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Barry Horwitz

Publications and source records attributed to Barry Horwitz.

At least 19 recordsLinked to original sources
PubMed2006

Experimental-neuromodeling framework for understanding auditory object processing: integrating data across multiple scales.

In this article, we review a combined experimental-neuromodeling framework for understanding brain function with a specific application to auditory object processing. Within this framework, a model is constructed using the best available experimental data and is used to make predictions. The predictions are verified by conducting specific or directed experiments and the resulting data are matched with the simulated data. The model is refined or tested on new data and generates new predictions. The predictions in turn lead to better-focused experiments. The auditory object processing model was constructed using available neurophysiological and neuroanatomical data from mammalian studies of auditory object processing in the cortex. Auditory objects are brief sounds such as syllables, words, melodic fragments, etc. The model can simultaneously simulate neuronal activity at a columnar level and neuroimaging activity at a systems level while processing frequency-modulated tones in a delayed-match-to-sample task. The simulated neuroimaging activity was quantitatively matched with neuroimaging data obtained from experiments; both the simulations and the experiments used similar tasks, sounds, and other experimental parameters. We then used the model to investigate the neural bases of the auditory continuity illusion, a type of perceptual grouping phenomenon, without changing any of its parameters. Perceptual grouping enables the auditory system to integrate brief, disparate sounds into cohesive perceptual units. The neural mechanisms underlying auditory continuity illusion have not been studied extensively with conventional neuroimaging or electrophysiological techniques. Our modeling results agree with behavioral studies in humans and an electrophysiological study in cats. The results predict a particular set of bottom-up cortical processing mechanisms that implement perceptual grouping, and also attest to the robustness of our model.

Acoustic Stimulation↗
PubMed2006

Frontal cortex functional connectivity changes during sound categorization.

Using functional connectivity analysis of functional magnetic resonance imaging data, we investigated the role of the inferior frontal gyrus in categorization of simple sounds. We found stronger functional connectivity between left inferior frontal gyrus and auditory processing areas in the temporal cortex during categorization of speech (vowels, syllables) and nonspeech (tones, combinations of tones and sweeps) sounds relative to an auditory discrimination task; the hemispheric lateralization varied depending on the speech-like properties of the sounds. Our results attest to the importance of interactions between temporal cortex and left inferior frontal gyrus in sound categorization. Further, we found different functional connectivity patterns between left inferior frontal gyrus and other brain regions implicated in categorization of syllables compared with other stimuli, reflecting the greater facility for categorization of syllables.

Acoustic Stimulation↗
PubMed2006

Large-scale neural models and dynamic causal modelling.

Dynamic causal modelling (DCM) is a method for estimating and making inferences about the coupling among small numbers of brain areas, and the influence of experimental manipulations on that coupling [Friston, K.J., Harrison, L., Penny, W., 2003 Dynamic causal modelling. Neuroimage 19, 1273-1302]. Large-scale neural modelling aims to construct neurobiologically grounded computational models with emergent behaviours that inform our understanding of neuronal systems. One such model has been used to simulate region-specific BOLD time-series [Horwitz, B., Friston, K.J., Taylor, J.G., 2000. Neural modeling and functional brain imaging: an overview. Neural Netw. 13, 829-846]. DCM was used to make inferences about effective connectivity using data generated by a model implementing a visual delayed match-to-sample task [Tagamets, M.A., Horwitz, B., 1998. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cereb. Cortex 8, 310-320]. The aim was to explore the validity of inferences made using DCM about the connectivity structure and task-dependent modulatory effects, in a system with a known connectivity structure. We also examined the effects of misspecifying regions of interest. Models with hierarchical connectivity and reciprocal connections were examined using DCM and Bayesian Model Comparison [Penny, W.D., Stephan, K.E., Mechelli, A., Friston, K.J., 2004. Comparing dynamic causal models. Neuroimage 22, 1157-1172]. This approach revealed strong evidence for those models with correctly specified anatomical connectivity. Furthermore, Bayesian model comparison favoured those models when bilinear effects corresponded to their implementation in the neural model. These findings generalised to an extended model with two additional areas and reentrant circuits. The conditional uncertainty of coupling parameter estimates increased in proportion to the number of incorrectly specified regions. These results highlight the role of neural models in establishing the validity of estimation and inference schemes. Specifically, Bayesian model comparison confirms the validity of DCM in relation to a well-characterised and comprehensive neuronal model.

Bayes Theorem↗
PubMed2006

Neural bases of categorization of simple speech and nonspeech sounds.

Categorization is fundamental to our perception and understanding of the environment. However, little is known about the neural bases underlying the categorization of sounds. Using human functional magnetic resonance imaging (fMRI) we compared the brain responses to a category discrimination task with an auditory discrimination task using identical sets of sounds. Our stimuli differed along two dimensions: a speech-nonspeech dimension and a fast-slow temporal dynamics dimension. All stimuli activated regions in the primary and nonprimary auditory cortices in the temporal cortex and in the parietal and frontal cortices for the two tasks. When comparing the activation patterns for the category discrimination task to those for the auditory discrimination task, the results show that a core group of regions beyond the auditory cortices, including inferior and middle frontal gyri, dorsomedial frontal gyrus, and intraparietal sulcus, were preferentially activated for familiar speech categories and for novel nonspeech categories. These regions have been shown to play a role in working memory tasks by a number of studies. Additionally, the categorization of nonspeech sounds activated left middle frontal gyrus and right parietal cortex to a greater extent than did the categorization of speech sounds. Processing the temporal aspects of the stimuli had a greater impact on the left lateralization of the categorization network than did other factors, particularly in the inferior frontal gyrus, suggesting that there is no inherent left hemisphere advantage in the categorical processing of speech stimuli, or for the categorization task itself.

Acoustic Stimulation↗
PubMed2005

Systems level modeling of a neuronal network subserving intrinsic alertness.

Cognitive control of alertness in unwarned situations (intrinsic alertness) relies on a predominantly right hemisphere cortical and subcortical network. In a previous functional activation study, we have demonstrated that this network comprises the anterior cingulate gyrus, the dorsolateral and polar frontal as well as the inferior parietal cortex, the thalamus and ponto-mesencephalic parts of the brain stem. The aim of this study was to study effective connectivity of this network by employing structural equation modeling. Fifteen right-handed male subjects participated in the PET study. The functional network showed stronger connectivity in the right hemisphere. Furthermore, there were strong effective connections between thalamus and brainstem on the one hand and between thalamus and anterior cingulate on the other. Our results suggest that the anterior cingulate functions as the central coordinating structure for the right hemispheric neural network of intrinsic alertness and that the anterior cingulate gyrus is modulated mainly by prefrontal and parietal cortex.

Adult↗
PubMed2005

Discrimination and categorization of speech and non-speech sounds in an MEG delayed-match-to-sample study.

We investigated the perception and categorization of speech (vowels, syllables) and non-speech (tones, tonal contours) stimuli using MEG. In a delayed-match-to-sample paradigm, participants listened to two sounds and decided if they sounded exactly the same or different (auditory discrimination, AUD), or if they belonged to the same or different categories (category discrimination, CAT). Stimuli across the two conditions were identical; the category definitions for each kind of sound were learned in a training session before recording. MEG data were analyzed using an induced wavelet transform method to investigate task-related differences in time-frequency patterns. In auditory cortex, for both AUD and CAT conditions, an alpha (8-13 Hz) band activation enhancement during the delay period was found for all stimulus types. A clear difference between AUD and CAT conditions was observed for the non-speech stimuli in auditory areas and for both speech and non-speech stimuli in frontal areas. The results suggest that alpha band activation in auditory areas is related to both working memory and categorization for new non-speech stimuli. The fact that the dissociation between speech and non-speech occurred in auditory areas, but not frontal areas, points to different categorization mechanisms and networks for newly learned (non-speech) and natural (speech) categories.

Acoustic Stimulation↗
PubMed2005

Investigating the neural basis for functional and effective connectivity. Application to fMRI.

Viewing cognitive functions as mediated by networks has begun to play a central role in interpreting neuroscientific data, and studies evaluating interregional functional and effective connectivity have become staples of the neuroimaging literature. The neurobiological substrates of functional and effective connectivity are, however, uncertain. We have constructed neurobiologically realistic models for visual and auditory object processing with multiple interconnected brain regions that perform delayed match-to-sample (DMS) tasks. We used these models to investigate how neurobiological parameters affect the interregional functional connectivity between functional magnetic resonance imaging (fMRI) time-series. Variability is included in the models as subject-to-subject differences in the strengths of anatomical connections, scan-to-scan changes in the level of attention, and trial-to-trial interactions with non-specific neurons processing noise stimuli. We find that time-series correlations between integrated synaptic activities between the anterior temporal and the prefrontal cortex were larger during the DMS task than during a control task. These results were less clear when the integrated synaptic activity was haemodynamically convolved to generate simulated fMRI activity. As the strength of the model anatomical connectivity between temporal and frontal cortex was weakened, so too was the strength of the corresponding functional connectivity. These results provide a partial validation for using fMRI functional connectivity to assess brain interregional relations.

Auditory Perception↗
PubMed2005

Integrating neuroscientific data across spatiotemporal scales.

A major challenge confronting neuroscientists is associated with the multiple spatial and temporal scales of investigation of neural structure and function. I shall discuss the use of computational neural modeling as one method to bridge some of the different spatial and temporal levels. This approach will be illustrated using large-scale, neurobiologically realistic network models of auditory and visual pattern recognition that relate neuronal dynamics to fMRI data. It will be demonstrated that the models are capable of exhibiting the salient features of both electrophysiological neuronal activities and fMRI values that are in agreement with empirically observed data.

Animals↗
PubMed2005

Investigating the neural basis of the auditory continuity illusion.

In this study, we investigated one type of auditory perceptual grouping phenomena--the auditory continuity illusion (also called temporal induction). We employed a previously developed, neurobiologically realistic, large-scale neural network model of the auditory processing pathway in the cortex, ranging from the primary auditory cortex to the prefrontal cortex, and simulated temporal induction without changing any model parameters. The model processes tonal contour stimuli, composed of combinations of upward and downward FM sweeps and tones, in a delayed match-to-sample task. The local electrical activities of the neuronal units of the model simulated accurately the experimentally observed electrophysiological data, where available, and the model's simulated BOLD-fMRI data were quantitatively matched with experimental fMRI data. In the present simulations, intact stimuli were matched with fragmented versions (i.e., with inserted silent gaps). The ability of the model to match fragmented stimuli declined as the duration of the gaps increased. However, when simulated broadband noise was inserted into these gaps, the matching response was restored, indicating that a continuous stimulus was perceived. The electrical activities of the neuronal units of the model agreed with electrophysiological data, and the behavioral activity of the model matched human behavioral data. In the model, the predominant mechanism implementing temporal induction is the divergence of the feedforward connections along the auditory processing pathway in the temporal cortex. These simulation results not only attest to the robustness of the model, but further predict the primary role of the anatomical connectivity of the auditory processing areas in mediating the continuity illusion.

Acoustic Stimulation↗
PubMed2004

Resting state brain glucose metabolism is not reduced in normotensive healthy men during aging, after correction for brain atrophy.

Studies using positron emission tomography (PET) have reported that global and regional values for cerebral blood flow and metabolic rates for glucose (CMRglc and rCMRglc) decline with age in humans. We wished to determine if such decreases could have reflected a partial volume effect (PVE) of cerebral atrophy in the elderly, rather than "intrinsic" reductions per gram brain. We used PET to compare rCMRglc, before and after correcting for the PVE, between 13 healthy older men (aged: 55-82 years) and 11 healthy young men (aged: 22-34 years). PET was performed with 18F-fluoro-2-deoxy-d-glucose while the subjects were in the "resting" state (eyes covered and ears plugged with cotton). The PET scans were normalized to a common brain volume after superimposing them on the subjects' tissue segmented magnetic resonance scans. Analysis showed that rCMRglc in the absence of a PVE correction was significantly less in the older group in insular, frontal, superior temporal cortical, and thalamic regions. Statistical significant differences in rCMRglc, however, were absent after the PVE correction. Thus, statistically significant age reductions in regional brain glucose metabolism, corrected for brain atrophy, are not detectable in healthy normotensive men scanned while in the resting state.

Adult↗
PubMed2004

Brain network interactions in auditory, visual and linguistic processing.

In the paper, we discuss the importance of network interactions between brain regions in mediating performance of sensorimotor and cognitive tasks, including those associated with language processing. Functional neuroimaging, especially PET and fMRI, provide data that are obtained essentially simultaneously from much of the brain, and thus are ideal for enabling one to assess interregional functional interactions. Two ways to use these types of data to assess network interactions are presented. First, using PET, we demonstrate that anterior and posterior perisylvian language areas have stronger functional connectivity during spontaneous narrative production than during other less linguistically demanding production tasks. Second, we show how one can use large-scale neural network modeling to relate neural activity to the hemodynamically-based data generated by fMRI and PET. We review two versions of a model of object processing - one for visual and one for auditory objects. The regions comprising the models include primary and secondary sensory cortex, association cortex in the temporal lobe, and prefrontal cortex. Each model incorporates specific assumptions about how neurons in each of these areas function, and how neurons in the different areas are interconnected with each other. Each model is able to perform a delayed match-to-sample task for simple objects (simple shapes for the visual model; tonal contours for the auditory model). We find that the simulated electrical activities in each region are similar to those observed in nonhuman primates performing analogous tasks, and the absolute values of the simulated integrated synaptic activity in each brain region match human fMRI/PET data. Thus, this type of modeling provides a way to understand the neural bases for the sensorimotor and cognitive tasks of interest.

Animals↗
PubMed2004

"What" and "where" in visual working memory: a computational neurodynamical perspective for integrating FMRI and single-neuron data.

Single-neuron recordings, functional magnetic resonance imaging (fMRI) data, and the effects of lesions indicate that the prefrontal cortex (PFC) is involved in some types of working memory and related cognitive processes. Based on these data, two different models of the topographical and functional organization of the PFC have been proposed: organization-by-stimulus-domain, and organization-by-process. In this article, we utilize an integrate-and-fire network to model both single-neuron and fMRI data on short-term memory in order to understand data obtained in topologically different parts of the PFC during working memory tasks. We explicitly model the mechanisms that underlie working memory-related activity during the execution of delay tasks that have a "what"-then-"where" design (with both object and spatial delayed responses within the same trial). The model contains different populations of neurons (as found experimentally) in attractor networks that respond in the delay period to the stimulus object, the stimulus position, and to combinations of both object and position information. The pools are arranged hierarchically and have global inhibition through inhibitory interneurons to implement competition. It is shown that a biasing attentional input to define the current relevant information (object or location) enables the system to select the correct neuronal populations during the delay period in what is a biased competition model of attention. The processes occurring at the AMPA and NMDA synapses are dynamically modeled in the integrate-and-fire implementation to produce realistic spiking dynamics. It is shown that the fMRI data characteristic of the dorsal PFC and linked to spatial processing and manipulation of items can be reproduced in the model by a high level of inhibition, whereas the fMRI data characteristic of the ventral PFC and linked to object processing can be produced by a lower level of inhibition, even though the network is itself topographically homogeneous with no spatial topology of the neurons. This article, thus, not only presents a model for how spatial versus object short-term memory could be implemented in the PFC, but also shows that the fMRI BOLD signal measured during such tasks from different parts of the PFC could reflect a higher level of inhibition dorsally, without this dorsal region necessarily being primarily spatial and the ventral region object-related.

Algorithms↗
PubMed2004

Relating fMRI and PET signals to neural activity by means of large-scale neural models.

This article reviews the four ways by which large-scale, neurobiologically realistic modeling can be used in conjunction with functional neuroimaging data, especially that obtained by functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), to help investigators understand the neural bases for sensorimotor and cognitive functions. The conceptually distinct purposes served are:(1) formulating and implementing specific hypotheses about how neuronal populations mediate a task, which will be illustrated using models of visual and auditory object processing; (2) determining how well an experimental design paradigm or analysis method works, which will be illustrated by examining event-related fMRI; (3) investigating the meaning in neural terms of macro-level concepts, which will be illustrated using functional connectivity; and (4) combining different types of macroscopic data with one another, which will be illustrated using transcranial magnetic stimulation (TMS) and PET.

Brain↗
PubMed2003

Activation of Broca's area during the production of spoken and signed language: a combined cytoarchitectonic mapping and PET analysis.

Broca's area in the inferior frontal gyrus consists of two cytoarchitectonically defined regions-Brodmann areas (BA) 44 and 45. Combining probabilistic maps of these two areas with functional neuroimaging data obtained using PET, it is shown that BA45, not BA44, is activated by both speech and signing during the production of language narratives in bilingual subjects fluent from early childhood in both American Sign Language (ASL) and English when the generation of complex movements and sounds is taken into account. It is BA44, not BA45, that is activated by the generation of complex articulatory movements of oral/laryngeal or limb musculature. The same patterns of activation are found for oral language production in a group of English speaking monolingual subjects. These findings implicate BA45 as the part of Broca's area that is fundamental to the modality-independent aspects of language generation.

Adult↗
PubMed2003

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.

Brain↗
PubMed2003

Interindividual differences in functional interactions among prefrontal, parietal and parahippocampal regions during working memory.

To clarify the neural systems deployed by individual subjects during working memory (WM), we collected functional neuroimaging data from healthy subjects, and constructed a model of 2-back WM using structural equation modeling (SEM). A group model was constructed, and models for each subject were validated against it. The group model consisted principally of regions in the prefrontal and parietal cortex, with considerable interindividual variance in the single-subject models. To explore this variance, subjects were split into two groups based on performance. Performance level and self-reported strategy scores were used in a correlation analysis against path weights between nodes of individual models. High performers utilized a left hemisphere sub-network involving inferior parietal lobule and Broca's area, whereas lower performers utilized a right hemisphere sub-network with interactions between inferior parietal lobule and dorsolateral prefrontal cortex. Further, we observed an interaction between the parahippocampal formation and the inferior parietal lobule that was related to the different strategies used by the individuals to perform the task. Strategy and performance level appear to be intricately related in this task, with neural systems supporting verbal processing producing better performance than those associated with spatial processing. These results demonstrate that individual behavioral characteristics are reflected in specific neurofunctional patterns at the system level and that these can be captured by analytical techniques such as SEM.

Adult↗
PubMed2003

Relation of corpus callosum and hippocampal size to age in nondemented adults with Down's syndrome.

OBJECTIVE: Aging in Down's syndrome is accompanied by amyloid and neurofibrillary pathology, the regional and laminar distribution of which resembles pathological changes seen in Alzheimer's disease. Previous studies using magnetic resonance imaging (MRI) demonstrated age-related atrophy of medial temporal lobe structures in nondemented older subjects with Down's syndrome, reflecting early allocortical pathology. Corpus callosum atrophy has been established as a marker of neocortical neuronal loss in Alzheimer's disease. This study investigated whether atrophy of the corpus callosum and hippocampus occurs in nondemented subjects with Down's syndrome and compared the degree of age-related atrophy between these structures. METHOD: Hippocampus and corpus callosum measures were obtained from volumetric T(1)-weighted MRI scans of 34 nondemented Down's syndrome adults (mean age=41.6 years, 17 women) and 31 healthy comparison subjects (mean age=41.8 years, 14 women). RESULTS: Down's syndrome subjects had smaller corpus callosum areas and hippocampal volumes relative to age-matched healthy comparison subjects, even after age and total intracranial volume were controlled. There was an age-related decrease of corpus callosum area (most prominent in posterior regions) and hippocampal volume in the Down's syndrome group. The degree of the age effect was comparable between the total corpus callosum and hippocampus, and corpus callosum size was correlated with cognitive performance in the Down's syndrome subjects. There was no correlation between age and corpus callosum or hippocampal size in the comparison group. CONCLUSIONS: Comparable decrease of corpus callosum and hippocampal size with age in nondemented subjects with Down's syndrome suggests that neocortical neuronal alterations accompany allocortical changes in the predementia phase of Down's syndrome.

Adult↗