Dopamine alters neural fingerprints and modulates hallucination-sensitivity in Parkinson’s disease

Poster No:

1434 

Submission Type:

Abstract Submission 

Authors:

Sara Stampacchia1, Fosco Bernasconi2, Killian Raude3, Lucas Burget4, Juan Carlos Farah3, Jevita Potheegadoo4, Marie Maradan5, Selim Habiby Alaoui12, Sabina Catalano6, Dimitri Van De Ville7, Vanessa Fleury6, Paul Krack5, Olaf Blanke4

Institutions:

1École polytechnique fédérale de Lausanne (EPFL), Geneva, Switzerland, 2EPFL, Geneva, GE, 3Laboratory of Cognitive Neuroscience, Neuro-X institute & Brain Mind Institute, EPFL, Geneva, Switzerland, 4Ecole Polytechnique Federale de Lausanne, Geneva, Switzerland, 5Inselspital, Bern, Bern, 6HUG, Geneva, GE, 7École polytechnique fédérale de Lausanne (EPFL), Geneva, Geneva

First Author:

Sara Stampacchia  
École polytechnique fédérale de Lausanne (EPFL)
Geneva, Switzerland

Co-Author(s):

Fosco Bernasconi  
EPFL
Geneva, GE
Killian Raude  
Laboratory of Cognitive Neuroscience, Neuro-X institute & Brain Mind Institute, EPFL
Geneva, Switzerland
Lucas Burget  
Ecole Polytechnique Federale de Lausanne
Geneva, Switzerland
Juan Carlos Farah  
Laboratory of Cognitive Neuroscience, Neuro-X institute & Brain Mind Institute, EPFL
Geneva, Switzerland
Jevita Potheegadoo  
Ecole Polytechnique Federale de Lausanne
Geneva, Switzerland
Marie Maradan  
Inselspital
Bern, Bern
Selim Habiby Alaoui1  
EPFL
Geneva, GE
Sabina Catalano  
HUG
Geneva, GE
Dimitri Van De Ville  
École polytechnique fédérale de Lausanne (EPFL)
Geneva, Geneva
Vanessa Fleury  
HUG
Geneva, GE
Paul Krack  
Inselspital
Bern, Bern
Olaf Blanke  
Ecole Polytechnique Federale de Lausanne
Geneva, Switzerland

Introduction:

Hallucinations in Parkinson's Disease (PD) are clinically significant and often linked to dopaminergic medication, but evidence remains inconclusive[1]. Our group developed a robotic-setup that allow to induce clinically relevant hallucinations (robot-induced presence hallucinations, riPH), allowing to empirically investigate hallucinations under controlled experimental settings[2,3]. Work also submitted to this conference demonstrated increased sensitivity to riPH in PD patients with hallucinations during dopaminergic treaement[4]. The present study complements that work by examining how dopaminergic medication impacts individual functional connectivity (FC) profiles, also known as FC fingerprints[5,6], and their relationship with sensitivity to riPH.

Methods:

20 PD patients underwent resting-state fMRI and the robot experiment in an ON- and an OFF-dopamine treatment session. riPH sensitivity was quantified for each individual as probability to report hallucinations as a function of sensorimotor delay dependency (slope of linear model response yes/no ~ delay)[3]. FC matrices were estimated using Pearson's correlations between 278 brain nodes[7]. Metrics for within- (ISelf) and between-subject (IOthers)[5,8] FC test-retest reliability were calculated within (ON and OFF) and across sessions (ON vs. OFF). The distance between ISelf and IOthers (IDiff) provided a group-level estimate of identifiability. Edgewise intra-class correlation (ICC) was used to assess spatial specificity of FC fingerprints. ICC measures how consistent the functional connectivity (FC) between two brain regions is across test and retest within subjects. A higher ICC indicates more stable connectivity patterns for that edge within subjects, and variability in connectivity patterns between subjects in the group[5,8]. ICC was estimated separately for ON- and OFF-medication states and the difference between the two was computed (delta-ICC = ICC ON – ICC OFF). Finally, linear mixed models tested whether individuals' FC edges with high ICC (≥ 0.1st percentile) was associated with riPH sensitivity, adjusting for medication state, age, sex, and disease duration and subjects as random effects to account for inter-individual variability (riPH ~ FC*Medication + Age + Sex + Disease Duration + (1|ID)).

Results:

Individual FC profiles were highly distinguishable within sessions regardless of medication status (IDiff ON=0.36; IDiff OFF=0.35; 100% identification success). Cross-medication comparisons (i.e., estimating identifiability across ON- vs. OFF-medication states) showed reduced identifiability (IDiff=0.17-0.21; mean success=97.9-99.2%) and decreased ISelf similarity (Fig.1). ON-medication increased ICC in visual, somatomotor, salience, subcortical, and cerebellar networks (FDR-corrected; Fig.2). Positive FC with high ICC (β=16.41, p=0.041) and medication state (β=67.52, p=0.017) significantly predicted riPH sensitivity. A significant interaction (β=-28.32, p=0.018) indicated FC effects were modified in the OFF-medication state, where a negative association was observed.
Supporting Image: Figure1.png
   ·Figure 1
Supporting Image: Figure2.png
   ·Figure 2
 

Conclusions:

Dopaminergic medication reconfigures FC fingerprints in PD, stabilizing networks linked to visual, somatomotor, salience, and subcortical-cerebellar functions. These findings align with roles of visual and salience networks in PD hallucinations[9,10] in PD hallucinations, and suggest sensorimotor alterations contribute to hallucinations[3]. Although individual FC profiles remained identifiable within sessions (ON- or OFF-dopamine treatment), cross-medication transitions (comparing ON- vs. OFF- dopamine states) reduced identifiability. High-ICC FC and medication state were significant predictors of riPH sensitivity, with altered effects during OFF-medication. These findings build on our previous work on FC fingerprinting[5,6] and group's research on riPH[2–4], advancing the understanding of how dopaminergic medication reconfigure individual functional connectomes and modulates hallucinations sensitivity in PD.

Disorders of the Nervous System:

Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2

Modeling and Analysis Methods:

fMRI Connectivity and Network Modeling 1

Novel Imaging Acquisition Methods:

BOLD fMRI

Physiology, Metabolism and Neurotransmission:

Pharmacology and Neurotransmission

Keywords:

Computational Neuroscience
DISORDERS
Dopamine
Neurological
Other - Brain fingeprints

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):

Patients

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.

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Not applicable

Please indicate which methods were used in your research:

Functional MRI

For human MRI, what field strength scanner do you use?

3.0T

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FSL

Provide references using APA citation style.

1. Ravina, B. et al. Diagnostic criteria for psychosis in Parkinson’s disease: Report of an NINDS, NIMH work group. Movement Disorders 22, 1061–1068 (2007).
2. Bernasconi, F. et al. Neuroscience robotics for controlled induction and real-time assessment of hallucinations. Nat Protoc 1–24 (2022) doi:10.1038/s41596-022-00737-z.
3. Bernasconi & Blondiaux et al. Robot-induced hallucinations in Parkinson’s disease depend on altered sensorimotor processing in fronto-temporal network. Sci. Transl. Med. 13, eabc8362 (2021).
4. Bernasconi & Stampacchia et al. Hallucinations in Parkinson’s disease are mediated by fronto-striatal sensorimotor networks and dopamine. (under preparation).
5. Stampacchia, S. et al. Fingerprints of brain disease: connectome identifiability in Alzheimer’s disease. Commun Biol 7, 1–16 (2024).
6. Stampacchia, S. et al. Functional connectivity fingerprints in Parkinson’s disease patients with hallucinations. in (in preparation).
7. Shen, X., Tokoglu, F., Papademetris, X. & Constable, R. T. Groupwise whole-brain parcellation from resting-state fMRI data for network node identification. NeuroImage 82, 403–415 (2013).
8. Amico, E. & Goñi, J. The quest for identifiability in human functional connectomes. Sci Rep 8, 8254 (2018).
9. Shine, J. M., O’Callaghan, C., Halliday, G. M. & Lewis, S. J. G. Tricks of the mind: Visual hallucinations as disorders of attention. Progress in Neurobiology 116, 58–65 (2014).
10. Shine, J. M. et al. Abnormal connectivity between the default mode and the visual system underlies the manifestation of visual hallucinations in Parkinson’s disease: a task-based fMRI study. NPJ Parkinsons Dis 1, 15003 (2015).
11. McGraw, K. O. & Wong, S. P. Forming Inferences About Some Intraclass Correlation Coefficients. Psychological Methods 17 (1996) doi:1082-989X/96/S3.00.
12. Shrout, P. E. & Fleiss, J. L. Intraclass Correlations: Uses in Assessing Rater Reliability. Psychological Bulletin 86, 420–428 (1979).

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