Gabriele Scheler
Gabriele Scheler (born 1960 in Göttingen) is a German-American computer scientist and neuroscientist. She is co-founder of the Carl Correns Foundation for Mathematical Biology,[1] a non-profit institute to further research and scholarship in mathematics applied to biology. The institute was founded in 2011, and went into operation in 2016. It was named after her great-grandfather Carl Erich Correns, who pioneered the application of mathematical and statistical tools for biological discovery.
Early life and education
Scheler grew up in Göttingen, as the daughter of Fritz Scheler, and Elisabeth Scheler née Correns, the daughter of Carl Wilhelm Correns, who had a formative influence on his granddaughter. She graduated from de:Theodor-Heuss-Gymnasium_(Göttingen) as valedictorian three years early in 1977. After a year at the Eberhard_Karls_Universität_Tübingen, she moved to the Institute for Logic and Theory of Science [1] at the Ludwig-Maximilians-Universität_München. She obtained a doctoral scholarship for Stanford University in 1982.[2] Scheler suffers from the consequences of a brain trauma, which she received in her early twenties, caused by a two-week coma in Berkeley 1983, probably induced by deliberate poisoning. The doctoral scholarship had to be declined because of this sudden illness. Her experience as a patient contributed to her resolve to investigate computational neuroscience problems with a view of later medical applications.
She did her Ph.D. with Godehard Link on a Prolog-based Language Interpretation System using a fragment of English. This system used medium-depth lexical analysis of surface lexemes into semantic primitives together with a translation of NL sentences into first order predicate logic (Horn clauses).[3]
Career
Scheler pioneered neural network research of linguistic phonology, semantics and grammatical categories[4] and co-edited the first book on ML in NLP.[5] While at Wilfried Brauer's group at the Technical University of Munich together with Sepp Hochreiter,[6] she developed a novel approach for classification based on adaptive distance measures,[7] later taken up by Yann LeCun and his group.[8][9]
She moved to the Salk Institute in 1998, where she worked on topics such as dopamine and neuromodulation,[10] neuronal synchronization, and whole-neuron (intrinsic) plasticity.[11]
At UC Berkeley (2001-2004),[6] she collaborated with the Redwood Neuroscience Institute. From 2005 until 2010, she was active at the Stanford (Department of Computer Science), leading the Biological Modelling Club with regular lectures on Computational Biology. This resulted in her work on protein signaling[12][13][14] initially with David Dill.
She invented a method for calculating dose-response matrices in protein signaling pathways with applications for drug development.[15] Since working with the Carl Correns Foundation she took up earlier work on lognormal distributions of neuronal frequencies and synaptic strengths from 2006.[16][17]
Several scholars were funded by the Carl Correns Foundation, including work on Boolean Neural Networks.[18][19]
With the Carl Correns Foundation, she published work on symbolic abstraction by a form of localist memory,[20] containing an original contribution[21] to the field of neuro-symbolic AI. Most significantly, she pioneered a new theory of neural plasticity ("there is room on the inside"), which is a significant advance since the Hebbian synaptic plasticity theory of LTP/LTD ("Neurons that fire together, wire together").[22]
References
- ↑ "Carl Correns Foundation for Mathematical Biology".
- ↑ "philosophies -Freunde der Philosophen-". YouTube. 18 November 2024.
- ↑ Gabriele Scheler (1989). LISL - konzeptionelle Repräsentation natürlichsprachlicher Information. Doctoral Dissertation, LMU Munich. OCLC 58619736. Search this book on
- ↑ Gabriele Scheler (1995). "Generating English plural determiners from semantic representations: A neural network learning approach". Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. Lecture Notes in Computer Science. 1040. Springer. pp. 61–74. doi:10.1007/3-540-60925-3_38. ISBN 978-3-540-60925-4. Search this book on
- ↑ S. Wermter, E. Riloff, G. Scheler, ed. (1996). Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing. Lecture Notes in Computer Science. 1040. Springer LNCS 1040. doi:10.1007/3-540-60925-3. ISBN 978-3-540-60925-4.CS1 maint: Multiple names: editors list (link) Search this book on
- ↑ 6.0 6.1 High-Tech Connect (2024). "Interview with Dr. Scheler on NeuroAI". YouTube.
- ↑ Gabriele Scheler (1992). "Feature Selection with Exception Handling-An Example from Phonology".
- ↑ https://cs.nyu.edu/~yann/talks/lecun-20070914-ipam-1.pdf
- ↑ Chopra, S.; Hadsell, R.; Lecun, Y. (2005). "Learning a Similarity Metric Discriminatively, with Application to Face Verification". 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). 1. pp. 539–546. doi:10.1109/CVPR.2005.202. ISBN 0-7695-2372-2. Search this book on
- ↑ Gabriele Scheler and Johann Schumann (2003). "Presynaptic modulation as fast synaptic switching: state-dependent modulation of task performance". Proceedings of the International Joint Conference on Neural Networks, 2003. 1. Proceedings of the International Joint Conference on Neural Networks. pp. 218–223. arXiv:cs/0401020. doi:10.1109/IJCNN.2003.1223347. ISBN 0-7803-7898-9. Search this book on
- ↑ Gabriele Scheler (2004). "Regulation of neuromodulator receptor efficacy—implications for whole-neuron and synaptic plasticity". Progress in Neurobiology. Progress in Neurobiology 72(6). 72 (6): 399–415. arXiv:q-bio/0401039. doi:10.1016/j.pneurobio.2004.03.008. PMID 15177784.
- ↑ Gabriele Scheler (2005). "Extracellular-to-intracellular signal transfer via G-proteins". arXiv:q-bio/0503031.
- ↑ Gabriele Scheler (2006). "Dynamic re-wiring of protein interaction: The case of transactivation". arXiv:q-bio/0609014.
- ↑ Gabriele Scheler (2013). "Transfer functions for protein signal transduction: application to a model of striatal neural plasticity". PLOS ONE. PLoS One, 8(2). 8 (2). arXiv:1208.1054. Bibcode:2013PLoSO...855762S. doi:10.1371/journal.pone.0055762. PMC 3565992. PMID 23405211. Unknown parameter
|article-number=ignored (help) - ↑ Gabriele Scheler (2013), Determination of output of biochemical reaction networks, Patent: US 20130246019 A1
- ↑ Gabriele Scheler and Johann Schumann (2006). "Diversity and stability in neuronal output rates". Society for Neuroscience annual Meeting. doi:10.13140/RG.2.1.1862.8967.
- ↑ Gabriele Scheler (2017). "Logarithmic distributions prove that intrinsic learning is Hebbian". F1000Research. F1000Res, 6:1222. 6: 1222. doi:10.12688/f1000research.12130.2. PMC 5639933. PMID 29071065.
- ↑ Sergey Nasonov (2018). "Design and Analysis of a Novel Boolean Neuron Model". Thesis for Master's Degree. Technical University of Munich.
- ↑ Gabriele Scheler and Johann Schumann (11 June 2014). "Boolean analysis of dendritic structure". F1000Research. F1000Posters 2014, 5:552. 5.
- ↑ Gabriele Scheler, Martin L Schumann, and Johann Schumann (2025). "Localist neural plasticity identified by mutual information". Journal of Computational Neuroscience. J Comput Neurosci. 53 (2): 321–331. doi:10.1007/s10827-025-00901-w. PMID 40120001 Check
|pmid=value (help).CS1 maint: Multiple names: authors list (link) - ↑ Brainwaves Consulting (2024). "'High achiever' neurons carry the brunt of memories". NewsWires.
- ↑ Gabriele Scheler (Jan 2023). "Sketch of a novel approach to a neural model". arXiv:2209.06865 [q-bio.NC].
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