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Hans Förstl

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers
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3

YNIMG Journal 2016 Journal Article

How do you make me feel better? Social cognitive emotion regulation and the default mode network

  • Xiyao Xie
  • Satja Mulej Bratec
  • Gabriele Schmid
  • Chun Meng
  • Anselm Doll
  • Afra Wohlschläger
  • Kathrin Finke
  • Hans Förstl

Socially-induced cognitive emotion regulation (Social-Reg) is crucial for emotional well-being and social functioning; however, its brain mechanisms remain poorly understood. Given that both social cognition and cognitive emotion regulation engage key regions of the default-mode network (DMN), we hypothesized that Social-Reg would rely on the DMN, and that its effectiveness would be associated with social functioning. During functional MRI, negative emotions were elicited by pictures, and – via short instructions – a psychotherapist either down-regulated participants' emotions by employing reappraisal (Reg), or asked them to simply look at the pictures (Look). Adult Attachment Scale was used to measure social functioning. Contrasting Reg versus Look, aversive emotions were successfully reduced during Social-Reg, with increased activations in the prefrontal and parietal cortices, precuneus and the left temporo-parietal junction. These activations covered key nodes of the DMN and were associated with Social-Reg success. Furthermore, participants' attachment security was positively correlated with both Social-Reg success and orbitofrontal cortex involvement during Social-Reg. In addition, specificity of the neural correlates of Social-Reg was confirmed by comparisons with participants' DMN activity at rest and their brain activations during a typical emotional self-regulation task based on the same experimental paradigm without a psychotherapist. Our results provide first evidence for the specific involvement of the DMN in Social-Reg, and the association of Social-Reg with individual differences in attachment security. The findings suggest that DMN dysfunction, found in many neuropsychiatric disorders, may impair the ability to benefit from Social-Reg.

YNICL Journal 2014 Journal Article

LRP-1 polymorphism is associated with global and regional amyloid load in Alzheimer's disease in humans in-vivo

  • Timo Grimmer
  • Oliver Goldhardt
  • Liang-Hao Guo
  • Behrooz H. Yousefi
  • Stefan Förster
  • Alexander Drzezga
  • Christian Sorg
  • Panagiotis Alexopoulos

OBJECTIVE: Impaired amyloid clearance has been proposed to contribute to β-amyloid deposition in sporadic late-onset Alzheimer's disease (AD). Low density lipoprotein receptor-related protein 1 (LRP-1) is involved in the active outward transport of β-amyloid across the blood-brain barrier (BBB). The C667T polymorphism (rs1799986) of the LRP-1 gene has been inconsistently associated with AD in genetic studies. We aimed to elucidate the association of this polymorphism with in-vivo brain amyloid load of AD patients using amyloid PET with [(11)C]PiB. MATERIALS AND METHODS: 72 patients with very mild to moderate AD were examined with amyloid PET and C667T polymorphism was obtained using TaqMan PCR assays. The association of C667T polymorphism with global and regional amyloid load was calculated using linear regression and voxel based analysis, respectively. The effect of the previously identified modulator of amyloid uptake, the apolipoprotein E genotype, on this association was also determined. RESULTS: The regression analysis between amyloid load and C667T polymorphism was statistically significant (p = 0.046, β = 0.236). In an additional analysis ApoE genotype and gender were identified to explain further variability of amyloid load. Voxel based analysis revealed a significant (p < 0.05) association between C667T polymorphism and amyloid uptake in the temporo-parietal cortex bilaterally. ApoE did not interact significantly with the LRP-1 polymorphism. DISCUSSION: In conclusion, C667T polymorphism of LRP-1 is moderately but significantly associated with global and regional amyloid deposition in AD. The relationship appears to be independent of the ApoE genotype. This finding is compatible with the hypothesis that impaired amyloid clearance contributes to amyloid deposition in late-onset sporadic AD.

YNIMG Journal 2013 Journal Article

Selectively and progressively disrupted structural connectivity of functional brain networks in Alzheimer's disease — Revealed by a novel framework to analyze edge distributions of networks detecting disruptions with strong statistical evidence

  • Klaus Hahn
  • Nicholas Myers
  • Sergei Prigarin
  • Karsten Rodenacker
  • Alexander Kurz
  • Hans Förstl
  • Claus Zimmer
  • Afra M. Wohlschläger

Alzheimer's disease (AD) disrupts selectively and progressively (increasing with severity) functional connectivity of intrinsic brain networks (IBNs), most prominent in the default mode network. Given that IBNs' functional connectivity depends on structural connectivity, we hypothesize for our study selective and progressive changes of IBN based structural connectivity in AD. To achieve strong statistical evidence, we introduce a novel statistical method based on the edge frequency distributions of structural connectivity networks. Such non-Gaussian distributions are compared in a multiple testing scheme, combining a flexible nonparametric test statistic with permutation based strong control of the family wise error rate. We assessed 26 healthy elderly, 23 patients with AD-dementia, and 28 patients with mild cognitive impairment (MCI) by resting-state functional MRI, diffusion tensor imaging, and clinical–neuropsychological testing including annual follow-up assessment. After 3years, 50% of the patients with MCI converted to AD. Tractography of diffusion tensor data identifies structural connectivity networks between regions of IBNs, which are detected by an independent component analysis of resting state fMRI data. We find that IBNs' structural connectivity is selectively and progressively disrupted with primary changes in the default mode network. Correspondent results are found for IBNs' functional connectivity. In addition, structural connectivity across the nodes of all IBNs separated individual MCI patients converting to AD from non-converters. Conclusively, our study provides a new approach to analyze connectivity networks by their non-Gaussian edge frequency distributions and achieves strong statistical evidence by application of the family wise error rate. Data analysis provides selective and progressive disruptions of IBN's structural connectivity in AD and demonstrates the increased power of our method compared to recent studies.