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In vivo MRI

Research group 8.12

Functional imaging of the brain

Functional magnetic resonance imaging (fMRI) is a modality to localize and image activated areas within the brain. A special head-gradient coil allows to investigate the human brain with high spatial and temporal resolution. Another focus of our activities is the simultaneous application of different modalities, e.g., electro-encephalography (EEG), near-infrared spectroscopy (NIRS), fMRI, arterial spin labeling (ASL), and MR spectroscopy including functional MRS. With its MR-physical background PTB is a core partner in the Berlin NeuroImaging Center (BNIC).

fMRI applications

The short switching times of the head-gradient system allow the acquisition of three-dimensional images of the whole human brain within 2 seconds at an isotropic resolution of 2 mm. With echo times as short as 25 ms susceptibility artifacts are significantly reduced. This way even difficult brain areas like the ventral striatum become accessible. Such experiments are, for instance, pursued within the BNIC project P12 "Multimodal imaging of dopamine-glutamate interaction during reward processing in schizophrenics and healthy controls", in cooperation with researchers from the Klinik für Psychiatrie und Psychotherapie der Charité, Campus Mitte.


Fig. 1: Head-gradient coil mounted in the tunnel of the 3-T MR scanner. In the background a projection screen for visual stimulation which can be viewed via a set of tilted mirrors.


Fig. 2: Brain areas activated by visual stimulation. fMRI parameters: matrix 80×80×37, 2.2 mm×2.5 mm×2.0 mm, TR=2.0 s, TE=25 ms

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Combination of fMRI with NIRS and ASL

The BOLD effect (Blood Oxygenation Level Dependence) underlying most fMRI experiments results in a local change of the MR signal when a brain area is activated. The contributing processes are rather complex, however, and not yet fully understood. Neurological research of the past five years has clearly demonstrated that additional modalities are needed in order to unravel the complex interplay of various contributing effects. By combining different modalities it is hoped that a mathematical model of the BOLD effect can be constructed. This, in turn, should lead to a deeper understanding of the underlying neurological mechanisms.
NIRS, like fMRI, is a non-invasive technique. It makes use of the different optical properties of oxygenated and non-oxygenated blood in the near infrared to detect brain activation. A setup for time-differential NIRS developed by PTB's biomedical-optics group (8.31) was adapted to the special environment of an MR scanner and can now be used for simultaneous fMRI/NIRS measurements. Typical results are shown in Fig. 3.


Fig. 3: Comparison of BOLD-fMRI data (upper 3 curves) and NIRS data (lower 3 curves). The colors indicate different periods of stimulation. Note the delay of about 4 s between stimulus and response.

ASL is a technique to measure the blood turnover in brain tissue. The arterial blood flowing into the brain is magnetically marked by inverting its nuclear spins. About one second later this labeled blood reaches the region of interest where it is detected. Fig. 4 shows a time course of ASL and BOLD in comparison.


Fig. 4: Comparison of fMRI (red) and ASL data (blue). In the selected voxel within the visual cortex stimulation by a flickering checkerboard results in increased perfusion.

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Selected references

K. Müller, et al.
No differences in ventral striatum responsivity between adolescents with a positive family history of alcoholism and controls
Addiction Biology 20, 534-45 (2015).

E. Loth, et al.
Oxytocin receptor genotype modulates ventral striatal activity to social cues and response to stressful life events
Biological Psychiatry 76, 367-76 (2014).

B. Meyer, et al.
Oppositional COMT Val158Met effects on resting state functional connectivity in adolescents and adults
Brain Structure & Function: (2014).

W. Khan, et al.
No differences in hippocampal volume between carriers and non-carriers of the ApoE ε4 and ε2 alleles in young healthy adolescents
Journal of Alzheimer’s Disease 40, 37 - 43 (2014).

A. Stringaris, et al.
Dimensions of manic symptoms in youth: psychosocial impairment and cognitive performance in the IMAGEN sample
Journal of Child Psychology and Psychiatry 55, 1380–89 (2014).

M. L. Paillère Martinot, et al.
White-matter microstructure and gray-matter volumes in adolescents with subthreshold bipolar symptoms
Molecular Psychiatry 19, 462 - 470 (2014).

T. White, et al.
Sex differences in COMT polymorphism effects on prefrontal inhibitory control in adolescence
Neuropsychopharmacology 38 (2014).

C. Nymberg, et al.
DRD2/ANKK1 polymorphism modulates the effect of ventral striatal activation on working memory performance
Neuropsychopharmacology 39 , 2357-65 (2014).

S. Kühn, et al.
Positive association of video game playing with left frontal cortical thickness in adolescents
PLoS one 9 (2014).

C. Nymberg, et al.
Neural mechanisms of attention-deficit/hyperactivity disorder symptoms are stratified by MAOA genotype
Biological psychiatry 74, 607-14 (2013).

N. Lee, et al.
Do you see what I see? sex differences in the discrimination of facial emotions during adolescence
Emotion 13, 1030-40 (2013).

A. Heinrich, et al.
From gene to brain to behavior: schizophrenia-associated variation in AMBRA1 alters impulsivity-related traits
European Journal of Neuroscience 38, 2941-45 (2013).

C. Schilling, et al.
Common structural correlates of trait impulsiveness and perceptual reasoning in adolescence
Human Brain Mapping 34, 374-83 (2013).

K. Müller, et al.
Altered reward processing in adolescents with prenatal exposure to maternal cigarette smoking
JAMA Psychiatry 70, 847-56 (2013).

C. Schilling, et al.
Cortical thickness of superior frontal cortex predicts impulsiveness and perceptual reasoning in adolescence
Molecular Psychiatry 18, 624-30 (2013).

F. Nees, et al.
Genetic risk for nicotine dependence in the cholinergic system and activation of the brain reward system in healthy adolescents
Neuropsychopharmacology 38, 2081-89 (2013).

E. Loth, et al.
A target sample of adolescents and reward processing: same neural and behavioral correlates engaged in common paradigms?
Experimental Brain Research 223, 429-39 (2012).

A. Tahmasebi, et al.
Creating probabilistic maps of the face network in the adolescent brain: A multicentre functional MRI study
Human Brain Mapping 33, 938-57 (2012).

D. Stacey, et al.
RASGRF2 regulates alcohol-induced reinforcement by influencing mesolimbic dopamine neuron activity and dopamine release
Proceedings of the National Academy of Sciences of the United States of America 109, 21128-33 (2012).

G. Schumann, et al.
The IMAGEN study: reinforcement-related behaviour in normal brain function and psychopathology
Molecular Psychiatry 15, 1128-39 (2010).

K. Licha, et al.
Cyanine dyes as contrast agents in biomedical optical imaging
Academic Radiology 9, S320-22 (2002).

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