Martin I. Sereno

Cortical surface-based analysis - I. Segmentation and surface reconstruction

Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging.

Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System

The surface of the human cerebral cortex is a highly folded sheet with the majority of its surface area buried within folds. As such, it is a difficult domain for computational as well as visualization purposes. We have therefore designed a set of procedures for modifying the representation of the cortical surface to (i) inflate it so that activity buried inside sulci may be visualized, (ii) cut and flatten an entire hemisphere, and (iii) transform a hemisphere into a simple parameterizable surface such as a sphere for the purpose of establishing a surface-based coordinate system.

High-resolution intersubject averaging and a coordinate system for the cortical surface.

The neurons of the human cerebral cortex are arranged in a highly folded sheet, with the majority of the cortical surface area buried in folds. Cortical maps are typically arranged with a topography oriented parallel to the cortical surface. Despite this unambiguous sheetlike geometry, the most commonly used coordinate systems for localizing cortical features are based on 3‐D stereotaxic coordinates rather than on position relative to the 2‐D cortical sheet. In order to address the need for a more natural surface‐based coordinate system for the cortex, we have developed a means for generating an average folding pattern across a large number of individual subjects as a function on the unit sphere and of nonrigidly aligning each individual with the average. This establishes a spherical surface‐based coordinate system that is adapted to the folding pattern of each individual subject, allowing for much higher localization accuracy of structural and functional features of the human brain. Hum. Brain Mapping 8:272–284, 1999.

Involvement of striate and extrastriate visual cortical areas in spatial attention.

We investigated the cortical mechanisms of visual-spatial attention while subjects discriminated patterned targets within distractor arrays. Functional magnetic resonance imaging (fMRI) was used to map the boundaries of retinotopic visual areas and to localize attention-related changes in neural activity within several of those areas, including primary visual (striate) cortex. Event-related potentials (ERPs) and modeling of their neural sources, however, indicated that the initial sensory input to striate cortex at 50–55 milliseconds after the stimulus was not modulated by attention. The earliest facilitation of attended signals was observed in extrastriate visual areas, at 70–75 milliseconds. We hypothesize that the striate cortex modulation found with fMRI may represent a delayed, re-entrant feedback from higher visual areas or a sustained biasing of striate cortical neurons during attention. ERP recordings provide critical temporal information for analyzing the functional neuroanatomy of visual attention.

Cortical sources of the early components of the visual evoked potential

This study aimed to characterize the neural generators of the early components of the visual evoked potential (VEP) to isoluminant checkerboard stimuli. Multichannel scalp recordings, retinotopic mapping and dipole modeling techniques were used to estimate the locations of the cortical sources giving rise to the early C1, P1, and N1 components. Dipole locations were matched to anatomical brain regions visualized in structural magnetic resonance imaging (MRI) and to functional MRI (fMRI) activations elicited by the same stimuli. These converging methods confirmed previous reports that the C1 component (onset latency 55 msec; peak latency 90–92 msec) was generated in the primary visual area (striate cortex; area 17). The early phase of the P1 component (onset latency 72–80 msec; peak latency 98–110 msec) was localized to sources in dorsal extrastriate cortex of the middle occipital gyrus, while the late phase of the P1 component (onset latency 110–120 msec; peak latency 136–146 msec) was localized to ventral extrastriate cortex of the fusiform gyrus. Among the N1 subcomponents, the posterior N150 could be accounted for by the same dipolar source as the early P1, while the anterior N155 was localized to a deep source in the parietal lobe. These findings clarify the anatomical origin of these VEP components, which have been studied extensively in relation to visual‐perceptual processes. Hum. Brain Mapping 15:95–111, 2001.

Voxel-based lesion–symptom mapping

For more than a century, lesion–symptom mapping studies have yielded valuable insights into the relationships between brain and behavior, but newer imaging techniques have surpassed lesion analysis in examining functional networks. Here we used a new method—voxel-based lesion–symptom mapping (VLSM)—to analyze the relationship between tissue damage and behavior on a voxel-by-voxel basis, as in functional neuroimaging. We applied VLSM to measures of speech fluency and language comprehension in 101 left-hemisphere-damaged aphasic patients: the VLSM maps for these measures confirm the anticipated contrast between anterior and posterior areas, and they also indicate that interacting regions facilitate fluency and auditory comprehension, in agreement with findings from modern brain imaging.

Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data

Cortical surface-based analysis of fMRI data has proven to be a useful method with several advantages over 3-dimensional volumetric analyses. Many of the statistical methods used in 3D analyses can be adapted for use with surface-based analyses. Operating within the framework of the FreeSurfer software package, we have implemented a surface-based version of the cluster size exclusion method used for multiple comparisons correction. Furthermore, we have a developed a new method for generating regions of interest on the cortical surface using a sliding threshold of cluster exclusion followed by cluster growth. Cluster size limits for multiple probability thresholds were estimated using random field theory and validated with Monte Carlo simulation. A prerequisite of RFT or cluster size simulation is an estimate of the smoothness of the data. In order to estimate the intrinsic smoothness of group analysis statistics, independent of true activations, we conducted a group analysis of simulated noise data sets. Because smoothing on a cortical surface mesh is typically implemented using an iterative method, rather than directly applying a Gaussian blurring kernel, it is also necessary to determine the width of the equivalent Gaussian blurring kernel as a function of smoothing steps. Iterative smoothing has previously been modeled as continuous heat diffusion, providing a theoretical basis for predicting the equivalent kernel width, but the predictions of the model were not empirically tested. We generated an empirical heat diffusion kernel width function by performing surface-based smoothing simulations and found a large disparity between the expected and actual kernel widths.

New images from human visual cortex

Recent developments in imaging and histology have greatly clarified our understanding of the nature and organization of human visual cortex. More than ten human cortical visual areas can now be differentiated, compared with the approximately 30 areas described in macaque monkeys. Most human areas and columns described so far appear quite similar to those in macaque but distinctive species differences also exist. Imaging studies suggest two general information-processing streams (parietal and temporal) in human visual cortex, as proposed in macaque. Several human areas are both motion- and direction-selective, and a progression of motion-processing steps can be-inferred from the imaging data. Human visual areas for recognizing form are less well defined but the evidence again suggests a progression of information-processing steps and areas, beginning posterior to the human middle temporal area (or V5), and extending inferiorly then anteriorly. This is consistent with findings from macaque, and with human clinical reports.

Human cortical representations for reaching: Mirror neurons for execution, observation, and imagery

We used functional magnetic resonance imaging (fMRI) to map the cortical representations of executed reaching, observed reaching, and imagined reaching in humans. Whereas previous studies have mostly examined hand actions related to grasping, hand-object interactions, or local finger movements, here we were interested in reaching only (i.e. the transport phase of the hand to a particular location in space), without grasping. We hypothesized that mirror neuron areas specific to reaching-related representations would be active in all three conditions. An overlap between executed, observed, and imagined reaching activations was found in dorsal premotor cortex as well as in the superior parietal lobe and the intraparietal sulcus, in accord with our hypothesis. Activations for observed reaching were more dorsal than activations typically reported in the literature for observation of hand-object interactions (grasping). Our results suggest that the mirror neuron system is specific to the type of hand action performed, and that these fronto-parietal activations are a putative human homologue of the neural circuits underlying reaching in macaques. The parietal activations reported here for executed, imagined, and observed reaching are also consistent with previous functional imaging studies on planned reaching and delayed pointing movements, and extend the proposed localization of human reach-related brain areas to observation as well as imagery of reaching.

Location of human face‐selective cortex with respect to retinotopic areas

Functional Magnetic Resonance Imaging (fMRI) was used to identify a small area in the human posterior fusiform gyrus that responds selectively to faces (PF). In the same subjects, phase‐encoded rotating and expanding checkerboards were used with fMRI to identify the retinotopic visual areas V1, V2, V3, V3A, VP and V4v. PF was found to lie anterior to area V4v, with a small gap present between them. Further recordings in some of the same subjects used moving low‐contrast rings to identify the visual motion area MT. PF was found to lie ventral to MT. In addition, preliminary evidence was found using fMRI for a small area that responded to inanimate objects but not to faces in the collateral sulcus medial to PF. The retinotopic visual areas and MT responded equally to faces, control randomized stimuli, and objects. Weakly face‐selective responses were also found in ventrolateral occipitotemporal cortex anterior to V4v, as well as in the middle temporal gyrus anterior to MT. We conclude that the fusiform face area in humans lies in non‐retinotopic visual association cortex of the ventral form‐processing stream, in an area that may be roughly homologous in location to area TF or CITv in monkeys. Hum. Brain Mapping 7:29–37, 1999.