Barry Horwitz

The functional organization of human extrastriate cortex: a PET-rCBF study of selective attention to faces and locations

The functional dissociation of human extrastriate cortical processing streams for the perception of face identity and location was investigated in healthy men by measuring visual task-related changes in regional cerebral blood flow (rCBF) with positron emission tomography (PET) and H2(15)O. Separate scans were obtained while subjects performed face matching, location matching, or sensorimotor control tasks. The matching tasks used identical stimuli for some scans and stimuli of equivalent visual complexity for others. Face matching was associated with selective rCBF increases in the fusiform gyrus in occipital and occipitotemporal cortex bilaterally and in a right prefrontal area in the inferior frontal gyrus. Location matching was associated with selective rCBF increases in dorsal occipital, superior parietal, and intraparietal sulcus cortex bilaterally and in dorsal right premotor cortex. Decreases in rCBF, relative to the sensorimotor control task, were observed for both matching tasks in auditory, auditory association, somatosensory, and midcingulate cortex. These results suggest that, within a sensory modality, selective attention is associated with increased activity in those cortical areas that process the attended information but is not associated with decreased activity in areas that process unattended visual information. Selective attention to one sensory modality, on the other hand, is associated with decreased activity in cortical areas dedicated to processing input from other sensory modalities. Direct comparison of our results with those from other PET-rCBF studies of extrastriate cortex demonstrates agreement in the localization of cortical areas mediating face and location perception and dissociations between these areas and those mediating the perception of color and motion.

The elusive concept of brain connectivity

Neurons and neural populations do not function as islands onto themselves. Rather, they interact with other such elements through their afferent and efferent connections in an orchestrated manner so as to enable different sensorimotor and cognitive tasks to be performed. The concept of functional connectivity and the allied notion of effective connectivity were introduced to designate the functional strengths of such interactions. Functional neuroimaging methods, especially PET and fMRI, have been used extensively to evaluate the functional connectivity between different brain regions. After providing a brief historical review of these notions of brain connectivity, I argue that the conceptual formulations of functional and effective connectivity are far from clear. Specifically, the terms functional and effective connectivity are applied to quantities computed on types of functional imaging data (e.g., PET, fMRI, EEG) that vary in spatial, temporal, and other features, using different definitions (even for data of the same modality) and employing different computational algorithms. Until it is understood what each definition means in terms of an underlying neural substrate, comparisons of functional and/or effective connectivity across studies may appear inconsistent and should be performed with great caution.

Longitudinal study of the early neuropsychological and cerebral metabolic changes in dementia of the Alzheimer type

To examine the progression of neuropsychologic and metabolic changes in the early stages of dementia of the Alzheimer type (DAT), we studied 11 midly demented patients longitudinally. Three aspects of neuropsychological function were measured: memory, attention to complex sets and abstract reasoning, and lateralized functions, i.e., language and visuoconstruction. Regional cerebral metabolic rates for glucose were measured in frontal, parietal, and temporal association cortices. Our results show that, in general, memory deficits are the first neuropsychological impairments to occur in DAT, followed by problems with attention to complex cognitive sets and abstract reasoning, which are followed in turn by deficits in language and visuospatial abilities. In addition, neocortical metabolic abnormalities usually precede impairment of neocortically mediated attention and abstract reasoning by 8 to 16 months, and precede impairment of neocortically mediated language and visuospatial function by 12 to 37 months. These findings suggest that the first nonmnestic neuropsychological consequence of neocortical physiological dysfunction in DAT is a loss of attentional capacity. Since neocortical metabolic changes generally precede the appearance of neocortically mediated neuropsychological dysfunction, physiologic dysfunction may exist for some time before cognition is affected.

Method for quantification of brain, ventricular, and subarachnoid CSF volumes from MR images

We describe a simple, rapid, and semiautomated method of MR analysis based on mathematical modeling of MR pixel intensity histograms. The method is shown to be accurate and reliable for regional analysis of brain, central, and subarachnoid CSF volumes. Application of the method to five young and six older subjects revealed significant age-related changes in regional brain volumes whereas no difference was found for traced central CSF volumes or subarachnoid CSF volumes. We conclude that this is a simple method that can be applied to further studies of quantification of brain structure in healthy aging and brain disease.

Regional brain activity when selecting a response despite interference: An H2 15O PET study of the stroop and an emotional stroop

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.

How Good Is Good Enough in Path Analysis of fMRI Data

This paper is concerned with the problem of evaluating goodness-of-fit of a path analytic model to an interregional correlation matrix derived from functional magnetic resonance imaging (fMRI) data. We argue that model evaluation based on testing the null hypothesis that the correlation matrix predicted by the model equals the population correlation matrix is problematic because P values are conditional on asymptotic distributional results (which may not be valid for fMRI data acquired in less than 10 min), as well as arbitrary specification of residual variances and effective degrees of freedom in each regional fMRI time series. We introduce an alternative approach based on an algorithm for automatic identification of the best fitting model that can be found to account for the data. The algorithm starts from the null model, in which all path coefficients are zero, and iteratively unconstrains the coefficient which has the largest Lagrangian multiplier at each step until a model is identified which has maximum goodness by a parsimonious fit index. Repeating this process after bootstrapping the data generates a confidence interval for goodness-of-fit of the best model. If the goodness of the theoretically preferred model is within this confidence interval we can empirically say that the theoretical model could be the best model. This relativistic and data-based strategy for model evaluation is illustrated by analysis of functional MR images acquired from 20 normal volunteers during periodic performance (for 5 min) of a task demanding semantic decision and subvocal rehearsal. A model including unidirectional connections from frontal to parietal cortex, designed to represent sequential engagement of rehearsal and monitoring components of the articulatory loop, is found to be irrefutable by hypothesis-testing and within confidence limits for the best model that could be fitted to the data.

Age-Related Changes in Regional Cerebral Blood Flow during Working Memory for Faces ☆

Young and old adults underwent positron emission tomography during the performance of a working memory task for faces (delayed match-to-sample), in which the delay between the sample and choice faces was varied from 1 to 21 s. Reaction time was slower and accuracy lower in the old group, but not markedly so. Values of regional cerebral blood flow (rCBF) were analyzed for sustained activity across delay conditions, as well as for changes as delay increased. Many brain regions showed similar activity during these tasks in both young and old adults, including left anterior prefrontal cortex, which had increased rCBF with delay, and ventral extrastriate cortex, which showed decreased rCBF with delay. However, old adults had less activation overall and less modulation of rCBF across delay in right ventrolateral prefrontal cortex than did the young adults. Old adults also showed greater rCBF activation in left dorsolateral prefrontal cortex across all WM delays and increased rCBF at short delays in left occipitoparietal cortex compared to young adults. Activity in many of these regions was differentially related to performance in that it was associated with decreasing response times in the young group and increasing response times in the older individuals. Thus despite the finding that performance on these memory tasks and associated activity in a number of brain areas are relatively preserved in old adults, differences elsewhere in the brain suggest that different strategies or cognitive processes are used by the elderly to maintain memory representations over short periods of time.

Intercorrelations of Glucose Metabolic Rates between Brain Regions: Application to Healthy Males in a State of Reduced Sensory Input

We use a correlational analysis of regional metabolic rates to characterize relations among different brain regions. Starting with rates of local glucose metabolism (rCMRglc) obtained by positron emission tomography using [18F]fluorodeoxyglucose, we propose that pairs of brain regions whose rCMRglc values are significantly correlated are functionally associated, and that the strength of the association is proportional to the magnitude of the correlation coefficient. Partial correlation coefficients, controlling for whole brain glucose metabolism, are used in the analysis. We also introduce a graphical technique to display simultaneously all the correlations, allowing us to examine patterns of relations among them. The method was applied to 40 very healthy males under conditions of reduced auditory and visual inputs (the “resting state”). Dividing the brain into 59 regions, and keeping only those partial correlation coefficients significant to p < 0.01, we found the following: (a) All regions were significantly correlated with their contralateral homologues. For the most part, the largest partial correlation coefficients were between homologous brain regions. (b) Generally, the pattern of significant correlations between any two lobes in the left hemisphere did not differ statistically from the corresponding pattern in the right hemisphere. (c) Strong correlations were observed between primary somatosensory areas and premotor association areas. Correlations between these association areas and primary visual and auditory regions were not statistically significant. (d) Significant correlations between inferior occipital and temporal areas were found. Metabolic rates in the superior part of the occipital lobe were not correlated significantly with metabolic rates in regions of the temporal lobe, nor with metabolism in the parietal lobe. (e) As a whole, there were numerous correlations among frontal and parietal lobe regions, on the one hand, and among temporal and occipital lobe regions, on the other, but few statistically significant correlations between these two domains. We relate our results to various aspects of known brain anatomy, physiology, and cognitive functioning.

Neural modeling, functional brain imaging, and cognition

The richness and complexity of data sets acquired from PET or fMRI studies of human cognition have not been exploited until recently by computational neural-modeling methods. In this article, two neural-modeling approaches for use with functional brain imaging data are described. One, which uses structural equation modeling, estimates the functional strengths of the anatomical connections between various brain regions during specific cognitive tasks. The second employs large-scale neural modeling to relate functional neuroimaging signals in multiple, interconnected brain regions to the underlying neurobiological time-varying activities in each region. Delayed match-to-sample (visual working memory for form) tasks are used to illustrate these models.

Functional interactions of the inferior frontal cortex during the processing of words and word-like stimuli.

The hypothesis that ventral/anterior left inferior frontal gyrus (LIFG) subserves semantic processing and dorsal/posterior LIFG subserves phonological processing was tested by determining the pattern of functional connectivity of these regions with regions in left occipital and temporal cortex during the processing of words and word-like stimuli. In accordance with the hypothesis, we found strong functional connectivity between activity in ventral LIFG and activity in occipital and temporal cortex only for words, and strong functional connectivity between activity in dorsal LIFG and activity in occipital and temporal cortex for words, pseudowords, and letter strings, but not for false font strings. These results demonstrate a task-dependent functional fractionation of the LIFG in terms of its functional links with posterior brain areas.