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

steriodorsal medial parietal areas were specifically involved in retrieval of spatial context compared to retrieval of nonspatial context. The posterior activations are consistent with a model of long-term storage of allocentric representations in medial temporal regions with translation to body-centered and head-centered representations computed in right posterior parietal cortex and buffered in the temporoparietal pathway so as to provide an imageable representation in the precuneus. Prefrontal activations are consistent with strategic retrieval processes, including those required to overcome the interference between the highly similar events. 2001 Academic Press INTRODUCTION Memory for the events we experience as we move around our environment is fundamental to normal functioning in daily life. This type of memory is often referred to as "episodic" (Tulving, 1983) and is crucially dependent on the medial temporal lobes (Scoville and Milner, 1957; A

Keywords: speech production; model; fMRI; Broca’s area; premotor cortex; motor cortex; speech acquisition; sensorimotor learning; neural transmission delays This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and somatosensory cortical areas. Computer simulations of the model verify its ability to account for compensation to lip and jaw perturbations during speech. Specific anatomical locations of the model’s components are estimated, and these estimates are used to simulate fMRI experiments of simple syllable production. 1 1

This Ph.D. thesis proposes methods for information retrieval in functional neuroimaging through automatic computerized authority identification, and searching and cleaning in a neuroscience database. Authorities are found through cocitation analysis of the citation pattern among scientific articles. Based on data from a single scientific journal it is shown that multivariate analyses are able to determine group structure that is interpretable as particular “known ” subgroups in functional neuroimaging. Methods for text analysis are suggested that use a combination of content and links, in the form of the terms in scientific documents and scientific citations, respectively. These included context sensitive author ranking and automatic labeling of axes and groups in connection with multivariate analyses of link data. Talairach foci from the BrainMap ™ database are modeled with conditional probability density models useful for exploratory functional volumes modeling. A further application is shown with conditional outlier detection where abnormal entries in the BrainMap ™ database are spotted using kernel density modeling and the redundancy between anatomical labels and spatial Talairach coordinates. This represents a combination of simple term and spatial modeling. The specific outliers that were found in the BrainMap ™ database constituted among others: Entry errors, errors in the article and unusual terminology.

In functional neuroimaging studies of episodic retrieval (ER), activations in prefrontal, parietal, anterior cingulate, and thalamic regions are typically attributed to episodic retrieval processes. However, these activations are also frequent during visual attention (VA) tasks, suggesting that their role in ER may reflect attentional rather than mnemonic processes. To investigate this possibility, we directly compared brain activity during ER and VA tasks using event-related fMRI. The ER task was a word recognition test with a retrieval mode component, and the VA task was a target detection task with a sustained attention component. The study yielded three main findings. First, a common fronto-parietal-cingulate-thalamic network was found for ER and VA, suggesting that the involvement of these regions during ER reflects general attentional processes. This idea is compatible with some of the interpretations proposed in the ER literature (e.g. postretrieval monitoring), which may be rephrased in terms of attentional processes. Second, several subregions were differentially involved in ER versus VA. For example, the frontopolar cortex and the precuneus were more activated for ER than for VA, possibly reflecting retrieval mode and processing of internally generated stimuli, respectively. Finally, the study yielded an unexpected finding: some medial temporal lobe regions were similarly activated for ER and VA. This finding suggests that the medial temporal lobes may be involved in indexing representations within the focus of consciousness, regardless of whether they are mnemonic or perceptual. Overall, the present results suggest that many of the activations attributed to specific cognitive processes, such as episodic memory, may actually reflect more general cognitive oper...

Divided attention (DA) disrupts episodic encoding, but has little effect on episodic retrieval. Furthermore, normal aging is associated with episodic memory impairments, and when young adults are made to encode information under DA conditions, their memory performance is reduced and resembles that of old adults working under full attention (FA) conditions. Together, these results suggest a common neurocognitive mechanism by which aging and DA during encoding disrupt memory performance. In the current study, we used PET to investigate younger and older adults' brain activity during encoding and retrieval under FA and DA conditions. In FA conditions, the old adults showed reduced activity in prefrontal regions that younger adults activated preferentially during encoding or retrieval, as well as increased activity in prefrontal regions young adults did not activate. These results indicate that prefrontal functional specificity of episodic memory is reduced by aging. During encoding, DA reduced memory performance, and reduced brain activity in left-prefrontal and medial-temporal lobe regions for both age groups, indicating that DA during encoding interferes with encoding processes that lead to better memory performance. During retrieval, memory performance and retrieval-related brain activity were relatively immune to DA for both age groups, suggesting that DA during retrieval does not interfere with the brain systems necessary for successful retrieval. Finally, left inferior prefrontal activity was reduced similarly by aging and by DA during encoding, suggesting that the behavioral correspondence between these effects is the result of a reduced ability to engage in elaborate encoding operations. &

common regions mediate? By comparing patterns of brain activity across different cognitive functions, answers to this question can be generated. ........ Figure 1 about here ........ The matrix in Figure 1 illustrates the difference between the traditional within-function approach and the cross-function approach we are advocating in this chapter. Let us assume that in functional neuroimaging studies Cognitive Function A typically is associated with activations in Brain Regions 1 and 3, Cognitive Function B with activations in Brain Regions 2 and 3, and Cognitive Function C with activations in Brain Regions 1 and 2. In the standard within-function approach, functional neuroimaging researchers are primarily concerned with one cognitive function and interpret activations in relation to this particular function. Thus, in a situation like the one depicted in Figure 1, researchers of Function A would attribute the activation of Region 1 to a certain aspect of Function A, whereas researchers

Simple text analysis and modeling of spatial data can be combined: Data from the BrainMap database containing functional neuroimaging studies can be examined for outliers/novelty by simple kernel density estimation of the spatial data ("Talairach coordinates" of activation) conditioned on words and phrases from the labeling of the spatial data. The present application ranks the individual spatial data according to novelty and a manual investigation finds a number of interesting errors and non-conforming terminologies. 2) Term-based text analysis and link analysis can be combined: Terms and the scientific citations were extracted from the functional neuroimaging journal "NeuroImage" and simple link analysis on the citations by singular value decomposisiton identifies hubs and authorities and clusters of similar authors and their subfield. Singular value decomposition of the term-based data together with the citation data enables context sensitive search for authors: Finding the authority related to a term or a set of terms, e.g., from the title or the abstract of a scientific article. This gives a possibility for automatic reviewer identification.

Results from functional neuroimaging such as positron emission tomography and functional magnetic resonance are often reported as sets of 3-dimensional coordinates in Talairach stereotactic space. By utilizing data collected in the BrainMap database and from our own small XML database we can automatically model and visualize several studies at once. We model a set of 3-dimensional coordinates by a voxelization step where exible probability density models such as kernel density estimators produce a voxel-volume representation of a study, allowing us to represent all coordinate data in one single data matrix. By conditioning on elements in the databases other than the coordinate data, e.g., anatomical labels associated with many coordinates we can make conditional novelty detection identifying outliers in the database that might be errorneous entries or seldom occuring patterns. In the BrainMap database we found errors, e.g., stemming from confusion of centimeters and millimeters during entering and errors in the original article. Conditional probability density modeling also enables generation of probabilistic atlases and automatic probabilistic anatomical labeling of new coordinates. By conditioning on the behavioral domains associated with each study, e.g, the words `word' and 'visual', we can make virtual brain activations. Voxelization also permits us to nd related volumes, where query volumes are matched with database items and the most related volumes are found and returned in sorted lists. Image-based indices can be created by singular value decomposition and by matching individual volumes against eigenimages. Individual experiments, sets of experiments as well as results from meta-analyses can be rendered as glyphs, cut-planes or isosurfaces in 3-dimensional Cor...

INTRODUCTION During the past decade, the field of functional neuroimaging of cognition has grown exponentially. From a handful of studies in the early 1990s, this research domain expanded to more than 800 studies by the early 2000s. Today, positron emission tomography (PET) and functional MRI (fMRI) studies cover almost every aspect of human cognition, from motion perception to moral reasoning. If each study is seen as a tree, the field has grown from minimal vegetation to a luxuriant tropical forest in less than 10 years. Yet, functional neuroimaging researchers sometimes focus exclusively on their own cognitive domain and do not see the forest through the trees. The goal of the present chapter is to call attention to the forest--- that is, to what many functional neuroimaging studies of cognition have in common. When we say that most researchers are focused on the trees, we refer to the fact that the vast majority of functional neuroimaging studies investigate a single cognitive fu