Newborn insula gray matter volume is prospectively associated with early life adiposity gain.

BACKGROUND: The importance of energy homeostasis brain circuitry in the context of obesity is well established, however, the developmental ontogeny of this circuitry in humans is currently unknown. Here, we investigate the prospective association between newborn gray matter (GM) volume in the insula, a key brain region underlying energy homeostasis, and change in percent body fat accrual over the first six months of postnatal life, an outcome that represents among the most reliable infant predictors of childhood obesity risk. METHODS: A total of 52 infants (29 male, 23 female, gestational age at birth=39(1.5) weeks) were assessed using structural MRI shortly after birth (postnatal age at MRI scan=25.9(12.2) days), and serial Dual X-Ray Absorptiometry shortly after birth (postnatal age at DXA scan 1=24.6(11.4) days) and at six months of age (postnatal age at DXA scan 2=26.7(3.3) weeks). RESULTS: Insula GM volume was inversely associated with change in percent body fat from birth to six-months postnatal age and accounted for 19% of its variance (ß=-3.6%/S.D., P=0.001). This association was driven by the central-posterior portion of the insula, a region of particular importance for gustation and interoception. The direction of this effect is in concordance with observations in adults, and the results remained statistically significant after adjusting for relevant covariates and potential confounding variables. CONCLUSIONS: Altogether, these findings suggest an underlying neural basis of childhood obesity that precedes the influence of the postnatal environment. The identification of plausible brain-related biomarkers of childhood obesity risk that predate the influence of the postnatal obesogenic environment may contribute to an improved understanding of propensity for obesity, early identification of at-risk individuals, and intervention targets for primary prevention.

MRI-based volumetry of head compartments: normative values of healthy adults.

The size of head compartments (head and brain volume, intracranial volume, gray and white matter volume, cerebrospinal fluid volume) and their ratios were determined on the basis of magnetic resonance images of the head acquired in a reference population of 502 healthy subjects. Age-matched subgroups were selected to reveal gender-related differences and changes with age. Normative data are provided in the form of simple equations that allow transforming measured compartment volumes into z scores, offering the possibility to relate individual data to a larger population.

Does the pattern of atrophy of the Corpus callosum differ between patients with frontotemporal dementia and patients with Alzheimer's disease?

The pattern of callosal atrophy might be useful for the differentiation between frontotemporal dementia (FTD) and Alzheimer's disease (AD) in advanced cases. However, it is unclear whether the pattern of callosal atrophy differs between patients with FTD and patients with AD in mild to moderate stages. Volumetric MR images were recorded from 48 probands (12 with FTD, 12 with late-onset AD, and 24 controls). All patients were in a mild or in a moderate stage. The corpus callosum was divided into five segments. A repeated-measures analysis of variance showed that there was no difference in the pattern of callosal atrophy between the groups. We provide evidence that patients with FTD and patients with late-onset AD do not differ in the pattern of callosal atrophy on condition that: (1) FTD patients and AD patients are in a mild to moderate stage and (2) FTD patients and AD patients differ in age.

Analyzing the neocortical fine-structure.

Cytoarchitectonic fields of the human neocortex are defined by characteristic variations in the composition of a general six-layer structure. It is commonly accepted that these fields correspond to functionally homogeneous entities. Diligent techniques were developed to characterize cytoarchitectonic fields by staining sections of post-mortem brains and subsequent statistical evaluation. Fields were found to show a considerable interindividual variability in extent and relation to macroscopic anatomical landmarks. With upcoming new high-resolution magnetic resonance imaging (MRI) protocols, it appears worthwhile to examine the feasibility of characterizing the neocortical fine-structure from anatomical MRI scans, thus, defining neocortical fields by in vivo techniques. A fixated brain hemisphere was scanned at a resolution of approximately 0.3 mm. After correcting for intensity inhomogeneities in the dataset, the cortex boundaries (the white/grey matter and grey matter/background interfaces) were determined as a triangular mesh. Radial intensity profiles following the shortest path through the cortex were computed and characterized by a sparse set of features. A statistical similarity measure between features of different regions was defined, and served to define the extent of Brodmann's Areas 4, 17, 44 and 45 in this dataset.

Morphometry of the corpus callosum in patients with questionable and mild dementia.

Previous studies have shown a reduction in corpus callosum area in advanced Alzheimer's disease, but it is unclear whether callosal atrophy is present in the transitional phase between health and the onset of dementia. The aim of this study was to investigate whether callosal atrophy is present in subjects with questionable and mild dementia and to assess the diagnostic value of callosal measures. In 83 subjects aged 72 to 85 years (33 normal controls, 27 patients with questionable dementia, 23 with mild Alzheimer's disease), magnetic resonance images were recorded and the mid-sagittal callosal area measured. Significant differences were found between normal controls and mild dementia. In subjects with questionable dementia callosal size was intermediate between normal controls and mild Alzheimer's disease. However, callosal measures were unsuitable for diagnostic differentiation between healthy subjects, subjects with questionable dementia, and subjects with mild Alzheimer's disease. The severity of white matter changes did not differ between the groups.

Estimating the effective degrees of freedom in univariate multiple regression analysis.

The general linear model provides the most widely applied statistical framework for analyzing functional MRI (fMRI) data. With the increasing temporal resolution of recent scanning protocols, and more elaborate data preprocessing schemes, data independency is no longer a valid assumption. In this paper, we revise the statistical background of the general linear model in the presence of temporal autocorrelations. First, when detecting the activation signal, we explicitly account for the temporal autocorrelation structure, which yields a generalized F-test and the associated corrected (or effective) degrees of freedom (DOF). The proposed approach is data driven and thus independent of any specific preprocessing method. Then, for event-related protocols, we propose a new model for the temporal autocorrelations ("damped oscillator" model) and compare this model to another, previously used in the field (first-order autoregressive model, or AR(1) model). In the case of long fMRI time series, an efficient approximation for the number of effective DOF is provided for both models. Finally, the validity of our approach is assessed using simulated and real fMRI data and is compared with more conventional methods.

Hemodynamic and electroencephalographic responses to illusory figures: recording of the evoked potentials during functional MRI.

The feasibility of recording event-related potentials (ERP) during functional MRI (fMRI) scanning using higher level cognitive stimuli was studied. Using responses to illusory figures in a visual oddball task, evoked potentials were obtained with their expected configurations and latencies. A rapid stimulation scheme using randomly varied trial lengths was employed, and class-wise characteristics of the hemodynamic response were obtained by a nonlinear analysis of the fMRI time series. Implications and limitations of conducting combined ERP-fMRI experiments using higher level cognitive stimuli are discussed. EEG/fMRI results revealed a sequential activation of striate and extrastriate occipital cortex along the ventral path of object processing for Kanizsa figures. Interestingly, Kanizsa figures activated the human motion area MT. Targets resulted in activations of frontal and parietal cortex which were not activated for standard stimuli.

Correlation between cortical theta activity and hippocampal volumes in health, mild cognitive impairment, and mild dementia.

Cognitive decline is known to be associated with both increased theta power over frontal regions and hippocampal atrophy. The aim of this study was to reveal the relation between these parameters in groups with mild dementia, mild cognitive impairment, and healthy control subjects. The authors examined a preliminary randomly selected sample of 39 right-handed subjects joining the Leipzig Longitudinal Study of the Aged, consisting of 17 normal elderly subjects, 12 patients with mild cognitive impairment, and 10 patients with mild dementia assessed by Clinical Dementia Rating. All subjects were between 75 and 85 years old (mean age, 78 years; standard deviation, 2.78 years) and underwent EEG and brain MRI. Mean spectral power densities were calculated, and hippocampal body volume was measured. Significant negative linear correlations between theta power over frontal regions and hippocampal volumes were found. The results support the assumption about a relationship between hippocampal atrophy and theta power, and may be helpful for a better understanding of the course of Alzheimer's disease.

Segmentation of large brain lesions.

This paper describes a region-growing algorithm for the segmentation of large lesions in T1-weighted magnetic resonance (MR) images of the head. The algorithm involves a gray level similarity criterion to expand the region and a size criterion to prevent from over-growing outside the lesion. The performance of the algorithm is evaluated and validated on a series of pathologic three-dimensional MR images of the head.

Three-dimensional texture analysis of MRI brain datasets.

A method is proposed for three-dimensional (3-D) texture analysis of magnetic resonance imaging brain datasets. It is based on extended, multisort co-occurrence matrices that employ intensity, gradient and anisotropy image features in a uniform way. Basic properties of matrices as well as their sensitivity and dependence on spatial image scaling are evaluated. The ability of the suggested 3-D texture descriptors is demonstrated on nontrivial classification tasks for pathologic findings in brain datasets.

Improvement of source localization by dynamical systems based modeling (DSBM).

Recently, we have proposed a new concept for analyzing EEG/MEG data (Uhl et al. 1998), which leads to a dynamical systems based modeling (DSBM) of neurophysiological data. We report the application of this approach to four different classes of simulated noisy data sets, to investigate the impact of DSBM-filtering on source localization. An improvement is demonstrated of up to above 50% of the distance between simulated and estimated dipole positions compared to principal component filtered and unfiltered data. On a noise level on which two underlying dipoles cannot be resolved from the unfiltered data, DSBM allows for an extraction of the two sources.

Hippocampal volume discriminates between normal cognition; questionable and mild dementia in the elderly.

The sensitivity of MRI volumetric measures to detect cognitive dysfunction is examined in 39 participants of an epidemiological field study (age 75-85, MMSE 19-30). According to Clinical dementia rating (CDR), 17 subjects had normal cognition (CDR 0), 12 had questionable (CDR 0.5) and 10 mild dementia (CDR 1). Discriminant analysis based on four hippocampal measures resulted in a correct classification of 76.9% of all subjects. Left-sided and posterior hippocampal measures were more responsible for group discrimination than right-sided and anterior measures. In CDR 0.5, a significant hippocampal volume reduction of 14.3% vs.11.3% (left vs. right) relative to normal was found. The right hippocampus was significantly greater than the left in CDR 0 and CDR 0.5, but not in CDR 1. The magnitude of non-directional hippocampal asymmetry increased with decreasing cognitive state. We conclude that hippocampal atrophy is sensitive to detect cognitive dysfunction and subjects at risk for Alzheimer's disease in the elderly population.

Detection of fixed points in spatiotemporal signals by a clustering method.

We present a method to determine fixed points in spatiotemporal signals. The method combines a clustering algorithm and a nonlinear analysis method fitting temporal dynamics. A 144-dimensional simulated signal, similar to a Kueppers-Lortz instability, is analyzed and its fixed points are reconstructed.

Recording of the event-related potentials during functional MRI at 3.0 Tesla field strength.

The feasibility of recording event-related potentials (ERP) during functional MRI (fMRI) scanning was studied. Using an alternating checkerboard stimulus in a blocked presentation, visually evoked potentials were obtained with their expected configuration and latencies. A clustered echoplanar imaging protocol was applied to observe the hemodynamic response due to the visual stimulus interleaved with measuring ERPs. Influences of the electrode/amplifier set up on MRI scanning and the scanning process on the recording of electrophysiological signals are reported and discussed. Artifacts overlaid on the electrophysiological recordings were corrected by post hoc filtering methods presented here. Implications and limitations of conducting combined ERP/fMRI experiments using higher-level cognitive stimuli are discussed. Magn Reson Med 44:277-282, 2000.

Nonlinear regression of functional MRI data: an item recognition task study.

A classical item-recognition task was used to examine human verbal working memory in an event-related functional MRI (fMRI) study. A highly flexible experimental design incorporated a broad variation of memory load and delay time. This design allows for only three or four repetitions per stimulus condition. In a first step, linear regression analysis was applied to locate functional activation in the fMRI data. As a second step, the time course of the hemodynamic response (HR) was analyzed using nonlinear regression, which served to quantify the dependency between HR shape properties and stimulation conditions in several regions-of-interest. On the basis of this study, a closer description of the frontoparietal network involved in verbal working memory was possible.

Probabilistic modeling of single-trial fMRI data.

This paper describes a probabilistic framework for modeling single-trial functional magnetic resonance (fMR) images based on a parametric model for the hemodynamic response and Markov random field (MRF) image models. The model is fitted to image data by maximizing a lower bound on the log likelihood. The result is an approximate maximum a posteriori estimate of the joint distribution over the model parameters and pixel labels. Examples show how this technique can used to segment two-dimensional (2-D) fMR images, or parts thereof, into regions with different characteristics of their hemodynamic response.

Comparison of filtering methods for fMRI datasets.

When studying complex cognitive tasks using functional magnetic resonance imaging (fMRI) one often encounters weak signal responses. These weak responses are corrupted by noise and artifacts of various sources. Preprocessing of the raw data before the application of test statistics helps to extract the signal and can vastly improve signal detection. Artifact sources and algorithms to handle them are discussed. In an empirical approach targeted to yield an optimal recovery of the hemodynamic response, we implemented a test bed for baseline correction and noise-filtering methods. A known signal is modulated onto foreground patches obtained from event-related fMRI experiments. Quantitative performance measures are defined to optimize the characteristics of a given filter and to compare their results. Marked improvements in the sensitivity and selectivity are achieved by optimized filtering. Examples using real data underline the usefulness of this preprocessing sequence.

Modeling the hemodynamic response in single-trial functional MRI experiments.

Today, most studies of cognitive processes using functional MRI (fMRI) experiments adopt a single-trial design. Highly flexible stimulation paradigms require new statistical models in which not only the activation amount but also the time course of the measured hemodynamic response is analyzed. Most previous approaches have been based on a linear regression context and have introduced hemodynamic model functions to improve the signal detection. In this report a nonlinear regression context is derived, from which shape parameters for the hemodynamic response are obtained per trial and per region of interest. These parameters allow the investigation of stimulus-induced shape variations of the hemodynamic response. By embedding the estimation into a robust statistical framework and rigorously analyzing the spatiotemporal interactions in the fMRI data, it is possible to derive statistically valid descriptions of single hemodynamic responses. The model, estimation algorithm, validation, and an example analysis from a single-trial fMRI study are reported. Magn Reson Med 42:787-797, 1999.

Combining electrophysiological and hemodynamic measures of the auditory oddball.

The neural mechanisms of deviancy and target detection were investigated by combining high density event-related potential (ERP) recordings with functional magnetic resonance imaging (fMRI). ERP and fMRI responses were recorded using the same paradigm and the same subjects. Unattended deviants elicited a mismatch negativity (MMN) in the ERP. In the fMRI data, activations of transverse/superior temporal gyri bilateral were found. Attended deviants generated an MMN followed by an N2/P3b complex. For this condition, fMRI activations in both superior temporal gyri and the neostriatum were found. These activations were taken as neuroanatomical constraints for the localization of equivalent current dipoles. Inverse solutions for dipole orientation provide evidence for significant activation close to Heschl's gyri during deviancy processing in the 110-160-ms time interval (MMN), whereas target detection could be modeled by two dipoles in the superior temporal gyrus between 320 and 380 ms.

Temporal properties of the hemodynamic response in functional MRI.

Today, most studies of cognitive processes using functional magnetic resonance imaging (fMRI) adopt an event-related experimental design. Highly flexible stimulation settings require new statistical models where not only the activation amount, but also the time course of the measured hemodynamic response is analyzed. It is possible to obtain statistically valid descriptions of single hemodynamic responses from a robust nonlinear estimation procedure. Focus is placed on the temporal behaviour of the hemodynamic response: relative temporal order, changes induced by modification of the experimental context, and interindividual differences. Example analyses from recent fMRI studies underline the usefulness of this approach.