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Meta-Analytic Connectivity Modeling of Brodmann Area 37 Florida International University FIU Digital Commons Nicole Wertheim College of Nursing and Health Nicole Wertheim College of Nursing and Health Sciences Sciences 12-17-2014 Language and Visual Perception Associations: Meta-Analytic Connectivity Modeling of Brodmann Area 37 Alfredo Ardilla Department of Communication Sciences and Disorders, Florida International University, [email protected] Byron Bernal Miami Children's Hospital Monica Rosselli Florida Atlantic University Follow this and additional works at: https://digitalcommons.fiu.edu/cnhs_fac Part of the Physical Sciences and Mathematics Commons Recommended Citation Ardilla, Alfredo; Bernal, Byron; and Rosselli, Monica, "Language and Visual Perception Associations: Meta-Analytic Connectivity Modeling of Brodmann Area 37" (2014). Nicole Wertheim College of Nursing and Health Sciences. 1. https://digitalcommons.fiu.edu/cnhs_fac/1 This work is brought to you for free and open access by the Nicole Wertheim College of Nursing and Health Sciences at FIU Digital Commons. It has been accepted for inclusion in Nicole Wertheim College of Nursing and Health Sciences by an authorized administrator of FIU Digital Commons. For more information, please contact [email protected]. Hindawi Publishing Corporation Behavioural Neurology Volume 2015, Article ID 565871, 14 pages http://dx.doi.org/10.1155/2015/565871 Research Article Language and Visual Perception Associations: Meta-Analytic Connectivity Modeling of Brodmann Area 37 Alfredo Ardila,1 Byron Bernal,2 and Monica Rosselli3 1 Department of Communication Sciences and Disorders, Florida International University, Miami, FL 33199, USA 2Radiology Department and Research Institute, Miami Children’s Hospital, Miami, FL 33155, USA 3Department of Psychology, Florida Atlantic University, Davie, FL 33314, USA Correspondence should be addressed to Alfredo Ardila; [email protected] Received 4 November 2014; Revised 9 December 2014; Accepted 17 December 2014 Academic Editor: Annalena Venneri Copyright © 2015 Alfredo Ardila et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas. Objectives. The purpose of this paper was to analyze the connectivity of Brodmann area (BA) 37 (posterior, inferior, and temporal/fusiform gyrus) in relation to (1) language and (2) visual processing. Methods. Two meta-analyses were initially conducted (first level analysis). The first one was intended to assess the language network in which BA37 is involved. The second one was intended to assess the visual perception network. A third meta-analysis (second level analysis) was then performed to assess contrasts and convergence between the two cognitive domains (language and visual perception). The DataBase of Brainmap was used. Results. Our results support the role of BA37 in language but by means of a distinct network from the network that supports its second most important function: visual perception. Conclusion. It was concluded that left BA37 is a common node of two distinct networks—visual recognition (perception) and semantic language functions. 1. Introduction neuroscience, however, emphasizes the idea of brain systems including the traditional language areas as well as other areas Understanding the specific function of different brain areas which could not be exclusively associated to language but are has represented one of the major challenges of neurosciences. involved in language processing (e.g., [6]), such as BA37. Based on the correlation between neurological deficits and During the last decades the concept of “connectome” has cerebral postmortem findings, the nineteen-century neuro- become particularly important in understanding the brain anatomists developed the brain function localization model. systems of interconnections [7, 8]. The term “connectome” Brodmann gave a strong support to this model in 1909 [1] was introduced in 2005 to refer to the comprehensive descrip- by describing 52 pairs of brain cortical areas characterized tion of the brain connections among the different areas pro- by different laminar organization. Despite the subsequent vided by cortical parcellation maps [9]. Parcellation maps development of more detailed cortical maps such as the map may vary in number of discrete independent areas (e.g., by published by Economo and Koskinas [2], the so-called “Brod- gyri, cytoarchitectonic criteria as proposed by Brodmann [1] mann areas” (BA) have become broadly used in contempo- or C. Vogt and O. Vogt [10]). As a result the connectome dimen- rary neuroanatomy providing a topographical substrate to sion may also vary. The brain connectome may be represented specific brain functions. as a matrix [9], as a complex graph of nodes and edges [11], Traditional models of language (e.g., [3–5]) consider lan- or as a collection of fiber tracts derived from diffusion tensor guage in terms of specific brain areas (such as Broca’s and imaging tractography [12]. These models parcel the brain in Wernicke’s area) devoted to specific functions (e.g., language a new manner. An intricate collection of volumes, virtual production and language understanding); contemporary shapes, and geometries arises, giving ground to paths for data 2 Behavioural Neurology flow through different processing centers. Here resides the areas. Noteworthy, BA37 has not overt anatomical limits. The importance of describing brain connectivity. posterior segment of the fusiform gyrus and the inferior and Several BA have been extensively studied while others medial temporal gyri composes it. have received less attention. Language areas are probably the Currently, there are several techniques that can demon- most frequently analyzed. Language production is related to strate brain networks. These techniques are grouped under theactivityofBA44andBA45,alsoknownasBroca’sarea[13– theterm“brainconnectivity.”Fibertractography,basedon 21]. Of note is that whereas Broca’s area is a well delimited diffusion tensor imaging, demonstrates structural connectiv- anatomical region encompassing the pars triangularis and ity or direct connection of brain areas through associative opercularis of the left inferior frontal gyrus, the extension tracts. Remote temporal correlation of the BOLD-signal and limits of the receptive language area or Wernicke’s area history of a voxel or cluster, based on resting state sequences, are not so well defined. Usually it is accepted that Wernicke’s demonstrates the functional connectivity through direct or area includes BA22 and probably BA21 [22, 23]. However, indirect pathways. several neuroimaging studies have reported left BA37 activa- Functional connectivity has been shown to be dynamic tion associated with different language tasks (see24 [ ]). Dif- as it changes from task to task [45, 46]whilestructural ferent reports support the involvement of BA37 in semantic connectivity is rather stable. Resting state-based functional categorization, that is, using a particular word to refer to connectivity represents a powerful tool to study and char- a collection of objects (i.e., many different objects can be acterize different networks, but it has the limitation that it named with the single word “chair,”because they have certain reflectsthebraininapassivestatusandhindersimportant commonality) (e.g., [5, 25]). Finding and producing words networks. (word retrieval and word generation) are potential functions Recently, an alternative approach to study the brain of BA37 considering that the destruction of this area is connectivity has been proposed by Robinson et al. [47], meta- associated with word selection anomia [16, 20]; some studies analytic connectivity modeling, or MACM. MACM allows indeed have found that word search results in an increased examining task independent coactivation patterns of a spe- activity in this area [26, 27]. Moreover, the involvement of cific anatomically defined brain region. MACM is based on BA37 in naming has been well documented [21, 28–34]. automatic meta-analysis done by pooling coactivation pat- The functions of this area are not limited to oral language terns. The technique takes advantage of the Brainmap.org’s but extend to written language as well. The activation of repository of functional MRI studies [48, 49]andofaspecial BA37 has been reported during reading, taking into account software (Sleuth) provided by the same group, to find, filter, that left occipital-temporal lesions are strongly associated organize, plot, and export the peak coordinates for further with alexia [35–39]. The function of linking orthography statistical analysis. Sleuth provides a list of foci, in Talairach to phonology reported by Hashimoto and Sakai [40]con- or MNI coordinates, each one representing the center of sequently points to the seemingly core function of BA37 mass of a cluster of activation. The method takes the region area: associating visual information (orthography—written of interest (for instance, a given Brodmann area), makes it language—or whatever visual representation) with auditory the independent variable, and interrogates the database for linguistic information
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