scholarly journals A double dissociation in sensitivity to verb and noun semantics across cortical networks

2018 ◽  
Author(s):  
Giulia V. Elli ◽  
Connor Lane ◽  
Marina Bedny
Keyword(s):  
Pattern Analysis ◽  
Light Emission ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Cortical Networks ◽  
Multivoxel Pattern Analysis ◽  
Double Dissociation ◽  
Neural Organization ◽  
Left Posterior

AbstractWhat is the neural organization of the mental lexicon? Previous research suggests that partially distinct cortical networks are active during verb and noun processing. Are these networks preferentially involved in representing the meanings of verbs as opposed to nouns? We used multivoxel pattern analysis (MVPA) to investigate whether brain regions that are more active during verb than noun processing are also more sensitive to distinctions among their preferred lexical class. Participants heard four types of verbs (light emission, sound emission, hand-related actions, mouth-related actions) and four types of nouns (birds, mammals, manmade places, natural places). As previously shown, the left posterior middle temporal gyrus (LMTG) and inferior frontal gyrus (LIFG) responded more to verbs, whereas areas in the inferior parietal lobule (LIP), precuneus (LPC), and inferior temporal (LIT) cortex responded more to nouns. MVPA revealed a double-dissociation in semantic sensitivity: classification was more accurate among verbs than nouns in the LMTG, and among nouns than verbs in the LIP, LPC, and LIT. However, classification was similar for verbs and nouns in the LIFG, and above chance for the non-preferred category in all regions. These results suggest that the meanings of verbs and nouns are represented in partially non-overlapping networks.

scholarly journals A Double Dissociation in Sensitivity to Verb and Noun Semantics Across Cortical Networks

2019 ◽  
Vol 29 (11) ◽  
pp. 4803-4817 ◽  
Author(s):  
Giulia V Elli ◽  
Connor Lane ◽  
Marina Bedny
Keyword(s):  
Pattern Analysis ◽  
Light Emission ◽  
Inferior Frontal Gyrus ◽  
Middle Temporal Gyrus ◽  
Cortical Networks ◽  
Multivoxel Pattern Analysis ◽  
Grammatical Class ◽  
Double Dissociation ◽  
Neural Organization ◽  
Left Posterior

AbstractWhat is the neural organization of the mental lexicon? Previous research suggests that partially distinct cortical networks are active during verb and noun processing, but what information do these networks represent? We used multivoxel pattern analysis (MVPA) to investigate whether these networks are sensitive to lexicosemantic distinctions among verbs and among nouns and, if so, whether they are more sensitive to distinctions among words in their preferred grammatical class. Participants heard 4 types of verbs (light emission, sound emission, hand-related actions, mouth-related actions) and 4 types of nouns (birds, mammals, manmade places, natural places). As previously shown, the left posterior middle temporal gyrus (LMTG+), and inferior frontal gyrus (LIFG) responded more to verbs, whereas the inferior parietal lobule (LIP), precuneus (LPC), and inferior temporal (LIT) cortex responded more to nouns. MVPA revealed a double-dissociation in lexicosemantic sensitivity: classification was more accurate among verbs than nouns in the LMTG+, and among nouns than verbs in the LIP, LPC, and LIT. However, classification was similar for verbs and nouns in the LIFG, and above chance for the nonpreferred category in all regions. These results suggest that the lexicosemantic information about verbs and nouns is represented in partially nonoverlapping networks.

scholarly journals Brain Activation of College Students in China With Premenstrual Syndrome Localized by BOLD-fMRI

2021 ◽  
Author(s):  
Dongmei Gao ◽  
Mingzhou Gao ◽  
Li An ◽  
Yanhong Yu ◽  
Jieqiong Wang ◽  
...  
Keyword(s):  
College Students ◽  
Premenstrual Syndrome ◽  
Brain Area ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Anterior Lobe ◽  
Middle Temporal Gyrus ◽  
Cerebellar Tonsil ◽  
Bold Fmri ◽  
Significant Difference

Abstract Background: Most studies on the mechanism behind premenstrual syndrome (PMS) have focused on fluctuating hormones, but little evidence exists regarding functional abnormalities in the affected brain regions of college students. Thus, the aim of this study is to localize PMS's abnormal brain regions by BOLD-fMRI in college students.Methods: Thirteen PMS patients and fifteen healthy control (HC) subjects underwent a BOLD-fMRI scan during the luteal phase induced by depressive emotion pictures. The BOLD-fMRI data were processed by SPM 8 software and rest software based on MATLAB platform. Each cluster volume threshold (cluster) was greater than 389 continuous voxels, and the brain area with single voxel threshold P < 0.05 (after correction) was defined as the area with a significant difference. The emotion report form and the instruction implementation checklist were used to evaluate the emotion induced by picture.Results: Compared to the HC, right inferior occipital gyrus, right middle occipital gyrus, right lingual gyrus, right fusiform gyrus, right inferior temporal gyrus, cerebelum_crus1_R，cerebelum_6_R, culmen, the cerebellum anterior lobe, tuber, cerebellar tonsil of PMS patients were enhanced activation. Sub-lobar，sub-gyral，extra-nuclear，right orbit part of superior frontal gyrus, right middle temporal gyrus, right Orbit part of inferior frontal gyrus, limbic lobe, right insula, bilateral anterior and adjacent cingulate gyrus, bilateral caudate, caudate head, bilateral putamen, left globus pallidus were decreased activation.Conclusion: Our findings may improve our understanding of the neural mechanisms involved in PMS.

scholarly journals Awake fMRI Reveals Brain Regions for Novel Word Detection in Dogs

2017 ◽  
Author(s):  
Ashley Prichard ◽  
Peter F. Cook ◽  
Mark Spivak ◽  
Raveena Chhibber ◽  
Gregory S. Berns
Keyword(s):  
Caudate Nucleus ◽  
Pattern Analysis ◽  
Novelty Detection ◽  
Temporal Cortex ◽  
Brain Regions ◽  
Neural Basis ◽  
Multivoxel Pattern Analysis ◽  
Word Detection ◽  
Left Caudate ◽  
Basic Level

AbstractHow do dogs understand human words? At a basic level, understanding would require the discrimination of words from non-words. To determine the mechanisms of such a discrimination, we trained 12 dogs to retrieve two objects based on object names, then probed the neural basis for these auditory discriminations using awake-fMRI. We compared the neural response to these trained words relative to “oddball” pseudowords the dogs had not heard before. Consistent with novelty detection, we found greater activation for pseudowords relative to trained words bilaterally in the parietotemporal cortex. To probe the neural basis for representations of trained words, searchlight multivoxel pattern analysis (MVPA) revealed that a subset of dogs had clusters of informative voxels that discriminated between the two trained words. These clusters included the left temporal cortex and amygdala, left caudate nucleus, and thalamus. These results demonstrate that dogs’ processing of human words utilizes basic processes like novelty detection, and for some dogs, may also include auditory and hedonic representations.

scholarly journals Vision-to-value transformations in artificial neural networks and human brain

2021 ◽  
Author(s):  
Trung Quang Pham ◽  
Takaaki Yoshimoto ◽  
Haruki Niwa ◽  
Haruka K Takahashi ◽  
Ryutaro Uchiyama ◽  
...  
Keyword(s):  
Neural Networks ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Brain Regions ◽  
Transformation Process ◽  
Neural Mechanisms ◽  
Association Cortex ◽  
Multivoxel Pattern Analysis ◽  
Parietal Cortices ◽  
The Relationship

AbstractHumans and now computers can derive subjective valuations from sensory events although such transformation process is essentially unknown. In this study, we elucidated unknown neural mechanisms by comparing convolutional neural networks (CNNs) to their corresponding representations in humans. Specifically, we optimized CNNs to predict aesthetic valuations of paintings and examined the relationship between the CNN representations and brain activity via multivoxel pattern analysis. Primary visual cortex and higher association cortex activities were similar to computations in shallow CNN layers and deeper layers, respectively. The vision-to-value transformation is hence proved to be a hierarchical process which is consistent with the principal gradient that connects unimodal to transmodal brain regions (i.e. default mode network). The activity of the frontal and parietal cortices was approximated by goal-driven CNN. Consequently, representations of the hidden layers of CNNs can be understood and visualized by their correspondence with brain activity–facilitating parallels between artificial intelligence and neuroscience.

scholarly journals The neural bases of program comprehension: a coordinate-based fMRI meta-analysis

2021 ◽  
Author(s):  
Yoshiharu Ikutani ◽  
Takeshi D. Itoh ◽  
Takatomi Kubo
Keyword(s):  
Brain Activity ◽  
Meta Analysis ◽  
Inferior Frontal Gyrus ◽  
Posterior Part ◽  
Program Comprehension ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Activation Patterns ◽  
Neural Bases ◽  
Kernel Density Analysis

AbstractThe understanding of brain activity during program comprehension have advanced thanks to noninvasive neuroimaging techniques, such as functional magnetic resonance imaging (fMRI). However, individual neuroimaging studies of program comprehension often provided inconsistent results and made it difficult to identify the neural bases. To identify the essential brain regions, this study performed a small meta-analysis on recent fMRI studies of program comprehension using multilevel kernel density analysis (MKDA). Our analysis identified a set of brain regions consistently activated in various program comprehension tasks. These regions consisted of three clusters, each of which centered at the left inferior frontal gyrus pars triangularis (IFG Tri), posterior part of middle temporal gyrus (pMTG), and right middle frontal gyrus (MFG). Additionally, subsequent analyses revealed relationships among the activation patterns in the previous studies and multiple cognitive functions. These findings suggest that program comprehension mainly recycles the language-related networks and partially employs other domain-general resources in the human brain.

scholarly journals Parental education is associated with differential engagement of neural pathways during inhibitory control

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Christopher N. Cascio ◽  
Nina Lauharatanahirun ◽  
Gwendolyn M. Lawson ◽  
Martha J. Farah ◽  
Emily B. Falk
Keyword(s):  
Socioeconomic Status ◽  
Response Inhibition ◽  
Parental Education ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Neural Pathways ◽  
Performance Differences ◽  
Education Performance

AbstractResponse inhibition and socioeconomic status (SES) are critical predictors of many important outcomes, including educational attainment and health. The current study extends our understanding of SES and cognition by examining brain activity associated with response inhibition, during the key developmental period of adolescence. Adolescent males (N = 81), aged 16–17, completed a response inhibition task while undergoing fMRI brain imaging and reported on their parents’ education, one component of socioeconomic status. A region of interest analysis showed that parental education was associated with brain activation differences in the classic response inhibition network (right inferior frontal gyrus + subthalamic nucleus + globus pallidus) despite the absence of consistent parental education-performance effects. Further, although activity in our main regions of interest was not associated with performance differences, several regions that were associated with better inhibitory performance (ventromedial prefrontal cortex, middle frontal gyrus, middle temporal gyrus, amygdala/hippocampus) also differed in their levels of activation according to parental education. Taken together, these results suggest that individuals from households with higher versus lower parental education engage key brain regions involved in response inhibition to differing degrees, though these differences may not translate into performance differences.

scholarly journals Neural Representation of Articulable and Inarticulable Novel Sound Contrasts: The Role of the Dorsal Stream

2020 ◽  
Vol 1 (3) ◽  
pp. 339-364
Author(s):  
David I. Saltzman ◽  
Emily B. Myers
Keyword(s):  
Right Hemisphere ◽  
Inferior Frontal Gyrus ◽  
Speech Sound ◽  
Dorsal Stream ◽  
Brain Regions ◽  
Sine Wave ◽  
Neural Representation ◽  
Middle Temporal Gyrus ◽  
Speech Sounds ◽  
Native Speech

The extent that articulatory information embedded in incoming speech contributes to the formation of new perceptual categories for speech sounds has been a matter of discourse for decades. It has been theorized that the acquisition of new speech sound categories requires a network of sensory and speech motor cortical areas (the “dorsal stream”) to successfully integrate auditory and articulatory information. However, it is possible that these brain regions are not sensitive specifically to articulatory information, but instead are sensitive to the abstract phonological categories being learned. We tested this hypothesis by training participants over the course of several days on an articulable non-native speech contrast and acoustically matched inarticulable nonspeech analogues. After reaching comparable levels of proficiency with the two sets of stimuli, activation was measured in fMRI as participants passively listened to both sound types. Decoding of category membership for the articulable speech contrast alone revealed a series of left and right hemisphere regions outside of the dorsal stream that have previously been implicated in the emergence of non-native speech sound categories, while no regions could successfully decode the inarticulable nonspeech contrast. Although activation patterns in the left inferior frontal gyrus, the middle temporal gyrus, and the supplementary motor area provided better information for decoding articulable (speech) sounds compared to the inarticulable (sine wave) sounds, the finding that dorsal stream regions do not emerge as good decoders of the articulable contrast alone suggests that other factors, including the strength and structure of the emerging speech categories are more likely drivers of dorsal stream activation for novel sound learning.

scholarly journals Distributed Patterns of Reactivation Predict Vividness of Recollection

2015 ◽  
Vol 27 (10) ◽  
pp. 2000-2018 ◽  
Author(s):  
Marie St-Laurent ◽  
Hervé Abdi ◽  
Bradley R. Buchsbaum
Keyword(s):  
Classification Accuracy ◽  
Memory Retrieval ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Brain Regions ◽  
Subjective Quality ◽  
Multivoxel Pattern Analysis ◽  
With Memory ◽  
Objective Marker

According to the principle of reactivation, memory retrieval evokes patterns of brain activity that resemble those instantiated when an event was first experienced. Intuitively, one would expect neural reactivation to contribute to recollection (i.e., the vivid impression of reliving past events), but evidence of a direct relationship between the subjective quality of recollection and multiregional reactivation of item-specific neural patterns is lacking. The current study assessed this relationship using fMRI to measure brain activity as participants viewed and mentally replayed a set of short videos. We used multivoxel pattern analysis to train a classifier to identify individual videos based on brain activity evoked during perception and tested how accurately the classifier could distinguish among videos during mental replay. Classification accuracy correlated positively with memory vividness, indicating that the specificity of multivariate brain patterns observed during memory retrieval was related to the subjective quality of a memory. In addition, we identified a set of brain regions whose univariate activity during retrieval predicted both memory vividness and the strength of the classifier's prediction irrespective of the particular video that was retrieved. Our results establish distributed patterns of neural reactivation as a valid and objective marker of the quality of recollection.

scholarly journals Executive Semantic Processing Is Underpinned by a Large-scale Neural Network: Revealing the Contribution of Left Prefrontal, Posterior Temporal, and Parietal Cortex to Controlled Retrieval and Selection Using TMS

2012 ◽  
Vol 24 (1) ◽  
pp. 133-147 ◽  
Author(s):  
Carin Whitney ◽  
Marie Kirk ◽  
Jamie O'Sullivan ◽  
Matthew A. Lambon Ralph ◽  
Elizabeth Jefferies
Keyword(s):  
Semantic Processing ◽  
Large Scale ◽  
Semantic Representation ◽  
Inferior Frontal Gyrus ◽  
Semantic Knowledge ◽  
Middle Temporal Gyrus ◽  
Neural Basis ◽  
Healthy Human ◽  
Left Posterior ◽  
Domain Dependence

To understand the meanings of words and objects, we need to have knowledge about these items themselves plus executive mechanisms that compute and manipulate semantic information in a task-appropriate way. The neural basis for semantic control remains controversial. Neuroimaging studies have focused on the role of the left inferior frontal gyrus (LIFG), whereas neuropsychological research suggests that damage to a widely distributed network elicits impairments of semantic control. There is also debate about the relationship between semantic and executive control more widely. We used TMS in healthy human volunteers to create “virtual lesions” in structures typically damaged in patients with semantic control deficits: LIFG, left posterior middle temporal gyrus (pMTG), and intraparietal sulcus (IPS). The influence of TMS on tasks varying in semantic and nonsemantic control demands was examined for each region within this hypothesized network to gain insights into (i) their functional specialization (i.e., involvement in semantic representation, controlled retrieval, or selection) and (ii) their domain dependence (i.e., semantic or cognitive control). The results revealed that LIFG and pMTG jointly support both the controlled retrieval and selection of semantic knowledge. IPS specifically participates in semantic selection and responds to manipulations of nonsemantic control demands. These observations are consistent with a large-scale semantic control network, as predicted by lesion data, that draws on semantic-specific (LIFG and pMTG) and domain-independent executive components (IPS).

scholarly journals Unification of Speaker and Meaning in Language Comprehension: An fMRI Study

2009 ◽  
Vol 21 (11) ◽  
pp. 2085-2099 ◽  
Author(s):  
Cathelijne M. J. Y. Tesink ◽  
Karl Magnus Petersson ◽  
Jos J. A. van Berkum ◽  
Daniëlle van den Brink ◽  
Jan K. Buitelaar ◽  
...  
Keyword(s):  
Language Comprehension ◽  
Inferior Frontal Gyrus ◽  
Social Background ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
World Knowledge ◽  
Sources Of Information ◽  
Related Information ◽  
Fmri Study ◽  
Crucial Component

When interpreting a message, a listener takes into account several sources of linguistic and extralinguistic information. Here we focused on one particular form of extralinguistic information, certain speaker characteristics as conveyed by the voice. Using functional magnetic resonance imaging, we examined the neural structures involved in the unification of sentence meaning and voice-based inferences about the speaker's age, sex, or social background. We found enhanced activation in the inferior frontal gyrus bilaterally (BA 45/47) during listening to sentences whose meaning was incongruent with inferred speaker characteristics. Furthermore, our results showed an overlap in brain regions involved in unification of speaker-related information and those used for the unification of semantic and world knowledge information [inferior frontal gyrus bilaterally (BA 45/47) and left middle temporal gyrus (BA 21)]. These findings provide evidence for a shared neural unification system for linguistic and extralinguistic sources of information and extend the existing knowledge about the role of inferior frontal cortex as a crucial component for unification during language comprehension.

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