Demonstration and validation of Kernel Density Estimation for spatial meta-analyses in cognitive neuroscience using simulated data

The data presented in this article are related to the research article entitled "Convergence of semantics and emotional expression within the IFG pars orbitalis" (Belyk et al., 2017) [1]. The research article reports a spatial meta-analysis of brain imaging experiments on the perception of semantic compared to emotional communicative signals in humans. This Data in Brief article demonstrates and validates the use of Kernel Density Estimation (KDE) as a novel statistical approach to neuroimaging data. First, we performed a side-by-side comparison of KDE with a previously published meta-analysis that applied activation likelihood estimation, which is the predominant approach to meta-analyses in cognitive neuroscience. Second, we analyzed data simulated with known spatial properties to test the sensitivity of KDE to varying degrees of spatial separation. KDE successfully detected true spatial differences in simulated data and displayed few false positives when no true differences were present. R code to simulate and analyze these data is made publicly available to facilitate the further evaluation of KDE for neuroimaging data and its dissemination to cognitive neuroscientists

Demonstration and validation of Kernel Density Estimation for spatial meta-analyses in cognitive neuroscience using simulated data

The data presented in this article are related to the research article entitled “Convergence of semantics and emotional expression within the IFG pars orbitalis” (Belyk et al., 2017) [1]. The research article reports a spatial meta-analysis of brain imaging experiments on the perception of semantic compared to emotional communicative signals in humans. This Data in Brief article demonstrates and validates the use of Kernel Density Estimation (KDE) as a novel statistical approach to neuroimaging data. First, we performed a side-by-side comparison of KDE with a previously published meta-analysis that applied activation likelihood estimation, which is the predominant approach to meta-analyses in cognitive neuroscience. Second, we analyzed data simulated with known spatial properties to test the sensitivity of KDE to varying degrees of spatial separation. KDE successfully detected true spatial differences in simulated data and displayed few false positives when no true differences were present. R code to simulate and analyze these data is made publicly available to facilitate the further evaluation of KDE for neuroimaging data and its dissemination to cognitive neuroscientists

Meta-analytic connectivity modeling of the left and right inferior frontal gyri

Background: Neurocognitive models of language processing highlight the role of the left inferior frontal gyrus (IFG) in the functional network underlying language. Furthermore, neuroscience research has shown that IFG is not a uniform region anatomically, cytoarchitectonically or functionally. However, no previous study explored the language-related functional connectivity patterns of IFG subdivisions using a meta-analytic connectivity modeling (MACM) approach. Purpose: The present MACM study aimed to identify language-related coactivation patterns of the left and right IFG subdivisions. Method: Six regions of interest (ROIs) were defined using a probabilistic brain atlas corresponding to pars opercularis, pars triangularis and pars orbitalis of IFG in both hemispheres. The ROIs were used to search the BrainMap functional database to identify neuroimaging experiments with healthy, right-handed participants reporting language-related activations in each ROI. Activation likelihood estimation analyses were then performed on the foci extracted from the identified studies to compute functional convergence for each ROI, which was also contrasted with the other ROIs within the same hemisphere. Results: A primarily left-lateralized functional network was revealed for the left and right IFG subdivisions. The left-hemispheric ROIs exhibited more robust coactivation than the right-hemispheric ROIs. Particularly, the left pars opercularis was associated with the most extensive coactivation pattern involving bilateral frontal, bilateral parietal, left temporal, left subcortical, and right cerebellar regions, while the left pars triangularis and orbitalis revealed a predominantly left-lateralized involvement of frontotemporal regions. Conclusion: The findings align with the neurocognitive models of language processing that propose a division of labor among the left IFG subdivisions and their respective functional networks. Also, the opercular part of left IFG stands out as a major hub in the language network with connections to diverse cortical, subcortical and cerebellar structures

THE LEFT HEMISPHERE’S STRUCTURAL CONNECTIVITY FOR THE INFERIOR FRONTAL GYRUS, STRIATUM, AND THALAMUS, AND INTRA-THALAMIC TOPOGRAPHY

The neuroanatomy of language cognition has an extensive history of scientific interest and inquiry. Over a century of behavioral lesion studies and decades of functional neuroimaging research have established the left hemisphere’s inferior frontal gyrus (IFG) as a critical region for speech and language processing. This region’s subcortical projections are thought to be instrumental for supporting and integrating the cognitive functions of the language network. However, only a subset of these projections have been shown to exist in humans, and structural evidence of pars orbitalis’ subcortical circuitry has been limited to non-human primates. This thesis demonstrates direct, intra-structural connectivity of each of the left IFG’s gyral regions with the thalamus and the putamen in humans, using high-angular, deterministic tractography. Novel processing and analysis methods elucidated evidence of predominantly segregated cortical circuits within the thalamus, and suggested the presence of parallel circuits for motor/language integration along the length of the putamen

Functional connectivity within the voice perception network and its behavioural relevance

International audienceRecognizing who is speaking is a cognitive ability characterized by considerable individual differences, which could relate to the inter-individual variability observed in voice-elicited BOLD activity. Since voice perception is sustained by a complex brain network involving temporal voice areas (TVAs) and, even if less consistently, extra-temporal regions such as frontal cortices, functional connectivity (FC) during an fMRI voice localizer (passive listening of voices vs non-voices) has been computed within twelve temporal and frontal voice-sensitive regions ("voice patches") individually defined for each subject (N ¼ 90) to account for inter-individual variability. Results revealed that voice patches were positively co-activated during voice listening and that they were characterized by different FC pattern depending on the location (anterior/posterior) and the hemisphere. Importantly, FC between right frontal and temporal voice patches was behaviorally relevant: FC significantly increased with voice recognition abilities as measured in a voice recognition test performed outside the scanner. Hence, this study highlights the importance of frontal regions in voice perception and it supports the idea that looking at FC between stimulus-specific and higher-order frontal regions can help understanding individual differences in processing social stimuli such as voices

Multiple prosodic meanings are conveyed through separate pitch ranges: Evidence from perception of focus and surprise in Mandarin Chinese

F0 variation is a crucial feature in speech prosody, which can convey linguistic information such as focus and paralinguistic meanings such as surprise. How can multiple layers of information be represented with F0 in speech: are they divided into discrete layers of pitch or overlapped without clear divisions? We investigated this question by assessing pitch perception of focus and surprise in Mandarin Chinese. Seventeen native Mandarin listeners rated the strength of focus and surprise conveyed by the same set of synthetically manipulated sentences. An fMRI experiment was conducted to assess neural correlates of the listeners’ perceptual response to the stimuli. The results showed that behaviourally, the perceptual threshold for focus was 3 semitones and that for surprise was 5 semitones above the baseline. Moreover, the pitch range of 5-12 semitones above the baseline signalled both focus and surprise, suggesting a considerable overlap between the two types of prosodic information within this range. The neuroimaging data positively correlated with the variations in behavioural data. Also, a ceiling effect was found as no significant behavioural differences or neural activities were shown after reaching a certain pitch level for the perception of focus and surprise respectively. Together, the results suggest that different layers of prosodic information are represented in F0 through different pitch ranges: paralinguistic information is represented at a pitch range beyond that used by linguistic information. Meanwhile, the representation of paralinguistic information is achieved without obscuring linguistic prosody, thus allowing F0 to represent the two layers of information in parallel

Laughter as a paradigm of socio-emotional signal processing in dementia

Laughter is a fundamental communicative signal in our relations with other people and is used to convey a diverse repertoire of social and emotional information. It is therefore potentially a useful probe of impaired socio-emotional signal processing in neurodegenerative diseases. Here we investigated the cognitive and affective processing of laughter in forty-seven patients representing all major syndromes of frontotemporal dementia, a disease spectrum characterised by severe socio-emotional dysfunction (twenty-two with behavioural variant frontotemporal dementia, twelve with semantic variant primary progressive aphasia, thirteen with nonfluent-agrammatic variant primary progressive aphasia), in relation to fifteen patients with typical amnestic Alzheimer’s disease and twenty healthy age-matched individuals. We assessed cognitive labelling (identification) and valence rating (affective evaluation) of samples of spontaneous (mirthful and hostile) and volitional (posed) laughter versus two auditory control conditions (a synthetic laughter-like stimulus and spoken numbers). Neuroanatomical associations of laughter processing were assessed using voxel-based morphometry of patients’ brain MR images. While all dementia syndromes were associated with impaired identification of laughter subtypes relative to healthy controls, this was significantly more severe overall in frontotemporal dementia than in Alzheimer’s disease and particularly in the behavioural and semantic variants, which also showed abnormal affective evaluation of laughter. Over the patient cohort, laughter identification accuracy was correlated with measures of daily-life socio-emotional functioning. Certain striking syndromic signatures emerged, including enhanced liking for hostile laughter in behavioural variant frontotemporal dementia, impaired processing of synthetic laughter in the nonfluent-agrammatic variant (consistent with a generic complex auditory perceptual deficit) and enhanced liking for numbers (‘numerophilia’) in the semantic variant. Across the patient cohort, overall laughter identification accuracy correlated with regional grey matter in a core network encompassing inferior frontal and cingulo-insular cortices; and more specific correlates of laughter identification accuracy were delineated in cortical regions mediating affective disambiguation (identification of hostile and posed laughter in orbitofrontal cortex) and authenticity (social intent) decoding (identification of mirthful and posed laughter in anteromedial prefrontal cortex) (all p<0.05 after correction for multiple voxel-wise comparisons over the whole brain). These findings reveal a rich diversity of cognitive and affective laughter phenotypes in canonical dementia syndromes and suggest that laughter is an informative probe of neural mechanisms underpinning socio-emotional dysfunction in neurodegenerative disease