Highly accurate surface models of the cerebral cortex are becoming increasingly important as tools in the investigation of the functional organization of the human brain. The construction of such models is difficult using current neuroimaging technology due to the high degree of cortical folding. Even single voxel misclassifications can result in erroneous connections being created between adjacent banks of a sulcus, resulting in a topologically inaccurate model. These topological defects cause the cortical model to no longer be homeomorphic to a sheet, preventing the accurate inflation, flattening, or spherical morphing of the reconstructed cortex. Surface deformation techniques can guarantee the topological correctness of a model, but are time-consuming and may result in geometrically inaccurate models. In order to address this need we have developed a technique for taking a model of the cortex, detecting and fixing the topological defects while leaving that majority of the model intact, resulting in a surface that is both geometrically accurate and topologically correct.

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erations, respectively; and (iii) left posterior/ventral (Broca's area) and bilateral posterior/dorsal areas were more activated during WM than during ER, possibly reflecting phonological and generic WM operations, respectively. Second, hippocampal and parahippocampal regions were activated not only for ER but also for WM. This result suggests that indexing operations mediated by the medial temporal lobes apply to both long-term and short-term memory traces. Overall, our results show that direct cross-function comparisons are critical to understand the role of different brain regions in various cognitive functions. 2002 Elsevier Science (USA) INTRODUCTION During the past decade, numerous positron emission tomography (PET) and functional MRI (fMRI) studies have investigated the neural correlates of different cognitive functions (for a review, see Cabeza and Nyberg, 2000). Although most studies have focused on a single function (see however, LaBar et al., 1999; Braver et al., 2001; Ny

Event-related functional magnetic resonance imaging is a recent and popular technique for detecting haemodynamic responses to brief stimuli or events. However, the design of event-related experiments requires careful consideration of numerous issues of measurement, modelling and inference. Here we review these issues, with particular emphasis on the use of basis functions within a general linear modelling framework to model and make inferences about the haemodynamic response. With these models in mind, we then consider how the properties of functional magnetic resonance imaging data determine the optimal experimental design for a specific hypothesis, in terms of stimulus ordering and interstimulus interval. Finally, we illustrate various event-related models with examples from recent studies.

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Human memory consists of multiple forms, including priming and explicit memory. Although considerable evidence indicates that priming and explicit memory are functionally and neuroanatomically distinct, little is know about when and how these different forms of memory interact. Here, behavioral and functional magnetic resonance imaging (fMRI) methods were used to examine a novel and counterintuitive hypothesis: Priming during episodic encoding may be negatively associated with subsequent explicit memory. Using an experimental design that exploited known properties of spacing or lag effects, the magnitudes of behavioral and neural priming during a second study episode were varied and the relation between these magnitudes of priming during re-encoding and performance on a subsequent explicit memory test was examined. Results revealed that greater behavioral priming (reduced reaction times) and neural priming (reduced left inferior prefrontal brain activation) during re-encoding were associated with lower levels of subsequent explicit memory. Moreover, those subjects who demonstrated greater behavioral and neural priming effects during re-encoding following a long lag tended to demonstrate the least benefit in subsequent explicit memory due to this second study episode. These findings suggest that priming for past experiences can hinder new episodic encoding.

& We used event-related functional magnetic resonance imaging (efMRI) to investigate brain regions showing differential responses as a function of confidence in an episodic word recognition task. Twelve healthy volunteers indicated whether their old±new judgments were made with high or low confidence. Hemodynamic responses associated with each judgment were modeled with an ``early' ' and a ``late' ' response function. As predicted by the monitoring hypothesis generated from a previous recognition study

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. Index Terms---Hemodynamic response, image segmentation, Markov random field, mean field theory. I.

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