Fritz Sommer: Difference between revisions
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Friedrich T. Sommer, Ph.D. <br /> | Friedrich T. Sommer, Ph.D. <br /> | ||
University of California, Berkeley <br /> | University of California, Berkeley <br /> | ||
Redwood Center for Theoretical Neuroscience - | Redwood Center for Theoretical Neuroscience - Helen Wills Neuroscience Institute <br /> | ||
Warren Hall <br /> | |||
Berkeley, CA 94720 | Berkeley, CA 94720 <br /> | ||
email F $ 0 M M E R (a) B E R K E L E Y * E D U (please retype)<br /> | email F $ 0 M M E R (a) B E R K E L E Y * E D U (please retype)<br /> | ||
<br style="clear:both;" /> | <br style="clear:both;" /> | ||
Adjunct Professor, Redwood Center for Theoretical Neuroscience & [http://neuroscience.berkeley.edu/ Helen Wills Neuroscience Institute], University of California, Berkeley <br /> | Research Engineer/Scientist, Intel Labs & Adjunct Professor, Redwood Center for Theoretical Neuroscience & [http://neuroscience.berkeley.edu/ Helen Wills Neuroscience Institute], University of California, Berkeley <br /> | ||
Faculty member (Hochschuldozent), Department of Computer Science, [http://www.uni-ulm.de/ University of Ulm]<br /> | Faculty member (Hochschuldozent), Department of Computer Science, [http://www.uni-ulm.de/ University of Ulm]<br /> | ||
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== Research Interests == | == Research Interests == | ||
Many impressive capabilities of the brain are not yet understood, for example, how unsupervised learning shapes the brains of animals and humans while controlling closed action-perception loops with the environment, or the virtually unlimited capacity of our long-term memory and its | Many impressive capabilities of the brain are not yet understood, for example, how unsupervised learning shapes the brains of animals and humans while controlling closed action-perception loops with the environment, or the virtually unlimited capacity of our long-term memory and its close connection to spatial navigation. | ||
In collaboration with experimental neuroscience labs, my lab investigates the theoretical principles of learning and perception and their biological bases in the circuit dynamics of the brain. At the same time, I am interested in neurobiological design principles for building artificial intelligence systems. | |||
For a full list of publications, see [https://scholar.google.com/citations?hl=en&view_op=list_works&gmla=AJsN-F6OQfburHGgSijJ71YjBkMzeChlIy-MFcZM2jCPQk78E2IGxggVw2f18ll6GXAXpj70ExNW52y9VETzujZFBE3a5ChB99X6jB_IWauOzL7Ilp7M2CE&user=lA-oLkgAAAAJ Google Scholar Profile] | |||
==Journal articles, book chapters and submissions== | ==Journal articles, book chapters and submissions== | ||
==== Submissions/arXiv'ed manuscripts ==== | ==== Submissions/arXiv'ed manuscripts ==== | ||
D. | C. Kymn, S. Mazelet, A. H. Thomas, D. Kleyko, E. P. Frady, F. T. Sommer, B. Olshausen: Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps (2024) | ||
Z. Li, Y. Chen, Y. LeCun, F. T. Sommer: Neural Manifold Clustering and Embedding. https://arxiv.org/abs/2201.10000 (2022) | |||
E. | C. Warner, F. T. Sommer: A probabilistic latent variable model for detecting structure in binary data. https://arxiv.org/abs/2201.11108 (2022) | ||
E. P. Frady, D. Kleyko, C. J. Kymn, B. A. Olshausen, F. T. Sommer: Computing on functions using randomized vector representations. https://arxiv.org/abs/2109.03429 (2021) | |||
C. Warner, F. T. Sommer: A Model for Image Segmentation in Retina [https://arxiv.org/abs/2005.02567 arXiv] (2020) | |||
Z. Li, F. T. Sommer: The amplitude-phase complex Boltzmann machine [https://arxiv.org/abs/2005.01862 arXiv] (2020) | |||
C. Bybee, E. P. Frady, F. T. Sommer: Deep learning in spiking phasor neural networks, in preparation | |||
==== Recent Publications ==== | ==== Recent Publications ==== | ||
A. Renner, L. Supic, A. Danielescu, G. Indiveri, B. A. Olshausen, Y. Sandamirskaya, F. T. Sommer, E. P. Frady: Neuromorphic visual scene understanding with resonator networks. Nature Machine Intelligence. June 2024 [https://rdcu.be/dL57G read-only pdf] (2024) | |||
A. Renner, L. Supic, A. Danielescu, G. Indiveri, E. P. Frady, F. T. Sommer, and Y. Sandamirskaya: Neuromorphic Visual Odometry with Resonator Networks. Nature Machine Intelligence. June 2024 [https://rdcu.be/dL57M read-only pdf] (2024) [https://www.nature.com/natmachintell/volumes/6/issues/6 Cover image of June 2024 issue] | |||
Z. Li, Y. Chen, F. T. Sommer: Learning energy-based models in high-dimensional spaces with multi-scale denoising-score matching. [https://www.mdpi.com/1099-4300/25/10/1367 Entropy] (2023) | |||
C. Bybee, D. Kleyko, D. E. Nikonov, A. Khosrowshahi, F. T. Sommer: Efficient optimization with higher-order Ising machines. [https://www.nature.com/articles/s41467-023-41214-9 Nature Communication] (2023)<br> | |||
(Earlier version [https://arxiv.org/abs/2212.03426 arXiv]) | |||
D. Kleyko, C. Bybee, P.-C. Huang, C. J. Kymn, B. A. Olshausen, E. P. Frady, F. T. Sommer: Efficient Decoding of Compositional Structure in Holistic Representations. Neural Computation 5/2023 p1-28, (2023) | |||
D. Kleyko, A. Rosato, E. P. Frady, M. Panella, F. T. Sommer: Perceptron Theory for Predicting the Accuracy of Neural Networks. IEEE Transactions on Neural Networks and Learning Systems (2023)<br> | |||
(Earlier version [https://arxiv.org/pdf/2012.07881.pdf arXiv]) | |||
F. T. Sommer, J. A Hirsch: How the LGN forwards retinal information in the cortex. Chapter in The cerebral cortex and thalamus, Eds: W. M. Usrey and M. Sherman, Oxford University Press (2023) | |||
D. Kleyko, M. Davies, E. P. Frady, P. Kanerva, S. J. Kent, B. A. Olshausen, E. Osipov, J. M. Rabaey, D. A. Rachkovskij, A. Rahimi, F. T. Sommer: Vector Symbolic Architectures as computing framework for nanoscale hardware. [https://proceedingsoftheieee.ieee.org/october-2022/ Proceedings of the IEEE, 110(10)], 1538-1571. (2022)<br> | |||
(Earlier version [https://arxiv.org/pdf/2106.05268.pdf arXiv]) | |||
D. Toker, I. Pappas, J. D. Lendner, J. Frohlich, D. M. Mateos, S. Muthukumaraswamy, R. Carhart-Harris, M. Pfaff, P. M. Vesta, M. M. Monti, F. T. Sommer, R. T. Knight, M. D'Esposito: Consciousness is supported by near-critical cortical electrodynamics. PNAS https://www.pnas.org/content/119/7/e2024455119 (2022) | |||
D. Kleyko, E. P. Frady, F. T. Sommer: Cellular Automata Can Reduce Memory Requirements of Collective-State Computing, IEEE Transactions on Neural Networks and Learning Systems. Print ISSN: 2162-237X, Online ISSN: 2162-2388, Digital Object Identifier: [https://ieeexplore.ieee.org/document/9586079 10.1109/TNNLS.2021.3119543] (2021)<br> | |||
(Earlier version [https://arxiv.org/abs/2010.03585 arXiv]) | |||
E. P. Frady, D. Kleyko, F. T. Sommer: Variable Binding for Sparse Distributed Representations: Theory and Applications. IEEE Transactions on Neural Networks and Learning Systems [https://ieeexplore.ieee.org/document/9528907 10.1109/TNNLS.2021.3105949] (2021)<br> | |||
(Earlier version [https://arxiv.org/abs/2009.06734 arXiv]) | |||
Zengyi Li, Yubei Chen, F. T. Sommer: A Neural Network MCMC Sampler That Maximizes Proposal Entropy. Entropy 23(3), 269; | |||
[https://www.mdpi.com/1099-4300/23/3/269?utm_campaign=releaseissue_entropyutm_medium=emailutm_source=releaseissueutm_term=titlelink4 doi:10.3390/e23030269] (2021)<br> | |||
(Earlier version [https://arxiv.org/abs/2010.03587 arXiv]) | |||
E. P. Frady, S. J. Kent, B. A. Olshausen and F. T. Sommer: Resonator Networks, 1: An Efficient Solution for Factoring High-Dimensional, Distributed Representations of Data Structures. Neural Computation 32 (12): [https://doi.org/10.1162/neco_a_01331 2311–2331] (2020) | |||
S. J. Kent, E. P. Frady, F. T. Sommer and B. A. Olshausen: Resonator Networks, 2: Factorization Performance and Capacity Compared to Optimization-Based Methods. Neural Computation 32 (12): [https://doi.org/10.1162/neco_a_01329 2332–2388] (2020) | |||
K. E. Bouchard, J. B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. Donofrio, L. M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. Simon, F. T. Sommer, Prabhat: International neuroscience initiatives through the lens of high-performance computing. [http://www.cell.com/neuron/fulltext/S0896-6273(16)30785-1?_returnURL=http%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627316307851%3Fshowall%3Dtrue Neuron] 92:628-631 ( | D. Toker, F. T. Sommer, M Desposito, M: A simple method for detecting chaos in nature. Communications Biology [https://www.nature.com/articles/s42003-019-0715-9 3, 11] (2020) | ||
E. P. Frady, G. Orchard, D. Florey, N. Imam, R. Liu, J. Mishra, J. Tse, A. Wild, F. T. Sommer, M. Davies: Neuromorphic Nearest-Neighbor Search Using Intel's Pohoiki Springs. NICE '20: Proceedings of the Neuro-inspired Computational Elements WorkshopMarch 2020 [https://doi.org/10.1145/3381755.3398695 Article No.: 23, Pages 1–10] (2020)<br> | |||
(Earlier version [https://arxiv.org/abs/2004.12691 arXiv]) | |||
Z. Li, Y. Chen, F. T. Sommer: Annealed Denoising Score Matching: Learning energy based models in high dimensional spaces [https://openreview.net/forum?id=HJeFmkBtvB ICLR 2020 Open Review] (2020) | |||
J. A. Livezey, A. F. Bujan, F. T. Sommer: Learning Overcomplete, low coherence dictionaries with linear inference. Journal of Machine Learning Research [http://jmlr.org/papers/v20/18-703.html 20(174):1−42] (2019) | |||
E. P. Frady, F. T. Sommer: Robust computation with rhythmic spike patterns. Proceedings of the National Academy of Sciences [https://doi.org/10.1073/pnas.1902653116 September 3, 116 (36) 18050-18059] (2019), [https://neuroscience.berkeley.edu/new-model-of-neural-processing-could-help-us-understand-the-brain-and-create-better-ai/ UCB press release]<br> | |||
(Earlier version [https://arxiv.org/abs/1901.07718 arXiv]) | |||
D. Toker, F. T. Sommer: Information integration in large brain networks. [https://doi.org/10.1371/journal.pcbi.1006807 PLOS Computational Biology] (2019)<br> | |||
(Earlier version [https://arxiv.org/abs/1708.02967 arXiv]) | |||
==== Publications 2018 - 2003 ==== | |||
E. P. Frady, D. Kleyko, F. T. Sommer: A theory of sequence indexing and working memory in recurrent neural networks. Neural Computation, 30(6), 1449-1513. (2018) | |||
K. E. Bouchard, J. B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. D. Donofrio, L. M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. D. Simon, F. T. Sommer, Prabhat: International neuroscience initiatives through the lens of high-performance computing. Computer, 51(4): 50-59 (2018) | |||
C. Soto-Sánchez, X. Wang, V. Vaingankar, F. T. Sommer, J. A. Hirsch: The spatial scale of receptive fields in the visual sector of the cat’s thalamic reticular nucleus. Nature Communications 8, 800 (2017) doi:10.1038/s41467-017-00762-7 (2017) | |||
K. E. Bouchard, A. F. Bujan, E. F. Chang, F. T. Sommer: Sparse coding of ECoG signals identifies interpretable components for speech control in human sensorimotor cortex. IEEE, EMBC (2017) | |||
K. E. Bouchard, J. B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. Donofrio, L. M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. Simon, F. T. Sommer, Prabhat: High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination. [http://www.cell.com/neuron/fulltext/S0896-6273(16)30785-1?_returnURL=http%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627316307851%3Fshowall%3Dtrue Neuron] 92:628-631 (2016) | |||
A. Knoblauch, F. T. Sommer: Structural plasticity, effectual connectivity and memory in cortex. [http://journal.frontiersin.org/article/10.3389/fnana.2016.00063/abstract Frontiers in Neuroanatomy] (2016) | A. Knoblauch, F. T. Sommer: Structural plasticity, effectual connectivity and memory in cortex. [http://journal.frontiersin.org/article/10.3389/fnana.2016.00063/abstract Frontiers in Neuroanatomy] (2016) | ||
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J. L. Teeters, K. Godfrey, R. Young, C. Dang, C. Friedsam, B. Wark, H. Asari, S.
Peron, N. Li, A. Peyrache, G. Denisov, J. H. Siegle, S. R. Olsen, C. Martin, M. Chun, S. Tripathy, T. J. Blanche, K. D. Harris, G. Buzsaki, C. Koch, M. Meister, K. Svoboda, F. T. Sommer: Neurodata Without Borders: Creating
a common data format for neurophysiology. [http://www.cell.com/neuron/fulltext/S0896-6273(15)00919-8?_returnURL=http%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627315009198%3Fshowall%3Dtrue Neuron] 88:629-634 (2015) | J. L. Teeters, K. Godfrey, R. Young, C. Dang, C. Friedsam, B. Wark, H. Asari, S.
Peron, N. Li, A. Peyrache, G. Denisov, J. H. Siegle, S. R. Olsen, C. Martin, M. Chun, S. Tripathy, T. J. Blanche, K. D. Harris, G. Buzsaki, C. Koch, M. Meister, K. Svoboda, F. T. Sommer: Neurodata Without Borders: Creating
a common data format for neurophysiology. [http://www.cell.com/neuron/fulltext/S0896-6273(15)00919-8?_returnURL=http%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627315009198%3Fshowall%3Dtrue Neuron] 88:629-634 (2015) | ||
C. J. Hillar and F. T. Sommer: When can dictionary learning uniquely recover sparse data from subsamples? [http://ieeexplore.ieee.org/document/7165675/ IEEE Transactions on Information Theory] 61(11):6290-6297 (2015). Earlier [http://arxiv.org/abs/1106.3616 arXiv version] (2013) | C. J. Hillar and F. T. Sommer: When can dictionary learning uniquely recover sparse data from subsamples? [http://ieeexplore.ieee.org/document/7165675/ IEEE Transactions on Information Theory] 61(11):6290-6297 (2015). (Earlier [http://arxiv.org/abs/1106.3616 arXiv version] (2013)) | ||
S. Mobin, J. Arnemann, F. T. Sommer: Information-based learning by agents in unbounded state spaces. Advances in Neural Information Processing Systems [https://papers.nips.cc/paper/5266-information-based-learning-by-agents-in-unbounded-state-spaces NIPS] 26, MIT Press (2014). | S. Mobin, J. Arnemann, F. T. Sommer: Information-based learning by agents in unbounded state spaces. Advances in Neural Information Processing Systems [https://papers.nips.cc/paper/5266-information-based-learning-by-agents-in-unbounded-state-spaces NIPS] 26, MIT Press (2014). | ||
G. Agarwal, I. H. Stevenson, A. Berényi, K. Mizuseki, G. Buzsáki, F. T. Sommer: Spatially distributed local fields in the hippocampus encode rat position. [http://science.sciencemag.org/content/344/6184/626.long Science] 344 (2014): 626-630. | G. Agarwal, I. H. Stevenson, A. Berényi, K. Mizuseki, G. Buzsáki, F. T. Sommer: Spatially distributed local fields in the hippocampus encode rat position. [http://science.sciencemag.org/content/344/6184/626.long Science] 344 (2014): 626-630. | ||
A. Knoblauch, E. Koerner, U. Koerner, F. T. Sommer: Structural synaptic plasticity has high memory capacity and can explain graded amnesia, catastrophic forgetting, and the spacing effect. [http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0096485 PLOS ONE] (2014) | A. Knoblauch, E. Koerner, U. Koerner, F. T. Sommer: Structural synaptic plasticity has high memory capacity and can explain graded amnesia, catastrophic forgetting, and the spacing effect. [http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0096485 PLOS ONE] (2014) | ||
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L. M. Martinez, M. Molano-Mazon, X. Wang, F. T. Sommer, J. A. Hirsch: Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image. [http://www.cell.com/neuron/fulltext/S0896-6273(13)01145-8 Neuron] 81 (2014) 943-956 [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4114508/ PubMed pdf] (2014) | L. M. Martinez, M. Molano-Mazon, X. Wang, F. T. Sommer, J. A. Hirsch: Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image. [http://www.cell.com/neuron/fulltext/S0896-6273(13)01145-8 Neuron] 81 (2014) 943-956 [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4114508/ PubMed pdf] (2014) | ||
F. T. Sommer: | J. A. Hirsch, X. Wang, V. Vaingankar, F. T. Sommer: Inhibitory circuits in the visual thalamus. Chapter in: The New Visual Neurosciences, Eds.: Leo M. Chalupa and John S. Werner, MIT Press (2013) | ||
F. T. Sommer: Neural oscillatons and synchrony as mechanisms for coding, communication and computation in the visual system. Chapter in: The New Visual Neurosciences, Eds.: Leo M. Chalupa and John S. Werner, MIT Press (2013) [http://www.rctn.org/w/images/c/c4/Sommer13chapt_vis_neurosci.pdf pdf] | |||
D. Y. Little, F. T. Sommer: Learning and exploration in action-perception loops. [http://www.frontiersin.org/neural_circuits/10.3389/fncir.2013.00037/abstract Frontiers in Neural Circuits]. doi: 10.3389/fncir.2013.00037 (2013). Earlier [http://arxiv.org/abs/1112.1125 arXiv version]: Learning in embodied action-perception loops through exploration (2011) | D. Y. Little, F. T. Sommer: Learning and exploration in action-perception loops. [http://www.frontiersin.org/neural_circuits/10.3389/fncir.2013.00037/abstract Frontiers in Neural Circuits]. doi: 10.3389/fncir.2013.00037 (2013). Earlier [http://arxiv.org/abs/1112.1125 arXiv version]: Learning in embodied action-perception loops through exploration (2011) | ||
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D. Y. Little, F. T. Sommer: Maximal mutual information, not minimal entropy, for escaping the "Dark Room". Comment on "Whatever next? Predictive brains, situated agents, and the future of cognitive science." in Behavioral Brain Sciences 2013 Jun;36(3):220-221. doi: 10.1017/S0140525X12002415 [http://www.ncbi.nlm.nih.gov/pubmed/23663756] | D. Y. Little, F. T. Sommer: Maximal mutual information, not minimal entropy, for escaping the "Dark Room". Comment on "Whatever next? Predictive brains, situated agents, and the future of cognitive science." in Behavioral Brain Sciences 2013 Jun;36(3):220-221. doi: 10.1017/S0140525X12002415 [http://www.ncbi.nlm.nih.gov/pubmed/23663756] | ||
G. | G. Agarwal, F. T. Sommer: Measuring information in spike trains about intrinsic brain signals. Chapter in: [http://books.google.com/books?id=KTHUIMUpQCUC&pg=PA137&lpg=PA137&dq=agarwal+sommer+information+theory&source=bl&ots=78JmjIQQPb&sig=Rt9ATxPLJDx-2kdf-g5LKbxlwYI&hl=en&sa=X&ei=QKiCUevFOsm2igLKiIGICw&ved=0CGcQ6AEwBw#v=onepage&q=agarwal%20sommer%20information%20theory&f=false Spike timing: Mechanisms and functions], Eds.: P. M. DiLorenzo, J. D. Victor, CRC Press - Taylor & Francis Group 137-152 (2013) | ||
V. Vaingankar, C. Soto-Sanchez, X. Wang, F. T. Sommer, J. A. Hirsch: Neurons in the thalamic reticular nucleus are selective for diverse and complex visual features. [http://journal.frontiersin.org/article/10.3389/fnint.2012.00118/abstract Frontiers in Integrative Neuroscience] 6:118. DOI: 10.3389/fnint.2012.00118 (2012) | |||
V. Vaingankar, C. Soto-Sanchez, X. Wang, F. T. Sommer, J. A. Hirsch: Neurons in the | |||
C. Hillar, F. T. Sommer: Comment on the article "Distilling free-form natural laws from experimental data" [http://arxiv.org/abs/1210.7273 arXiv] (2012) | C. Hillar, F. T. Sommer: Comment on the article "Distilling free-form natural laws from experimental data" [http://arxiv.org/abs/1210.7273 arXiv] (2012) | ||
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X. Wang, V. Vaingankar, C. Soto Sanchez, F. T. Sommer, J. A. Hirsch: Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing. [http://www.nature.com/neuro/journal/v14/n2/full/nn.2707.html Nature Neuroscience] 14 (2011) 224-231 [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767474/ PubMed pdf] | X. Wang, V. Vaingankar, C. Soto Sanchez, F. T. Sommer, J. A. Hirsch: Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing. [http://www.nature.com/neuro/journal/v14/n2/full/nn.2707.html Nature Neuroscience] 14 (2011) 224-231 [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767474/ PubMed pdf] | ||
F. T. Sommer: Associative memory and learning. Chapter in Encyclopedia of the Sciences of Learning, Ed.: N. Seel, Springer (2011) | F. T. Sommer: Associative memory and learning. Chapter in [https://link.springer.com/referenceworkentry/10.1007%2F978-1-4419-1428-6_375 Encyclopedia of the Sciences of Learning], Ed.: N. Seel, Springer (2011) | ||
G. Isely, C. Hillar, F. T. Sommer: Decyphering subsampled data: Adaptive compressive sampling as a principle of brain communication. Advances in Neural Information Processing Systems [http://papers.nips.cc/paper/4093-deciphering-subsampled-data-adaptive-compressive-sampling-as-a-principle-of-brain-communication NIPS] 23. Eds: J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta (2011) 910-918 [http://www.google.com/url?sa=t&source=web&cd=1&ved=0CBoQFjAA&url=http%3A%2F%2Fbooks.nips.cc%2Fpapers%2Ffiles%2Fnips23%2FNIPS2010_1099.pdf&ei=aPFvTdLvLZHGsAPZ-5i_Cw&usg=AFQjCNGKtk3i_t5iSyxpdMcqMoLFhKf8OA&sig2=dnZxP1kl2pav20u7wloNSw pdf] | G. Isely, C. Hillar, F. T. Sommer: Decyphering subsampled data: Adaptive compressive sampling as a principle of brain communication. Advances in Neural Information Processing Systems [http://papers.nips.cc/paper/4093-deciphering-subsampled-data-adaptive-compressive-sampling-as-a-principle-of-brain-communication NIPS] 23. Eds: J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta (2011) 910-918 [http://www.google.com/url?sa=t&source=web&cd=1&ved=0CBoQFjAA&url=http%3A%2F%2Fbooks.nips.cc%2Fpapers%2Ffiles%2Fnips23%2FNIPS2010_1099.pdf&ei=aPFvTdLvLZHGsAPZ-5i_Cw&usg=AFQjCNGKtk3i_t5iSyxpdMcqMoLFhKf8OA&sig2=dnZxP1kl2pav20u7wloNSw pdf] | ||
C. Hillar, F. T. Sommer: Ramsey theory reveals the conditions when sparse coding on subsampled data is unique. | C. Hillar, F. T. Sommer: Ramsey theory reveals the conditions when sparse coding on subsampled data is unique. [https://arxiv.org/abs/1106.3616v1 arXiv] (2010) | ||
X. Wang, J. A. Hirsch, F. T. Sommer: Recoding of sensory information across the retinothalamic synapse. [http://www.jneurosci.org/content/30/41/13567 Journal of Neuroscience] 30: 13567-13577 [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842493/ PubMed pdf] (2010) | X. Wang, J. A. Hirsch, F. T. Sommer: Recoding of sensory information across the retinothalamic synapse. [http://www.jneurosci.org/content/30/41/13567 Journal of Neuroscience] 30: 13567-13577 [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842493/ PubMed pdf] (2010) | ||
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K. Koepsell, F. T. Sommer: Information transmission in oscillatory neural activity. [https://link.springer.com/article/10.1007/s00422-008-0273-6 Biological Cybernetics] 99 (2008) 403-416 [http://rctn.org/fsommer/papers/koepsellsommer08bicy.pdf pdf] | K. Koepsell, F. T. Sommer: Information transmission in oscillatory neural activity. [https://link.springer.com/article/10.1007/s00422-008-0273-6 Biological Cybernetics] 99 (2008) 403-416 [http://rctn.org/fsommer/papers/koepsellsommer08bicy.pdf pdf] | ||
J. L. Teeters, K. D. Harris, K. J. Millman, B. A. Olshausen, F. T. Sommer: Data sharing for computational neuroscience. Neuroinformatics 6 (2008) 47-55 [http://rctn.org/fsommer/papers/teetersetal08.pdf pdf] | J. L. Teeters, K. D. Harris, K. J. Millman, B. A. Olshausen, F. T. Sommer: Data sharing for computational neuroscience. [https://link.springer.com/article/10.1007/s12021-008-9009-y Neuroinformatics] 6 (2008) 47-55 [http://rctn.org/fsommer/papers/teetersetal08.pdf pdf] | ||
X. Wang, Y. Wei, V. Vaingankar, Q. Wang, K. Koepsell, F. T. Sommer, J. A. Hirsch: Feedforward excitation and inhibition evoke dual modes of firing in the cat’s visual thalamus during naturalistic viewing. Neuron 55 (2007) 465-478. [http://rctn.org/fsommer/papers/wangetal07neuron.pdf pdf] See also the preview about this paper: P. Reinagel: The inner life of bursts. Neuron 55 (2007) 339-341 | X. Wang, Y. Wei, V. Vaingankar, Q. Wang, K. Koepsell, F. T. Sommer, J. A. Hirsch: Feedforward excitation and inhibition evoke dual modes of firing in the cat’s visual thalamus during naturalistic viewing. [http://www.cell.com/neuron/fulltext/S0896-6273(07)00496-5 Neuron] 55 (2007) 465-478. [http://rctn.org/fsommer/papers/wangetal07neuron.pdf pdf] See also the preview about this paper: P. Reinagel: The inner life of bursts. Neuron 55 (2007) 339-341 | ||
F. T. Sommer: Bunte Theorien für graue Zellen. [http://www.gehirn-und-geist.de/artikel/872207 Gehirn und Geist], Juni (2007) 70-76 | F. T. Sommer: Bunte Theorien für graue Zellen. [http://www.gehirn-und-geist.de/artikel/872207 Gehirn und Geist], Juni (2007) 70-76 | ||
M. Rehn, F. T. Sommer: A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. | M. Rehn, F. T. Sommer: A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. [https://link.springer.com/article/10.1007/s10827-006-0003-9 Journal of Computational Neuroscience] 22 (2) 135-146 (2007). [http://rctn.org/fsommer/papers/rehnsommer07jcns.pdf pdf] | ||
M. Rehn, F. T. Sommer: Storing and restoring visual input with collaborative rank coding and associative memory. | M. Rehn, F. T. Sommer: Storing and restoring visual input with collaborative rank coding and associative memory. | ||
Neurocomputing 69 (10-12) (2006) 1219-1223 [http://rctn.org/fsommer/papers/rehnsommer06neurocomp.pdf pdf] | [http://www.sciencedirect.com/science/article/pii/S0925231205004066 Neurocomputing] 69 (10-12) (2006) 1219-1223 [http://rctn.org/fsommer/papers/rehnsommer06neurocomp.pdf pdf] | ||
F. T. Sommer, P. Kanerva: Can neural models of cognition benefit from the advantages of connectionism? | F. T. Sommer, P. Kanerva: Can neural models of cognition benefit from the advantages of connectionism? | ||
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F. T. Sommer, T. Wennekers: Synfire chains with conductance-based neurons: internal timing and coordination with timed input. | F. T. Sommer, T. Wennekers: Synfire chains with conductance-based neurons: internal timing and coordination with timed input. | ||
Neurocomputing 65-66 (2005) 449 - 454 [http://rctn.org/fsommer/papers/sommerwennekers05.pdf pdf] | [http://www.sciencedirect.com/science/article/pii/S092523120400400X Neurocomputing] 65-66 (2005) 449 - 454 [http://rctn.org/fsommer/papers/sommerwennekers05.pdf pdf] | ||
D. George, F. T. Sommer: Computing with inter-spike inverval codes in networks of integrate and fire neurons. | D. George, F. T. Sommer: Computing with inter-spike inverval codes in networks of integrate and fire neurons. | ||
Neurocomputing 65-66 (2005) 414 - 420 [http://rctn.org/fsommer/papers/georgesommer05.pdf pdf] | [http://www.sciencedirect.com/science/article/pii/S0925231204004230 Neurocomputing] 65-66 (2005) 414 - 420 [http://rctn.org/fsommer/papers/georgesommer05.pdf pdf] | ||
L. M. Martinez, Q. Wang, R. C. Reid, C. Pillai, J.-M. Alonso, F. T. Sommer, J. A. Hirsch: Receptive field structure varies with layer in the primary visual cortex. | L. M. Martinez, Q. Wang, R. C. Reid, C. Pillai, J.-M. Alonso, F. T. Sommer, J. A. Hirsch: Receptive field structure varies with layer in the primary visual cortex. | ||
Nature Neuroscience 8 (12) (2005) 372 - 379 [http://rctn.org/fsommer/papers/martinezetal05.pdf pdf] | [http://www.nature.com/neuro/journal/v8/n3/full/nn1404.html Nature Neuroscience] 8 (12) (2005) 372 - 379 [http://rctn.org/fsommer/papers/martinezetal05.pdf pdf] | ||
A. Knoblauch, F. T. Sommer: Spike-timing dependent plasticity can form "zero-lag" links for cortical oscillations. | A. Knoblauch, F. T. Sommer: Spike-timing dependent plasticity can form "zero-lag" links for cortical oscillations. | ||
Neurocomputing 52-54 (2004) 301 - 306 [http://rctn.org/fsommer/papers/KnoblauchSommer04.pdf pdf] | [http://www.sciencedirect.com/science/article/pii/S0925231204000372 Neurocomputing] 52-54 (2004) 301 - 306 [http://rctn.org/fsommer/papers/KnoblauchSommer04.pdf pdf] | ||
G. Glatting, F. M. Mottaghy, J. Karitzky, A. Baune, F. T. Sommer, G. B. Landwehrmeyer, S. N. Reske: Improving binding potential analysis in [11C]raclopide PET studies using cluster analysis. | G. Glatting, F. M. Mottaghy, J. Karitzky, A. Baune, F. T. Sommer, G. B. Landwehrmeyer, S. N. Reske: Improving binding potential analysis in [11C]raclopide PET studies using cluster analysis. | ||
Medical Physics 31 (4) (2004) 902-906 [http://rctn.org/fsommer/papers/glattingetal04.pdf pdf] | [http://onlinelibrary.wiley.com/doi/10.1118/1.1668392/abstract;jsessionid=0883CB4A1FA57FB25969CE9AEEEB9C8D.f03t03 Medical Physics] 31 (4) (2004) 902-906 [http://rctn.org/fsommer/papers/glattingetal04.pdf pdf] | ||
J. A. Hirsch, L. M. Martinez, C. Pillai, J.-M. Alonso, Q. Wang, F. T. Sommer: Functionally distinct inhibitory neurons at the first stage of visual cortical processing. | J. A. Hirsch, L. M. Martinez, C. Pillai, J.-M. Alonso, Q. Wang, F. T. Sommer: Functionally distinct inhibitory neurons at the first stage of visual cortical processing. | ||
Nature Neuroscience 6 (12) (2003) 1300 - 1308 [http://rctn.org/fsommer/papers/hirschetal03.pdf pdf] | [http://www.nature.com/neuro/journal/v6/n12/full/nn1152.html Nature Neuroscience] 6 (12) (2003) 1300 - 1308 [http://rctn.org/fsommer/papers/hirschetal03.pdf pdf] | ||
F. T. Sommer, T. Wennekers: Models of distributed associative memory networks in the brain. | F. T. Sommer, T. Wennekers: Models of distributed associative memory networks in the brain. | ||
Theory in Biosciences (122) (2003) 70 - 86 [http://rctn.org/fsommer/papers/sommerwennekers03.pdf pdf] | [http://www.sciencedirect.com/science/article/pii/S1431761304700749 Theory in Biosciences] (122) (2003) 70 - 86 [http://rctn.org/fsommer/papers/sommerwennekers03.pdf pdf] | ||
A. Knoblauch, F. T. Sommer: Synaptic plasticity, conduction delays, and inter-areal phase relations of spike activity in a model of reciprocally connected areas. | A. Knoblauch, F. T. Sommer: Synaptic plasticity, conduction delays, and inter-areal phase relations of spike activity in a model of reciprocally connected areas. | ||
Neurocomputing (52-54) (2003) 301-306 [http://redwood.berkeley.edu/fsommer/papers/knoblauchsommer03.pdf pdf] | [http://www.sciencedirect.com/science/article/pii/S0925231202007920 Neurocomputing] (52-54) (2003) 301-306 [http://redwood.berkeley.edu/fsommer/papers/knoblauchsommer03.pdf pdf] | ||
== Workshops, Conferences, Seminar Series and Teaching Courses == | == Workshops, Conferences, Seminar Series and Teaching Courses == | ||
'''Workshop and conference organization:''' | '''Workshop and conference organization:''' | ||
* [https://simons.berkeley.edu/workshops/brain2018-2 Targeted Discovery in Brain Data], co-organizer, Brain and Computation program 2018 at the Simon Center for the Theory of Computing, UC Berkeley | |||
* Open Data Ecosystem for the Neurosciences. Ronald Reagan Building and International Trade Center, Washington, DC on July 25-26, 2016, co-organizer | * Open Data Ecosystem for the Neurosciences. Ronald Reagan Building and International Trade Center, Washington, DC on July 25-26, 2016, co-organizer | ||
* [http://nips.cc/Conferences/2013/Program/event.php?ID=3699 NIPS Workshop: High-dimensional Statistical Inference in the Brain], Lake Tahoe, 2013, co-organizer | * [http://nips.cc/Conferences/2013/Program/event.php?ID=3699 NIPS Workshop: High-dimensional Statistical Inference in the Brain], Lake Tahoe, 2013, co-organizer | ||
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International summer courses | International summer courses | ||
* [https://crcns.org/course Modeling and Mining of Neuroscience Data], UC Berkeley 2013- | * [https://crcns.org/course Modeling and Mining of Neuroscience Data], UC Berkeley 2013-present (paused in 2020/2021), organizer, moderator | ||
Semester courses | Semester courses | ||
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Eds: F. T. Sommer, A. Wichert: Exploratory analysis and data modeling in functional neuroimaging. | Eds: F. T. Sommer, A. Wichert: Exploratory analysis and data modeling in functional neuroimaging. | ||
MIT Press, Boston, MA (2003) | MIT Press, Boston, MA (2003) | ||
Tool for analysis of functional neuroimaging: The brain positioning software (BPS) gives access to the Brodmann atlas and can be called directly from the SPM data analysis software. For description, see: Schmitt V., Wichert A., Grothe J., Sommer F. T.: [http://link.springer.com/chapter/10.1007%2F978-1-4615-1079-6_17 The brain positioning software. A Practical guide of neuroscience databases.] Ed.: R. Kötter, Kluwer, NY, 2002 | Tool for analysis of functional neuroimaging: The brain positioning software (BPS) gives access to the Brodmann atlas and can be called directly from the SPM data analysis software. For description, see: Schmitt V., Wichert A., Grothe J., Sommer F. T.: [http://link.springer.com/chapter/10.1007%2F978-1-4615-1079-6_17 The brain positioning software. A Practical guide of neuroscience databases.] Ed.: R. Kötter, Kluwer, NY, 2002 | ||
== Earlier Neuroscience Publications by Theme == | == Earlier Neuroscience Publications by Theme == | ||
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==Funding== | ==Funding== | ||
Currently, my research is funded by | Currently, my research is funded by National Institute of Health, the National Science Foundation and the Kavli Foundation. | ||
In the past, I have received support from the Hawkins-Strauss trust, the German Science Foundation, the Ministry of Education and Research of Baden-Wuerttemberg and by the Wilhelm-Schweizer-Zinnfiguren GmbH. I enjoyed a free and broad academic training due to the public university system of the Federal Republic of Germany. | In the past, I have received support from the Hawkins-Strauss trust, the German Science Foundation, the Ministry of Education and Research of Baden-Wuerttemberg and by the Wilhelm-Schweizer-Zinnfiguren GmbH. I enjoyed a free and broad academic training due to the public university system of the Federal Republic of Germany. |
Latest revision as of 22:14, 1 July 2024
Friedrich T. Sommer, Ph.D.
University of California, Berkeley
Redwood Center for Theoretical Neuroscience - Helen Wills Neuroscience Institute
Warren Hall
Berkeley, CA 94720
email F $ 0 M M E R (a) B E R K E L E Y * E D U (please retype)
Research Engineer/Scientist, Intel Labs & Adjunct Professor, Redwood Center for Theoretical Neuroscience & Helen Wills Neuroscience Institute, University of California, Berkeley
Faculty member (Hochschuldozent), Department of Computer Science, University of Ulm
Previous appointments:
2005-2011 Associate Adjunct Professor, University of California, Berkeley
2009 Acting director of the Redwood Center for Theoretical Neuroscience at UC Berkeley
Research Interests
Many impressive capabilities of the brain are not yet understood, for example, how unsupervised learning shapes the brains of animals and humans while controlling closed action-perception loops with the environment, or the virtually unlimited capacity of our long-term memory and its close connection to spatial navigation.
In collaboration with experimental neuroscience labs, my lab investigates the theoretical principles of learning and perception and their biological bases in the circuit dynamics of the brain. At the same time, I am interested in neurobiological design principles for building artificial intelligence systems.
For a full list of publications, see Google Scholar Profile
Journal articles, book chapters and submissions
Submissions/arXiv'ed manuscripts
C. Kymn, S. Mazelet, A. H. Thomas, D. Kleyko, E. P. Frady, F. T. Sommer, B. Olshausen: Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps (2024)
Z. Li, Y. Chen, Y. LeCun, F. T. Sommer: Neural Manifold Clustering and Embedding. https://arxiv.org/abs/2201.10000 (2022)
C. Warner, F. T. Sommer: A probabilistic latent variable model for detecting structure in binary data. https://arxiv.org/abs/2201.11108 (2022)
E. P. Frady, D. Kleyko, C. J. Kymn, B. A. Olshausen, F. T. Sommer: Computing on functions using randomized vector representations. https://arxiv.org/abs/2109.03429 (2021)
C. Warner, F. T. Sommer: A Model for Image Segmentation in Retina arXiv (2020)
Z. Li, F. T. Sommer: The amplitude-phase complex Boltzmann machine arXiv (2020)
C. Bybee, E. P. Frady, F. T. Sommer: Deep learning in spiking phasor neural networks, in preparation
Recent Publications
A. Renner, L. Supic, A. Danielescu, G. Indiveri, B. A. Olshausen, Y. Sandamirskaya, F. T. Sommer, E. P. Frady: Neuromorphic visual scene understanding with resonator networks. Nature Machine Intelligence. June 2024 read-only pdf (2024)
A. Renner, L. Supic, A. Danielescu, G. Indiveri, E. P. Frady, F. T. Sommer, and Y. Sandamirskaya: Neuromorphic Visual Odometry with Resonator Networks. Nature Machine Intelligence. June 2024 read-only pdf (2024) Cover image of June 2024 issue
Z. Li, Y. Chen, F. T. Sommer: Learning energy-based models in high-dimensional spaces with multi-scale denoising-score matching. Entropy (2023)
C. Bybee, D. Kleyko, D. E. Nikonov, A. Khosrowshahi, F. T. Sommer: Efficient optimization with higher-order Ising machines. Nature Communication (2023)
(Earlier version arXiv)
D. Kleyko, C. Bybee, P.-C. Huang, C. J. Kymn, B. A. Olshausen, E. P. Frady, F. T. Sommer: Efficient Decoding of Compositional Structure in Holistic Representations. Neural Computation 5/2023 p1-28, (2023)
D. Kleyko, A. Rosato, E. P. Frady, M. Panella, F. T. Sommer: Perceptron Theory for Predicting the Accuracy of Neural Networks. IEEE Transactions on Neural Networks and Learning Systems (2023)
(Earlier version arXiv)
F. T. Sommer, J. A Hirsch: How the LGN forwards retinal information in the cortex. Chapter in The cerebral cortex and thalamus, Eds: W. M. Usrey and M. Sherman, Oxford University Press (2023)
D. Kleyko, M. Davies, E. P. Frady, P. Kanerva, S. J. Kent, B. A. Olshausen, E. Osipov, J. M. Rabaey, D. A. Rachkovskij, A. Rahimi, F. T. Sommer: Vector Symbolic Architectures as computing framework for nanoscale hardware. Proceedings of the IEEE, 110(10), 1538-1571. (2022)
(Earlier version arXiv)
D. Toker, I. Pappas, J. D. Lendner, J. Frohlich, D. M. Mateos, S. Muthukumaraswamy, R. Carhart-Harris, M. Pfaff, P. M. Vesta, M. M. Monti, F. T. Sommer, R. T. Knight, M. D'Esposito: Consciousness is supported by near-critical cortical electrodynamics. PNAS https://www.pnas.org/content/119/7/e2024455119 (2022)
D. Kleyko, E. P. Frady, F. T. Sommer: Cellular Automata Can Reduce Memory Requirements of Collective-State Computing, IEEE Transactions on Neural Networks and Learning Systems. Print ISSN: 2162-237X, Online ISSN: 2162-2388, Digital Object Identifier: 10.1109/TNNLS.2021.3119543 (2021)
(Earlier version arXiv)
E. P. Frady, D. Kleyko, F. T. Sommer: Variable Binding for Sparse Distributed Representations: Theory and Applications. IEEE Transactions on Neural Networks and Learning Systems 10.1109/TNNLS.2021.3105949 (2021)
(Earlier version arXiv)
Zengyi Li, Yubei Chen, F. T. Sommer: A Neural Network MCMC Sampler That Maximizes Proposal Entropy. Entropy 23(3), 269;
doi:10.3390/e23030269 (2021)
(Earlier version arXiv)
E. P. Frady, S. J. Kent, B. A. Olshausen and F. T. Sommer: Resonator Networks, 1: An Efficient Solution for Factoring High-Dimensional, Distributed Representations of Data Structures. Neural Computation 32 (12): 2311–2331 (2020)
S. J. Kent, E. P. Frady, F. T. Sommer and B. A. Olshausen: Resonator Networks, 2: Factorization Performance and Capacity Compared to Optimization-Based Methods. Neural Computation 32 (12): 2332–2388 (2020)
D. Toker, F. T. Sommer, M Desposito, M: A simple method for detecting chaos in nature. Communications Biology 3, 11 (2020)
E. P. Frady, G. Orchard, D. Florey, N. Imam, R. Liu, J. Mishra, J. Tse, A. Wild, F. T. Sommer, M. Davies: Neuromorphic Nearest-Neighbor Search Using Intel's Pohoiki Springs. NICE '20: Proceedings of the Neuro-inspired Computational Elements WorkshopMarch 2020 Article No.: 23, Pages 1–10 (2020)
(Earlier version arXiv)
Z. Li, Y. Chen, F. T. Sommer: Annealed Denoising Score Matching: Learning energy based models in high dimensional spaces ICLR 2020 Open Review (2020)
J. A. Livezey, A. F. Bujan, F. T. Sommer: Learning Overcomplete, low coherence dictionaries with linear inference. Journal of Machine Learning Research 20(174):1−42 (2019)
E. P. Frady, F. T. Sommer: Robust computation with rhythmic spike patterns. Proceedings of the National Academy of Sciences September 3, 116 (36) 18050-18059 (2019), UCB press release
(Earlier version arXiv)
D. Toker, F. T. Sommer: Information integration in large brain networks. PLOS Computational Biology (2019)
(Earlier version arXiv)
Publications 2018 - 2003
E. P. Frady, D. Kleyko, F. T. Sommer: A theory of sequence indexing and working memory in recurrent neural networks. Neural Computation, 30(6), 1449-1513. (2018)
K. E. Bouchard, J. B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. D. Donofrio, L. M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. D. Simon, F. T. Sommer, Prabhat: International neuroscience initiatives through the lens of high-performance computing. Computer, 51(4): 50-59 (2018)
C. Soto-Sánchez, X. Wang, V. Vaingankar, F. T. Sommer, J. A. Hirsch: The spatial scale of receptive fields in the visual sector of the cat’s thalamic reticular nucleus. Nature Communications 8, 800 (2017) doi:10.1038/s41467-017-00762-7 (2017)
K. E. Bouchard, A. F. Bujan, E. F. Chang, F. T. Sommer: Sparse coding of ECoG signals identifies interpretable components for speech control in human sensorimotor cortex. IEEE, EMBC (2017)
K. E. Bouchard, J. B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. Donofrio, L. M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. Simon, F. T. Sommer, Prabhat: High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination. Neuron 92:628-631 (2016)
A. Knoblauch, F. T. Sommer: Structural plasticity, effectual connectivity and memory in cortex. Frontiers in Neuroanatomy (2016)
J. A. Livezey, A. F. Bujan, F. T. Sommer: On degeneracy control in overcomplete ICA arXiv (2016)
V. Suresh, U.M. Çiftçioğlu, X. Wang, B. M. Lala, K. R. Ding, W. A. Smith, F. T. Sommer, J. A. Hirsch: Synaptic Contributions to Receptive Field Structure and Response Properties in the Rodent Lateral Geniculate Nucleus of the Thalamus. Journal of Neuroscience 36(43), 10949-10963 (2016)
J. L. Teeters, K. Godfrey, R. Young, C. Dang, C. Friedsam, B. Wark, H. Asari, S. Peron, N. Li, A. Peyrache, G. Denisov, J. H. Siegle, S. R. Olsen, C. Martin, M. Chun, S. Tripathy, T. J. Blanche, K. D. Harris, G. Buzsaki, C. Koch, M. Meister, K. Svoboda, F. T. Sommer: Neurodata Without Borders: Creating a common data format for neurophysiology. Neuron 88:629-634 (2015)
C. J. Hillar and F. T. Sommer: When can dictionary learning uniquely recover sparse data from subsamples? IEEE Transactions on Information Theory 61(11):6290-6297 (2015). (Earlier arXiv version (2013))
S. Mobin, J. Arnemann, F. T. Sommer: Information-based learning by agents in unbounded state spaces. Advances in Neural Information Processing Systems NIPS 26, MIT Press (2014).
G. Agarwal, I. H. Stevenson, A. Berényi, K. Mizuseki, G. Buzsáki, F. T. Sommer: Spatially distributed local fields in the hippocampus encode rat position. Science 344 (2014): 626-630.
A. Knoblauch, E. Koerner, U. Koerner, F. T. Sommer: Structural synaptic plasticity has high memory capacity and can explain graded amnesia, catastrophic forgetting, and the spacing effect. PLOS ONE (2014)
L. M. Martinez, M. Molano-Mazon, X. Wang, F. T. Sommer, J. A. Hirsch: Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image. Neuron 81 (2014) 943-956 PubMed pdf (2014)
J. A. Hirsch, X. Wang, V. Vaingankar, F. T. Sommer: Inhibitory circuits in the visual thalamus. Chapter in: The New Visual Neurosciences, Eds.: Leo M. Chalupa and John S. Werner, MIT Press (2013)
F. T. Sommer: Neural oscillatons and synchrony as mechanisms for coding, communication and computation in the visual system. Chapter in: The New Visual Neurosciences, Eds.: Leo M. Chalupa and John S. Werner, MIT Press (2013) pdf
D. Y. Little, F. T. Sommer: Learning and exploration in action-perception loops. Frontiers in Neural Circuits. doi: 10.3389/fncir.2013.00037 (2013). Earlier arXiv version: Learning in embodied action-perception loops through exploration (2011)
D. Y. Little, F. T. Sommer: Maximal mutual information, not minimal entropy, for escaping the "Dark Room". Comment on "Whatever next? Predictive brains, situated agents, and the future of cognitive science." in Behavioral Brain Sciences 2013 Jun;36(3):220-221. doi: 10.1017/S0140525X12002415 [1]
G. Agarwal, F. T. Sommer: Measuring information in spike trains about intrinsic brain signals. Chapter in: Spike timing: Mechanisms and functions, Eds.: P. M. DiLorenzo, J. D. Victor, CRC Press - Taylor & Francis Group 137-152 (2013)
V. Vaingankar, C. Soto-Sanchez, X. Wang, F. T. Sommer, J. A. Hirsch: Neurons in the thalamic reticular nucleus are selective for diverse and complex visual features. Frontiers in Integrative Neuroscience 6:118. DOI: 10.3389/fnint.2012.00118 (2012)
C. Hillar, F. T. Sommer: Comment on the article "Distilling free-form natural laws from experimental data" arXiv (2012)
X. Wang, F. T. Sommer, J. A. Hirsch: Inhibitory circuits for visual processing in thalamus. Current Opinion in Neurobiology 21 (2011) 726-733 PubMed pdf
X. Wang, V. Vaingankar, C. Soto Sanchez, F. T. Sommer, J. A. Hirsch: Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing. Nature Neuroscience 14 (2011) 224-231 PubMed pdf
F. T. Sommer: Associative memory and learning. Chapter in Encyclopedia of the Sciences of Learning, Ed.: N. Seel, Springer (2011)
G. Isely, C. Hillar, F. T. Sommer: Decyphering subsampled data: Adaptive compressive sampling as a principle of brain communication. Advances in Neural Information Processing Systems NIPS 23. Eds: J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta (2011) 910-918 pdf
C. Hillar, F. T. Sommer: Ramsey theory reveals the conditions when sparse coding on subsampled data is unique. arXiv (2010)
X. Wang, J. A. Hirsch, F. T. Sommer: Recoding of sensory information across the retinothalamic synapse. Journal of Neuroscience 30: 13567-13577 PubMed pdf (2010)
K. Koepsell, X. Wang, J. A. Hirsch, F. T. Sommer: Exploring the function of neural oscillations in early sensory systems. Focused review in Frontiers in Neuroscience 4: 53-61 (2010)
A. Knoblauch, G. Palm, F. T. Sommer: Memory capacities for synaptic and structural plasticity. Neural Computation 22 (2010) 289-341 pdf
G. Monaci, P. Vandergheynst, F. T. Sommer: Learning bimodal structure in audio-visual data. IEEE Transactions on Neural Networks 20 (2009) 1898-1910 pdf
K. Koepsell, X. Wang, V. Vaingankar, Y. Wei, Q. Wang, D. L. Rathbun, W. M. Usrey, J. A. Hirsch, F. T. Sommer: Retinal oscillations carry visual information to cortex. Frontiers in Systems Neuroscience (2009)
K. Koepsell, F. T. Sommer: Information transmission in oscillatory neural activity. Biological Cybernetics 99 (2008) 403-416 pdf
J. L. Teeters, K. D. Harris, K. J. Millman, B. A. Olshausen, F. T. Sommer: Data sharing for computational neuroscience. Neuroinformatics 6 (2008) 47-55 pdf
X. Wang, Y. Wei, V. Vaingankar, Q. Wang, K. Koepsell, F. T. Sommer, J. A. Hirsch: Feedforward excitation and inhibition evoke dual modes of firing in the cat’s visual thalamus during naturalistic viewing. Neuron 55 (2007) 465-478. pdf See also the preview about this paper: P. Reinagel: The inner life of bursts. Neuron 55 (2007) 339-341
F. T. Sommer: Bunte Theorien für graue Zellen. Gehirn und Geist, Juni (2007) 70-76
M. Rehn, F. T. Sommer: A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. Journal of Computational Neuroscience 22 (2) 135-146 (2007). pdf
M. Rehn, F. T. Sommer: Storing and restoring visual input with collaborative rank coding and associative memory. Neurocomputing 69 (10-12) (2006) 1219-1223 pdf
F. T. Sommer, P. Kanerva: Can neural models of cognition benefit from the advantages of connectionism? Behavoral and Brain Sciences 29 (1) 86-87 (2006) pdf
F. T. Sommer, T. Wennekers: Synfire chains with conductance-based neurons: internal timing and coordination with timed input. Neurocomputing 65-66 (2005) 449 - 454 pdf
D. George, F. T. Sommer: Computing with inter-spike inverval codes in networks of integrate and fire neurons. Neurocomputing 65-66 (2005) 414 - 420 pdf
L. M. Martinez, Q. Wang, R. C. Reid, C. Pillai, J.-M. Alonso, F. T. Sommer, J. A. Hirsch: Receptive field structure varies with layer in the primary visual cortex. Nature Neuroscience 8 (12) (2005) 372 - 379 pdf
A. Knoblauch, F. T. Sommer: Spike-timing dependent plasticity can form "zero-lag" links for cortical oscillations. Neurocomputing 52-54 (2004) 301 - 306 pdf
G. Glatting, F. M. Mottaghy, J. Karitzky, A. Baune, F. T. Sommer, G. B. Landwehrmeyer, S. N. Reske: Improving binding potential analysis in [11C]raclopide PET studies using cluster analysis. Medical Physics 31 (4) (2004) 902-906 pdf
J. A. Hirsch, L. M. Martinez, C. Pillai, J.-M. Alonso, Q. Wang, F. T. Sommer: Functionally distinct inhibitory neurons at the first stage of visual cortical processing. Nature Neuroscience 6 (12) (2003) 1300 - 1308 pdf
F. T. Sommer, T. Wennekers: Models of distributed associative memory networks in the brain. Theory in Biosciences (122) (2003) 70 - 86 pdf
A. Knoblauch, F. T. Sommer: Synaptic plasticity, conduction delays, and inter-areal phase relations of spike activity in a model of reciprocally connected areas. Neurocomputing (52-54) (2003) 301-306 pdf
Workshops, Conferences, Seminar Series and Teaching Courses
Workshop and conference organization:
- Targeted Discovery in Brain Data, co-organizer, Brain and Computation program 2018 at the Simon Center for the Theory of Computing, UC Berkeley
- Open Data Ecosystem for the Neurosciences. Ronald Reagan Building and International Trade Center, Washington, DC on July 25-26, 2016, co-organizer
- NIPS Workshop: High-dimensional Statistical Inference in the Brain, Lake Tahoe, 2013, co-organizer
- Workshop on Perception and Action, Santa Fe Institute, 2010, co-organizer, see article about this workshop
- COSYNE 2009 Program, member of program committee
- COSYNE 2008 Workshops, workshop chair
- COSYNE 2007 Workshops, workshop chair
- NIPS 2005 Program, program chair for Neuroscience
- CNS 2002 Workshop: Neural assemblies, co-organizer
- NIPS 2000 Workshop: Exploratory analysis and data modeling in functional neuroimaging, organizer
Seminar series organization:
- Redwood Seminar Series, Talks at the Redwood Center, UC Berkeley, 2005-present (most talks you can watch online via the link), co-organizer
Teaching at UC Berkeley:
International summer courses
- Modeling and Mining of Neuroscience Data, UC Berkeley 2013-present (paused in 2020/2021), organizer, moderator
Semester courses
- Theoretical and computational neuroscience (2003, 2005; 2007; 2009; 2010; teaching participation at course MCB262/PSYCH290P/VS265)
- Neural Computation (2006; teaching participation at course VS298)
Teaching at University of Ulm:
Summer course:
- Statistics of natural signals (2005)
Semester courses (1997-2002):
- Information retrieval and associative memory
- Computational Neuroscience
- Theoretical methods for the interpretation of medical functional imaging data
- Information Retrieval
- Associative memories: conventional and neuronal
- Neural Cell Assemblies
Earlier Edited Book and Software for Neuroimaging
Eds: F. T. Sommer, A. Wichert: Exploratory analysis and data modeling in functional neuroimaging. MIT Press, Boston, MA (2003)
Tool for analysis of functional neuroimaging: The brain positioning software (BPS) gives access to the Brodmann atlas and can be called directly from the SPM data analysis software. For description, see: Schmitt V., Wichert A., Grothe J., Sommer F. T.: The brain positioning software. A Practical guide of neuroscience databases. Ed.: R. Kötter, Kluwer, NY, 2002
Earlier Neuroscience Publications by Theme
For a brief description of some of the research projects, see synopsis of research.
Computational models and analysis of cell physiology in the early visual system
X. Wang, V. Vaingankar, C. Soto Sanchez, F. T. Sommer, J. A. Hirsch: Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing. Nature Neuroscience 14 (2011) 224-231
X. Wang, J. A. Hirsch, F. T. Sommer: Recoding of sensory information across the retinothalamic synapse. Journal of Neuroscience 30 (2010) 13567-13577
X. Wang, Y. Wei, V. Vaingankar, Q. Wang, K. Koepsell, F. T. Sommer, J. A. Hirsch: Feedforward excitation and inhibition evoke dual modes of firing in the cat’s visual thalamus during naturalistic viewing. Neuron 55 (2007) 465-478. See also the preview about this paper: P. Reinagel: The inner life of bursts. Neuron 55 (2007) 339-341
M. Rehn, F. T. Sommer: A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. J. Comp. Neurosci. 22 (2) 135-146 (2007). pdf Earlier online prepublication SpringerLink DOI 10.1007/s10827-006-003-9 (2006)
M. Rehn, F. T. Sommer: Storing and restoring visual input with collaborative rank coding and associative memory. Neurocomputing 69 (10-12) (2006) 1219-1223 pdf
L. M. Martinez, Q. Wang, R. C. Reid, C. Pillai, J.-M. Alonso, F. T. Sommer, J. A. Hirsch: Receptive field structure varies with layer in the primary visual cortex. Nature Neuroscience 8 (12) (2005) 372 - 379 pdf
J. A. Hirsch, L. M. Martinez, C. Pillai, J.-M. Alonso, Q. Wang, F. T. Sommer: Functionally distinct inhibitory neurons at the first stage of visual cortical processing. Nature Neuroscience 6 (12) (2003) 1300 - 1308 pdf
Mechanisms of memory in realistic neural networks
Structural plasticity
A. Knoblauch, E. Koerner, U. Koerner, F. T. Sommer: Structural synaptic plasticity has high memory capacity and can explain graded amnesia, catastrophic forgetting, and the spacing effect. to appear in PLOS ONE (2014)
A. Knoblauch, G. Palm, F. T. Sommer: Memory capacities for synaptic and structural plasticity. Neural Computation 22 (2010) 289-341 pdf
Long-term memory
F. T. Sommer, T. Wennekers: Associative memory in networks of spiking neurons Neural Networks 14 (6-7) Special Issue: Spiking Neurons in Neuroscience and Technology (2001) 825 - 834 pdf
F. T. Sommer, T. Wennekers: Modeling studies on the computational function of fast temporal structure in cortical circuit activity Journal of Physiology - Paris 94 (5/6) (2000) 473-488 pdf
F. T. Sommer: On cell assemblies in a cortical column Neurocomputing (32-33) (2000) 517 - 522 pdf
T. Wennekers, F. T. Sommer: Gamma-oscillations support optimal retrieval in associative memories of two-compartment neurons Neurocomputing 26-27 (1999) 573 - 578 pdf
T. Wennekers, F. T. Sommer, G. Palm: Iterative Retrieval in Associative Memories by Threshold Control of Different Neural Models In: Supercomputers in Brain Research: From Tomography to Neural Networks World Scientific Publishing Comp (1995) 301-319
Short-term memory
A. Knoblauch, T. Wennekers, F. T. Sommer: Is voltage dependent synaptic transmission in NMDA receptors a robust mechanism for working memory? Neurocomputing (44-46) (2002) 19-24 pdf
U. Vollmer, F. T. Sommer: Coexistence of short and long term memory in a model network of realistic neurons Neurocomputing (38-40) (2001) 1031 - 1036 pdf
Large-scale integration of cortical representations
F. T. Sommer, T. Wennekers: Models of distributed associative memory networks in the brain Theory in Biosciences (122) (2003) 70 - 86 pdf
Associative memory in reciprocal cortico-cortical projections
F. T. Sommer, T. Wennekers: Associative memory in a pair of cortical cell groups with reciprocal projections Neurocomputing (38-40) (2001) 1575 - 1580 pdf
F. T. Sommer, T. Wennekers, G. Palm: Bidirectional completion of cell assemblies in the cortex Computational Neuroscience: Trends in Research 1998, Plenum Press, New York, (1998) ps
Large-scale integration relying on neural oscillations
A. Knoblauch, F. T. Sommer: Spike-timing dependent plasticity can form "zero-lag" links for cortical oscillations Neurocomputing (58-60) 185 - 190 (2004) pdf
A. Knoblauch, F. T. Sommer: Synaptic plasticity, conduction delays, and inter-areal phase relations of spike activity in a model of reciprocally connected areas Neurocomputing (52-54) (2003) 301-306 pdf
Models of macroscopic activity spread in cortex
V. Schmitt, R. Koetter, F. T. Sommer: The impact of thalamo-cortical projections on activity spread in cortex Neurocomputing (2003) (52-54) (2003) 919-924 pdf
R. Kötter and F. T. Sommer: Global relationship between anatomical connectivity and activity propagation in the cerebral cortex Phil. Trans. R. Soc. Lond. B (355) (2000) 127 - 134 pdf
F. T. Sommer, R. Kötter: Simulating a Network of Cortical Areas Using Anatomical Connection Data in the Cat Computational Neuroscience: Trends in Research 1997, Plenum Press, New York (1997) 511-517 ps
R. Koetter, P. Nielsen, J. Dyhrfjeld, F. T. Sommer, G. Northoff: Multi-level integration of quantitative neuroanatimical data Chapter in Computational Neuroanatomy: Principles and Methods. Ed.: G. A. Ascoli, Humana Press Inc., Totowa, NJ (2002)
Theory of associative memory
Review on capacity analysis of memory networks
A. Knoblauch, G. Palm, F. T. Sommer: Memory capacities for synaptic and structural plasticity. Neural Computation, Volume 22, Issue 2, pp. 289-341 (2010) pdf
Bayesian theory of autoassociative memory
F. T. Sommer, P. Dayan: Bayesian Retrieval in Associative Memories with Storage Errors. IEEE Transactions on Neural Networks 9 (4) (1998) 705-713 pdf
Bidirectional sparse associative memory
F. T. Sommer, G. Palm: Improved Bidirectional Retrieval of Sparse Patterns Stored by Hebbian Learning. Neural Networks 12 (2) (1999) 281 - 297 pdf
F. T. Sommer, G. Palm: Bidirectional Retrieval from Associative Memory. Advances in Neural Information Processing Systems 10, MIT Press, Cambridge, MA (1998) 675 - 681 pdf
Capacity analysis of recurrent sparse autoassociative memories
F. Schwenker, F. T. Sommer, G. Palm: Iterative Retrieval of sparsely coded associative memory patterns. Neural Networks 9 (1996) 445-455 pdf
Capacity analysis of sparse pattern recognition
G. Palm, F. T. Sommer: Information capacity in recurrent Mc.Culloch-Pitts networks with sparsely coded memory states. Network 3 (1992) 177-186 pdf
G. Palm, F. T. Sommer: Information and pattern capacities in neural associative memories with feedback for sparse memory patterns. In: Neural Network Dynamics, Springer New York (1992). Eds.: J.G.Taylor, E.R.Caianello, R.M.J.Cotterill, J.W.Clark, 3-18
Analysis of local learning rules
G. Palm, F. T. Sommer: Associative data Storage and Retrieval in Neural Nets. In: Models of Neural Networks III, Springer New York (1996) Eds: E.Domany, J.L.van Hemmen, K.Schulten, 79-118 pdf
Book, PhD-Thesis (in german)
F. T. Sommer: Theorie neuronaler Assoziativspeicher - Lokales Lernen und iteratives Retrieval von Information. Verlag Hänsel-Hohenhausen (1993) ISBN 3-89349-901-6 ps
Neuroimaging
Edited book
Eds: F. T. Sommer, A. Wichert: Exploratory analysis and data modeling in functional neuroimaging. MIT Press, Boston, MA (2003)
General issues of Neuroimaging
F. T. Sommer, J. A. Hirsch, A. Wichert: Theories, data analysis and simulation models in neuroimaging - an overview In Exploratory analysis and data modeling in functional neuroimaging. Eds.: F.T. Sommer and A. Wichert, MIT Press, Boston, MA (2003) pdf
V. Schmitt, A. Wichert, J. Grothe, F. T. Sommer: The brain positioning software. In: A practical guide of neuroscience databases and associated tools, Ed. R. Koetter, Kluwer, NY (2002)
Unsupervised method of detecting functional activity in Neuroimaging
A. Wichert, B. Abler, J. Grothe, H. Walter, F. T. Sommer: Exploratory analysis of event-related fMRI demonstrated in a working memory study. In Exploratory analysis and data modeling in functional neuroimaging. Eds.: F.T. Sommer and A. Wichert, MIT Press, Boston, MA (2003) pdf
A. Wichert, H. Walter, G. Groen, A. Baune, J. Grothe, A. Wunderlich, F. T. Sommer: Detection of delay selective activity during a working memory task by explorative data analysis. Neuroimage (13) (2001) 282
A. Baune, F. T. Sommer, M. Erb, D. Wildgruber, B. Kardatzki, G. Palm, W. Grodd: Dynamical Cluster Analysis of Cortical fMRI Activation. NeuroImage 6 (5) (1999) 477 - 489 pdf
Analysis techniques in Positron Emission Tomography
G. Glatting, F. M. Mottaghy, J. Karitzky, A. Baune, F. T. Sommer, G. B. Landwehrmeyer, S. N. Reske: Improving binding potential analysis in [11C]raclopide PET studies using cluster analysis. Medical Physics 31 (4) (2004) 902-906 pdf
A. Baune, A. Wichert, G. Glatting, F. T. Sommer: Dynamical cluster analysis for the detection of microglia activation in Artificial Neural Nets and Genetic Algorithms. Eds. V. Kurkova, N. C. Stelle, R. Neruda, M. Karny. Springer, Wien (2001) 442 - 445
J. Ruckgaber, G. Glatting, J. Karitzky, A. Baune, F. T. Sommer, B. Neumaier, S. N. Reske: Clusteranalyse in der Positronen-Emissions-Tomographie des Hirns mit C-11-PK11195. Nuklearmedizin (40) (2001) A95
Neural associative memories in information technology
M. Rehn, F. T. Sommer: Storing and restoring visual input with collaborative rank coding and associative memory. Neurocomputing 69 (10-12) (2006) 1219-1223 pdf
G. Palm, F. Schwenker, F. T. Sommer, A. Strey: Neural associative memory. In Associative Processing and Processors, Eds. A. Krikelis and C. C. Weems, IEEE CS Press, Los Alamitos, CA, USA (1997) 307-326 ps
F. T. Sommer, F. Schwenker, G. Palm: Assoziative Speicher als Module in informationsverarbeitenden Systemen. In: Contributions to the Workshop Aspekte Neuronalen Lernens, Eds. L.Cromme, J. Wille, T. Kolb Tech Report, TU Cottbus M-01/1995 (1995)
G. Palm, F. Schwenker, F. T. Sommer: Associative memory and sparse similarity preserving codes. In: From Statistics to Neural Networks: Theory and Pattern Recognition Applications, Ed. V.Cherkassky, Springer NATO ASI Series F, New York (1994) 282-302
Earlier Publications in Physics
P. Frodl, F. T. Sommer, K. Hau, F. Wahl: On the effective interaction of two hydrogen centres in Niobium. Z. f. Naturforsch. 43a (1990) 857-866
K. Hau, P. Frodl, M. Gnirß, F. T. Sommer, F. Wahl: A Microscopic Theory of a alpha-Phase Hydrogen in Niobium. Z. f. physikalische Chemie 163 (1989) 549-554
F. T. Sommer, K. Hau, P. Frodl, F. Wahl: Calculation of the excitation energies of a hydrogen impurity in Niobium. Z. f. Naturforsch. 43a (1988) 923-929
K. Hau, P. Frodl, F. T. Sommer, F. Wahl: A microscopic theory of a single hydrogen centre in Niobium. Z. f. Naturforsch. 43a (1988) 914-922
Roots
Funding
Currently, my research is funded by National Institute of Health, the National Science Foundation and the Kavli Foundation.
In the past, I have received support from the Hawkins-Strauss trust, the German Science Foundation, the Ministry of Education and Research of Baden-Wuerttemberg and by the Wilhelm-Schweizer-Zinnfiguren GmbH. I enjoyed a free and broad academic training due to the public university system of the Federal Republic of Germany.