Functional and structural mapping of human cerebral cortex: solutions are in the surfaces

Estimating linear cortical magnification in human primary visual cortex via dynamic programming

Human primary visual cortex is organized retinotopically, with adjacent locations in cortex representing adjacent locations on the retina. The spatial sampling in cortex is highly nonuniform: the amount of cortex devoted to a unit area of retina decreases with increasing retinal eccentricity. This sampling property can be quantified by the linear cortical magnification factor, which is expressed in terms of millimeters of cortex per degree of visual angle. In this paper, we present a new method using dynamic programming and fMRI retinotopic eccentricity mapping to estimate the linear cortical magnification factor in human primary visual cortex (V1). We localized cortical activity while subjects viewed each of seven stationary contrast- reversing radial checkerboard rings of equal thickness that tiled the visual field from 1.62 to 12.96 degrees of eccentricity. Imaging data from all epochs of each ring were contrasted with data from fixation epochs on a subject-by-subject basis. The resulting t statistic maps were then superimposed on a local coordinate system constructed from the gray/white matter boundary surface of each individual subject's occipital lobe, separately for each ring. Smoothed maps of functional activity on the cortical surface were constructed using orthonormal bases of the Laplace-Beltrami operator that incorporate the geometry of the cortical surface. This allowed us to stably track the ridge of maximum activation due to each ring via dynamic programming optimization over all possible paths on the cortical surface. We estimated the linear cortical magnification factor by calculating geodesic distances between activation ridges on the cortical surface in a population of five normal subjects. The reliability of these estimates was assessed by comparing results based on data from one quadrant to those based on data from the full hemifield along with a split-half reliability analysis.

Cortical surface-based analysis of 18F-FDG PET: measured metabolic abnormalities in schizophrenia are affected by cortical structural abnormalities

The purpose of the study is to propose a new framework for surface-based statistical parametric mapping of PET images using MRI-based cortical surface analysis, including partial volume correction, intensity normalization and spatial normalization on the cortical surface. Maximum PET intensities along the path between inner and outer layer of the cortical gray matter are mapped onto the cortical surface to generate a metabolic activity surface map. For the partial volume correction, the metabolic activity surface map was divided by the partial volume effect map. The regional metabolic activity was normalized by the global activity iteratively calculated at the surface nodes, statistically independent of the group, as measured by F statistics. After surface-based spatial normalization, a statistical evaluation of both cortical thickness and cortical metabolic activity was conducted on the normalized surfaces of 16 patients with schizophrenia and 16 age- and gender-matched healthy controls. The patients with schizophrenia were found to have significant cortical thinning in the temporal and inferior frontal cortices. Accordingly, their PET imaging was significantly affected by the partial volume effect, indicating that partial volume correction could change the statistical results. After correction of the partial volume effects, the patients showed hyperactivity in the temporal cortex, whereas hypoactivity in the prefrontal cortex, predominantly in the left hemisphere. Our results demonstrate that anatomical factors affect an analysis for functional data from the PET, and therefore the importance of combining anatomy and function in the analysis of imaging data for schizophrenia should be considered.

Information-based functional brain mapping

The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data. The complexity of the data creates a need for statistical summary, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest. In neuroimaging, for example, brain mapping analysis has focused on the discovery of activation, i.e., of extended brain regions whose average activity changes across experimental conditions. Here we propose to ask a more general question of the data: Where in the brain does the activity pattern contain information about the experimental condition? To address this question, we propose scanning the imaged volume with a "searchlight," whose contents are analyzed multivariately at each location in the brain.

Simplified intersubject averaging on the cortical surface using SUMA

Task and group comparisons in functional magnetic resonance imaging (fMRI) studies are often accomplished through the creation of intersubject average activation maps. Compared with traditional volume-based intersubject averages, averages made using computational models of the cortical surface have the potential to increase statistical power because they reduce intersubject variability in cortical folding patterns. We describe a two-step method for creating intersubject surface averages. In the first step cortical surface models are created for each subject and the locations of the anterior and posterior commissures (AC and PC) are aligned. In the second step each surface is standardized to contain the same number of nodes with identical indexing. An anatomical average from 28 subjects created using the AC-PC technique showed greater sulcal and gyral definition than the corresponding volume-based average. When applied to an fMRI dataset, the AC-PC method produced greater maximum, median, and mean t-statistics in the average activation map than did the volume average and gave a better approximation to the theoretical-ideal average calculated from individual subjects. The AC-PC method produced average activation maps equivalent to those produced with surface-averaging methods that use high-dimensional morphing. In comparison with morphing methods, the AC-PC technique does not require selection of a template brain and does not introduce deformations of sulcal and gyral patterns, allowing for group analysis within the original folded topology of each individual subject. The tools for performing AC-PC surface averaging are implemented and freely available in the SUMA software package.

Gender difference analysis of cortical thickness in healthy young adults with surface-based methods

We have examined gender differences of cortical thickness using a 3-D surface-based method that enables more accurate measurement in deep sulci and localized regional mapping compared to volumetric analyses. Cortical thickness was measured using a direct method for calculating the distance between corresponding vertices from inner and outer cortical surfaces. We normalized cortical surfaces using 2-D surface registration and performed diffusion smoothing to reduce the variability of folding patterns and to increase the power of the statistical analysis. In stereotaxic space, significant localized cortical thickening in women was found extensively in frontal, parietal and occipital lobes, including the superior frontal gyrus (SFG), superior parietal gyrus (SPG), inferior frontal gyrus (IFG) and postcentral gyrus (PoCG) in the left hemisphere and mostly in the parietal lobe, including the SPG in the right hemisphere. In the temporal lobe, small regions of the left and right caudal superior temporal gyrus (STG) and the left temporal pole showed significantly greater cortical thickness in women. The temporal lobe shows relatively less significant thickening than other lobes in both hemispheres. In native space, significantly greater cortical thickness in women was detected in left parietal region, including SPG and PoCG. No significant local increases of cortical thickness were observed in men in both spaces. These findings suggest statistically significant cortical thickening in women in localized anatomical regions, which is consistent with several previous studies and may support a hypothesis of sexual dimorphism.

MRI and fMRI analysis of oculomotor function

This chapter reviews the anatomical correlations of the cortical oculomotor centers in humans. The modern structural methods allow a better anatomical definition of the parietal, frontal and temporal structures involved in oculomotor control. Functional imaging reveals the cortical networks involved in saccadic, pursuit, and vestibular eye movements. Finally, the interaction of the network between attention and eye movements is discussed.

Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data

The acquisition of both structural MRI (sMRI) and functional MRI (fMRI) data for a given study is a very common practice. However, these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform independent component analysis across image modalities, specifically, gray matter images and fMRI activation images as well as a joint histogram visualization technique. Joint independent component analysis (jICA) is used to decompose a matrix with a given row consisting of an fMRI activation image resulting from auditory oddball target stimuli and an sMRI gray matter segmentation image, collected from the same individual. We analyzed data collected on a group of schizophrenia patients and healthy controls using the jICA approach. Spatially independent joint-components are estimated and resulting components were further analyzed only if they showed a significant difference between patients and controls. The main finding was that group differences in bilateral parietal and frontal as well as posterior temporal regions in gray matter were associated with bilateral temporal regions activated by the auditory oddball target stimuli. A finding of less patient gray matter and less hemodynamic activity for target detection in these bilateral anterior temporal lobe regions was consistent with previous work. An unexpected corollary to this finding was that, in the regions showing the largest group differences, gray matter concentrations were larger in patients vs. controls, suggesting that more gray matter may be related to less functional connectivity in the auditory oddball fMRI task.

Differences of monkey and human overt attention under natural conditions

Rhesus monkeys are widely used as animal models of human attention. Such research rests upon the assumption that similar mechanisms underlie attention in both species. Here, we directly compare the influence of low-level stimulus features on overt attention in monkeys and humans under natural conditions. We recorded eye-movements in humans and rhesus monkeys during free-viewing of natural images. We find that intrinsic low-level features, such luminance-contrast, texture-contrast and saliency-as predicted by a standard model, are elevated at fixation points in the majority of images. These correlative effects are not significantly different between species. However, local image modifications affect both species differently: moderate modifications, which are in the range of natural fluctuations, attract overt attention in monkeys significantly stronger than they do in humans. In addition, humans show a higher inter-individual consistency regarding which locations they fixate than monkeys, in spite of the similarity for intrinsic low-level features. Taken together, these data demonstrate that-under natural conditions-low-level stimulus features affect attention in monkeys and humans differently.

Quantitative evaluation of three cortical surface flattening methods

During the past decade, several computational approaches have been proposed for the task of mapping highly convoluted surfaces of the human brain to simpler geometric objects such as a sphere or a topological disc. We report the results of a quantitative comparison of FreeSurfer, CirclePack, and LSCM with respect to measurements of geometric distortion and computational speed. Our results indicate that FreeSurfer performs best with respect to a global measurement of metric distortion, whereas LSCM performs best with respect to angular distortion and best in all but one case with a local measurement of metric distortion. FreeSurfer provides more homogeneous distribution of metric distortion across the whole cortex than CirclePack and LSCM. LSCM is the most computationally efficient algorithm for generating spherical maps, while CirclePack is extremely fast for generating planar maps from patches.

Modulation of the C1 visual event-related component by conditioned stimuli: evidence for sensory plasticity in early affective perception

Previous research has demonstrated optimized processing of motivationally significant stimuli early in perception. In the present study, the time course and underlying mechanisms for such fast differentiation are of interest. We investigated the involvement of the primary visual cortex in affective evaluation of conditioned stimuli (CSs). In order to elicit learning within the visual system we chose affective pictures as unconditioned stimuli and used laterally presented gratings as CSs. Using high-density electroencephalography, we demonstrated modulation of the C1 visual event-related component for threat-related stimuli versus neutral stimuli, which increased with continuing acquisition of affective meaning. The differentiation between aversive and neutral visual stimuli occurred as early as 65-90 ms after stimulus onset and suggested involvement of the primary visual areas in affective evaluation. As an underlying mechanism, we discuss short-term reorganization in visual cortex, enabling sensory amplification of specific visual features that are related to motivationally relevant information.

The human connectome: A structural description of the human brain

The connection matrix of the human brain (the human "connectome") represents an indispensable foundation for basic and applied neurobiological research. However, the network of anatomical connections linking the neuronal elements of the human brain is still largely unknown. While some databases or collations of large-scale anatomical connection patterns exist for other mammalian species, there is currently no connection matrix of the human brain, nor is there a coordinated research effort to collect, archive, and disseminate this important information. We propose a research strategy to achieve this goal, and discuss its potential impact.

Volumetric vs. surface-based alignment for localization of auditory cortex activation

The high degree of intersubject structural variability in the human brain is an obstacle in combining data across subjects in functional neuroimaging experiments. A common method for aligning individual data is normalization into standard 3D stereotaxic space. Since the inherent geometry of the cortex is that of a 2D sheet, higher precision can potentially be achieved if the intersubject alignment is based on landmarks in this 2D space. To examine the potential advantage of surface-based alignment for localization of auditory cortex activation, and to obtain high-resolution maps of areas activated by speech sounds, fMRI data were analyzed from the left hemisphere of subjects tested with phoneme and tone discrimination tasks. We compared Talairach stereotaxic normalization with two surface-based methods: Landmark Based Warping, in which landmarks in the auditory cortex were chosen manually, and Automated Spherical Warping, in which hemispheres were aligned automatically based on spherical representations of individual and average brains. Examination of group maps generated with these alignment methods revealed superiority of the surface-based alignment in providing precise localization of functional foci and in avoiding mis-registration due to intersubject anatomical variability. Human left hemisphere cortical areas engaged in complex auditory perception appear to lie on the superior temporal gyrus, the dorsal bank of the superior temporal sulcus, and the lateral third of Heschl's gyrus.

Control of basement membrane remodeling and epithelial branching morphogenesis in embryonic lung by Rho and cytoskeletal tension

Local alterations in the mechanical compliance of the basement membrane that alter the level of isometric tension in the cell have been postulated to influence tissue morphogenesis. To explore whether cell tension contributes to tissue pattern formation in vivo, we modulated cytoskeletal force generation in embryonic mouse lung (embryonic days 12-14) rudiments using inhibitors of Rho-associated kinase (ROCK), myosin light chain kinase, myosin ATPase, and microfilament integrity, or a Rho stimulator (cytotoxic necrotizing factor-1). Tension inhibition resulted in loss of normal differentials in basement membrane thickness, inhibition of new terminal bud formation, and disorganization of epithelial growth patterns as well as disruption of capillary blood vessels. In contrast, increasing cell tension through Rho activation, as confirmed by quantitation of myosin light chain phosphorylation and immunohistocytochemical analysis of actin organization, accelerated lung branching and increase capillary elongation. These data suggest that changes in cytoskeletal tension mediated by Rho signaling through ROCK may play an important role in the establishment of the spatial differentials in cell growth and extracellular matrix remodeling that drive embryonic lung development.

A direct comparison of anterior prefrontal cortex involvement in episodic retrieval and integration

Retrieval of information from episodic memory reliably engages regions within the anterior prefrontal cortex (aPFC). This observation has led researchers to suggest that these regions may subserve processes intimately tied to episodic retrieval. However, the aPFC is also recruited by other complex tasks not requiring episodic retrieval. One hypothesis concerning these results is that episodic retrieval recruits a general cognitive process that is subserved by the aPFC. The current study tested a specific version of this hypothesis--namely, that the integration of internally represented information is this process. Event-related fMRI was employed in a 2 (memory task: encoding versus retrieval) x 2 (level of integration: low versus high) factorial within-subjects design. A functional dissociation was observed, with one aPFC subregion uniquely sensitive to level of integration and another jointly sensitive to level of integration and memory task. Analysis of event-related activation latencies indicated that level of integration and memory task effects occurred with significantly different timing. The results provide the first direct evidence regarding the functional specialization within lateral aPFC and the nature of its recruitment during complex cognitive tasks. Moreover, the study highlights the benefits of activation latency analysis for understanding functional contributions and dissociations between closely linked brain regions.

Cortical thickness analysis in autism with heat kernel smoothing

We present a novel data smoothing and analysis framework for cortical thickness data defined on the brain cortical manifold. Gaussian kernel smoothing, which weights neighboring observations according to their 3D Euclidean distance, has been widely used in 3D brain images to increase the signal-to-noise ratio. When the observations lie on a convoluted brain surface, however, it is more natural to assign the weights based on the geodesic distance along the surface. We therefore develop a framework for geodesic distance-based kernel smoothing and statistical analysis on the cortical manifolds. As an illustration, we apply our methods in detecting the regions of abnormal cortical thickness in 16 high functioning autistic children via random field based multiple comparison correction that utilizes the new smoothing technique.

Increasing the power of functional maps of the medial temporal lobe by using large deformation diffeomorphic metric mapping

The functional magnetic resonance imagery responses of declarative memory tasks in the medial temporal lobe (MTL) are examined by using large deformation diffeomorphic metric mapping (LDDMM) to remove anatomical variations across subjects. LDDMM is used to map the structures of the MTL in multiple subjects into extrinsic atlas coordinates; these same diffeomorphic mappings are used to transfer the corresponding functional data activation to the same extrinsic coordinates. The statistical power in the averaged LDDMM mapped signals is significantly increased over conventional Talairach-Tournoux averaging. Activation patterns are highly localized within the MTL. Whereas the present demonstration has been aimed at enhancing alignment within the MTL, this technique is general and can be applied throughout the brain.

A stochastic model for studying the laminar structure of cortex from MRI

The human cerebral cortex is a laminar structure about 3 mm thick, and is easily visualized with current magnetic resonance (MR) technology. The thickness of the cortex varies locally by region, and is likely to be influenced by such factors as development, disease and aging. Thus, accurate measurements of local cortical thickness are likely to be of interest to other researchers. We develop a parametric stochastic model relating the laminar structure of local regions of the cerebral cortex to MR image data. Parameters of the model include local thickness, and statistics describing white, gray and cerebrospinal fluid (CSF) image intensity values as a function of the normal distance from the center of a voxel to a local coordinate system anchored at the gray/white matter interface. Our fundamental data object, the intensity-distance histogram (IDH), is a two-dimensional (2-D) generalization of the conventional 1-D image intensity histogram, which indexes voxels not only by their intensity value, but also by their normal distance to the gray/white interface. We model the IDH empirically as a marked Poisson process with marking process a Gaussian random field model of image intensity indexed against normal distance. In this paper, we relate the parameters of the IDH model to the local geometry of the cortex. A maximum-likelihood framework estimates the parameters of the model from the data. Here, we show estimates of these parameters for 10 volumes in the posterior cingulate, and 6 volumes in the anterior and posterior banks of the central sulcus. The accuracy of the estimates is quantified via Cramer-Rao bounds. We believe that this relatively crude model can be extended in a straightforward fashion to other biologically and theoretically interesting problems such as segmentation, surface area estimation, and estimating the thickness distribution in a variety of biologically relevant contexts.

Implicit brain imaging

We describe how implicit surface representations can be used to solve fundamental problems in brain imaging. This kind of representation is not only natural following the state-of-the-art segmentation algorithms reported in the literature to extract the different brain tissues, but it is also, as shown in this paper, the most appropriate one from the computational point of view. Examples are provided for finding constrained special curves on the cortex, such as sulcal beds, regularizing surface-based measures, such as cortical thickness, and for computing warping fields between surfaces such as the brain cortex. All these result from efficiently solving partial differential equations (PDEs) and variational problems on surfaces represented in implicit form. The implicit framework avoids the need to construct intermediate mappings between 3-D anatomical surfaces and parametric objects such planes or spheres, a complex step that introduces errors and is required by many other cortical processing approaches.

Cortical cartography using the discrete conformal approach of circle packings

Cortical flattening algorithms are becoming more widely used to assist in visualizing the convoluted cortical gray matter sheet of the brain. Metric-based approaches are the most common but suffer from high distortions. Conformal, or angle-based algorithms, are supported by a comprehensive mathematical theory. The conformal approach that uses circle packings is versatile in the manipulation and display of results. In addition, it offers some new and interesting metrics that may be useful in neuroscientific analysis and are not available through numerical partial differential equation conformal methods. In this paper, we begin with a brief description of cortical "flat" mapping, from data acquisition to map displays, including a brief review of past flat mapping approaches. We then describe the mathematics of conformal geometry and key elements of conformal mapping. We introduce the mechanics of circle packing and discuss its connections with conformal geometry. Using a triangulated surface representing a cortical hemisphere, we illustrate several manipulations available using circle packing methods and describe the associated "ensemble conformal features" (ECFs). We conclude by discussing current and potential uses of conformal methods in neuroscience and computational anatomy.

Computational anatomy: shape, growth, and atrophy comparison via diffeomorphisms

Computational anatomy (CA) is the mathematical study of anatomy I in I = I(alpha) o G, an orbit under groups of diffeomorphisms (i.e., smooth invertible mappings) g in G of anatomical exemplars I(alpha) in I. The observable images are the output of medical imaging devices. There are three components that CA examines: (i) constructions of the anatomical submanifolds, (ii) comparison of the anatomical manifolds via estimation of the underlying diffeomorphisms g in G defining the shape or geometry of the anatomical manifolds, and (iii) generation of probability laws of anatomical variation P(.) on the images I for inference and disease testing within anatomical models. This paper reviews recent advances in these three areas applied to shape, growth, and atrophy.

Cortical activity to vibrotactile stimulation: an fMRI study in blind and sighted individuals

Blind individuals show visual cortex activity during Braille reading. We examined whether such cross-modal activations reflect processing somatosensory stimuli independent of language by identifying cortical activity during a one-back vibrotactile matching task. Three groups (sighted, early-onset, and late-onset [>12 years] blind) detected whether paired vibrations (25 and 100 Hz), delivered to the right index finger, differed in frequency. Three successive paired vibrations, followed by a no-stimulation interval, were presented in a long event-related design. A fixed effects average z-score analysis showed increased activity throughout the visuotopic visual cortex, where it was mostly restricted to foveal and parafoveal eccentricities. Early blind showed the most extensive distribution of activity. Late blind exhibited activity mostly in similar regions but with declining response magnitudes with age of blindness onset. Three sighted individuals had suprathreshold activity in V1 but negative responses elsewhere in visual cortex. Mixed effects ANOVA confirmed group distinctions in defined regions (V1, V3, V4v, V7, LOC, and MT). These results suggest cross-modal adaptation to tactile stimulation in visual cortex independent of language processes. All groups showed increased activity in left primary (S1) and bilateral second somatosensory areas, but without response magnitude differences between groups throughout sensorimotor cortex. Early blind showed the greatest spatial extent of S1 activity. Blind participants had more extensive bilateral activity in anterior intraparietal sulcus and supramarginal gyrus. Extensive usage of touch in Braille reading may underlie observed S1 expansions in the reading finger representation. In addition, learned attentiveness to touch may explain similar expansion of parietal tactile attention regions.

Positioning of retinotopic areas and patterning of cerebral cortex layout

We examined the positioning of human retinotopic areas, which were considered to be homologous with the macaque visual cortices, by applying computational geometry to MRI and fMRI data sets. We found a similarity between the positional relationship of the retinotopic areas in the human and macaque visual cortex, despite the large difference in brain size. This suggests that area maps in different species may share topological features, probably resulting from broad similarities in the patterning mechanism of cerebral cortex layout.

Dynamics of thalamo-cortical network oscillations and human perception

There is increasing evidence that human cognitive functions can be addressed from a robust neuroscience perspective. In particular, the distributed coherent electrical properties of central neuronal ensembles are considered to be a promising avenue of inquiry concerning global brain functions. The intrinsic oscillatory properties of neurons (Llinás, R. (1988) The intrinsic electrophysiological properties of mammalian neurons: Insights into central nervous system function. Science, 242: 1654-1664), supported by a large variety of voltage-gated ionic conductances are recognized to be the central elements in the generation of the temporal binding required for cognition. Research in neuroscience further indicates that oscillatory activity in the gamma band (25-50 Hz) can be correlated with both sensory acquisition and pre-motor planning, which are non-continuous functions in the time domain. From this perspective, gamma-band activity is viewed as serving a broad temporal binding function, where single-cell oscillators and the conduction time of the intervening pathways support large multicellular thalamo-cortical resonance that is closely linked with cognition and subjective experience. Our working hypothesis is that although dedicated units achieve sensory processing, the cognitive binding process is a common mechanism across modalities. Moreover, it is proposed that such time-dependent binding when altered, will result in modifications of the sensory motor integration that will affect and impair cognition and conscious perception.

The shape operator for differential analysis of images

This work provides a new technique for surface oriented volumetric image analysis. The method makes no assumptions about topology, instead constructing a local neighborhood from image information, such as a segmentation or edge map, to define a surface patch. Neighborhood constructions using extrinsic and intrinsic distances are given. This representation allows one to estimate differential properties directly from the image's Gauss map. We develop a novel technique for this purpose which estimates the shape operator and yields both principal directions and curvatures. Only first derivatives need be estimated, making the method numerically stable. We show the use of these measures for multi-scale classification of image structure by the mean and Gaussian curvatures. Finally, we propose to register image volumes by surface curvature. This is particularly useful when geometry is the only variable. To illustrate this, we register binary segmented data by surface curvature, both rigidly and non-rigidly. A novel variant of Demons registration, extensible for use with differentiable similarity metrics, is also applied for deformable curvature-driven registration of medical images.

Object-based morphometry of the cerebral cortex

Most of the approaches dedicated to automatic morphometry rely on a point-by-point strategy based on warping each brain toward a reference coordinate system. In this paper, we describe an alternative object-based strategy dedicated to the cortex. This strategy relies on an artificial neuroanatomist performing automatic recognition of the main cortical sulci and parcellation of the cortical surface into gyral patches. A set of shape descriptors, which can be compared across subjects, is then attached to the sulcus and gyrus related objects segmented by this process. The framework is used to perform a study of 142 brains of the International Consortium for Brain Mapping (ICBM) database. This study reveals some correlates of handedness on the size of the sulci located in motor areas, which was not detected previously using standard voxel based morphometry.

Local landmark-based mapping of human auditory cortex

Mammalian sensory cortex is functionally partitioned into cortical fields that are specialized for different processing operations. In theory, averaging functional and anatomical images across subjects can reveal both the average anatomy and the mean functional organization of sensory regions. However, this averaging process must overcome at least two obstacles: (1) the relative locations and sizes of cortical sensory areas vary in different subjects so that across-subject averaging introduces spatial smearing; (2) the relative locations and sizes of cortical areas vary between hemispheres, making it difficult to compare activations between hemispheres or to combine activations across hemispheres. These difficulties are particularly acute for small cortical regions such as auditory cortex. In whole-brain averaging procedures, considerable intersubject variance in the location and orientation of auditory cortex is introduced by variance of the size and shape of structures outside auditory cortex. Here, we compared these global methods with local landmark-based methods (LLMs) that use warping based on local anatomical landmarks. In comparison to maps made with global methods, LLMs produced anatomical maps of auditory cortex with clearer gyral and sulcal structure, and produce functional maps with improved resolution. These results suggest that LLMs have significant advantages over global mapping procedures in studying the details of auditory cortex organization.

Deformable registration of cortical structures via hybrid volumetric and surface warping

Registration of cortical structures across individuals is a very important step for quantitative analysis of the human brain cortex. This paper presents a method for deformable registration of cortical structures across individuals, using hybrid volumetric and surface warping. In the first step, a feature-based volumetric registration algorithm is used to warp a model cortical surface to the individual's space. This step greatly reduces the variation between the model and individual, thus providing a good initialization for the next step of surface warping. In the second step, a surface registration method, based on matching geometric attributes, warps the model surface to the individual. Point correspondences are also established at this step. The attribute vector, as the morphological signature of surface, was designed to be as distinctive as possible, so that each vertex on the model surface can find its correspondence on the individual surface. Experimental results on both synthesized and real brain data demonstrate the performance of the proposed method in the registration of cortical structures across individuals.

Investigations of the human visual system using functional magnetic resonance imaging (FMRI)

The application of functional magnetic resonance imaging (fMRI) in studies of the visual system provided significant advancement in our understanding of the organization and functional properties of visual areas in the human cortex. Recent technological and methodological improvements allowed studies to correlate neuronal activity with visual perception and demonstrated the ability of fMRI to observe distributed neural systems and to explore modulation of neural activity during higher cognitive processes. Preliminary applications in patients with visual impairments suggest that this method provides a powerful tool for the assessment and management of brain pathologies. Recent research focuses on obtaining new information about the spatial localization, organization, functional specialization and participation in higher cognitive functions of visual cortical areas in the living human brain and in further establishment of the method as a useful clinical tool of diagnostic and prognostic significance for various pathologic processes affecting the integrity of the visual system. It is anticipated that the combined neuroimaging approach in patients with lesions and healthy controls will provide new insight on the topography and functional specialization of cortical visual areas and will further establish the clinical value of the method for improving diagnostic accuracy and treatment planning.

Coordinate-based versus structural approaches to brain image analysis

A basic issue in neurosciences is to look for possible relationships between brain architecture and cognitive models. The lack of architectural information in magnetic resonance images, however, has led the neuroimaging community to develop brain mapping strategies based on various coordinate systems without accurate architectural content. Therefore, the relationships between architectural and functional brain organizations are difficult to study when analyzing neuroimaging experiments. This paper advocates that the design of new brain image analysis methods inspired by the structural strategies often used in computer vision may provide better ways to address these relationships. The key point underlying this new framework is the conversion of the raw images into structural representations before analysis. These representations are made up of data-driven elementary features like activated clusters, cortical folds or fiber bundles. Two classes of methods are introduced. Inference of structural models via matching across a set of individuals is described first. This inference problem is illustrated by the group analysis of functional statistical parametric maps (SPMs). Then, the matching of new individual data with a priori known structural models is described, using the recognition of the cortical sulci as a prototypical example.

A multimodal, multidimensional atlas of the C57BL/6J mouse brain

Strains of mice, through breeding or the disruption of normal genetic pathways, are widely used to model human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison. We have developed a digital atlas of the adult C57BL/6J mouse brain as a comprehensive framework for storing and accessing the myriad types of information about the mouse brain. Our implementation was constructed using several different imaging techniques: magnetic resonance microscopy, blockface imaging, classical histology and immunohistochemistry. Along with raw and annotated images, it contains database management systems and a set of tools for comparing information from different techniques. The framework allows facile correlation of results from different animals, investigators or laboratories by establishing a canonical representation of the mouse brain and providing the tools for the insertion of independent data into the same space as the atlas. This tool will aid in managing the increasingly complex and voluminous amounts of information about the mammalian brain. It provides a framework that encompasses genetic information in the context of anatomical imaging and holds tremendous promise for producing new insights into the relationship between genotype and phenotype. We describe a suite of tools that enables the independent entry of other types of data, facile retrieval of information and straightforward display of images. Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at http://www.loni.ucla.edu/MAP.

Re-examining the brain regions crucial for orchestrating speech articulation

A traditional method of localizing brain functions has been to identify shared areas of brain damage in individuals who have a particular deficit. The rationale of this 'lesion overlap' approach is straightforward: if the individuals can no longer perform the function, the area of brain damaged in most of these individuals must have been responsible for that function. However, the reciprocal association, i.e. the probability of the lesion causing the deficit, is often not evaluated. In this study, we illustrate potential weaknesses of this approach, by re-examining regions of the brain essential for orchestrating speech articulation. A particularly elegant and widely cited lesion overlap study identified the superior part of the precentral gyrus of the insula (in the anterior insula) as the shared area of damage in chronic stroke patients with 'apraxia of speech', a disorder of motor planning and programming of speech. Others have confirmed that patients with apraxia of speech commonly have damage to the anterior insula. However, this reliable association might reflect the vulnerability of the insula to damage following occlusion or narrowing of the middle cerebral artery (which can independently cause apraxia of speech and many other deficits). To evaluate this possibility, we examined the relationship between apraxia of speech and the insula in three unique ways: (i) we determined the probability of the lesion causing the deficit, as well as the deficit being associated with the lesion, by examining speech articulation and advanced MRIs in two consecutive series of patients with acute left hemisphere, non-lacunar stroke, 40 with and 40 without insular damage; (ii) we studied patients at stroke onset to identify the deficit before it resolved in cases of small stroke; and (iii) we identified regions of dysfunctional brain tissue, as well as structural damage. Using this approach, we found no association between apraxia of speech and lesions of the left insula, anterior insula or superior tip of the precentral gyrus of the insula. Instead, in patients with and without insular lesions, apraxia of speech was associated with structural damage or low blood flow in left posterior inferior frontal gyrus. These results illustrate a potential limitation of lesion overlap studies, and illustrate an alternative method for identifying brain-behaviour relationships.

Invariant surface alignment in the presence of affine and some nonlinear transformations

In this paper, we introduce a non-iterative geometric-based method to align 3D brain surfaces into standard coordinate system, which is based on a novel set of surface landmarks (e.g., inflection and/or zero torsion points residing on parabolic contours), which are intrinsic and are computed from the differential geometry of the surface. This is in contrast to existing methods that depend on anatomical landmarks that require expert intervention to locate--a very hard task. The landmarks are local and are preserved under affine transformations. To reduce the sensitivity of the landmarks to noise, we use a B-Spline surface representation that smoothes out the surface prior to the computation of the landmarks. The alignment is achieved by establishing correspondences between the landmarks after a sorting of the landmarks based on derived absolute invariants (volumes confined between parallelepipeds spanned by sets of the landmark point quadruplets). The method is tested for intra- and inter-brain alignments while entertaining affine, cubic and fourth-order polynomial nonlinear transformations using distance mapping as well as comparison with an expert alignment, and promising results are obtained. When comparing our automatic alignment with that of an expert we arrived at complete agreement for the more difficult case of partial alignment of sectional slab materials of five rats with an atlas (a whole brain of rat). This perfect alignment was only based on the surface structure for our procedure, whereas it was based on the staining and the external and internal structures for the expert.

Surface-based approaches to spatial localization and registration in primate cerebral cortex

Explicit surface reconstructions provide invaluable substrates for visualizing and analyzing the complex convolutions of cerebral cortex. This report illustrates the utility of surface-based atlases of human and macaque monkey for representing many aspects of cortical organization and function. These include a variety of cortical partitioning schemes plus an open-ended collection of complex activation patterns obtained from fMRI studies. Surface-based registration from one hemisphere to an atlas provides powerful approach to (i) objectively and quantitatively representing both the consistencies and the variability of the pattern of convolutions and the patterns of functional activation from any given task; and (ii) making comparisons across species and evaluating candidate homologies between cortical areas or functionally delineated regions.

Computational anatomy and neuropsychiatric disease: probabilistic assessment of variation and statistical inference of group difference, hemispheric asymmetry, and time-dependent change

Three components of computational anatomy (CA) are reviewed in this paper: (i) the computation of large-deformation maps, that is, for any given coordinate system representations of two anatomies, computing the diffeomorphic transformation from one to the other; (ii) the computation of empirical probability laws of anatomical variation between anatomies; and (iii) the construction of inferences regarding neuropsychiatric disease states. CA utilizes spatial-temporal vector field information obtained from large-deformation maps to assess anatomical variabilities and facilitate the detection and quantification of abnormalities of brain structure in subjects with neuropsychiatric disorders. Neuroanatomical structures are divided into two types: subcortical structures-gray matter (GM) volumes enclosed by a single surface-and cortical mantle structures-anatomically distinct portions of the cerebral cortical mantle layered between the white matter (WM) and cerebrospinal fluid (CSF). Because of fundamental differences in the geometry of these two types of structures, image-based large-deformation high-dimensional brain mapping (HDBM-LD) and large-deformation diffeomorphic metric matching (LDDMM) were developed for the study of subcortical structures and labeled cortical mantle distance mapping (LCMDM) was developed for the study of cortical mantle structures. Studies of neuropsychiatric disorders using CA usually require the testing of hypothesized group differences with relatively small numbers of subjects per group. Approaches that increase the power for testing such hypotheses include methods to quantify the shapes of individual structures, relationships between the shapes of related structures (e.g., asymmetry), and changes of shapes over time. Promising preliminary studies employing these approaches to studies of subjects with schizophrenia and very mild to mild Alzheimer's disease (AD) are presented.

Labeled cortical mantle distance maps of the cingulate quantify differences between dementia of the Alzheimer type and healthy aging

The cingulate gyri in 37 subjects with and without early dementia of the Alzheimer type (DAT) were studied by using MRI at 1.0 mm3 isotropic resolution. Groups were segregated into young controls (n = 10), age-matched normal controls (n = 10), very mild DAT (n = 8), and mild DAT (n = 9). By using automated Bayesian segmentation of the cortex and gray matter/white matter (GM/WM) isosurface generation, tissue compartments were labeled into gray, white, and cerebrospinal fluid as a function of distance from the GM/WM isosurface. Cortical mantle distance maps are generated profiling the GM volume and cortical mantle distribution as a function of distance from the cortical surface. Probabilistic tests based on generalizations of Wilcoxon-Mann-Whitney tests were applied to quantify cortical mantle distribution changes with normal and abnormal aging. We find no significant change between young controls and healthy aging as measured by the GM volume and cortical mantle distribution as a function of distance in both anterior and posterior regions of the cingulate. Significant progression of GM loss is seen in the very mild DAT and mild DAT groups in all areas of the cingulate. Posterior regions show both GM volume loss as well as significant cortical mantle distribution decrease with the onset of mild DAT. The "shape of the cortical mantle" as measured by the cortical mantle distance profiles manifests a pronounced increase in variability with mild DAT.

Dynamic programming generation of boundaries of local coordinatized submanifolds in the neocortex: application to the planum temporale

Dynamic programming is used to define boundaries of cortical submanifolds with focus on the planum temporale (PT) of the superior temporal gyrus (STG), which has been implicated in a variety of neuropsychiatric disorders. To this end, automated methods are used to generate the PT manifold from 10 high-resolution MRI subvolumes ROI masks encompassing the STG. A procedure to define the subvolume ROI masks from original MRI brain scans is developed. Bayesian segmentation is then used to segment the subvolumes into cerebrospinal fluid, gray matter (GM), and white matter (WM). 3D isocontouring using the intensity value at which there is equal probability of GM and WM is used to reconstruct the triangulated graph representing the STG cortical surface, enabling principal curvature at each point on the graph to be computed. Dynamic programming is used to delineate the PT manifold by tracking principal curves from the retro-insular end of the Heschl's gyrus (HG) to the STG, along the posterior STG up to the start of the ramus and back to the retro-insular end of the HG. A coordinate system is then defined on the PT manifold. The origin is defined by the retro-insular end of the HG and the y-axis passes through the point on the posterior STG where the ramus begins. Automated labeling of GM in the STG is robust with L(1) distances between Bayesian and manual segmentation in the range 0.001-0.12 (n = 20). PT reconstruction is also robust with 90% of the vertices of the reconstructed PT within about 1 voxel (n = 20) from semiautomated contours. Finally, the reliability index (based on interrater intraclass correlation) for the surface area derived from repeated reconstructions is 0.96 for the left PT and 0.94 for the right PT, thus demonstrating the robustness of dynamic programming in defining a coordinate system on the PT. It provides a method with potential significance in the study of neuropsychiatric disorders.

Geometric atlas: modeling the cortex as an organized surface

Recent atlases of the cortical surface are based on a modelization of the cerebral cortex as a topological sphere. This captures effectively its organization as a regular bidimensional sheet of layers parallel to the surface and with perpendicular cortical columns. Yet, while in the vertical direction cortices are almost the same throughout phylia, in the sense of its surface the cerebral cortex is one of the most variable and distinctive parts of the nervous system. Indeed, gyri and sulci appear to have a crucial organizing role in an architectonic, connectional, and functional sense. This organization is not explicitly captured by the surface model of the cortex. We propose a geometric model of the cortical anatomy based on flat representations of principal sulci obtained from surface reconstructions of MRI data, and on neuroanatomical and theoretical considerations concerning the folding patterns of the cortex. The cortex is modeled by a sphere where primary sulci are included as axes. The arrangement of the axes is a simplification of the arrangement of principal sulci observed in flat stereographic representations of the whole cortical surface. The position of secondary and tertiary sulci is then defined by a field of orientations parallel and orthogonal to the axes. We consider the use of the geometric model as a synthetic reference cortex for addressing reconstructions of cortical surfaces. We present a method which establishes a bijection between the geometric model and a cortical surface reconstruction by using the axes of the model as boundary conditions for a set of partial differential equations solved over both surfaces. Using the geometric model as atlas provides a natural parameterization of the cortical surface that, unlike angular coordinates, allows for a localization based on the surface distance to its main organizing landmarks and folding patterns.

Zen and the art of medical image registration: correspondence, homology, and quality

Nonrigid registration (NRR) is routinely used in the study of neuroanatomy and function and is a standard component of analysis packages such as SPM. There remain many unresolved correspondence problems that arise from attempts to associate functional areas with specific neuroanatomy and to compare both function and anatomy across patient groups. Problems can result from ignorance of the underlying neurology which is then compounded by unjustified inferences drawn from the results of NRR. Usually the magnitude, distribution, and significance of errors in NRR are unknown so the errors in correspondences determined by NRR are also unknown and their effect on experimental results cannot easily be quantified. In this paper we review the principles by which the presumed correspondence and homology of structures is used to drive registration and identify the conceptual and algorithmic areas where current techniques are lacking. We suggest that for applications using NRR to be robust and achieve their potential, context-specific definitions of correspondence must be developed which properly characterise error. Prior knowledge of image content must be utilised to monitor and guide registration and gauge the degree of success. The use of NRR in voxel-based morphometry is examined from this context and found wanting. We conclude that a move away from increasingly sophisticated but context-free registration technology is required and that the veracity of studies that rely on NRR should be keenly questioned when the error distribution is unknown and the results are unsupported by other contextual information.

Object-based strategy for morphometry of the cerebral cortex

Most of the approaches dedicated to automatic morphometry rely on a point-by-point strategy based on warping each brain towards a reference coordinate system. In this paper, we describe an alternative object-based strategy dedicated to the cortex. This strategy relies on an artificial neuroanatomist performing automatic recognition of the main cortical sulci and parcellation of the cortical surface into gyral patches. A set of shape descriptors, which can be compared across subjects, is then attached to the sulcus and gyrus related objects segmented by this process. The framework is used to perform a study of 142 brains of the ICBM database. This study reveals some correlates of handedness on the size of the sulci located in motor areas, which seem to be beyond the scope of the standard voxel based morphometry.

The LONI Pipeline Processing Environment

The analysis of raw data in neuroimaging has become a computationally entrenched process with many intricate steps run on increasingly larger datasets. Many software packages exist that provide either complete analyses or specific steps in an analysis. These packages often possess diverse input and output requirements, utilize different file formats, run in particular environments, and have limited abilities with certain types of data. The combination of these packages to achieve more sensitive and accurate results has become a common tactic in brain mapping studies but requires much work to ensure valid interoperation between programs. The handling, organization, and storage of intermediate data can prove difficult as well. The LONI Pipeline Processing Environment is a simple, efficient, and distributed computing solution to these problems enabling software inclusion from different laboratories in different environments. It is used here to derive a T1-weighted MRI atlas of the human brain from 452 normal young adult subjects with fully automated processing. The LONI Pipeline Processing Environment's parallel processing efficiency using an integrated client/server dataflow model was 80.9% when running the atlas generation pipeline from a PC client (Acer TravelMate 340T) on 48 dedicated server processors (Silicon Graphics Inc. Origin 3000). The environment was 97.5% efficient when the same analysis was run on eight dedicated processors.

Functional dissociation among components of remembering: control, perceived oldness, and content

Remembering is the ability to bring back to mind episodes from one's past and is presumably accomplished by multiple, interdependent processes. In the present functional magnetic resonance imaging study, neural correlates of three hypothesized components of remembering were explored, including those associated with control, perceived oldness, and retrieved content. Levels of each component were separately manipulated by varying study procedures and sorting trials by subject response. Results suggest that specific regions in the left prefrontal cortex, including anterior-ventral Brodmann's Area (BA) 45/47 and more dorsal BA 44, increase activity when high levels of control are required but do not necessarily modulate on the basis of perceived oldness. Parietal and frontal regions, particularly the left parietal cortex near BA 40/39, associate with the perception that information is old and generalize across levels of control and retrieved content. Activity in the parietal cortex correlated with perceived oldness even when judgments were in error. The inferior temporal cortex near BA 19/37 associated differentially with retrieval of visual object content. Within the ventral visual processing stream, content-based modulation was specific to late object-responsive regions, suggesting an efficient retrieval process that spares areas that process more primitive retinotopically mapped visual features. Taken collectively, the results identify neural correlates of distinct components of remembering and provide evidence for a functional dissociation. Frontal regions may contribute to control processes that interact with different posterior regions that contribute a signal that information is old and support the contents of retrieval.

Subcortical, cerebellar, and magnetic resonance based consistent brain image registration

A new landmark-initialized segmentation and intensity-based (LI-SI) inverse-consistent linear elastic image registration algorithm is presented. This method uses manually identified landmarks, segmented volumetric (anatomical) structures, and normalized image signal intensity information to coregister datasets. The features used for image registration and evaluation include 35 cortical, cerebellar, and commissure landmarks manually identified by experts, subcortical and cerebellar regions defined semi-automatically by an artificial neural network and manually trimmed for validity by experts, and tissue classified images that were generated using a discriminant analysis of three magnetic resonance image sets representing T1, T2, and PD modalities. Four groups of results were computed for coregistering 16 datasets with the following registration techniques: rigid registration, extended Talairach registration, intensity-only inverse-consistent linear elastic registration, and the new LI-SI registration. Results are presented showing that relative overlap measurements increased as the dimensionality of the registration algorithm and amount of anatomical information increased. The average relative overlap improved from 0.53 for the rigid registration to 0.55 for the Talairach registration to 0.74 for the intensity-only and to 0.85 for the LI-SI algorithm. We showed a statistically significant improvement for all but one structure using the intensity-only algorithm compared to the Talairach registration. Furthermore, statistically significant improvements for all structures were achieved using the LI-SI algorithm compared to the intensity-only algorithm.

Functional dissociation among components of remembering: control, perceived oldness, and content

Remembering is the ability to bring back to mind episodes from one's past and is presumably accomplished by multiple, interdependent processes. In the present functional magnetic resonance imaging study, neural correlates of three hypothesized components of remembering were explored, including those associated with control, perceived oldness, and retrieved content. Levels of each component were separately manipulated by varying study procedures and sorting trials by subject response. Results suggest that specific regions in the left prefrontal cortex, including anterior-ventral Brodmann's Area (BA) 45/47 and more dorsal BA 44, increase activity when high levels of control are required but do not necessarily modulate on the basis of perceived oldness. Parietal and frontal regions, particularly the left parietal cortex near BA 40/39, associate with the perception that information is old and generalize across levels of control and retrieved content. Activity in the parietal cortex correlated with perceived oldness even when judgments were in error. The inferior temporal cortex near BA 19/37 associated differentially with retrieval of visual object content. Within the ventral visual processing stream, content-based modulation was specific to late object-responsive regions, suggesting an efficient retrieval process that spares areas that process more primitive retinotopically mapped visual features. Taken collectively, the results identify neural correlates of distinct components of remembering and provide evidence for a functional dissociation. Frontal regions may contribute to control processes that interact with different posterior regions that contribute a signal that information is old and support the contents of retrieval.

Automatic volumetric segmentation of human visual retinotopic cortex

Previous identification of early visual cortical areas in humans with phase-encoded retinotopic mapping techniques have relied on an accurate cortical surface reconstruction. Here a 3D phase-encoded retinotopic mapping technique that does not require a reconstruction of the cortical surface is demonstrated. The visual field sign identification is completely automatic and the method directly supplies volumes for a region-of-interest analysis, facilitating the application of cortical mapping to a wider population. A validation of the method is provided by simulations and comparison to cortical surface-based methodology.

Functional reorganization and stability of somatosensory-motor cortical topography in a tetraplegic subject with late recovery

The functional organization of somatosensory and motor cortex was investigated in an individual with a high cervical spinal cord injury, a 5-year absence of nearly all sensorymotor function at and below the shoulders, and rare recovery of some function in years 6-8 after intense and sustained rehabilitation therapies. We used functional magnetic resonance imaging to study brain activity to vibratory stimulation and voluntary movements of body parts above and below the lesion. No response to vibratory stimulation of the hand was observed in the primary somatosensory cortex (SI) hand area, which was conversely recruited during tongue movements that normally evoke responses only in the more lateral face area. This result suggests SI reorganization analogous to previously reported neuroplasticity changes after peripheral lesions in animals and humans. In striking contradistinction, vibratory stimulation of the foot evoked topographically appropriate responses in SI and second somatosensory cortex (SII). Motor cortex responses, tied to a visuomotor tracking task, displayed a near-typical topography, although they were more widespread in premotor regions. These findings suggest possible preservation of motor and some somatosensory cortical representations in the absence of overt movements or conscious sensations for several years after spinal cord injury and have implications for future rehabilitation and neural-repair therapies.

Surface-based atlases of cerebellar cortex in the human, macaque, and mouse

This study describes surface reconstructions and associated flat maps that represent the highly convoluted shape of cerebellar cortex in three species: human, macaque, and mouse. The reconstructions were based on high-resolution structural MRI data obtained from other laboratories. The surface areas determined for the fiducial reconstructions are about 600 cm(2) for the human, 60 cm(2) for the macaque, and 0.8 cm(2) for the mouse. As expected from the ribbon-like pattern of cerebellar folding, the cerebellar flat maps are elongated along the axis parallel to the midline. However, the degree of elongation varies markedly across species. The macaque flat map is many times longer than its mean width, whereas the mouse flat map is only slightly elongated and the human map is intermediate in its aspect ratio. These cerebellar atlases, along with associated software for visualization and for mapping experimental data onto the atlas, are freely available to the neuroscience community (see http:/brainmap.wustl.edu).