatic steatosis.

Incidence and mechanisms of cerebral ischemia in early clinical head injury.

Antemortem demonstration of ischemia has proved elusive in head injury because regional CBF reductions may represent hypoperfusion appropriately coupled to hypometabolism. Fifteen patients underwent positron emission tomography within 24 hours of head injury to map cerebral blood flow (CBF), cerebral oxygen metabolism (CMRO2), and oxygen extraction fraction (OEF). We estimated the volume of ischemic brain (IBV) and used the standard deviation of the OEF distribution to estimate the efficiency of coupling between CBF and CMRO2. The IBV in patients was significantly higher than controls (67 ± 69 vs. 2 ± 3 mL; P < 0.01). The coexistence of relative ischemia and hyperemia in some patients implies mismatching of perfusion to oxygen use. Whereas the saturation of jugular bulb blood (SjO2) correlated with the IBV (r = 0.8, P < 0.01), SjO2 values of 50% were only achieved at an IBV of 170 ± 63 mL (mean ± 95% CI), which equates to 13 ± 5% of the brain. Increases in IBV correlated with a poor Glasgow Outcome Score 6 months after injury (ρ = −0.6, P < 0.05). These results suggest significant ischemia within the first day after head injury. The ischemic burden represented by this “traumatic penumbra” is poorly detected by bedside clinical monitors and has significant associations with outcome.

A STUDY OF ROTATIONALLY INVARIANT AND SYMMETRIC INDICES OF DIFFUSION ANISOTROPY

This study investigated the properties of a class of rotationally invariant and symmetric (relative to the principal diffusivities) indices of the anisotropy of water self-diffusion, namely fractional anisotropy (FA), relative anisotropy (RA), and volume ratio (VR), with particular emphasis to their measurement in brain tissues. A simplified theoretical analysis predicted significant differences in the sensitivities of the anisotropy indices (AI) over the distribution of the principal diffusivities. Computer simulations were used to investigate the effects on AI image quality of three magnetic resonance (MR) diffusion tensor imaging (DTI) acquisition schemes, one being novel: the schemes were simulated on cerebral model fibres varying in shape and spatial orientation. The theoretical predictions and the results of the simulations were corroborated by experimentally determined spatial maps of the AI in a normal feline brain in vivo. We found that FA mapped diffusion anisotropy with the greatest detail and SNR whereas VR provided the strongest contrast between low- and high-anisotropy areas at the expense of increased noise contamination and decreased resolution in anisotropic regions. RA proved intermediate in quality. By sampling the space of the effective diffusion ellipsoid more densely and uniformly and requiring the same total imaging time as the published schemes, the novel DTI scheme achieved greater rotational invariance than the published schemes, with improved noise characteristics, resulting in improved image quality of the AI examined. Our findings suggest that significant improvements in diffusion anisotropy mapping are possible and provide criteria for the selection of the most appropriate AI for a particular application.

Hyperventilation following head injury : Effect on ischemic burden and cerebral oxidative metabolism

Objective:To determine whether hyperventilation exacerbates cerebral ischemia and compromises oxygen metabolism (CMRO2) following closed head injury. Design:A prospective interventional study. Setting:A specialist neurocritical care unit. Patients:Ten healthy volunteers and 30 patients within 10 days of closed head injury. Interventions:Subjects underwent oxygen-15 positron emission tomography imaging of cerebral blood flow, cerebral blood volume, CMRO2, and oxygen extraction fraction. In patients, positron emission tomography studies, somatosensory evoked potentials, and jugular venous saturation (SjO2) measurements were obtained at Paco2 levels of 36 ± 3 and 29 ± 2 torr. Measurements and Main Results:We estimated the volume of ischemic brain and examined the efficiency of coupling between oxygen delivery and utilization using the sd of the oxygen extraction fraction distribution. We correlated CMRO2 to cerebral electrophysiology and examined the effects of hyperventilation on the amplitude of the cortical somatosensory evoked potential response. Patients showed higher ischemic brain volume than controls (17 ± 22 vs. 2 ± 3 mL; p ≤ .05), with worse matching of oxygen delivery to demand (p < .001). Hyperventilation consistently reduced cerebral blood flow (p < .001) and resulted in increases in oxygen extraction fraction and ischemic brain volume (17 ± 22 vs. 88 ± 66 mL; p < .0001), which were undetected by SjO2 monitoring. Mean CMRO2 was slightly increased following hyperventilation, but responses were extremely variable, with 28% of patients demonstrating a decrease in CMRO2 that exceeded 95% prediction intervals for zero change in one or more regions. CMRO2 correlated with cerebral electrophysiology, and cortical somatosensory evoked potential amplitudes were significantly increased by hyperventilation. Conclusions:The acute cerebral blood flow reduction and increase in CMRO2 secondary to hyperventilation represent physiologic challenges to the traumatized brain. These challenges exhaust physiologic reserves in a proportion of brain regions in many subjects and compromise oxidative metabolism. Such ischemia is underestimated by common bedside monitoring tools and may represent a significant mechanism of avoidable neuronal injury following head trauma.

Formal characterization and extension of the linearized diffusion tensor model.

We analyzed the properties of the logarithm of the Rician distribution leading to a full characterization of the probability law of the errors in the linearized diffusion tensor model. An almost complete lack of bias, a simple relation between the variance and the signal‐to‐noise ratio in the original complex data, and a close approximation to normality facilitated estimation of the tensor components by an iterative weighted least squares algorithm. The theory of the linear model has also been used to derive the distribution of mean diffusivity, to develop an informative statistical test for relative lack of fit of the ellipsoidal (or spherical) model compared to an unrestricted linear model in which no specific shape is assumed for the diffusion process, and to estimate the signal‐to‐noise ratios in the original data. The false discovery rate (FDR) has been used to control thresholds for statistical significance in the context of multiple comparisons at voxel level. The methods are illustrated by application to three diffusion tensor imaging (DTI) datasets of clinical interest: a healthy volunteer, a patient with acute brain injury, and a patient with hydrocephalus. Interestingly, some salient features, such as a region normally comprising the basal ganglia and internal capsule, and areas of edema in patients with brain injury and hydrocephalus, had patterns of error largely independent from their mean diffusivities. These observations were made in brain regions with sufficiently large signal‐to‐noise ratios (>2) to justify the assumptions of the log Rician probability model. The combination of diffusivity and its error may provide added value in diagnostic DTI of acute pathologic expansion of the extracellular fluid compartment in brain parenchymal tissue. Hum. Brain Mapping 24:144–155, 2005.

Minimal gradient encoding for robust estimation of diffusion anisotropy

This study has investigated the relationship between the noise sensitivity of measurement by magnetic resonance imaging (MRI) of the diffusion tensor (D) of water and the number N of diffusion-weighting (DW) gradient directions, using computer simulations of strongly anisotropic fibers with variable orientation. The DW directions uniformly sampled the diffusion ellipsoid surface. It is shown that the variation of the signal-to-noise ratio (SNR) of three ideally rotationally invariant scalars of D due to variable fiber orientation provides an objective quantitative measure for the diffusion ellipsoid sampling efficiency, which is independent of the SNR value of the baseline signal obtained without DW; the SNR variation decreased asymptotically with increasing N. The minimum number N(0) of DW directions, which minimized the SNR variation of the three scalars of D was determined, thereby achieving the most efficient ellipsoid sampling. The resulting time efficient diffusion tensor imaging (DTI) protocols provide robust estimation of diffusion anisotropy in the presence of noise and can improve the repeatability/reliability of DTI experiments when there is high variability in the orientation of similar anisotropic structures, as for example, in studies which require repeated measurement of one individual, intersubject comparisons or multicenter studies.

Motor Imagery After Subcortical Stroke A Functional Magnetic Resonance Imaging Study

Background and Purpose— In recovered subcortical stroke, the pattern of motor network activation during motor execution can appear normal or not, depending on the task. Whether this applies to other aspects of motor function is unknown. We used functional MRI to assess motor imagery (MI), a promising new approach to improve motor function after stroke, and contrasted it to motor execution. Methods— Twenty well-recovered patients with hemiparetic subcortical stroke (14 males; mean age, 66.5 years) and 17 aged-matched control subjects were studied. Extensive behavioral screening excluded 8 patients and 4 control subjects due to impaired MI abilities. Subjects performed MI and motor execution of a paced finger–thumb opposition sequence using a functional MRI paradigm that monitored compliance. Activation within the primary motor cortex (BA4a and 4p), dorsal premotor, and supplementary motor areas was examined. Results— The pattern of activation during affected-hand motor execution was not different from control subjects. Affected-hand MI activation was also largely similar to control subjects, including involvement of BA4, but with important differences: (1) unlike control subjects and the nonaffected hand, activation in BA4a and dorsal premotor was not lower during MI as compared with motor execution; (2) the hemispheric balance of BA4p activation was significantly less lateralized than control subjects; and (3) ipsilesional BA4p activation positively correlated with motor performance. Conclusions— In well-recovered subcortical stroke, the motor system, including ipsilesional BA4, is activated during MI despite the lesion. It, however, remains disorganized in proportion to residual motor impairment. Thus, components of movement upstream from execution appear differentially affected after stroke and could be targeted by rehabilitation in more severely affected patients.

Consensus statement from the 2014 International Microdialysis Forum

Microdialysis enables the chemistry of the extracellular interstitial space to be monitored. Use of this technique in patients with acute brain injury has increased our understanding of the pathophysiology of several acute neurological disorders. In 2004, a consensus document on the clinical application of cerebral microdialysis was published. Since then, there have been significant advances in the clinical use of microdialysis in neurocritical care. The objective of this review is to report on the International Microdialysis Forum held in Cambridge, UK, in April 2014 and to produce a revised and updated consensus statement about its clinical use including technique, data interpretation, relationship with outcome, role in guiding therapy in neurocritical care and research applications.