Grapheme-color synesthetes show peculiarities in their emotional brain: cortical and subcortical evidence from VBM analysis of 3D-T1 and DTI data

Melero, Helena; Peña-Melián, Ángel; Ríos-Lago, Marcos; Pajares, Gonzalo; Hernández-Tamames, Juan Antonio; Álvarez‐Linera, Juan

doi:10.1007/s00221-013-3514-4

Cited by 15 publications

(21 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The literature on automatic classification systems based on fMRI is depth and breadth. From deception detection using fMRI feature selection [3] to emotional analysis of synesthetes [4], the apparently endless list of neurological applications of this technology is growing all the time [5]. Regarding AD in particular, MRI-based automatic classification of scans in AD [6] or advances in the diagnosis of AD patients using fMRI-derived features [7] have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Voxel-Based Diagnosis of Alzheimer's Disease Using Classifier Ensembles

Armañanzas¹,

Iglesias²,

Morales³

et al. 2017

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

Functional magnetic resonance imaging (fMRI) is one of the most promising noninvasive techniques for early Alzheimer's disease (AD) diagnosis. In this paper, we explore the application of different machine learning techniques to the classification of fMRI data for this purpose. The functional images were first preprocessed using the statistical parametric mapping toolbox to output individual maps of statistically activated voxels. A fast filter was applied afterwards to select voxels commonly activated across demented and nondemented groups. Four feature ranking selection techniques were embedded into a wrapper scheme using an inner-outer loop for the selection of relevant voxels. The wrapper approach was guided by the performance of six pattern recognition models, three of which were ensemble classifiers based on stochastic searches. Final classification performance was assessed from the nested internal and external cross-validation loops taking several voxel sets ordered by importance. Numerical performance was evaluated using statistical tests, and the best combination of voxel selection and classification reached a 97.14% average accuracy. Results repeatedly pointed out Brodmann regions with distinct activation patterns between demented and nondemented profiles, indicating that the machine learning analysis described is a powerful method to detect differences in several brain regions between both groups.

show abstract

Section: Introductionmentioning

confidence: 99%

Voxel-Based Diagnosis of Alzheimer's Disease Using Classifier Ensembles

Armañanzas¹,

Iglesias²,

Morales³

et al. 2017

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

show abstract

“…It is important to note that our result is in fact compatible with a number of other studies --in both synaesthesia and elsewhere --all sho i g edu ed FA i ta de ith additio al behavioural experiences. These include, for example, studies associating posterior tract reductions in FA with visual and other hallucinations (Ashtari et al, 2007;Fujiwara et al, 2007 (Melero et al, 2013;Hänggi et al, 2008;and Whitaker et al, 2014 respectively). Yet other researchers may have been in a position to find reduced FA but stated a priori they would not to explore this direction within their results (Jäncke et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

Social responsiveness to inanimate entities: Altered white matter in a ‘social synaesthesia’

et al. 2016

View full text Add to dashboard Cite

, M (2016) Social responsiveness to inanimate entities: altered white matter in a 'social synaesthesia '. Neuropsychologia, This version is available from Sussex Research Online: http://sro.sussex.ac.uk/64745/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. 1 Social responsiveness to inanimate entities:Alte ed hite atte i a so ial s aesthesia ABSTRACTJudgments about personalities and social traits can be made by relatively brief exposure to animate living things. Here we show that unusual architecture in the microstructure of the human brain is related to atypical mental projections of personality and social structure onto things that are neither living nor animate. Our participants experience automatic, life-long and consistent crossmodal associations between language sequences (e.g., letters, numbers and days) and complex personifications (e.g., A is a businessman; 7 a good-atu ed o a . Pa ti ipa ts ith this O di al Li guisti Pe so ifi atio "i e & Hu a d, hi h e des i e he e as a fo of so ial synaesthesia, showed lower fractional anisotropy (FA) values in five clusters at whole-brain significance, compared with non-synaesthetes (in the pre-postcentral gyrus/ dorsal corticospinal tract, left superior corona radiata, and the genu, body and left side of the corpus callosum). We found no regions of the brain with increased FA in synaesthetes. A number of these regions with reduced FA play a role in social responsiveness, and our study is the first to show that unusual differences in white matter microstructure in these regions is associated with compelling feelings of social cohesion and personality towards non-animate entities. We show too that altered patterns of connectivity known to t pif s aesthesia a e ot li ited to a ia ts i ol i g a e gi g of the se ses , ut also e te d to 2 what might be thought of as a cogno-social variant of synaesthesia, linking language and personality attributes in this surprising way.

show abstract

“…The emotional component has been emphasized in recent publications (Cytowic and Eagleman 2009) and synesthetes' accounts reveal that emotion can act as an inducer but also as a concurrent . Moreover, in the last years, neuroanatomical research has found variations in areas of the synesthetic brain that participate in the emotional processing of the world (Hupé et al 2011;Jäncke et al 2009;Melero et al 2013). Nevertheless, at present, emotion is still not fully integrated in explanatory neurocognitive models.…”

Section: ) the Key Point Of Synesthesia: The Emotional Binding Systemmentioning

confidence: 99%

“…Recent research has provided evidence of structural variations in the synesthetic brain (Hänggi et al 2008;Hänggi et al 2011;Hupé et al 2011;Jäncke et al 2009;Melero et al 2013;Scholte 2007, 2010;Weiss and Fink 2009). Nonetheless, it is still too soon to conclude if these variations (direct and/or indirect, anatomically and/or functionally altered pathways) are present in every synesthete.…”

Section: A) the Neuroanatomical Dimensionmentioning

confidence: 99%

“…Currently, taking into account neurodynamics and the emotional component emphasized above, the regions of interest have been extended. In order to complete the synesthetic brain puzzle, the emotional networks, including the subcortical nucleus, have been explored and a neurocognitive explanatory hypothesis, namely the Emotional Binding System hypothesis, has been proposed (Melero et al 2013). Nonetheless, neuroanatomical information is not sufficient to understand the dynamics of synesthesia…”

Section: A) the Neuroanatomical Dimensionmentioning

confidence: 99%

See 1 more Smart Citation

Synesthesia: a return to the body

Melero

2014

THS

Self Cite

View full text Add to dashboard Cite

Synesthesia is a neurological phenomenon whose nature and etiology remain unknown. In this paper, I apply the neurophenomenological perspective to reflect on the very nature of inducers and concurrents, including their perceptual and conceptual dimensions and their stability over time. Additionally, I analyze the role of attention and its influence over synesthesia, which contributes to the difficulties that we, synesthetes, find when sharing our personal experiences with non-synesthetes. Finally, I expose some examples of the current neuroscientific data and propose some insights into the embodied character of synesthesia, stressing the key role of its emotional component. I conclude describing the clinical applications of the findings in the field of synesthesia and their implications for the understanding of cognition in general.

show abstract

Grapheme-color synesthetes show peculiarities in their emotional brain: cortical and subcortical evidence from VBM analysis of 3D-T1 and DTI data

Cited by 15 publications

References 60 publications

Voxel-Based Diagnosis of Alzheimer's Disease Using Classifier Ensembles

Voxel-Based Diagnosis of Alzheimer's Disease Using Classifier Ensembles

Social responsiveness to inanimate entities: Altered white matter in a ‘social synaesthesia’

Synesthesia: a return to the body

Contact Info

Product

Resources

About