• Neuroinformatics
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In an event-related fMRI study, we examined the cortical networks involved in establishing. reference during language comprehension. We compared BOLD responses to sentences containing referentially ambiguous pronouns (e.g., "Ronald told Frank that he..."), referentially failing pronouns (e.g., "Rose told Emily that he...") or coherent pronouns. Referential ambiguity selectively recruited media[ prefrontal regions, suggesting that readers engaged in problemsolving to select a unique referent from the discourse model. Referential failure elicited activation increases in brain regions associated with mo rp ho -syntactic processing, and, for those readers who took failing pronouns to refer to unmentioned entities, additional regions associated with elaborative inferencing were observed. The networks activated by these two referential problems did not overlap with the network activated by a standard semantic anomaly. Instead, we observed a double dissociation, in that the systems activated by semantic anomaly are deactivated by referential ambiguity, and vice versa. This inverse coupling may reflect the dynamic recruitment of semantic and episodic processing to resolve semantically or referentially problematic situations. More generally, our findings suggest that neurocognitive accounts of language comprehension need to address not just how we parse a sentence and combine individual word meanings, but also how we determine who's who and what's what during language COmprehension. (c) 2007 Elsevier Inc. All rights reserved.

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions.

The blood oxygen level dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is widely used as a proxy for changes in neural activity in the brain. Physiological variables such as heart rate (HR) and respiratory variation (RV) affect the BOLD signal in a way that may interfere with the estimation and detection of true task-related neural activity. This interference is of particular concern when these variables themselves show task-related modulations. We first establish that a simple movement task reliably induces a change in HR but not RV. In group data, the effect of HR on the BOLD response was larger and more widespread throughout the brain than were the effects of RV or phase regressors. The inclusion of HR regressors, but not RV or phase regressors, had a small but reliable effect on the estimated hemodynamic response function (HRF) in M1 and the cerebellum. We next asked whether the inclusion of a nested set of physiological regressors combining phase, RV, and HR significantly improved the model fit in individual participants' data sets. There was a significant improvement from HR correction in M1 for the greatest number of participants, followed by RV and phase correction. These improvements were more modest in the cerebellum. These results indicate that accounting for task-related modulation of physiological variables can improve the detection and estimation of true neural effects of interest.

Recent brain imaging studies suggest that semantic processing of words and images may share a common neural network, although modality-specific activation can also be observed. Other studies using event-related potentials (ERPs) report that brain responses to words and images may already differ at ~150 ms following stimulus presentation. The question thus remains, which differences are due to perceptual categorization processes and which differences are due to the semantic ones? Using ERP recordings and spatio-temporal source localization analysis, we investigated the dynamics of brain activation during a recognition task. The stimuli consisted of a randomized set of verbal (words vs. non-words) and pictorial items (line drawings of objects vs. scrambled drawings). After each stimulus, subjects had to decide whether it corresponds to a recognizable word or objects. ERP map series were first analyzed in terms of segments of quasi-stable map topography using a cluster analysis. This showed that verbal and pictorial stimuli elicited different field patterns in two time segments between ~190-400 ms. Before and after this period, map patterns were similar between verbal and pictorial conditions indicating that the same brain structures were engaged during the early and late steps of processing. Source localization analysis of map segments corresponding to the P100 and the N150 components first showed activation of posterior bilateral regions and then of left temporo-posterior areas. During the period differentiating conditions, other patterns of activation, involving mainly left anterior and posterior regions for words and bilateral posterior regions for images, were observed. These findings suggest that, while sharing an initial common network, recognition of verbal and pictorial stimuli subsequently engage different brain regions during time periods generally allocated to the semantic processing of stimuli.

The use of quantitative T(1) mapping in neuroscience and neurology has raised strong interest in the development of T(1)-mapping techniques that can measure T(1) in the whole brain, with high accuracy and precision and within short imaging and computation times. Here, we present a new inversion-recovery (IR) based T(1)-mapping method using a standard 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence. By varying only the inversion time (TI), but keeping other parameters constant, MPRAGE image signals become linear to exp(-TI/T(1)), allowing for accurate T(1) estimation without flip angle correction. We also show that acquiring data at just 3 TIs, with the three different TI values optimized, gives maximum T(1) precision per unit time, allowing for new efficient approaches to measure and compute T(1). We demonstrate the use of our method at 7 T to obtain 3D T(1) maps of the whole brain in common marmosets at 0.60mm resolution and within 11 min. T(1) maps from the same individuals were highly reproducible across different days. Across subjects, the peak of cerebral gray matter T(1) distribution was 1735±52 ms, and the lower edge of cerebral white matter T(1) distribution was 1270±43 ms. We found a significant decrease of T(1) in both gray and white matter of the marmoset brain with age over a span of 14 years, in agreement with previous human studies. This application illustrates that MPRAGE-based 3D T(1) mapping is rapid, accurate and precise, and can facilitate high-resolution anatomical studies in neuroscience and neurological diseases.

The successes of PET and fMRI in non-invasively localizing sensory functions had encouraged efforts to transform the subjective concepts of cognitive psychology into objective physical measures. The assumption was that mental functions could be decomposed into non-overlapping, context-independent modules that are operated on by separable areas of a computer-like brain. The failures of cognitive modularity and of a very localized phrenology are generally, but not universally, accepted; but in their place, and usually not distinguished from the original revolutionary hopes of clarification, experimental results are being interpreted in terms of rather flexible definitions of both cognitive concepts and the degree of localization. In an alternative approach, we have connected fMRI, (13)C MRS, and electrophysiology measurements of brain energy to connect with observable properties of mental life (i.e., awareness). We illustrate this approach with a sensory stimulation experiment; the degree of localization found in BOLD signals was related to the global energy of the brain which, when manipulated by anesthetics, affected the degree of awareness. The influence of brain energy upon functional imaging maps is changing the interpretations of neuroimaging experiments, from psychological concepts generating computer-like responses to empirical responses dominated by the high brain energy and signaling at rest. In our view "baseline" is an operational term, an adjective that defines a property of a state of the system before it is perturbed by a stimulus. Given the dependence of observable psychological properties upon the "baseline" energy, we believe that it is unnecessarily limiting to de. ne a particular state as the baseline. (C) 2008 Elsevier Inc. All rights reserved.

A key objective in neuroscience is to improve our understanding of the relationship between brain function and structure. We investigated this in the posterior visual pathways of healthy volunteers by applying functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) with tractography. The optic radiations were segmented using the Probabilistic Index of Connectivity (PICo) tractography algorithm and extracted at several thresholds of connection confidence. The mean fractional anisotropy (FA) of the estimated tracts was found to correlate significantly with fMRI measures of visual cortex activity (induced by a photic stimulation paradigm). The results support the hypothesis that the visual cortical fMRI response is constrained by the external anatomical connections of the subserving optic radiations.

The mechanisms underlying the progressive course of multiple sclerosis (MS) are not fully understood yet. Since diffusion tensor (DT) MRI can provide quantitative estimates of both MRI-visible and MRI-occult brain damage related to MS, the present study investigated the value of DT MRI-derived measures for the assessment of the short-term accumulation of white and gray matter (GM) pathology in patients with primary progressive (PP) and secondary progressive (SP) MS. Fifty-four patients with PPMS and 22 with SPMS were studied at baseline and after a mean follow-up of 15 months. Dual-echo, T1-weighted, and DT MRI scans of the brain were acquired on both occasions. Total lesion volumes (TLV) and percentage brain volume changes (PBVC) were computed. Mean diffusivity (MD) and fractional anisotropy (FA) maps of the normal-appearing white (NAWM) and gray matter (NAGM) were produced, and histogram analysis was performed. In both patient groups, a significant increase of average lesion MD (P = 0.01) and of average NAGM MD (P = 0.007) was found at follow-up. No significant differences between PPMS and SPMS patient groups were found for the on-study changes of any MRI-derived measure. No significant correlations were found between the percentage changes of DT MRI-derived measures and those of TLV and PBVC. No significant changes of DT MRI-derived measures were observed in age-matched healthy controls over the same study period. Over a 1-year period of follow-up, DT MRI can detect tissue changes beyond the resolution of conventional MRI in the NAGM of patients with progressive MS. The accumulation of DT MRI-detectable gray matter damage does not seem to merely depend upon the concomitant increase of T2-visible lesion load and the reduction of brain volume. These observations suggest that progressive NAGM damage might yet be an additional factor leading to the accumulation of disability in progressive MS. (C) 2004 Elsevier Inc. All rights reserved.