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M. Sc. Stettler, Michael

Section for Computational Sensomotorics
Department of Cognitive Neurology
Hertie Institute for Clinical Brain Research
Centre for Integrative Neuroscience
University Clinic Tübingen
Otfried-Müller-Str. 25
72076 Tübingen, Germany
michael.stettler@cin.uni-tuebingen.de
Michael Stettler

Projects

Publications

Stettler, M. (2025). Investigation and Modelling of Dynamical Facial Expression Perception. Phd Thesis.
Investigation and Modelling of Dynamical Facial Expression Perception
Research Areas: Uncategorized
Type of Publication: Phd Thesis
[Bibtex]
Stettler, M., Lappe, A., Taubert, N. & Giese, M. A. (2023). Multi-Domain Norm-referenced Encoding Enables Data Efficient Transfer Learning of Facial Expression Recognition..
Multi-Domain Norm-referenced Encoding Enables Data Efficient Transfer Learning of Facial Expression Recognition
Abstract:

People can innately recognize human facial expressions in unnatural forms, such as when depicted on the unusual faces drawn in cartoons or when applied to an animal’s features. However, current machine learning algorithms struggle with out-of-domain transfer in facial expression recognition (FER). We propose a biologically-inspired mechanism for such transfer learning, which is based on norm-referenced encoding, where patterns are encoded in terms of difference vectors relative to a domain-specific reference vector. By incorporating domain-specific reference frames, we demonstrate high data efficiency in transfer learning across multiple domains. Our proposed architecture provides an explanation for how the human brain might innately recognize facial expressions on varying head shapes (humans, monkeys, and cartoon avatars) without extensive training. Norm-referenced encoding also allows the intensity of the expression to be read out directly from neural unit activity, similar to face-selective neurons in the brain. Our model achieves a classification accuracy of 92.15% on the FERG dataset with extreme data efficiency. We train our proposed mechanism with only 12 images, including a single image of each class (facial expression) and one image per domain (avatar). In comparison, the authors of the FERG dataset achieved a classification accuracy of 89.02% with their FaceExpr model, which was trained on 43,000 images.

Type of Publication: Misc
Full text: Online version
[Bibtex]
Stettler, M., Lappe, A., Siebert, R., Taubert, N., Thier, P. & Giese, M. A (2023). Norm-referenced encoding of facial expressions facilitates transfer learning to novel head shapes. 2023 Neuroscience Meeting Planner . Washington, D.C..
Norm-referenced encoding of facial expressions facilitates transfer learning to novel head shapes
Authors: Stettler, Michael; Lappe, Alexander; Siebert, Ramona Taubert, Nick; Thier, Peter Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: In Collection
JRESEARCH_BOOK_TITLE: 2023 Neuroscience Meeting Planner
Organization: Society for Neuroscience
Address: Washington, D.C.
[Bibtex]
Bognár, A., Mukovskiy, A., Nejad, G. G., Taubert, N., Stettler, M., Martini, L. M. et al (2023). Simultaneous recordings from posterior and anterior body responsive regions in the macaque Superior Temporal Sulcus . VSS 2023, May 19-24 2023, St. Pete Beach, Florida.
Simultaneous recordings from posterior and anterior body responsive regions in the macaque Superior Temporal Sulcus
Authors: Bognár, A. Mukovskiy, Albert; Nejad, G. Ghamkhari Taubert, Nick; Stettler, Michael; Martini, Lucas M.; Raman, R. Giese, Martin A.; Vogels, R.
Type of Publication: In Collection
[Bibtex]
Bognár, A., Mukovskiy, A., Nejad, G. G., Taubert, N., Stettler, M., Martini, L. M. et al (2023). Feature selectivity of body-patch neurons assessed with a large set of monkey avatars . 13th Annual Meeting on PrimateNeurobiology, Apr.26-28 2023, Göttingen Primate Center..
Feature selectivity of body-patch neurons assessed with a large set of monkey avatars
Authors: Bognár, A. Mukovskiy, Albert; Nejad, G. Ghamkhari Taubert, Nick; Stettler, Michael; Martini, Lucas M.; Raman, R. Giese, Martin A.; Vogels, R.
Type of Publication: In Collection
[Bibtex]
Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A., Stettler, M., Vogels, R. & Giese, M. A (2022). Neurophysiologically-inspired computational model of the visual recognition of social behavior and intent . FENS Forum, Paris.
Neurophysiologically-inspired computational model of the visual recognition of social behavior and intent
Abstract:

AIMS: Humans recognize social interactions and intentions from videos of moving abstract stimuli, including simple geometric figures (Heider {&} Simmel, 1944). The neural machinery supporting such social interaction perception is completely unclear. Here, we present a physiologically plausible neural model of social interaction recognition that identifies social interactions in videos of simple geometric figures and fully articulating animal avatars, moving in naturalistic environments. METHODS: We generated the trajectories for both geometric and animal avatars using an algorithm based on a dynamical model of human navigation (Hovaidi-Ardestani, et al., 2018, Warren, 2006). Our neural recognition model combines a Deep Neural Network, realizing a shape-recognition pathway (VGG16), with a top-level neural network that integrates RBFs, motion energy detectors, and dynamic neural fields. The model implements robust tracking of interacting agents based on interaction-specific visual features (relative position, speed, acceleration, and orientation). RESULTS: A simple neural classifier, trained to predict social interaction categories from the features extracted by our neural recognition model, makes predictions that resemble those observed in previous psychophysical experiments on social interaction recognition from abstract (Salatiello, et al. 2021) and naturalistic videos. CONCLUSION: The model demonstrates that recognition of social interactions can be achieved by simple physiologically plausible neural mechanisms and makes testable predictions about single-cell and population activity patterns in relevant brain areas. Acknowledgments: ERC 2019-SyG-RELEVANCE-856495, HFSP RGP0036/2016, BMBF FKZ 01GQ1704, SSTeP-KiZ BMG: ZMWI1-2520DAT700, and NVIDIA Corporation.

Authors: Mukovskiy, Albert; Hovaidi-Ardestani, Mohammad Salatiello, Alessandro; Stettler, Michael; Vogels, Rufin Giese, Martin A.
Type of Publication: In Collection
[Bibtex]
Siebert, R., Stettler, M., Taubert, N., Dicke, P., Giese, M. A. & Thier, P (2022). Encoding of dynamic facial expressions in the macaque superior temporal sulcus . Society for Neuroscience.
Encoding of dynamic facial expressions in the macaque superior temporal sulcus
Authors: Siebert, Ramona Stettler, Michael; Taubert, Nick; Dicke, Peter Giese, Martin A.; Thier, Peter
Type of Publication: In Collection
[Bibtex]
Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A., Stettler, M., Vogels, R. & Giese, M. A (2022). Physiologically-inspired neural model for social interaction recognition from abstract and naturalistic videos . VSS Annual Meeting 2022.
Physiologically-inspired neural model for social interaction recognition from abstract and naturalistic videos
Authors: Mukovskiy, Albert; Hovaidi-Ardestani, Mohammad Salatiello, Alessandro; Stettler, Michael; Vogels, Rufin Giese, Martin A.
Type of Publication: In Collection
[Bibtex]
Taubert, N., Stettler, M., Siebert, R., Spadacenta, S., Sting, L., Dicke, P. et al. (2021). Shape-invariant encoding of dynamic primate facial expressions in human perception. eLife.
Shape-invariant encoding of dynamic primate facial expressions in human perception
Abstract:

Dynamic facial expressions are crucial for communication in primates. Due to the difficulty to control shape and dynamics of facial expressions across species, it is unknown how species-specific facial expressions are perceptually encoded and interact with the representation of facial shape. While popular neural network models predict a joint encoding of facial shape and dynamics, the neuromuscular control of faces evolved more slowly than facial shape, suggesting a separate encoding. To investigate these alternative hypotheses, we developed photo-realistic human and monkey heads that were animated with motion capture data from monkeys and humans. Exact control of expression dynamics was accomplished by a Bayesian machine-learning technique. Consistent with our hypothesis, we found that human observers learned cross-species expressions very quickly, where face dynamics was represented largely independently of facial shape. This result supports the co-evolution of the visual processing and motor control of facial expressions, while it challenges appearance-based neural network theories of dynamic expression recognition.

Authors: Taubert, Nick; Stettler, Michael; Siebert, R. Spadacenta, S. Sting, L. Dicke, P. Thier, P. Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: Article
Journal: eLife
Year: 2021
Month: June
Full text: PDF Online version
[Bibtex]
Giese, M. A., Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A. & Stettler, M. (2021). Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli. VSS 2021.
Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli
Research Areas: Uncategorized
Type of Publication: Article
[Bibtex]
Kumar, P., Taubert, N., Stettler, M., Vogels, R., de Gelder, B. & Giese, M. A (2021). Neurodynamical model for the visual recognition of dynamic bodies . ECVP 2021.
Neurodynamical model for the visual recognition of dynamic bodies
Authors: Kumar, Prerana; Taubert, Nick; Stettler, Michael; Vogels, Rufin de Gelder, Beatrice Giese, Martin A.
Type of Publication: In Collection
[Bibtex]
Kumar, P., Taubert, N., Stettler, M., Vogels, R., de Gelder, B. & Giese, M. A (2021). Neurodynamical model for the visual recognition of dynamic bodies . CNS 2021.
Neurodynamical model for the visual recognition of dynamic bodies
Authors: Kumar, Prerana; Taubert, Nick; Stettler, Michael; Vogels, Rufin de Gelder, Beatrice Giese, Martin A.
Type of Publication: In Collection
[Bibtex]
Giese, M. A., Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A. & Stettler, M (2021). Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli. VSS 2021, May 21-26 .
Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli
Type of Publication: In Collection
[Bibtex]
Mukovskiy, A., Ardestani, M. H., Salatiello, A., Stettler, M. & Giese, M. A (2021). Physiologically-inspired neural model for social interactions recognition from abstract and naturalistic stimuli. Göttingen Meeting of the German Neuroscience Society 2021, Germany .
Physiologically-inspired neural model for social interactions recognition from abstract and naturalistic stimuli
Type of Publication: In Collection
[Bibtex]
Stettler, M., Taubert, N., Siebert, R., Spadacenta, S., Dicke, P., Thier, P. et al (2021). Neural models for the (cross-species) recognition of dynamic facial expressions. Göttingen Meeting of the German Neuroscience Society 2021, Germany .
Neural models for the (cross-species) recognition of dynamic facial expressions
Authors: Stettler, Michael; Taubert, Nick; Siebert, Ramona Spadacenta, Silvia Dicke, Peter Thier, Peter Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: In Collection
Full text: PDF
[Bibtex]
Stettler, M., Taubert, N., Siebert, R., Spadacenta, S., Dicke, P., Thier, P. et al (2021). Neural models for the cross-species recognition of dynamic facial expressions. VSS 2021, May 21-26 .
Neural models for the cross-species recognition of dynamic facial expressions
Authors: Stettler, Michael; Taubert, Nick; Siebert, Ramona Spadacenta, Silvia Dicke, Peter Thier, Peter Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: In Collection
Full text: PDF
[Bibtex]
Mukovskiy, A., Ardestani, M. H., Salatiello, A., Stettler, M. & Giese, M. A. (2021). Physiologically-inspired neural model for social interactions recognition from abstract and naturalistic stimuli.. Göttingen Meeting of the German Neuroscience Society.
Physiologically-inspired neural model for social interactions recognition from abstract and naturalistic stimuli.
Research Areas: Uncategorized
Type of Publication: Article
[Bibtex]
Stettler, M., Taubert, N., Azizpour, T., Siebert, R., Spadacenta, S., Dicke, P. et al. (2020). Physiologically-inspired Neural Circuits for the Recognition of Dynamic Faces. Artificial Neural Networks and Machine Learning – ICANN 2020 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part I. Springer, Berlin(168-179).
Physiologically-inspired Neural Circuits for the Recognition of Dynamic Faces
Authors: Stettler, Michael; Taubert, Nick; Azizpour, Tahereh Siebert, Ramona Spadacenta, Silvia Dicke, Peter Thier, Hans Peter Giese, Martin A.
Type of Publication: Article
Full text: Online version
[Bibtex]
Ardestani, M. H., Mukovskiy, A., Stettler, M., Saini, N. & Giese, M. A (2020). Physiologically-inspired neural model for the visual recognition of social interactions from abstract and natural stimuli. VSS 2020, 19-24 Jun .
Physiologically-inspired neural model for the visual recognition of social interactions from abstract and natural stimuli
Authors: Ardestani, Mohammad Hovaidi Mukovskiy, Albert; Stettler, Michael; Saini, Nitin Giese, Martin A.
Type of Publication: In Collection
[Bibtex]
Taubert, N., Stettler, M., Sting, L., Siebert, R., Spadacenta, S., Dicke, P. et al (2020). Cross-species diferences in the perception of dynamic facial expressions. VSS 2020, 19-24 Jun .
Cross-species diferences in the perception of dynamic facial expressions
Authors: Taubert, Nick; Stettler, Michael; Sting, Louisa Siebert, Ramona Spadacenta, Silvia Dicke, Peter Thier, Hans-Peter Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: In Collection
Full text: PDF
[Bibtex]
Stettler, M. & Giese, M. A (2020). Physiologically-inspired Neural Circuits for the Recognition of Dynamic Faces. ICANN 2020 .
Physiologically-inspired Neural Circuits for the Recognition of Dynamic Faces
Research Areas: Uncategorized
Type of Publication: In Collection
[Bibtex]
Stettler, M., Taubert, N., Sting, L., Siebert, R., Spadacenta, S., Dicke, P. et al (2019). Cross-species differences in the perception of dynamic facial expressions. Talk at ECVP Conference 2019, Perception 48(2S),63 .
Cross-species differences in the perception of dynamic facial expressions
Authors: Stettler, Michael; Taubert, Nick; Sting, Louisa Siebert, Ramona Spadacenta, Silvia Dicke, Peter Thier, Hans-Peter Giese, Martin A.
Type of Publication: In Collection
[Bibtex]
Taubert, N., Stettler, M., Sting, L., Siebert, R., Spadacenta, S., Dicke, P. et al (2019). Cross-species differences in the perception of dynamic facial expressions. VSS Annual Meeting 2019, Journal of Vision 19(10):155 .
Cross-species differences in the perception of dynamic facial expressions
Authors: Taubert, Nick; Stettler, Michael; Sting, Louisa Siebert, Ramona Spadacenta, Silvia Dicke, Peter Thier, Hans-Peter Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: In Collection
Full text: PDF
[Bibtex]
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