Publikationen von E Lacosse

Lacosse, E.; Scheffler, K.; Lohmann, G.; Martius, G.: Jumping over baselines with new methods to predict activation maps from resting-state fMRI. Scientific Reports 11 (1), 3480, S. 1 - 15 (2021)

Bause, J.; Polimeni, J.; Stelzer, J.; In, M.-H.; Ehses, P.; Kraemer-Fernandez, P.; Aghaeifar, A.; Lacosse, E.; Pohmann, R.; Scheffler, K.: Impact of prospective motion correction, distortion correction methods and large vein bias on the spatial accuracy of cortical laminar fMRI at 9.4 Tesla. NeuroImage 208, 116434, S. 1 - 16 (2020)

Stelzer, J.; Lacosse, E.; Bause, J.; Scheffler, K.; Lohmann, G.: Brainglance: visualizing group level MRI data at one glance. Frontiers in Neuroscience 13, 972, S. 1 - 13 (2019)

Lohmann, G.; Stelzer, J.; Lacosse, E.; Kumar, V.; Mueller, K.; Kuehn, E.; Grodd, W.; Scheffler, K.: LISA improves statistical analysis for fMRI. Nature Communications 9, 4014, S. 1 - 9 (2018)

Lacosse, E.; Lohmann, G.; Himmelbach, M.; Scheffler, K.; Martius, G.: Task fMRI Prediction from Task Free Resting State Measurements. In 11th International Conference on Brain Informatics (BI 2018), B262, S. 47. 11th International Conference on Brain Informatics (BI 2018), Arlington, TX, USA, 07. Dezember 2018 - 09. Dezember 2018. (2018)

Lacosse, E.; Bause, J.; Lohmann, G.; Scheffler, K.; Schaal, S.; Sternad, D.: Neural Control of Discrete and Rhythmic Movements. 26th Annual Meeting of the Society for the Neural Control of Movement (NCM 2016), Montego Bay, Jamaica (2016)

Lacosse, E.; Lohmann, G.; Sternad, D.; Schaal, S.: Investigating human rhythmic and discrete arm movement at 3 and 9.4T. 16th Conference of Junior Neuroscientists of Tübingen (NeNa 2015): Communicating the Challenges of Science, Schramberg, Germany (2015)

Lacosse, E.: Towards a learning fingerprint: new methods and paradigms for complex motor skill learning in fMRI. Dissertation, Eberhard-Karls-Universität Tübingen, Tübingen, Germany (2021)

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. (eingereicht)

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. (eingereicht)