Biology subjects

Fedorenko, E.

Publications and source records attributed to Fedorenko, E..

7 recordsLinked to original sources

bioRxiv2018

Gene Expression Correlates of the Cortical Network Underlying Sentence Processing

A pivotal question in modern neuroscience is which genes regulate brain circuits that underlie cognitive functions. However, the field is still in its infancy. Here we report an integrated investigation of the high-level language network (i.e., sentence processing network) in the human cerebral cortex, combining regional gene expression profiles, task fMRI, large-scale neuroimaging meta-analysis, and resting-state functional network approaches. We revealed reliable gene expression-functional network correlations using three different network definition strategies, and identified a consensus set of genes related to connectivity within the sentence-processing network. The genes involved showed enrichment for neural development and actin-related functions, as well as association signals with autism, which can involve disrupted language functioning. Our findings help elucidate the molecular basis of the brains infrastructure for language. The integrative approach described here will be useful to study other complex cognitive traits.

neuroscience↗

bioRxiv2018

High local mutual information drives the response in the human language network

The fronto-temporal language network responds robustly and selectively to sentences. But the features of linguistic input that drive this response and the computations these language areas support remain debated. Two key features of sentences are typically confounded in natural linguistic input: words in sentences a) are semantically and syntactically combinable into phrase- and clause-level meanings, and b) occur in an order licensed by the languages grammar. Inspired by recent psycholinguistic work establishing that language processing is robust to word order violations, we hypothesized that the core linguistic computation is composition, and, thus, can take place even when the word order violates the grammatical constraints of the language. This hypothesis predicts that a linguistic string should elicit a sentence-level response in the language network as long as the words in that string can enter into dependency relationships as in typical sentences. We tested this prediction across two fMRI experiments (total N=47) by introducing a varying number of local word swaps into naturalistic sentences, leading to progressively less syntactically well-formed strings. Critically, local dependency relationships were preserved because combinable words remained close to each other. As predicted, word order degradation did not decrease the magnitude of the BOLD response in the language network, except when combinable words were so far apart that composition among nearby words was highly unlikely. This finding demonstrates that composition is robust to word order violations, and that the language regions respond as strongly as they do to naturalistic linguistic input as long as composition can take place.

neuroscience↗

bioRxiv2017

A robust dissociation among the language, multiple demand, and default mode networks: evidence from inter-region correlations in effect size

Complex cognitive processes, including language, rely on multiple mental operations that are carried out by several large-scale functional networks in the frontal, temporal, and parietal association cortices of the human brain. The central division of cognitive labor is between two fronto-parietal bilateral networks: (a) the multiple demand (MD) network, which supports executive processes, such as working memory and cognitive control, and is engaged by diverse task domains, including language, especially when comprehension gets difficult; and (b) the default mode network (DMN), which supports introspective processes, such as mind wandering, and is active when we are not engaged in processing external stimuli. These two networks are strongly dissociated in both their functional profiles and their patterns of activity fluctuations during naturalistic cognition. Here, we focus on the functional relationship between these two networks and a third network: (c) the fronto-temporal left-lateralized \"core\" language network, which is selectively recruited by linguistic processing. Is the language network distinct and dissociated from both the MD network and the DMN, or is it synchronized and integrated with one or both of them? Recent work has provided evidence for a dissociation between the language network and the MD network. However, the relationship between the language network and the DMN is less clear, with some evidence for coordinated activity patterns and similar response profiles, perhaps due to the role of both in semantic processing. Here we use a novel fMRI approach to examine the relationship among the three networks: we measure the strength of activations in different language, MD, and DMN regions to functional contrasts typically used to identify each network, and then test which regions co-vary in their contrast effect sizes across 60 individuals. We find that effect sizes correlate strongly within each network (e.g., one language region and another language region, or one DMN region and another DMN region), but show little or no correlation for region pairs across networks (e.g., a language region and a DMN region). Thus, we replicate the language/MD network dissociation discovered previously with other methods, and also show that the language network is robustly dissociated from the DMN, overall suggesting that these three networks support distinct computations and contribute to high-level cognition in different ways. Inter-individual differences in effect sizes therefore do not simply reflect general differences in vascularization or attention, but exhibit sensitivity to the functional architecture of the brain. The strength of activation in each network can thus be probed separately in studies that attempt to link neural variability to behavioral or genetic variability.

neuroscience↗

bioRxiv2017

An attempt to replicate a dissociation between syntax and semantics during sentence comprehension reported by Dapretto & Bookheimer (1999, Neuron)

Does processing the meanings of individual words vs. assembling words into phrases and sentences rely on distinct pools of cognitive and neural resources? Many have argued for such a dissociation, although the field is lacking a consensus on which brain region(s) support lexico-semantic vs. syntactic processing. Although some have also argued against such a dissociation, the dominant view in the field remains that distinct brain regions support these two fundamental components of language. One of the earlier and most cited pieces of evidence in favor of this dissociation comes from a paper by Dapretto & Bookheimer (1999, Neuron; DB). Using a sentence meaning comparison task, DB observed two distinct peaks within the left inferior frontal gyrus (LIFG): one more active when comparisons relied on lexico-semantic cues, and another - when they instead relied on syntactic cues. Although the paper has been highly cited over the years, no attempt has been made, to our knowledge, to replicate the original finding. We here report an fMRI study that attempts to do so. Using a combination of three approaches - whole-brain, group-level ROIs, and individual functional ROIs - we fail to replicate the originally reported dissociation. In particular, parts of the LIFG respond reliably more strongly during lexico-semantic than syntactic processing, but no part of the LIFG (including in the region defined around the peak reported by DB) shows the opposite response pattern. We hypothesize that the original result was a false positive, possibly driven by one participant or item given the use of a fixed-effects analysis and a small number of items (8 per condition) and participants (n=8).

neuroscience↗

bioRxiv2017

Multiple Demand (MD) system’s activity predicts individual differences in working memory and fluid intelligence

Numerous brain lesion and fMRI studies have linked individual differences in executive abilities and fluid intelligence to brain regions of the fronto-parietal "multiple-demand" (MD) network. Yet, fMRI studies have yielded conflicting evidence as to whether better executive abilities are associated with stronger or weaker MD activations and whether this relationship is restricted to the MD network. Here, in a large-sample (n=216) fMRI investigation, we found that stronger activity in MD regions - functionally defined in individual participants - was robustly associated with more accurate and faster responses on a spatial working memory task performed in the scanner, as well as fluid intelligence measured independently (n=114). In line with some prior claims about a relationship between language and fluid intelligence, we also found a weak association between activity in the brain regions of the left fronto-temporal language network during an independent passive reading task, and performance on the working memory task. However, controlling for the level of MD activity abolished this relationship, whereas the MD activity-behavior association remained highly reliable after controlling for the level of activity in the language network. Finally, we demonstrate how unreliable MD activity measures, coupled with small sample sizes, could falsely lead to the opposite, negative, association that has been reported in some prior studies. Taken together, these results demonstrate that a core component of individual differences variance in executive abilities and fluid intelligence is selectively and robustly positively associated with the level of activity in the MD network, a result that aligns well with lesion studies.

neuroscience↗

bioRxiv2016

Expanding the language network: Domain-specific hippocampal recruitment during high-level linguistic processing

Language processing requires us to encode linear relations between acoustic forms and map them onto hierarchical relations between meaning units. Such relational binding of linguistic elements might recruit the hippocampus given its engagement by similar operations in other cognitive domains. Historically, hippocampal engagement in online language use has received little attention because patients with hippocampal damage are not aphasic. However, recent studies have found that these patients exhibit language impairments when the demands on flexible relational binding are high, suggesting that the hippocampus does, in fact, contribute to linguistic processing. A fundamental question is thus whether language processing engages domain-general hippocampal mechanisms that are also recruited across other cognitive processes or whether, instead, it relies on certain language-selective areas within the hippocampus. To address this question, we conducted the first systematic analysis of hippocampal engagement during comprehension in healthy adults (n=150 across three experiments) using fMRI. Specifically, we functionally localized putative \"language-regions\" within the hippocampus using a language comprehension task, and found that these regions (i) were selectively engaged by language but not by six non-linguistic tasks; and (ii) were coupled in their activity with the cortical language network during both \"rest\" and especially story comprehension, but not with the domain-general \"multiple-demand (MD)\" network. This functional profile did not generalize to other hippocampal regions that were localized using a non-linguistic, working memory task. These findings suggest that some hippocampal mechanisms that maintain and integrate information during language comprehension are not domain-general but rather belong to the language-specific brain network.\n\nSignificance statementAccording to popular views, language processing is exclusively supported by neocortical mechanisms. However, recent patient studies suggest that language processing may also require the hippocampus, especially when relations among linguistic elements have to be flexibly integrated and maintained. Here, we address a core question about the place of the hippocampus in the cognitive architecture of language: are certain hippocampal operations language-specific rather than domain-general? By extensively characterizing hippocampal recruitment during language comprehension in healthy adults using fMRI, we show that certain hippocampal subregions exhibit signatures of language specificity in both their response profiles and their patterns of activity synchronization with known functional regions in the neocortex. We thus suggest that the hippocampus is a satellite constituent of the language network.

neuroscience↗

bioRxiv2016

Measuring and Modeling Transformations of Information Between Brain Regions with fMRI

In the study of connectivity in large-scale networks of brain regions, a standard assumption is made that the statistical dependence between regions is univariate and linear. However, brain regions encode information in multivariate responses, and neural computations are nonlinear. Multivariate and nonlinear statistical dependence between regions is likely ubiquitous, but it is not captured by current methods. To fill this gap, we introduce a novel analysis framework: fMRI responses are characterized as points in multidimensional spaces, and nonlinear dependence is modeled using artificial neural networks. Converging evidence from multiple experiments shows that nonlinear dependence 1) models mappings between brain regions more accurately than linear dependence, explaining more variance in left-out data; 2) reveals functional subdivisions within cortical networks, and 3) is modulated by the task participants are performing.

neuroscience↗