| Shutting down sensorimotor interference unblocks the networks for stimulus processing: An SMR neurofeedback training study SE Kober, M Witte, M Stangl, A Väljamäe, C Neuper, G Wood Clinical Neurophysiology 126 (1), 82-95, 2015 | 150 | 2015 |
| Neural substrates of cognitive control under the belief of getting neurofeedback training M Ninaus, SE Kober, M Witte, K Koschutnig, M Stangl, C Neuper, G Wood Frontiers in human neuroscience 7, 914, 2013 | 148 | 2013 |
| Near-infrared spectroscopy based neurofeedback training increases specific motor imagery related cortical activation compared to sham feedback SE Kober, G Wood, J Kurzmann, EVC Friedrich, M Stangl, T Wippel, ... Biological psychology 95, 21-30, 2014 | 132 | 2014 |
| Compromised grid-cell-like representations in old age as a key mechanism to explain age-related navigational deficits M Stangl, J Achtzehn, K Huber, C Dietrich, C Tempelmann, T Wolbers Current Biology 28 (7), 1108-1115. e6, 2018 | 115 | 2018 |
| Boundary-anchored neural mechanisms of location-encoding for self and others M Stangl, U Topalovic, CS Inman, S Hiller, D Villaroman, ZM Aghajan, ... Nature 589 (7842), 420-425, 2021 | 92 | 2021 |
| Wireless programmable recording and stimulation of deep brain activity in freely moving humans U Topalovic, ZM Aghajan, D Villaroman, S Hiller, L Christov-Moore, ... Neuron 108 (2), 322-334. e9, 2020 | 80 | 2020 |
| Changes in pattern completion–a key mechanism to explain age-related recognition memory deficits? P Vieweg, M Stangl, LR Howard, T Wolbers Cortex 64, 343-351, 2015 | 76 | 2015 |
| Sources of path integration error in young and aging humans M Stangl, I Kanitscheider, M Riemer, I Fiete, T Wolbers Nature communications 11 (1), 2626, 2020 | 54 | 2020 |
| A haemodynamic brain-computer interface based on real-time classification of near infrared spectroscopy signals during motor imagery and mental arithmetic M Stangl, G Bauernfeind, J Kurzmann, R Scherer, C Neuper Journal of Near Infrared Spectroscopy 21 (3), 157-171, 2013 | 54 | 2013 |
| Mobile cognition: imaging the human brain in the ‘real world’ M Stangl, SL Maoz, N Suthana Nature Reviews Neuroscience 24, 347-362, 2023 | 48 | 2023 |
| A wearable platform for closed-loop stimulation and recording of single-neuron and local field potential activity in freely moving humans U Topalovic, S Barclay, C Ling, A Alzuhair, W Yu, V Hokhikyan, ... Nature neuroscience 26 (3), 517-527, 2023 | 38 | 2023 |
| Sequential effects in continued visual search: Using fixation‐related potentials to compare distractor processing before and after target detection C Körner, V Braunstein, M Stangl, A Schlögl, C Neuper, A Ischebeck Psychophysiology 51 (4), 385-395, 2014 | 33 | 2014 |
| The GridCAT: a toolbox for automated analysis of human grid cell codes in fMRI M Stangl, J Shine, T Wolbers Frontiers in Neuroinformatics 11, 47, 2017 | 27 | 2017 |
| A pilot study of closed-loop neuromodulation for treatment-resistant post-traumatic stress disorder JL Gill, JA Schneiders, M Stangl, ZM Aghajan, M Vallejo, S Hiller, ... Nature communications 14 (1), 2997, 2023 | 15 | 2023 |
| Path integration selectively predicts midlife risk of Alzheimer’s disease C Newton, M Pope, C Rua, R Henson, Z Ji, N Burgess, CT Rodgers, ... bioRxiv, 2023 | 7 | 2023 |
| Entorhinal grid-like codes and time-locked network dynamics track others navigating through space IC Wagner, LP Graichen, B Todorova, A Lüttig, DB Omer, M Stangl, ... Nature communications 14 (1), 231, 2023 | 6 | 2023 |
| Population-Level Analysis of Human Grid Cell Activation M Stangl, T Wolbers, JP Shine Spatial Learning and Attention Guidance, 257-279, 2020 | 6 | 2020 |
| Entorhinal‐based path integration selectively predicts midlife risk of Alzheimer's disease C Newton, M Pope, C Rua, R Henson, Z Ji, N Burgess, CT Rodgers, ... Alzheimer's & Dementia, 2024 | 3 | 2024 |
| Dynamic neural representations of memory and space during human ambulatory navigation SLL Maoz, M Stangl, U Topalovic, D Batista, S Hiller, ZM Aghajan, ... Nature Communications 14 (1), 6643, 2023 | 3 | 2023 |
| The Future of iEEG: What Are the Promises and Challenges of Mobile iEEG Recordings? SL Maoz, M Stangl, U Topalovic, N Suthana Intracranial EEG: A Guide for Cognitive Neuroscientists, 891-906, 2023 | 1 | 2023 |
Thomas WolbersProfessor for Aging, Cognition & Technology在 dzne.de 的电子邮件经过验证
