Should Broca's area include Brodmann area 47?/?Deberia el area de Broca incluir el area 47 de Brodmann?
Recent functional studies have demonstrated that BA47 participates in different language functions, including, semantic processing (Left) (Chou et al., 2006; De Carli et al., 2006; Wong et al., 2002), semantic encoding (Demb & Glover, 1995; Li et al., 2000), semantic retrieval (Desmond et al., 1995; Lehtonen et al., 2005; Zhang et al., 2004), phonological processing (De Carli et al., 2007; McDermott et al., 2003), lexical inflection (Sahin, Pinker, & Halgren, 2006), syntactic processing (Tyler et al., 2011), and selective attention to speech (Vorobyev et al., 2004). Right BA47 has been related with affective prosody (Belyk & Brown, 2014; Wildgruber et al., 2005). However, left BA47 has been observed to participate not only in language but also in other domains such as working memory (e.g., Ranganath, Johnson, & D'Esposito, 2003) and deductive reasoning (Goel, Gold, Kapur, & Houle, 1998) (for a review of the function of BA47 found in functional studies see: http://www.fmriconsulting.com/brodmann/)
The significant amount of language-related functions that have been associated with BA47, such as semantic processing, phonological processing, semantic encoding, and others, is surprising. In these cases, it can be assumed that BA47 is simply one of the multiple steps in the brain language production network ("Broca' s complex"). However, the specific participation of BA47 in a language production circuit undoubtedly requires further analysis. That is the goal of the current meta-analytic study. This study is the continuation of a research program devoted to analyzing the participation of different Brodmann areas in language (Ardila, Bernal, & Rosselli, 2014a, 2014b; 2015; 2016a, 2016b, 2016c; Bernal, Ardila, & Rosselli, 2015, Rosselli, Bernal, & Ardila, 2015).
Nowadays there are several techniques that can potentially demonstrate brain circuitries or networks (Friston, 2011; Li, Guo, Nie, & Liu, 2009). These techniques are grouped under the term "brain connectivity". Recently, a new alternative to studying brain connectivity has been proposed by Robinson et al. (2010) known as meta-analytic connectivity modeling or MACM. MACM is based in automatic meta-analysis done by pooling co-activation patterns. The technique takes advantage of Brainmap.org's repository of functional MRI studies, and of special software (Sleuth) provided by the same group, to find, filter, organize, plot, and export the peak coordinates for further statistical analysis of its results. Sleuth provides a list of foci, in Talairach or MNI coordinates, each one representing the center of mass of a cluster of activation. The method takes the region of interest (for instance, BA46), makes it the independent variable, and interrogates the database for studies showing activation of the chosen target. The query is easily filtered with different conditions (such as age, normal vs. patients, type of paradigm, domain of cognition, etc.). By pooling the data with these conditions the tool provides a universe of co-activations that can be statistically analyzed for significant commonality. As a final step, Activation Likelihood Estimation (ALE) (Laird et al., 2005; Turkeltaub et al., 2002) that can be performed utilizing GingerALE, another piece of software also provided by Brainmap, assesses the probability of an event occuring at voxel level across the studies. Areas of coactivation will show a network related to the function and domains selected as filter criteria. A diversity of studies have used this procedure to investigate brain connectivity (e.g., Kohn et al., 2014; Laird et al., 2009; Torta & Cauda, 2011; Zald et al., 2014).
Considering the complex role of BA47 in language, a metaanalytic connectivity analysis utilizing MACM on the participation of BA47 in language was developed. The objective of this study as to analyze the left BA47 participation in the brain language networks associated with different language functions. The present study is aimed to support the involvement of BA47 in a brain language production system.
Twenty papers corresponding to 29 experimental conditions with a total of 373 subjects were selected (subjects participating in two different experiments were counted as two subjects) (Table 1).
A meta-analysis of fMRI studies was developed.
The Brainmap database (brainmap.org) was accessed utilizing Sleuth 2.2 on August 2, 2015. Sleuth is the software provided by Brainmap to query its database. The meta-analysis was intended to assess the network of coactivations in which BA47 is involved.
The search conditions were: (1) studies reporting BA47 activation; (2) studies using fMRI; (3) context: normal subjects; (4) activations: activation only; (5) handedness: right-handed subjects; (6) age 18-60 years; (7) domain: cognition, subtype: language; (8) Language: English.
(ALE) meta-analysis was then performed utilizing GingerALE. ALE maps were thresholded at p<0.01 corrected for multiple comparisons and false discovery rate. Only clusters of 200 or more cubic mm where accepted as valid clusters. ALE results were overlaid onto an anatomical template suitable for MNI coordinates, also provided by BrainMap.org. For this purpose we utilized the Multi-Image Analysis GUI (Mango) (http://ric.uthscsa. edu/mango/). Mosaics of 7 x 7 insets of transversal fusion images were generated utilizing a plugin of the same tool, selecting every other image, and exported to a 2D-jpg image.
Table 2 presents the main loci of brain connectivity of BA47 by Meta-analytic Connectivity Modeling (MACM). Nine different clusters of activation were found, mostly related to the left hemisphere (Figure 1).
The first cluster includes the frontal areas 46, 47, and 6 in the left hemisphere. Noteworthy, this as an extensive cluster with a volume about five times larger than Cluster #2 and about eight times larger than Cluster #3. Indeed, the rest of the activation clusters are relatively small.
The second cluster includes the left insula and the anterior cerebellum, but most likely the source of activation is located in the fusiforme gyrus (BA37); the simultaneous activation in the same cluster of the Inferior temporal lobe (BA20) emphasizes the activation of BA37. Cluster #3 refer to the right insula. Cluster #4 is located in the left superior frontal lobe superior (BA6) consequently corresponding to the supplementary motor area. Cluster #5 is located in the left inferior occipital gyrus (BA 18). Cluster #6 is the Wernicke's area (BA21 and BA22). The last three clusters are small and are located in the left superior parietal area (BA7), left inferior occipital lobe (BA18), and anterior right cerebellum (quite likely, the fusiform gyrus).
It is well known that BA47 has some participation in language, although pinpointing its specific function has not been easy. It has been suggested that the major language functions include semantic and phonological processing, grammatical processing (including lexical inflection and syntactic processing, and selective attention to speech (see Brodmann's Interactive Atlas). Because of its location in the brain (below Broca's area), it is understandable that BA47 participates in language production and grammar. However, it has also been proposed that BA47 may participate in some other functions. Levitin & Menon (2003) have suggested that BA47 may be more generally responsible for processing fine-structured stimuli that evolve over time, not merely those that are linguistic.
Functional and clinical studies corroborate the involvement of BA47 in language production. Neuroimaging studies have demonstrated that brain areas activated during speaking are notoriously larger than the classical Broca's area (Ardila, Bernal, & Rosselli, 2016d; Gernsbacher & Kaschak, 2003; Pickering & Garrod, 2013). This extended brain activation during language production has been demonstrated using diverse techniques such as magnetoencephalography (MEG) (Salmelin, 2007). From the clinical point of view, it is well known that damage restricted to Broca's area does not result in the classical Broca's aphasia; extension to the insula, lower motor cortex (including BA47), and subjacent subcortical and periventricular white matter is required (Alexander, Naeser, & Palumbo, 1990; Benson & Ardila, 1996).
In the current meta-analytic study it was found a major cluster of coactivation, including BA46, BA47, and BA6 in the left hemisphere. That means, during linguistic tasks BA47 become activated simultaneously with other frontal adjacent areas, conforming a single focus of activation. The second of activation cluster included the left insula and some posterior language areas (BA37 and BA20), suggesting (as it has been reported in the literature) and involvement of BA47 is semantic aspects of the language. The rest of the clusters were indeed small, and locate in parietal and occipital areas.
Current results illustrate that BA47, (1) participates in a frontal language production system, which probable includes not only the classical Broca's area, but also BA46 and the medial extension of BA6, corresponding to the supplementary motor area, and some subcortical areas ("Broca complex", Ardila, Bernal, & Rosselli, 2016c) (Figure 2); (2) it also has a secondary participation in semantic processing; coactivartion with left temporal areas involved in semantic processing (BA37 and BA20).
Many limitations could be mentioned regarding the present study. The major critique of meta-analysis studies commonly refers to the lack of homogeneity of the pooled tasks, methods, and individuals. Furthermore, MACM is still new requiring performance of future validation studies. We have used BA47 as the independent variable and a spectrum of co-activated areas as the dependent variable, which may be unusual.
As mentioned before, there are diverse techniques that potentially could be used to detect brain connectivity. Each one of the available techniques to study brain connectivity have some advantages but also disadvantages. According to Friston (2011) the most prevalent approaches to effective connectivity analysis are dynamic causal modeling (DCM), structural equation modeling, and Granger causality; however, each of them have some important limitations. Li et al. (2009) propose to divide the computational methodologies used to analyze brain connectivity using fMRI into two general categories: model-driven methods and data-driven methods. Data driven methods are a large family, and thus are further sub-classified into decomposition-based methods and clustering analysis methods. In our study we used a cluster analysis approach. According to these authors, a major limitation of cluster analysis is that it is based on intensity proximity that may be not enough for functional connectivity detection in fMRI. This is obviously an additional limitation of our study. However, the current results are quite consistent with clinical observations, positively supporting the structural connectivity findings.
Our gratitude to Adriana Ardila for her editorial support.
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Alfredo Ardila (1), Byron Bernal (2) and Monica Rosselli (3)
(1) Florida International University, (2) Miami Children's Hospital and 3 Florida Atlantic University
Received: January 14, 2016 * Accepted: September 12, 2016
Corresponding author: Alfredo Ardila Florida International University 11200 8th Street 33199 Miami (Estados Unidos)
Caption: Figure 1. Language-related BA47's network. ALE results overlaid on an axial-T1 MRI MNI-template. Left hemisphere appears in the left side of the insets (neurological convention). ALE scores are color coded from red (lower scores) to white (higher scores). In addition to the left BA47 (Inferior frontal gyrus --Pars orbitalis) that has the highest intensity, the following regions appear "activated": BA46, BA6, BA 13, BA37, BA20, BA21, BA22, BA7 and BA18
Caption: Figure 2. "Broca's complex" includes BA44, BA45, BA46, BA47, mesial BA6 (supplementary motor area; not seen) and extending subcortically toward the basal ganglia and the thalamus (not seen) (according to Ardila et al., 2016b)
Table 1 Studies of language paradigms included in the meta-analysis Publication Paradigm n Foci Booth et al., 2002 Visual Rhyming - Control 13 11 Auditory Meaning - Control 13 9 Meaning - Rhyming 13 8 Mechelli et al., Pseudowords - Rest 6 2 2000 Pseudowords - Words 6 7 Dapretto et al., Syntactic vs. Rest 8 8 1999 Semantic vs. Rest 8 8 Semantic vs. Syntactic 8 1 Devlin et al., Semantic + Phonological - Rest 12 26 2003 Phonological > Semantic 12 34 Noppeney et al., Abstract> Sounds, Visual, Hand 15 4 2004 Jackson et al., Associative Encoding - Fixation 12 61 2004 Successful Associ - Unsucces Assoc 12 10 Binder et al., Word > Nonword 24 26 2003 Tagamets et al., Words vs. Shapes 11 18 2000 Pseudowords vs. Shapes 11 20 Booth et al., 2002 Rhyming, Vis - Aud 13 5 Peck et al., 2004 Sent Gen vs. View Nonsense Obj 10 13 Rowan et al., 2004 Verb Generation - Activations 10 13 Leff et al., 2008 Idioms + Rearranged Idioms 23 3 Damasio et al., Action Tool Word Retrieval 20 7 2001 Sharp et al., 2010 Semantic Perceptual 12 5 Davis et al., 2008 Words vs. Letter Strings 12 9 Desai et al., 2006 Generate Regular Verbs - Read 25 21 Longe et al., 2007 Inflections vs. Baseline 12 14 Tyler et al., 2004 Words - Letter Strings 12 14 Diaz et al., 2011 Metaphor > Literal 16 6 Lee et al., 2006 Literal > Rest 12 21 Nonliteral > Rest 12 20 Table 2 Main loci of brain connectivity of BA47 in language tasks by Meta-analytic Connectivity Modeling (MACM) Region (BA) x y z Cluster #1 L Inferior frontal gyrus (47) -46 18 -2 L. Middle Frontal gyrus (46) -44 24 20 L. Inferior frontal gyrus (47) -44 28 0 L. Inferior gyrus (47) -34 26 -4 L. Precentral gyrus (6) -42 0 28 Cluster #2 L. Cerebellum culmen -44 -50 -20 L. Inferior temporal lobe (20) -52 -52 -12 L. Cerebellum declive -42 -66 -18 Cluster #3 R. Insula (13) 36 22 0 Cluster #4 L. Frontal lobe superior (6) -4 8 48 Cluster #5 L. Inferior occipital gyrus (18) -34 -88 -14 L. cerebellum declive -32 80 -16 Cluster #6 L. Middle temporal gryus (21) -58 -40 -4 L. Middle temporal gyrus (22) -58 -36 6 Cluster #7 L. Superior parietal (7) -26 -66 42 Cluster #8 L. Inferior occipital (18) -22 -88 -10 Cluster #9 R. Lingual gyrus (18) 16 -88 -12 R. Cerebellum declive 20 82 -18 Region (BA) ALE Volume ([mm.sup.3]) Cluster #1 L Inferior frontal gyrus (47) 0.051 16120 L. Middle Frontal gyrus (46) 0.044 L. Inferior frontal gyrus (47) 0.433 L. Inferior gyrus (47) 0.383 L. Precentral gyrus (6) 0.315 Cluster #2 3328 L. Cerebellum culmen 0.029 L. Inferior temporal lobe (20) 0.260 L. Cerebellum declive 0.021 Cluster #3 R. Insula (13) 0.032 1992 Cluster #4 L. Frontal lobe superior (6) 0.031 1800 Cluster #5 L. Inferior occipital gyrus (18) 0.026 1144 L. cerebellum declive 0.021 Cluster #6 L. Middle temporal gryus (21) 0.026 1104 L. Middle temporal gyrus (22) 0.018 Cluster #7 L. Superior parietal (7) 0.023 464 Cluster #8 L. Inferior occipital (18) 0.018 248 Cluster #9 R. Lingual gyrus (18) 0.017 224 R. Cerebellum declive 0.016