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Empathising-systemising along the unimodal-transmodal axis

Poster No:

790 

Submission Type:

Abstract Submission 

Authors:

Marcin Radecki1,2, Amin Saberi3,4,5, Bin Wan3,4, Dorothea Floris6,7,8, Richard Bethlehem9, Meng-Chuan Lai2,10,11, Michael Lombardo12, Luca Cecchetti1, Simon Baron-Cohen2, Sofie Valk3,4,5

Institutions:

1Social and Affective Neuroscience Group, IMT School for Advanced Studies Lucca, Lucca, Italy, 2Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, 3Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 4Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany, 5Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany, 6Methods of Plasticity Research, Department of Psychology, University of Zürich, Zürich, Switzerland, 7Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, 8Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands, 9Department of Psychology, University of Cambridge, Cambridge, United Kingdom, 10The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada, 11Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada, 12Laboratory for Autism and Neurodevelopmental Disorders, Istituto Italiano di Tecnologia, Rovereto, Italy

First Author:

Marcin Radecki  
Social and Affective Neuroscience Group, IMT School for Advanced Studies Lucca|Autism Research Centre, Department of Psychiatry, University of Cambridge
Lucca, Italy|Cambridge, United Kingdom

Co-Author(s):

Amin Saberi  
Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences|Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich|Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf
Leipzig, Germany|Jülich, Germany|Düsseldorf, Germany
Bin Wan  
Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences|Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich
Leipzig, Germany|Jülich, Germany
Dorothea Floris  
Methods of Plasticity Research, Department of Psychology, University of Zürich|Donders Institute for Brain, Cognition and Behaviour, Radboud University|Department of Cognitive Neuroscience, Radboud University Medical Center
Zürich, Switzerland|Nijmegen, Netherlands|Nijmegen, Netherlands
Richard Bethlehem  
Department of Psychology, University of Cambridge
Cambridge, United Kingdom
Meng-Chuan Lai  
Autism Research Centre, Department of Psychiatry, University of Cambridge|The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health|Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto
Cambridge, United Kingdom|Toronto, ON, Canada|Toronto, ON, Canada
Michael Lombardo  
Laboratory for Autism and Neurodevelopmental Disorders, Istituto Italiano di Tecnologia
Rovereto, Italy
Luca Cecchetti  
Social and Affective Neuroscience Group, IMT School for Advanced Studies Lucca
Lucca, Italy
Simon Baron-Cohen  
Autism Research Centre, Department of Psychiatry, University of Cambridge
Cambridge, United Kingdom
Sofie Valk  
Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences|Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich|Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf
Leipzig, Germany|Jülich, Germany|Düsseldorf, Germany
E-Poster

Introduction:

The unimodal-transmodal gradient of functional organisation (G1) [1] was shown to differentially situate meta-analytic activations underlying cognitive and affective empathy – understanding others' mental states and responding to them with an appropriate emotion, respectively [2]. Leveraging this empathic distinction, we hypothesised that G1 reflects the "D-score" – the drive to systemise (understand and build systems) relative to empathise, as proposed by the Empathising-Systemising (E-S) theory [3].

Methods:

We included 100 typical adults (Mage = 29 ± 7 years, range = 18-48; 43 F) with two 3T multi-band resting-state acquisitions [4]. For each participant, two 32k-fsLR time series were parcellated using multimodal solutions [5] (Fig. 1A), functional-connectivity (rsFC) matrices were averaged, and 10 gradients were extracted via diffusion-map embedding with normative HCP gradients (N = 207 [6]) as the reference (Fig. 1B) in a Procrustes alignment [7] (Fig. 1C). G1 loadings were averaged within: two meta-analytically thresholded empathy clusters (Cognitive and Affective) [2]; four novel empathy clusters building on these (Fig. 1E); and seven canonical rsFC networks [8] (Fig. 1D). The D-score was the difference between standardised scores on the 40-item Empathy Quotient (EQ) and 75-item Systemising Quotient-R (SQ) [9]. From each score, we subtracted the mean and divided the outcome by the maximum possible score, such that D-score = S – E (i.e. the higher the D-score, the stronger the drive to systemise relative to empathise). Based on the D-score percentiles, we identified those of Type E ("empathisers"; 0-35th), Type B ("balanced"; 35-65th), and Type S ("systemisers"; 65-100th) [9, 10]. The EQ and SQ had good-to-excellent internal consistency (Cronbach's α = 0.89 and 0.92) and explained 40 and 28% of the variance in the D-score, respectively.
Supporting Image: Figure_1.png
   ·Figure 1 | Gradients, rsFC networks, and meta-analytic empathy clusters
 

Results:

First, we tested whether mean G1 loadings within four empathy clusters (Fig. 2A) had an effect on the D-score, controlling for age and sex in a robust linear regression. A > C G1 had a positive effect on the D-score following Bonferroni correction (βZ = 0.25 [95% CI: 0.06, 0.44], PBon = 0.039, adj. R2 = 0.16) (Fig. 2B). Next, we tested whether these clusters differed by E-S type. Similarly, A > C G1 differed by E-S type following Bonferroni correction (F[2, 95] = 6.02, PBon = 0.014, adj. R2 = 0.24), becoming progressively transmodal from Type E to Type S – although these two groups differed on every cluster (Fig. 2C). Next, we tested the effect of G1 loading within each parcel on the D-score. No parcel survived FDR correction (all PsFDR ≥ 0.660) (Fig. 2D). Finally, we spatially correlated these standardised D-score betas with two raw empathy maps and two thresholded empathy clusters excluding null parcels (Fig. 2E). Following 1,000 spin permutations, the D-score map correlated negatively with the Cognitive cluster (Spearman's ρ = -0.50, Pspin = 0.001, Nparcel = 158), such that a stronger meta-analytic loading of the parcel reflected its stronger unimodal relationship with the D-score. Conversely, the D-score map correlated positively with the Affective map (Spearman's ρ = 0.34, Pspin = 0.017, Nparcel = 360), such that a stronger meta-analytic loading of the parcel reflected its stronger transmodal relationship with the D-score (Fig. 2F).
Supporting Image: Figure_2.png
   ·Figure 2 | D-score, G1, and meta-analytic empathy maps/clusters
 

Conclusions:

A > C G1 correlated positively with the D-score and differed by E-S type; a stronger transmodal loading within this cluster reflected a stronger drive to systemise relative to empathise. As reflected in G1 across the cortex, the D-score showed opposite relationships with meta-analytic cognitive and affective empathy, further suggesting the importance of this distinction for the D-score in the brain. We will probe these findings using independent data and in a neurodevelopmental condition well-characterised in relation to E-S – autism [3, 9, 10].

Emotion, Motivation and Social Neuroscience:

Social Cognition 1
Social Interaction
Social Neuroscience Other 2
Emotion and Motivation Other

Higher Cognitive Functions:

Higher Cognitive Functions Other

Keywords:

ADULTS
Autism
Cognition
Cortex
Emotions
FUNCTIONAL MRI
Meta- Analysis
NORMAL HUMAN
Social Interactions
Other - Empathy

1|2Indicates the priority used for review

Provide references using author date format

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