Poster No:
2048
Submission Type:
Abstract Submission
Authors:
Liping Lan1, Maria Azanova2,3, Paul Steinfath1, Frauke Beyer2, Vadim Nikulin2, Karsten Mueller2, Arno Villringer2,3,1
Institutions:
1International Max Planck Research School Neurocom / CONI, Leipzig, Germany, 2Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Max Planck School of Cognition, Leipzig, Germany
First Author:
Liping Lan
International Max Planck Research School Neurocom / CONI
Leipzig, Germany
Co-Author(s):
Maria Azanova
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences|Max Planck School of Cognition
Leipzig, Germany|Leipzig, Germany
Paul Steinfath
International Max Planck Research School Neurocom / CONI
Leipzig, Germany
Frauke Beyer
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Vadim Nikulin, Dr.
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Karsten Mueller
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Arno Villringer
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences|Max Planck School of Cognition|International Max Planck Research School Neurocom / CONI
Leipzig, Germany|Leipzig, Germany|Leipzig, Germany
Introduction:
Heartbeat-evoked potentials (HEP), measured as neural responses to heartbeats, have been studied as a marker for cardiac interoception (Coll et al., 2021). Although HEP is believed to indicate cardiac signalling to central autonomic (CAN) regions of the brain (Park & Blanke, 2019), the relationship between the EEG-based HEP and the distributed neural activity of CAN regions is poorly studied. Here we explored whether higher HEP amplitude relates to higher degree centrality (more connections in the whole brain), a network importance measure of CAN regions.
Methods:
32-channel electroencephalogram (EEG) and resting-state functional magnetic resonance imaging (fMRI) were obtained at different time points from the participants in LIFE (Leipzig Research Centre for Civilization Diseases). Subjects were without neurologic disease and above 60 years old (N = 903; M = 69.49, SD = 4.65). Resting-state HEP was investigated by simultaneous electroencephalography and electrocardiography recordings. Cardiac field artifacts were removed from the EEG using independent component analysis (ICA). Based on the ECG data, we identified R-peak onsets (HEPLAB toolbox) and segmented the EEG with respect to these markers (-200 to 600 ms). Degree centrality (DC) was used to evaluate functional network properties (Rubinov & Sporns, 2010) of CAN regions (the insula, cingulate cortex, thalamus, amygdala and hippocampus; based on the Dosenbach160 Atlas and the AAL90 Atlas). We used the DC metric to discriminate high and low groups based on median split and performed cluster-based permutation tests to detect the HEP clusters that show significant differences. Furthermore, we conducted correlation analyses and then multiple regression analyses to confirm if the amplitudes of the resting-state HEP clusters were associated with the degree centrality of specific CAN regions controlling for age, sex, heart rate, blood pressure, and head motion.
Results:
The temporal component of the HEP which was related to DC of CAN regions was characterised by a frontoparietal location between around 300 to 550 ms after the R-peak. HEP amplitude differences remained significant after controlling for age, sex, heart rate, blood pressure and head motion, and there were no ECG amplitude differences. The amplitude of HEP in significant clusters was correlated with the DC of the right anterior insula (r = 0.076, p = 0.020), left anterior insula (r = -0.069, p = 0.035), and the left hippocampus (r = -0.083, p = 0.012), brain regions which have been implicated in cardiac signal processing in prior fMRI studies. The degree centrality of these regions was negatively correlated with the frontal HEP amplitudes and positively correlated with parietal HEP amplitudes in this elderly sample.
Conclusions:
In this elderly population, neural correlates of the amplitude of late HEP components pointed to a neural representation within the left and right insular cortex, areas known as a hub for central autonomic control, and the hippocampus. The neuroimaging evidence may help to understand the role of the cortical regions in the dynamics of heart-brain interaction.
Lifespan Development:
Aging
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis 2
fMRI Connectivity and Network Modeling
Task-Independent and Resting-State Analysis
Perception, Attention and Motor Behavior:
Perception: Pain and Visceral 1
Keywords:
Aging
Autonomics
Electroencephaolography (EEG)
FUNCTIONAL MRI
Other - heartbeat-evoked potentials, central autonomic control, heart-brain interaction
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
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.
Yes
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.
Not applicable
Please indicate which methods were used in your research:
Functional MRI
EEG/ERP
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
SPM
Other, Please list
-
MNE in python; Gretna, Fieldtrip in Matlab
Provide references using APA citation style.
1. Coll MP, Hobson H, Bird G, Murphy J. (2021). "Systematic review and meta-analysis of the relationship between the heartbeat-evoked potential and interoception." Neuroscience & Biobehavioral Reviews 122: 190-200.
2. Park, H.-D. and O. Blanke (2019). "Heartbeat-evoked cortical responses: Underlying mechanisms, functional roles, and methodological considerations." NeuroImage 197: 502-511.
3. Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. NeuroImage, 52(3), 1059–1069.
No