Large quantities of imaging data enable us to generalise our findings and make predictions. © solvod/stock.adobe.com

Large quantities of imaging data enable us to generalise our findings and make predictions. © solvod/stock.adobe.com

Can imaging techniques help to predict the effect of treatment expectations on therapeutic outcome?

Imaging techniques such as functional magnetic resonance imaging (fMRI) or electroencephalography (EEG) enable us to visualise the anatomy, blood flow and function of the brain. This central research project analyses imaging data from ten collaborative research centre (CRC) projects, with the objective of pooling the findings and improving our understanding of the mechanisms underlying the effect of expectations on treatment outcome. Another objective is to identify characteristic biological features (predictive biomarkers), which in future will enable us to predict the effect of treatment expectations and optimise treatment for individual patients.

Research summary

Central research project: neural imaging

This project is a pooled multicentre analysis of all neural imaging data generated by the CRC. The objective is to combine mechanistic data from individual projects with key general information in the form of biomarkers that are predictive of individual expectation effects on treatment outcome. The research strategy of this project focuses on a comprehensive data management plan, which includes the standardisation of data and metadata structure, imaging sequences and experimental protocols, automatic quality assessment and coordination of data transmission.

Recommended reading:

Büchel C, Peters J, Banaschewski T, Bokde ALW, Bromberg U, Conrod PJ, Flor H, Papadopoulos D, Garavan H, Gowland P, Heinz A, Walter H, Ittermann B, Mann K, Martinot J-L, Paillère-Martinot M-L, Nees F, Paus T, Pausova Z, Poustka L, Rietschel M, Robbins TW, Smolka MN, Gallinat J, Schumann G, Knutson B, IMAGEN consortium (2017) Blunted ventral striatal responses to anticipated rewards foreshadow problematic drug use in novelty-seeking adolescents. Nat Commun 8:14140. PubMed

Spisak T, Spisak Z, Zunhammer M, Bingel U, Smith S, Nichols T, Kincses T (2019) Probabilistic TFCE: A generalized combination of cluster size and voxel intensity to increase statistical power. NeuroImage 185:12-26. PubMed

Spisak T, Kincses B, Schlitt F, Zunhammer M, Schmidt-Wilcke T, Kincses ZT, Bingel U (2019) Pain-free resting-state functional brain connectivity predicts individual pain sensitivity. Nature Communications volume 11: 187 (2020) PubMed

Zunhammer M, Bingel U, Wager TD (2018) Placebo effects on the neurologic pain signature: a meta-analysis of individual participant functional magnetic resonance imaging data. JAMA neurology 75(11):1321-30. PubMed

In close cooperation with these projects

A01

A01

A02

A02

A03

A03

A04

A04

A06

A06

A07

A07

How do positive expectations improve mood?

Prof. Dr. Erik M. Müller
Prof. Dr. Dominik M. Endres

A08

A08

Do positive expectations improve the effect of antidepressants?

Prof. Dr. Tilo Kircher
PD Dr. Irina Falkenberg

A11

A11

A13

A13

Project Lead

Prof. Dr. Ulrike Bingel

Prof. Dr. Ulrike Bingel
Neurologist and Neuroscientist

Prof. Dr. Christian Büchel

Prof. Dr. Christian Büchel
Neuroscientist

Dr. Tamas Spisak

Dr. Tamas Spisak
Neuroscientist

Team

Dr. Balint Kincses
Postdoc, Neuroscientist

Robert Englert
PhD Student, Medical Technician