Barry Horwitz, Ph.D.

Chief
Section on Brain Imaging and Modeling
Voice, Speech, and Language Branch

Ph.D., University of Pennsylvania, 1972

Research Statement

Current research focuses on understanding how the brain constructs networks of interacting regions (i.e., neural networks) to perform cognitive tasks, especially those associated with audition and language, and how these networks are altered in brain disorders. These issues are addressed by combining computational neuroscience techniques with functional neuroimaging data, obtained using fMRI, PET, or MEG. The network analysis methods allow us to evaluate how brain operations differ between tasks and between normal and patient populations. This research will allow us to ascertain which networks are dysfunctional, and the role neural plasticity plays in enabling compensatory behavior to occur. A unique aspect of our research is that most of the experiments we do are linked to our modeling, in that these experiments are performed to either acquire data for developing our models or else for testing them.

Recent Accomplishments

Recently, we tested the hypothesis that ventral/anterior left inferior frontal gyrus (LIFG) subserves semantic processing and dorsal/posterior LIFG subserves phonological processing by determining the pattern of functional connectivity of these regions with regions in left occipital and temporal cortex during the processing of word 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. These results demonstrate a task-dependent functional fractionation of the LIFG in terms of its functional links with posterior brain areas (Bokde et al., 2001) and illustrate the importance of determining how different brain regions work together to mediate specific cognitive tasks.

In a set of recent studies, we constructed various large-scale computer models of neuronal dynamics that can perform object-matching tasks similar to those designed for fMRI and PET investigations. These were implemented in order to understand the relationship between what is observed in functional neuroimaging studies and the underlying neural dynamics. These models are composed of elements that correspond to neuronal assemblies in cerebral cortex, and contain different elements that are based on types identified by electrophysiological recordings from monkeys as they perform similar tasks. One model, corresponding to the visual object processing system, includes an "active" memory network involving the occipitotemporal visual pathway and a frontal circuit, and is capable of performing a match-to-sample task in which a response is made if the second stimulus matches the first. A PET or fMRI study is simulated by presenting pairs of stimuli to an area of the model that represents the lateral geniculate nucleus. Simulated fMRI/PET data are computed from the model as it performs the tasks by integrating synaptic activity within the different areas. Simulated PET data similar to that found in actual PET delayed match-to-sample visual tasks were obtained, as were the correct neuronal dynamics in each brain region (Tagamets and Horwitz, 1998; Horwitz and Tagamets, 1999). This model was extended not long ago so that it could also simulate studies of transcranial magnetic stimulation (Husain et al., 2002). Recently, we have constructed a similar model for auditory object processing. The simulated fMRI data generated by the model agreed with experimental fMRI data that we acquired.

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Lab Personnel

Fatima Husain, Ph.D., Research Fellow (Send e-mail)
Antonio Ulloa, Ph.D., Postdoctoral Fellow (Send e-mail)
Yukiko Kikuchi-Yorioka, Ph.D., Postdoctoral Fellow
Huan Luo, B.S., Predoctoral Fellow

Selected Publications

• Horwitz B. Relating fMRI and PET signals to neural activity by means of large-scale neural models. Neuroinformatics 2(2):251–66, 2004.
• Deco G, Rolls ET, Horwitz B. "What" and "where" in visual working memory: a computational neurodynamical perspective for integrating FMRI and single-neuron data. Journal of Cognitive Neuroscience 16(4):683–701, 2004.
• Ibanez V, Pietrini P, Furey ML, Alexander GE, Millet P, Bokde AL, Teichberg D, Schapiro MB, Horwitz B, Rapoport SI. Resting state brain glucose metabolism is not reduced in normotensive healthy men during aging, after correction for brain atrophy. Brain Research Bulletin 63(2):147–54, 2004.
• Horwitz B, Braun AR. Brain network interactions in auditory, visual and linguistic processing. Brain and Language 89(2):377–84, 2004.
• Husain FT, Tagamets MA, Fromm SJ, Braun AR, Horwitz B. Relating neuronal dynamics for auditory object processing to neuroimaging activity: a computational modeling and an fMRI study. Neuroimage 21(4):1701–20, 2004.
• Glabus MF, Horwitz B, Holt JL, Kohn PD, Gerton BK, Callicott JH, Meyer-Lindenberg A, Berman KF. Interindividual differences in functional interactions among prefrontal, parietal and parahippocampal regions during working memory. Cerebral Cortex 13(12):1352–61, 2003.
• Teipel SJ, Schapiro MB, Alexander GE, Krasuski JS, Horwitz B, Hoehne C, Moller HJ, Rapoport SI, Hampel H. Relation of corpus callosum and hippocampal size to age in nondemented adults with Down's syndrome. The American Journal of Psychiatry 160(10):1870–8, 2003.
• Horwitz B. The elusive concept of brain connectivity. Neuroimage 19(2 Pt 1):466–70, 2003.
• Horwitz B, Amunts K, Bhattacharyya R, Patkin D, Jeffries K, Zilles K, Braun AR. Activation of Broca's area during the production of spoken and signed language: a combined cytoarchitectonic mapping and PET analysis. Neuropsychologia 41(14):1868–76, 2003.
• Sevostianov A, Fromm S, Nechaev V, Horwitz B, Braun A. Effect of attention on central auditory processing: an fMRI study. the International Journal of Neuroscience 112(5):587–606, 2002.
• Sevostianov A, Horwitz B, Nechaev V, Williams R, Fromm S, Braun AR. fMRI study comparing names versus pictures of objects. Human0 Brain Mapping 16(3):168–75, 2002.
• Horwitz B, Poeppel D. How can EEG/MEG and fMRI/PET data be combined? Human Brain Mapping 17:1–3, 2002.
• Husain FT, Nandipati G, Braun AR, Cohen LG, Tagamets MA, Horwitz B. Simulating transcranial magnetic stimulation during PET with a large-scale neural network model of the prefrontal cortex and the visual system. Neuroimage 5:58–73, 2002.
• Bokde AL, Tagamets MA, Friedman RB, Horwitz B. Functional interactions of the inferior frontal cortex during the processing of words and word-like stimuli. Neuron 30:609–617, 2001.
• Tagamets MA, Horwitz B. Interpreting PET and fMRI measures of functional neural activity: the effects of synaptic inhibition on cortical activation in human imaging studies. Brain Research Bulletin 54:267–273, 2001.
• Horwitz B, Friston KJ, Taylor JG. Neural modeling and functional brain imaging: an overview. Neural Networks 13:829–846, 2000.
• Tagamets MA, Horwitz B. A model of working memory: bridging the gap between electrophysiology and human brain imaging. Neural Networks 13:941–952, 2000.
• Horwitz B, Tagamets MA. Predicting human functional maps with neural net modeling. Human Brain Mapping 8:137–142, 1999.
• Horwitz B, Tagamets MA, McIntosh AR. Neural modeling, functional brain imaging, and cognition. Trends in Cognitive Science 3:91–98, 1999.
• Tagamets MA, Horwitz B. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral Cortex 8:310–320, 1998.

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