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In chronological order (starting from the earliest):Fedorenko, E. & Kanwisher, N. (2009). Neuroimaging of language: Why hasn't a clearer picture emerged? Language and Linguistics Compass, 3, 839-865.
Abstract: Two broad questions have driven dozens of studies on the neural basis of language published in the last several decades: (i) Are distinct cortical regions engaged in different aspects of language? (ii) Are regions engaged in language processing specific to the domain of language? Neuroimaging has not yet provided clear answers to either question. In this paper, we discuss one factor that is a likely contributor to the unclear state of affairs in the neurocognition of language, and that, in our opinion, has not received sufficient attention in the recent literature. In particular, fMRI studies of language have relied, almost exclusively, on group analyses, in which data from multiple individuals are co-registered to and analyzed in a common space. We argue that this approach can obscure functional specificity because of the anatomical variability across individual brains, and we advocate the use of an alternative approach – the functional localization approach – that circumvents this problem.
Fedorenko, E., Hsieh, P.-J., Nieto-Castañon, A., Whitfield-Gabrieli, S. & Kanwisher, N. (2010). A new method for fMRI investigations of language: Defining ROIs functionally in individual subjects. Journal of Neurophysiology, 104, 1177-1194.
Abstract: Previous neuroimaging research has identified a number of brain regions sensitive to different aspects of linguistic processing, but precise functional characterization of these regions has proven challenging. We hypothesize that clearer functional specificity may emerge if candidate language-sensitive regions are identified functionally within each subject individually, a method that has revealed striking functional specificity in visual cortex but that has rarely been applied to neuroimaging studies of language. This method enables pooling of data from corresponding functional regions across subjects, rather than from corresponding locations in stereotaxic space (which may differ functionally because of the anatomical variability across subjects). However, it is far from obvious a priori that this method will work, as it requires that multiple stringent conditions be met. Specifically, candidate language-sensitive brain regions i) must be identifiable functionally within individual subjects in a short scan, ii) must be replicable within subjects and have clear correspondence across subjects, and iii) must manifest key signatures of language processing (e.g., a higher response to sentences than nonword strings, whether visual or auditory). We show here that this method does indeed work: we identify 13 candidate language-sensitive regions that meet these criteria, each present in at least 80 percent of subjects individually. The selectivity of these regions is stronger using our method than when standard group analyses are conducted on the same data, suggesting that the future application of this method may reveal clearer functional specificity than has been evident in prior neuroimaging research on language.
Fedorenko, E. & Kanwisher, N. (2011). Functionally localizing language-sensitive regions in individual subjects with fMRI: A reply to Grodzinsky's critique of Fedorenko & Kanwisher (2009). Language and Linguistics Compass, 5, 78-94.
[You can find Yosef Grodzinsky's response to our 2009 paper here.]
Abstract: In Fedorenko & Kanwisher (2009) we argued that defining regions of interest functionally in individual subjects may lead to a clearer picture of the functional architecture of the language system because it affords higher sensitivity and selectivity. Grodzinsky (2010) takes issue with two aspects of the F&K paper. First, he argues that the picture of the neural basis of language that has emerged from previous work is not as murky as F&K argue, with the implication that perhaps a new method is not needed. And second, he raises some concerns with the individual-subjects functional localization approach and argues instead for the use of probabilistic cytoarchitectonic maps (e.g., Amunts et al., 1999). In the current manuscript, we respond to both of Grodzinsky’s points. Regarding the first point, we stand by our assessment of the brain basis of language literature, and argue that many core questions related to functional specialization remain unanswered. We explain why we remain unconvinced by Grodzinsky’s example of Broca’s area (or a portion of it) as a region with a well-understood functional profile. Regarding the concerns that Grodzinsky raises with respect to the use of functional localizers in investigating the language system, we respond to the main comments and refer the reader to Fedorenko et al. (2010) where the remaining concerns are addressed (with both data and argumentation). Finally, we point out that the probabilistic cytoarchitectonic maps that Grodzinsky advocates have some of the same limitations as other group-based methods. We conclude that the individual-subjects functional localization approach, advocated in F&K, holds promise for better understanding the brain basis of language by enabling a detailed characterization of language-sensitive regions with respect to their role in both linguistic and non-linguistic processes.
Fedorenko, E. & Kanwisher, N. (2011). Some regions within Broca's area do respond more strongly to sentences than to linguistically degrdaded stimuli: A comment on Rogalsky & Hickok (2011). Journal of Cognitive Neuroscience, 23(10), 2632-2635.
Abstract: Based on their review of the literature, Rogalsky & Hickok (2011, JoCN) conclude that there is currently no strong evidence for the existence of “sentence-specific processing regions within Brocaʼs area” (p. 1). Their argument is based, in part, on the observation that many previous studies have failed to detect an effect in the left inferior frontal regions for contrasts between sentences and linguistically degraded control conditions (e.g., lists of unconnected words, lists of nonwords, or acoustically degraded sentence stimuli). Our data largely replicate this lack of activation in inferior frontal regions when traditional random-effects group analyses are conducted, but crucially show robust activations in the same data for the same contrasts in almost every subject individually. Thus, it is the use of group analyses in studies of language processing, not the idea that sentences robustly activate frontal regions, that needs to be reconsidered. This reconsideration has important methodological and theoretical implications.
Fedorenko, E., Behr, M. & Kanwisher, N. (2011). Functional specificity for high-level linguistic processing in the human brain. Proceedings of the National Academy of Sciences.
Abstract: Neuroscientists have debated for centuries whether some regions of the human brain are selectively engaged in specific high-level mental functions, or whether instead cognition is implemented in multifunctional brain regions. For the critical case of language, conflicting answers arise from the neuropsychological literature, which features striking dissociations between deficits in linguistic and nonlinguistic abilities, versus the neuroimaging literature, which has argued for overlap between activations for linguistic and nonlinguistic processes including arithmetic, domain-general abilities like cognitive control, and music. Here we use fMRI to define classic language regions functionally in each subject individually and then examine the response of these regions to the nonlinguistic functions most commonly argued to engage these regions: arithmetic, working memory, cognitive control and music. We find little or no response in language regions to these nonlinguistic functions. These data support a clear distinction between language and other cognitive processes, resolving the prior conflict between the neuropsychological and neuroimaging literatures.
Fedorenko, E., Nieto-Castañon, A. & Kanwisher, N. (2012). Syntactic processing in the human brain: What we know, what we don't know and a suggestion for how to proceed. Brain & Language, 120, 187-207.
Abstract: For every claim in the neuroimaging literature about a particular brain region supporting syntactic processing, there exist other claims implicating the target region in different linguistic processes, and, in many cases, in non-linguistic cognitive processes (e.g., Blumstein, 2009). We argue that traditional group analysis methods in neuroimaging may obscure functional specificity because of inter-subject anatomical variability (Fedorenko & Kanwisher, 2009). In Fedorenko et al. (2010) we presented a functional localizer that allows quick and reliable identification of key language-sensitive regions in each individual brain. This approach enables pooling data from corresponding functional regions across subjects rather than from the same locations in stereotaxic space that may differ functionally due to inter-subject anatomical variability. In the current paper we demonstrate that the individual-subjects functional localization approach is superior to the traditional methods in its ability to distinguish among conditions in a brain region’s response. This ability is at the core of all neuroimaging research and is critical for answering questions of functional specialization (e.g., does a brain region specialize for processing syntactic aspects of the linguistic signal), which is in turn essential for making inferences about the precise computations conducted in each brain region. Based on our results, we argue that supplementing existing methods with an individual-subjects functional localization approach may lead to a clearer picture of the neural basis of syntactic processing, as it has in some other domains, such as high-level vision (e.g., Kanwisher, 2010) and social cognition (e.g., Saxe & Kanwisher, 2003).
Fedorenko, E., Nieto-Castañon, A. & Kanwisher, N. (2012). Lexical and syntactic representations in the brain: An fMRI investigation with multi-voxel pattern analyses. Neuropsychologia, 50, 499-513.
Abstract: Work in theoretical linguistics and psycholinguistics suggests that human linguistic knowledge forms a continuum between individual lexical items and abstract syntactic representations, with most linguistic representations falling between the two extremes and taking the form of lexical items stored together with the syntactic/semantic contexts in which they frequently occur. Neuroimaging evidence further suggests that no brain region is selectively sensitive to only lexical information or only syntactic information. Instead, all the key brain regions that support high-level linguistic processing have been implicated in both lexical and syntactic processing, suggesting that our linguistic knowledge is plausibly represented in a distributed fashion in these brain regions. Given this distributed nature of linguistic representations, multi-voxel pattern analyses (MVPAs) can help uncover important functional properties of the language system. In the current study we use MVPAs to ask two questions: (1) Do language brain regions differ in how robustly they represent lexical vs. syntactic information? and (2) Do any of the language bran regions distinguish between “pure” lexical information (lists of words) and “pure” abstract syntactic information (jabberwocky sentences) in the pattern of activity? We show that lexical information is represented more robustly than syntactic information across many language regions (with no language region showing the opposite pattern), as evidenced by a better discrimination between conditions that differ along the lexical dimension (sentences vs. jabberwocky, and word lists vs. nonword lists) than between conditions that differ along the syntactic dimension (sentences vs. word lists, and jabberwocky vs. nonword lists). This result suggests that lexical information may play a more critical role than syntax in the representation of linguistic meaning. We also show that several language regions reliably discriminate between “pure” lexical information and “pure” abstract syntactic information in their patterns of neural activity.
Julian, J., Fedorenko, E., Webster, J. & Kanwisher, N. (2012). An algorithmic method for functionally defining regions of interest in the ventral visual pathway. Neurooimage, 60, 2357-2364.
Abstract: In a widely used functional magnetic resonance imaging (fMRI) data analysis method, functional regions of interest (fROIs) are handpicked in each participant using macroanatomic landmarks as guides, and the response of these regions to new conditions is then measured. A key limitation of this standard handpicked fROI method is the subjectivity of decisions about which clusters of activated voxels should be treated as the particular fROI in question in each subject. Here we apply the Group-Constrained Subject-Specific (GSS) method for defining fROIs, recently developed for identifying language fROIs (Fedorenko et al., 2010), to algorithmically identify fourteen well-studied category-selective regions of the ventral visual pathway (Kanwisher, 2010). We show that this method retains the benefit of defining fROIs in individual subjects without the subjectivity inherent in the traditional handpicked fROI approach. The tools necessary for using this method are available on our website (http://web.mit.edu/bcs/nklab/GSS.shtml).
Some manuscripts under review (to be available soon):
Nieto-Castañon, A., & Fedorenko, E. (submitted). Subject-specific functional localizers increase sensitivity and functional resolution of multi-subject analyses.