Lesion-gradient mapping: Observed and simulated effects of stroke on connectivity gradients
Poster No:
799
Submission Type:
Abstract Submission
Authors:
Elizabeth Jefferies1, Ramya Balakrishnan1, Tirso Gonzalez-Alam2, Nick Souter3, Theodoros Karapanagiotidis3, Boris Bernhardt4, Jonathan Smallwood5
Institutions:
1University of York, York, York, 2University of Bangor, Bangor, Gwynedd, 3University of Sussex, Brighton, East Sussex, 4McGill University, Montreal, Quebec, 5Queens University, Kingston, Ontario
First Author:
Co-Author(s):
Introduction:
Post-stroke semantic aphasia is characterised by multimodal semantic deficits and is thought to reflect network-level disruption affecting frontal and temporal regions (Jefferies & Lambon Ralph, 2006). Connectivity gradients characterise key dimensions of whole-brain variation in functional connectivity, providing a promising method for understanding the global impact of stroke on semantic cognition. We examine how post-stroke changes in connectivity gradients can explain deficits in semantic aphasia. In Study 1, we ask if structural MRI, providing information about lesion size and location, can predict changes in connectivity gradients measured using resting-state functional MRI. In Study 2, we examine whether simulated gradient changes can predict the severity of semantic deficits.
Methods:
Study 1 analyzed intrinsic connectivity data from a 9-minute resting-state fMRI scan of 8 left hemispheric infarct patients with semantic control deficits and 39 age-matched controls. Functional time series were extracted from resting-state fMRI using 400 ROIs based on the Schaefer parcellation. A 400 x 400 functional connectivity matrix was generated for each patient by computing Pearson correlations between parcels. Gradients were extracted from these matrices using the Brainspace toolbox. To simulate post-stroke gradient changes, intact tissue per parcel was estimated from structural MRI using 400 Schaefer ROIs and a lesion matrix was generated by multiplying these 400 parcel values. Functional time series for the same 400 ROIs were extracted from resting-state fMRI of aged-matched controls, and functional connectivity matrices were created for each control. Each lesion matrix was multiplied with 39 control functional connectivity matrices, and these simulated lesion connectivity matrices were averaged for each lesion. Finally, gradients were extracted from each average simulated lesion connectivity matrix. Study 2 employed the same methods to generate post-stroke simulated gradients for 21 participants with semantic aphasia following left-hemisphere stroke. Permutation testing was used to identify brain regions in which gradient changes predicted performance on semantic tasks.
Results:
Gradient data for each lesion were subtracted from the age-matched controls to isolate the effects of stroke in gradient space. In Study 1, we evaluated how accurately the simulated gradient change data captured the real effects of stroke using spin permutation. There were significant correlations between observed gradient changes and simulated gradient changes the majority of patients on Gradient 1 (mean r = 0.42, SD = ±0.14) and in over half the patients on Gradient 2 (mean r = 0.15, SD = ±0.20). In Study 2, poorer semantic performance was associated with stronger connectivity with the unimodal end of Gradient 1 in left inferior frontal cortex, which is associated with semantic control (Fig. 1: Panel 2). Semantic deficits were also associated with changes on Gradient 2: right parahippocampal gyrus showed reduced visual connectivity in patients with poorer semantic performance (Fig. 1: Panel 3).
Conclusions:
This study shows that gradients of functional connectivity capture post-stroke changes in global brain organisation that predict cognitive impairment and can be estimated from structural MRI alone, increasing the clinical utility of our findings. Semantic impairment is associated with connectivity changes in Gradients 1 and 2, consistent with the role of heteromodal and unimodal processes in semantic cognition. Gradient 1 captures the separation of transmodal and unimodal cortex (Wang et al., 2020), with better semantic performance in stroke survivors associated with this separation. Poorer semantic performance was also associated with more motor than visual connectivity in the right parahippocampal gyrus, in line with the importance of visual connectivity to anterior medial temporal cortex in semantic access from written words and pictures.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Language:
Language Comprehension and Semantics 1
Learning and Memory:
Long-Term Memory (Episodic and Semantic)
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Keywords:
Aphasia
FUNCTIONAL MRI
Language
MRI
Other - stroke
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
Wang, X., Margulies, D. S., Smallwood, J., & Jefferies, E. (2020). A gradient from long-term memory to novel cognition: Transitions through default mode and executive cortex. Neuroimage, 220. https://doi.org/10.1016/J.NEUROIMAGE.2020.117074