Showing papers in "Human Brain Mapping in 1994"
TL;DR: In this paper, the authors present a general approach that accommodates most forms of experimental layout and ensuing analysis (designed experiments with fixed effects for factors, covariates and interaction of factors).
Abstract: + Abstract: Statistical parametric maps are spatially extended statistical processes that are used to test hypotheses about regionally specific effects in neuroimaging data. The most established sorts of statistical parametric maps (e.g., Friston et al. (1991): J Cereb Blood Flow Metab 11:690-699; Worsley et al. 119921: J Cereb Blood Flow Metab 12:YOO-918) are based on linear models, for example ANCOVA, correlation coefficients and t tests. In the sense that these examples are all special cases of the general linear model it should be possible to implement them (and many others) within a unified framework. We present here a general approach that accommodates most forms of experimental layout and ensuing analysis (designed experiments with fixed effects for factors, covariates and interaction of factors). This approach brings together two well established bodies of theory (the general linear model and the theory of Gaussian fields) to provide a complete and simple framework for the analysis of imaging data. The importance of this framework is twofold: (i) Conceptual and mathematical simplicity, in that the same small number of operational equations is used irrespective of the complexity of the experiment or nature of the statistical model and (ii) the generality of the framework provides for great latitude in experimental design and analysis.
9,614 citations
TL;DR: This article presents one approach that has been used in functional imaging and shows how the integration within and between functionally specialized areas is mediated by functional or effective connectivity.
Abstract: The brain appears to adhere to two principles of functional organization; junctional segregation and functional intryration. The integration within and between functionally specialized areas is mediated by functional or ejectiue connectioity. The characterization of this sort of connectivity is an important theme in many areas of neuroscience. This article presents one approach that has been used in functional imaging. This article reviews the basic distinction between functional and effective connectivity (as the terms are used in neuroimaging) and their role in addressing several aspects of functional organization (e.g. the topography of distributed systems, integration between cortical areas, time-dependent changes in connectivity and nonlinear interactions). Emphasis is placed on the points of contact between the apparently diverse applications of these concepts and in particular the central role of eigenimages or spatial modes. Although the framework that has been developed is inherently linear, it has been extended to assess nonlinear interactions among cortical areas.
2,270 citations
TL;DR: The results mean that detecting significant activations no longer depends on a fixed threshold, but can be effected at any (lower) threshold, in terms of the spatial extent of the activated region.
Abstract: Current approaches to detecting significantly activated regions of cerebral tissue use statistical parametric maps, which are thresholded to render the probability of one or more activated regions of one voxel, or larger, suitably small (e. g., 0.05). We present an approximate analysis giving the probability that one or more activated regions of a specified volume, or larger, could have occurred by chance. These results mean that detecting significant activations no longer depends on a fixed (and high) threshold, but can be effected at any (lower) threshold, in terms of the spatial extent of the activated region. The substantial improvement in sensitivity that ensues is illustrated using a power analysis and a simulated phantom activation study. © 1994 Wiley-Liss, Inc.
1,936 citations
TL;DR: A method for detecting significant and regionally specific correlations between sensory input and the brain's physiological response, as measured with functional magnetic resonance imaging (MRI), is presented in this paper.
Abstract: A method for detecting significant and regionally specific correlations between sensory input and the brain's physiological response, as measured with functional magnetic resonance imaging (MRI), is presented in this paper. The method involves testing for correlations between sensory input and the hemodynamic response after convolving the sensory input with an estimate of the hernodynamic response function. This estimate is obtained without reference to any assumed input. To lend the approach statistical validity, it is brought into the framework of statistical parametric mapping by using a measure of cross-correlations between sensory input and hemodynamic response that is valid in the presence of intrinsic autocorrelations. These autocorrelations are necessarily present, due to the hemodynamic response function or temporal point spread function.
1,748 citations
TL;DR: It is suggested that neural covariances may be a more accurate way to examine the dynamic functional organization of the central nervous system.
Abstract: The analysis of brain imaging data has recently focused on the examination of the covariances of activity among neural regions during different behaviors. We present some of the theoretical and technical issues surrounding one of these covariance-based methods: structural equation modeling. In structural equation modeling, connections between brain areas are based on known neuroanatomy, and the interregional covariances of activity are used to calculate path coefficients representing the magnitude of the influence of each directional path. The logic behind the use of structural equation modeling stems from the suggestion that brain function is the result of changes in the covariances of activity among neural elements. The technical foundations for neural structural equation models are presented, emphasizing the ability to make inferential comparisons to evaluate the experimental changes in path coefficients. Simulated data sets were used to test the effects of omitted regions and omitted connections. The results suggested that structural modeling algorithms can give hints as to possible external influences and missing paths, but that the final decision as to model modifications requires the guidance of the researcher. The utility of anatomically based models to distinguish between the direct effect of one region on another, and indirect effects of darkness or patterned light on the metabolic activity in the rat visual system. The anatomical framework for the structural equation models revealed that the total impact of ascending thalamocortical influences was modified by corticocortical interactions. Extensions of structural equation modeling to human brain imaging experiments are presented. We conclude by suggesting that neural covariances may be a more accurate way to examine the dynamic functional organization of the central nervous system. ©1994 Wiley-Liss, Inc.
834 citations
TL;DR: These findings corroborate the results of positron emission tomography studies, which suggest that the prefrontal cortex is engaged by tasks that rely on working memory, and demonstrate the applicability of newly developed fMRI techniques using conventional scanners to study the associative cortex in individual subjects.
Abstract: Functional magnetic resonance imaging (fMRI) was used to examine the pattern of activity of the prefrontal cortex during performance of subjects in a nonspatial working memory task. Subjects observed sequences of letters and responded whenever a letter repeated with exactly one nonidentical letter intervening. In a comparison task, subjects monitored similar sequences of letters for any occurrence of a single, prespecified target letter. Functional scanning was performed using a newly developed spiral scan image acquisition technique that provides high-resolution, multislice scanning at approximately five times the rate usually possible on conventional equipment (an average of one image per second). Using these methods, activation of the middle and inferior frontal gyri was reliably observed within individual subjects during performance of the working memory task relative to the comparison task. Effect sizes (2-4%) closely approximated those that have been observed within primary sensory and motor cortices using similar fMRI techniques. Furthermore, activation increased and decreased with a time course that was highly consistent with the task manipulations. These findings corroborate the results of positron emission tomography studies, which suggest that the prefrontal cortex is engaged by tasks that rely on working memory. Furthermore, they demonstrate the applicability of newly developed fMRI techniques using conventional scanners to study the associative cortex in individual subjects. © 1994 Wiley-Liss, Inc.
571 citations
TL;DR: This study investigated the cortical sources of the early components of the pattern‐onset visual evoked potential (VEP) and found the C1 component was found to change its polarity and topography systematically as a function of stimulus position in a manner consistent with the retinotopic organization of the striate cortex.
Abstract: This study investigated the cortical sources of the early (50-250 ms) components of the pattern-onset visual evoked potential (VEP) VEPs were recorded in response to a small circular checkerboard stimulus that was flashed over a range of visual field positions Temporally and spatially overlapping VEP components were distinguished by differences in retinotopic sensitivity and scalp topography, and by inverse dipole modeling The C1 component (50-80 ms) was found to change its polarity and topography systematically as a function of stimulus position in a manner consistent with the retinotopic organization of the striate cortex The P1 component (comprised of the P75 and P100 subcomponents) had a time course that overlapped the C1 but could be distinguished from the C1 by its differing topography and reduced sensitivity to stimulus position The P1 generators were localized to the lateral extrastriate cortex Inverse dipole models were consistent with these striate and extrastriate source locations for the C1 and P1, respectively The N1 component (120-180 ms) was found to originate from several spatially distinct generators that differed in their retinotopic organization © 1995 Wiley-Liss, Inc
562 citations
TL;DR: Results suggest that the left midcingulate region is likely to be part of a neural network activated when one attempts to override a competing verbal response and underscore the important role of the cingulate gyrus in selecting appropriate and suppressing inappropriate verbal responses.
Abstract: The Stroop interference test requires a person to respond to specific elements of a stimulus while suppressing a competing response. Previous positron emission tomography (PET) work has shown increased activity in the right anterior cingulate gyrus during the Stroop test. It is unclear, however, whether the anterior cingulate participates more in the attentional rather than the response selection aspects of the task or whether different interference stimuli might activate different brain regions. We sought to determine (1) whether the Stroop interference task causes increased activation in the right anterior cingulate as previously reported, (2) whether this activation varied as a function of response time, (3) what brain regions were functionally linked to the cingulate during performance of the Stroop, and (4) whether a modified Stroop task involving emotionally distracting words would activate the cingulate and other limbic and paralimbic regions. Twenty-one healthy volunteers were scanned with H215O PET while they performed the Stroop interference test (standard Stroop), a modified Stroop task using distracting words with sad emotional content (sad Stroop), and a control task of naming colors. These were presented in a manner designed to maximize the response selection aspects of the task. Images were stereotactically normalized and analyzed using statistical parametric mapping (SPM). Predictably, subjects were significantly slower during the standard Stroop than the sad Stroop or the control task. The left mideingulate region robustly activated during the standard Stroop compared to the control task. The sad Stroop activated this same region, but to a less significant degree. Correlational regional network analysis revealed an inverse relationship between activation in the left mideingulate and the left insula and temporal lobe. Additionally, activity in different regions of the cingulate gyrus correlated with performance speed during the standard Stroop. These results suggest that the left midcingulate is likely to be part of a neural network activated when one attempts to override a competing verbal response. Finally, the left midcingulate region appears to be functionally coupled to the left insula, temporal, and frontal cortex during cognitive interference tasks involving language. These results underscore the important role of the cingulate gyrus in selecting appropriate and suppressing inappropriate verbal responses. © 1994 Wiley-Liss, Inc.
249 citations
TL;DR: The HBA, even when based only on standard brain surface and central structures, reduced interindividual anatomical variance to the level of the variance in structure position between the right and left hemisphere in individual brains.
Abstract: We present the new computerized Human Brain Atlas (HBA) for anatomical and functional mapping studies of the human brain. The HBA is based on many high-resolution magnetic resonance images of normal subjects and provides continuous updating of the mean shape and position of anatomical structures of the human brain. The structures are transformable by linear and nonlinear global and local transformations applied anywhere in 3-D pictures to fit the anatomical structures of individual brains, which, by reformatting, are transformed into a high-resolution standard anatomical format. The power of the HBA to reduce anatomical variations was evaluated on a randomized selection of anatomical landmarks in brains of 27 young normal male volunteers who were different from those on whom the standard brain was selected. The HBA, even when based only on standard brain surface and central structures, reduced interindividual anatomical variance to the level of the variance in structure position between the right and left hemisphere in individual brains. © 1994 Wiley-Liss, Inc.
245 citations
TL;DR: It is proposed that an important first step for functional studies is to examine accurate, time‐dynamic maps of the brain's electrical fields at the head surface, given an adequate spatial sampling of the surface potentials.
Abstract: Psychological studies with reaction time methodology show that there is meaningful variability in the performance of cognitive operations when responses are measured in milliseconds. Temporal precision is also required to reveal the rapid neurophysiological events in cortical networks. Sampling the brain's electrical activity at the scalp surface characterizes regional brain function with millisecond temporal resolution. The problem with electroencephalographic (EEG) data is localizing the areas of the cortex that generate the observed scalp fields. Although the eventual goal will be to specify the neural generators of the EEG, we propose that an important first step for functional studies is to examine accurate, time-dynamic maps of the brain's electrical fields at the head surface. Given an adequate spatial sampling of the surface potentials, accurate electrical studies require measures that are independent of the location of the reference sensor. The 2D Laplacian of the potential field may be used to define the local features of the scalp current flow. Because the electrical fields are dynamic, brain mapping with electrical data requires animations rather than static images. © 1994 Wiley-Liss, Inc.
220 citations
TL;DR: In this article, changes of local synaptic activity during acquisition of a visuomotor skill were examined with positron emission tomography (PET) imaging of regional cerebral blood flow (rCBF).
Abstract: Changes of local synaptic activity during acquisition of a visuomotor skill were examined with positron emission tomography (PET) imaging of regional cerebral blood flow (rCBF). Eight subject learned the pursuit rotor task, a predictable tracking task, during three sequential PET scans (day 1). Subjects returned 2 days later and repeated the three pursuit trials and PET scans (day 2) after completing an extensive practice session. Control scans without movement bracketed the pursuit trials on both days to rule out time effects unrelated to motor skill learning. PET images were transformed to a common stereotaxic space using matched magnetic resonance imaging (MRI) scans. Group learning effects were determined by a repeated measures multivariate analysis of variance (ANOVA). During motor skill acquisition (day 1), increases of synaptic activity were identified in cortical motor areas and cerebellum, supporting the hypothesis that procedural motor learning occurs in motor execution areas. During long-term practice (day 2), changes were limited to the bilateral putamen, bilateral parietal cortex, and left premotor cortex. To characterize differences in the rate of learning between subjects, each subject's performance data from day 1 was fit with a power function. The exponents were correlated with rCBF data on a pixel-by-pixel basis. Rapid skill acquisition was associated with increasing rCBF in premotor, prefrontal, and cingulate areas, and decreasing rCBF in visual processing areas located in the temporal and occipital cortex. This pattern in fast learners may reflect a more rapid shift from a visually guided strategy (accessing perceptual areas) to an internally generated model (accessing premotor and prefrontal areas). © 1994 Wiley-Liss, Inc.
TL;DR: The results of the SSM analyses suggest that neuropsychiatric disorders may alter functional networks or systems of neural activity in ways that can be expressed as regional covariance patterns in resting functional imaging data.
Abstract: Recent advances in functional neuroimaging have presented a challenge to traditional statistical methods in characterizing the effects of neuropsychiatric illness on brain function. The most common approach for analyzing regional group differences has relied on t-tests with significance thresholds selected to reduce the potential effect of multiple statistical tests. Regional covariance analysis offers an alternative to this threshold-based, group difference approach by identifying the functional interactions among brain regions that can be spatially distributed throughout the brain. The Scaled Subprofile Model (SSM) is one form of regional covariance analysis that has been applied to the study of patient groups. Based on a modified principal component analysis, the SSM offers a method for modeling regionally specific patterns of brain function whose expression can be evaluated between groups and validated against clinical measures of patient disease severity and neuropsychological test scores. We review the application of the SSM, to date, in studies of the effects of neurological and psychiatric illness on brain function, including a discussion of SSM methodology and its application to the study of resting state functional neuroimaging in patient groups. SSM analyses applied to studies of Alzheimer's disease, Parkinson's disease, major depressive disorder, AIDS dementia complex, and neoplastic disease each identified functionally specific topographic effects that were associated with clinical disease severity. The results of the SSM analyses suggest that neuropsychiatric disorders may alter functional networks or systems of neural activity in ways that can be expressed as regional covariance patterns in resting functional imaging data. © 1994 Wiley-Liss, Inc.
TL;DR: It is suggested to brain‐mappers that new discoveries about these language and cognitive functions can be found by imaging those parts of the cerebro‐cerebellar system that evolved uniquely in the human brain, and where to look is indicated.
Abstract: New evidence on the structure and function of the cerebellum, which is summarized in this review, is beginning to clarify the role of the cerebellum in the human brain. The new evidence challenges the traditional concept that the cerebellum serves essentially as a motor mechanism. Instead, a more powerful role is suggested in which the cerebellum contributes to other functions as well, by sending its output to other locations in the cerebral cortex besides the well-known motor areas. Structural evidence about the cerebellar output to such cerebral targets was obtained by using a new anatomical tracing technique on the monkey, which shows that the cerebellum sends a significant projection of nerve fibers to cognitive areas of the prefrontal cortex. Congruent with this anatomical evidence is the neuroimaging evidence obtained on normal human brains, which shows that the cerebellum is strongly activated when the brain performs some cognitive and language functions. Both structurally and functionally, therefore, the cerebellum is underestimated when it is regarded solely as a motor mechanism. Instead, it can be regarded as a more versatile information-processing mechanism whose circuitry carries out two basic processes that are commonly performed by computers: (1) the cerebellar circuitry performs transformations on the streams of information flowing into it, and (2) it distributes the transformed streams to the right places in the brain at the right time. When such processing is performed repeatedly on motor, or cognitive, or language tasks, the cerebellum and its cerebral targets can learn through practice to perform these tasks automatically, thereby improving the speed of performance. This speed is needed, for example, in learning to speak a language fluently because such fluency requires a very rapid selection of words, which can be achieved if the search process for finding the words is performed automatically in the brain. We suggest to brain-mappers that new discoveries about these language and cognitive functions can be found by imaging those parts of the cerebro-cerebellar system that evolved uniquely in the human brain, and we indicate where to look. © 1995 Wiley-Liss, Inc.
TL;DR: PET measures provide a more global view of brain function where neurophysiological data and individual arrays of neural networks give us a very fine‐grained view of the behavior of just a few neurons within nonhumans.
Abstract: Synthetic PET is introduced as a new computational technique for connecting neural network studies based on animal data and image studies of human brain function. Synthetic PET comparisons are taken from a computational model of interacting neural networks in, for example, the monkey brain by integrating synaptic activity in each subnetwork as different simulated tasks are performed. Given a pair of tasks, comparative synaptic activity levels for each modeled neural region are then painted into the homologous regions of a three-dimensional model of the human brain corresponding to the Talairach atlas. The resulting comparison then offers predictions of relative changes of neuronal activity as obtained from PET comparisons of humans performing a similar pair of tasks. Where neurophysiological data and individual arrays of neural networks give us a very fine-grained view of the behavior of just a few neurons within nonhumans, PET measures provide a more global view of brain function. Synthetic PET allows us to integrate human and monkey studies in the construction of more complete models of the neural mechanisms used by both species in similar tasks. The technique is demonstrated in a saccade generation task. The method readily generalizes to other forms of brain imaging. © 1995 Wiley-Liss, Inc.
TL;DR: In this paper, Liss et al. present evidence for a homologous asymmetry in reciprocal connections between V1 and V2 in human cortex using physiological measurements obtained with functional MRI.
Abstract: Reversible cooling experiments in monkey visual cortex have demonstrated that visually driven neuronal activity in V2 depends on feedforward projections from V1, whereas neuronal activity in V1 is modulated by feedback, or reentrant, projections from V2. We present evidence for a homologous asymmetry in reciprocal connections between V1 and V2 in human cortex using physiological measurements obtained with functional MRI. The analysis was based on a nonlinear model of effective connectivity that partitioned the influence that one region exerted over another into an obligatory effect (an effect that depended only on the input) and a modulatory effect (an effect that represented an interaction between input and activity intrinsic to the target region). Using estimates of the modulatory effect we tested two related hypotheses: (1) that V2 would be a major source of modulatory influences on V1; and (2) that the modulatory effects of V2 on V1 would be greater than those of V1 on V2. The first constitutes a hypothesis about the regional or topographic organization of (modulatory) effective connectivity and the second hypothesis directly addresses the functional asymmetry suggested by reversible cooling experiments. The results confirmed that the origins of feedback modulatory effects on V1 were regionally specific and most pronounced in V2. In contrast, feedforward modulatory influences on V1 on V2 were negligible. This apparent asymmetry between feedforward and feedback modulatory interactions was evident in both hemispheres and appears to be a fairly robust feature of nonlinear interactions between striate and extrastriate cortex. © 1995 Wiley‐Liss, Inc. Copyright © 1995 Wiley‐Liss, Inc.
TL;DR: Localized brain activation in response to moving visual stimuli was studied by functional magnetic resonance imaging (fMRI) using 100 small white dots randomly arranged on a visual display.
Abstract: Localized brain activation in response to moving visual stimuli was studied by functional magnetic resonance imaging (fMRI). Stimuli were 100 small white dots randomly arranged on a visual display. During the Motion condition, the dots moved along random, noncoherent linear trajectories at different velocities. During the Blink condition, the dots remained stationary but blinked on and off every 500 ms. The Motion and Blink conditions continuously alternated with 10 cycles per run and 6–8 runs per experiment. In half of the runs, the starting stimulus condition was Motion, while in the remaining runs it was Blink.
A series of 128 gradient echo echoplanar images were acquired from 5–7 slices during each run using a 1.5 T GE Signa with an Advanced NMR echoplanar subsystem. The time series for each voxel were analyzed in the frequency domain. Voxels which demonstrated a significant spectral peak at the alternation frequency and whose phase changed in response to stimulus order were considered activated. These activated voxels were displayed upon high resolution anatomical images to determine the sites of activation and were also transformed into the coordinates of Talairach and Tournoux ([1988] Co-planar Stereotaxic Atlas of the Human Brain, New York: Thieme) for comparison to prior neuroimaging studies.
Seven of ten subjects showed clusters of activation bilaterally at the junction of the temporal and occipital lobes (area 37) in response to moving stimuli. Most activated voxels were located within or adjacent to a region designated the parietal-temporal-occipital fossa, or PTOF. Five subjects also showed activation to moving stimuli in midline occipital cortex. The activated voxels in midline cortex had a significantly shorter phase delay in their MR signal change relative to voxels in PTOF. © 1995 Wiley-Liss, Inc.1
TL;DR: This article used functional magnetic resonance imaging (FMRI) to examine the neuroanatomic loci of lexical-semantic as opposed to phonological processing, and found that semantic processing makes demands on, and activates widespread areas within, brain including the inferior frontal regions bilaterally and the left posterior temporal region.
Abstract: The relationship between the functional components of language and the anatomic foci of their neural systems represents a central issue in cognitive neuroscience. Conflicting results from a number of laboratories using positron emission tomography (PET) imaging techniques have led to a significant controversy over the specific neuroanatomic sites engaged by semantic processing. We report here results of an experiment designed to address this controversy, that is, whether semantic processing activates temporal and/or frontal brain regions. In this experiment we used cognitive tasks that emphasized either semantic or phonological information processing but that were similar on both memory search and responce generation components, together with functional magnetic resonance imaging, to examine the neuroanatomic loci of lexical-semantic as opposed to phonological processing. We studied nine right-handed men performing two silent generation tasks: rhyme, and semantic category. The former focuses on word form (phonological information) while the latter focuses on word meaning (semantic information). By “phonological” we mean the process of apprehending the sound structures of language. By “semantic” we mean information about the word's contextually specified meanings. Semantic processing makes demands on, and activates widespread areas within, brain including the inferior frontal regions bilaterally and the left posterior temporal region. Phonological processing engages a more restricted neuroanatomic assembly involving primarily anterior left temporal lobe sites. © 1995 Wiley-Liss, Inc.
TL;DR: There are ample reasons to link functional neuroimaging and neural modeling, and it is suggested that combining the results from the two disciplines will result in furthering the authors' understanding of the central nervous system.
Abstract: Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America.
TL;DR: Structural equation modeling was used to examine functional interactions between cortical and subcortical motor areas in Parkinson's disease patients and normal subjects and found significant reductions in the strength of interactions between the globus pallidus projection to thalamus, and the thalus, projection to mesial frontal motor areas, consistent with the presumed physiologic interactions of these areas.
Abstract: Structural equation modeling was used to examine functional interactions between cortical and subcortical motor areas in Parkinson's disease patients and normal subjects. Neuronal activity was defined by positron emission tomography (PET) imaging of regional cerebral blood flow (rCBF) during performance of movement and control tasks. Patients were scanned before and 8-12 weeks after stereotactic unilateral left posterovental globus pallidotomy. Pallidotomy attenuates basal ganglion inhibition of thalamocortical neurons involved in motor control and reduces the severity of bradykinesia in Parkinson's disease patients. It was hypothesized that with surgery there would be a similar alteration in thalamocortical interactions as measured with PET rCBF. A path analysis model of cortical and basal ganglia circuitry (defined by anatomic and electrophysiologic connectivity) was used to estimate unidirectional path coefficients describing the magnitude of region to region interactions. The resultant interactions defined a composite task-and disease-specific functional network of connectivity. After pallidotomy, there were significant reductions in the strength of interactions between the globus pallidus projection to thalamus, and the thalamus, projection to mesial frontal motor areas, consistent with the presumed physiologic interactions of these areas. This modeling approach can identify regional interactions that are not always apparent in categorical comparisons of inmaging data. ©1994 Wiley-Liss, Inc.
TL;DR: Two primary data analysis techniques are used with functional neuroimaging data: the subtraction paradigm and the covariance paradigm, which assumes that tasks are mediated by networks of interacting regions and that different tasks involve differences in the pattern of functional connections among brain regions.
Abstract: Two primary data analysis techniques are used with functional neuroimaging data: the subtraction paradigm and the covariance paradigm. The first is based on the assumption that a brain region participating in a specific task should show altered neural activity (relative to a control task). The second, which is not mutually contradictory with the first, assumes that tasks are mediated by networks of interacting regions and that different tasks involve differences in the pattern of functional connections among brain regions. The neurobiological assumptions governing each paradigm and the kinds of questions each seeks to address are discussed. Illustrations of each technique using positron emission tomographic data of a blood flow study of visual processing are given. The use of neural modeling techniques for analyzing functional neuroimaging data is also discussed, with explicit reference to such systems-level approaches as structural equation modeling. © 1994 Wiley-Liss, Inc.
TL;DR: These data, obtained using a within‐subject design, extend previously reported findings that used mixed within‐and between‐subject designs and demonstrate important functional components of normal auditoryverbal short‐term memory.
Abstract: The functional neuroanatomy of verbal memory was investigated using verbal free recall during H2 (15) O positron emission tomography (PET). Twelve young (25-40 years old) normal control subjects participated in eight scans during a single scanning session during which they performed three memory tasks differing by word list length. Four subjects also had scans during a "rest" condition. Temporal lobe activation was observed during all tasks, including single-word repetition. The frontal cortices, specifically Brodmann areas 9 and 10, were activated only when the recall word lists exceeded the memory spans (i. e., 12 and 15 words). Activation was also observed in the anterior cingulate cortex (BA24 and BA32). These data, obtained using a within-subject design, extend previously reported findings that used mixed within-and between-subject designs and demonstrate important functional components of normal auditoryverbal short-term memory. © 1994 Wiley-Liss, Inc.
TL;DR: FMRI was used to record cortical activation across multiple stages in the visual system during single character visual search and reversing checkerboard stimulation, and issues relating to fMRI signal variability across the imagining plane, statistical data analysis, signal sensitivity, statistical power, fMRI experimental protocols, and comparisons with positron emission tomography (PET) data are discussed.
Abstract: Functional magnetic resonance imaging (fMRI) was used to record cortical activation across multiple stages in the visual system during single character visual search and reversing checkerboard stimulation. Scanning used T2-weighted, gradient echo sequences with late echo times (TE = 36 ms) with a voxel size of 0.94 * 1.88 mm in-plane resolution, 4–5 mm deep, on a conventional scanner. A scout experiment recorded six slices to identify major regions of activation. Two slices were selected for extensive assessment. Character stimuli activated small (average 16 mm2), reliable, statistically defined regions of activation in the calcarine fissure, superior occipital cortex, and fusiform-lingual gyrus. The results include: (1) for character search, the MRI signal change increased linearly from 2.1 to 3.1% for stimulation from 1 to 8 Hz; (2) the character rate effect was equivalent across three levels of the visual system; (3) the checkerboard stimuli showed broader, more intense primary visual activation and less intense secondary visual activation than did character search. Issues relating to fMRI signal variability across the imagining plane, statistical data analysis, signal sensitivity, statistical power, fMRI experimental protocols, and comparisons with positron emission tomography (PET) data are discussed. © 1994 Wiley-Liss, Inc.
TL;DR: The data suggest that, in addition to damage of the efferent cortico‐spinal or afferent somatosensory tract, impairment of other circuits may contribute to the severe hemiparesis initially observed after stroke.
Abstract: Depressions of regional cerebral glucose metabolism (rCMRGlu) as measured with positron emission tomography in 28 patients with first hemiparetic stroke were mapped anatomically and related to the involvement of the cortico-spinal tract and the somatosensory pathway. Cortico-spinal tract and somatosensory pathway status were examined by magnetic evoked motor potentials (MEP) and somatosensory evoked potentials (SSEP), respectively. Patients were grouped with respect to the stroke lesions as assessed by magnetic resonance images into striatocapsular, thalamocapsular, and corticosubcortical groups. In spite of identical clinical presentation, the topography of significant remote rCMRGlu depressions varied in the affected cerebral hemisphere among the three groups, involving also the contralateral hemisphere in the thalamocapsular and cortico-subcortical group. The thalamus was the only area with a significant mean rCMRGlu depression in all groups, although it was structurally spared in striatocapsular and cortico-subcortical strokes. The remote rCMRGlu depressions in the primary sensorimotor cortex were associated with significantly abnormal MEPs in striatocapsular stroke, while both the MEPs and SSEPs were significantly abnormal in the cortico-subcortical group. Further, depressed rCMRGlu in the putamen of the lesion side and in the cerebellar hemisphere ipsilateral to the hemiparesis correlated with motor impairment. Our data suggest that, in addition to damage of the efferent cortico-spinal or afferent somatosensory tract, impairment of other circuits may contribute to the severe hemiparesis initially observed after stroke. We hypothesize that the chronic remote rCMRGlu depressions described in the present study result from axonal damage interfering with connectivity patterns. © 1994 Wiley-Liss, Inc.
TL;DR: The hypothesis that auditory attention can exert a selective control over the sensory processing of acoustic stimuli in tonotopic auditory cortex at an early stage of sensory processing is supported, even in low attentional load conditions.
Abstract: This study reinvestigates some aspects of the neurophysiological mechanisms of auditory selective attention, by testing the hypothesis that auditory attention can exert a selective control over the sensory processing of acoustic stimuli in tonotopic auditory cortex. Event-related potentials (ERPs) were recorded from human subjects while they listened selectively to a tone sequence in one ear and ignored a concurrent sequence of a different frequency in the opposite ear. The tone frequencies were 500, 1,000, 2,000, or 4,000 Hz in separate sequences, and were delivered at a constant rate of one every 800 ms. The effects of attention were analyzed in the difference waves obtained by subtracting ERPs to ignore tones from those of the same tones when attended. The earliest effect of attention (70–80 ms post-stimulus) was found to present the same spatio-temporal organization as the obligatory, sensory-evoked N1 wave, with similar tonotopic changes in scalp distribution with the tone frequencies. At longer latencies, two other attentional effects were observed, of probable endogenous origin: one around 175 ms post-stimulus, possibly originating from non-tonotropic auditory cortex, and the latest one (after 300 ms) from non-specific areas. The results support the hypothesis of a genuine sensory gating mechanism for auditory attention, taking place in tonotopic auditory cortex at an early stage of sensory processing, even in low attentional load conditions. © 1995 Wiley-Liss, Inc.
TL;DR: This analysis supports the hypothesis that auditory learning is an emergent network property, distributed among connected brain regions showing specific patterns of interaction, and quantifies the interactions among neural regions in terms of networks.
Abstract: If learning is an emergent property of interacting brain regions, understanding it requires a network analysis of the patterns of interaction between brain regions. Brain mapping techniques have the potential of providing information about functional interactions within entire neural systems, but computational methods are needed to make sense of the complex interactions that take place in the brain. This review paper illustrates, with examples from auditory learning studies, the application of a computational method that quantifies the interactions among neural regions in terms of networks, and what is gained from this approach. The method is Structural Equation Modeling, and it computes network interactions by combining anatomical circuitry with the covariation in the activity between auditory structures. Activity was assessed by fluorodeoxyglucose uptake, and the functional strengths of auditory pathways were quantified by computing path coefficients representing the strength of the functional influence through each anatomical path. Changes in these values were used as indices of how learned information was processed and modified within the auditory system. Structural models of the auditory system revealed the patterns of network interactions related to habituation to a sound, as well as the patterns related to the opposite learned associative properties of the same sound. They illustrated how the functional interactions among parallel auditory neural pathways were modified as a result of auditory learning. This analysis supports the hypothesis that auditory learning is an emergent network property, distributed among connected brain regions showing specific patterns of interaction. ©1994 Wiley-Liss, Inc.
TL;DR: A technique for magnetic resonace imaging (MRI) positron emission tomography (PET) coregistration and the optimization of PET slice orientation that enhances and complements existing techniques is reported and validated.
Abstract: We report and validate a technique for magnetic resonace imaging (MRI) positron emission tomography (PET) coregistration and the optimization of PET slice orientation that enhances and complements existing techniques. The technique depends on an external fiducial system and on software that models the relationship of the PET gantry with respect to a three-dimensional (3D) MR reconstruction of each subject's brain anatomy. The technique offers the possibility of using individual neuroanatomical information to plan PET activation studies. Estimated 3D errors average 3 mm in [15O]H2O PET activation studies. In-plane interinjection movement averages less than 1 mm. The resulting MRI-PET coregistration provides a basis for bringing neuroanatomical information to bear on a number of issues critical for the interpretation of functional imaging studies. © 1995 Wiley-Liss, Inc.
TL;DR: This work proposes some new techniques to enhance detection sensitivity in the analysis of brain activation maps by using a multi‐filtering strategy and the use of a hierarchical decomposition.
Abstract: Low signal-to-noise ratio is the fundamental limit of current voxel-based strategies for detecting activations in functional brain maps. We propose some new techniques to enhance detection sensitivity in the analysis of brain activation maps. These new techniques are: (1) a multi-filtering strategy; and (2) the use of a hierarchical decomposition. Multi-filtering is used to optimize detection sensitivity when multiple signals of various sizes are present, while hierarchical decomposition allows selection of activation foci on the basis of their spatial extent and magnitude. Both techniques are combined within a single testing procedure that contrals the overall type I error. This approach shows significantly higher detectioin sensitivity on both simulated and experimental single-subject datasets. ©1994 Wiley-Liss, Inc.
TL;DR: Obsessive‐compulsive patients had significantly higher relative cerebral perfusion in medial‐frontal and right frontal cortex and in cerebellum, and significantly reduced perfusions in right visual association cortex, and Increased frontal Perfusion agrees with several prior reports.
Abstract: Locations of cerebral perfusion abnormalities in obsessive-compulsive disorder (OCD) were mapped with single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI). This report is a new, more thorough analysis of a previous study of these subjects that used region-of-interest methods. Ten obsessive-compulsive patients and seven age- and sex-matched control subjects were studied. Image sets were converted into stereotaxic space, normalized to each subject's mean cerebral value, then group averaged. Difference images were calculated and searched for regions with significant between-group cerebral perfusion differences. Obsessive-compulsive patients had significantly higher relative cerebral perfusion in medial-frontal and right frontal cortex and in cerebellum, and significantly reduced perfusion in right visual association cortex. Increased frontal Perfusion agrees with several prior reports. The caudate nucleus, which has been controversial in neuroimaging studies of OCD, did not display a difference between groups. The results of this study provide information about the locations and extents of cerebral perfusion abnormalities in OCD. Regional abnormalities were compared with those reported in prior functional neuroimaging studies. Issues related to OCD hyperfrontality and frontal lateralization of psychopathology are discussed. Normal caudate nucleus findings are considered in relation to prior functional imaging studies and hypotheses of OCD pathology. © 1994 Wiley-Liss, Inc.