Publications of G Lohmann

Lohmann, G.; Neumann, J.: FMRI data analysis using Bayesian random effects models. 11th Annual Meeting of the Organization for Human Brain Mapping (HBM 2005), Toronto, Canada (2005)

Neumann, J.; Lohmann, G.; Forstmann, B.; von Cramon, D.: Using Replicator Dynamics and Canonical Correlation for Clustering FMRI Time Series. 11th Annual Meeting of the Organization for Human Brain Mapping, Toronto, Canada (2005)

Müller, K.; Lohmann, G.; Neumann, J.; Mildner, T.; von Cramon, D.: Investigating the Coupling between BOLD Signal Strength and Latency. 10th Annual Meeting of the Organization for Human Brain Mapping (HBM 2004), Budapest, Hungary (2004)

Busch, N.; Lohmann, G.; von Cramon, D.: LIMA: An object-oriented segmentation and visualization framework for medical data sets. Seventh Annual Meeting of the Organization for Human Brain Mapping (HBM 2001), Brighton, UK (2001)

Lohmann, G.; Müller, K.; Bosch, V.; Mentzel, H.; Busch, N.; von Cramon, D.: Lipsia: A software package for the analysis of fMRI data. Seventh Annual Meeting of the Organization for Human Brain Mapping (HBM 2001), Brighton, UK (2001)

Müller, K.; Bosch, V.; Lohmann, G.; von Cramon, D.: Comparison of approaches for multi-subject fMRI-analysis. Sixth Annual Meeting of the Organization for Human Brain Mapping (HBM 2000), San Antonio, TX, USA (2000)

Lohmann, G.: An evidential reasoning approach to the classification of satellite images. Dissertation, 103 pp., Technische Universität, München, Germany (1991)

Lohmann, G.; Müller, K.; Bosch, V.; Mentzel, H.; Hessler, S.; Chen, L.; von Cramon, D.: LIPSIA: Leipzig Image Processing and Statistical Inference Algorithms. Max-Planck-Institute of Mathematics in the Sciences, Leipzig, Germany (2001), 33 pp.

Mahler, L.; Steiglechner, J.; Bender, B.; Lindig, T.; Ramadan, D.; Bause, J.; Birk, F.; Heule, R.; Charyasz, E.; Erb, M. et al.; Kumar, V.; Hagberg, G.; Martin, P.; Lohmann, G.; Scheffler, K.: UltraCortex: Submillimeter Ultra-High Field 9.4 T Brain MR Image Collection and Manual Cortical Segmentations. (submitted)

Lohmann, G.; Heczko, S.; Mahler, L.; Wang, Q.; Steiglechner, J.; Kumar, V.; Roost, M.; Jost, J.; Scheffler, K.: Improving the reliability of fMRI-based predictions of intelligence via semi-blind machine learning. (submitted)

Lohmann, G.; Lacosse, E.; Ethofer, T.; Kumar, V.; Scheffler, K.; Jost, J.: Predicting intelligence from fMRI data of the human brain in a few minutes of scan time. (submitted)

Lohmann, G.; Loktyushin, A.; Stelzer, J.; Scheffler, K.: Eigenvector centrality mapping for ultrahigh resolution fMRI data of the human brain. (submitted)

Weber, M.; Stelzer, J.; Saucan, E.; Naitsat, A.; Lohmann, G.; Jost, J.: Curvature-based Methods for Brain Network Analysis. (submitted)

Lohmann, G.; Stelzer, J.; Mueller, K.; Lacosse, E.; Buschmann, T.; Kumar, V.; Grodd, W.; Scheffler, K.: Inflated False Negative Rates Undermine Reproducibility In Task-Based fMRI. (submitted)