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Alexei Koulakov

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Alexei Koulakov
Koulakov speaking at the Collaborative Research in Computational Neuroscience meeting in 2023
Occupation(s)Theoretical physicist and neuroscientist
Academic background
EducationEngineer-Physicist (MS equivalent), Applied Mathematics and Physics (1990)
PhD., Physics (1998)
Alma materMoscow Institute of Physics and Technology
University of Minnesota
Academic work
InstitutionsCold Spring Harbor Laboratory

Alexei Koulakov is a theoretical physicist and a neuroscientist. He is the Charles Robertson Professor of Neuroscience at the Cold Spring Harbor Laboratory.[1]

Koulakov's group has used mathematics and theoretical physics to explore the brain, with focus on neural computation, brain development, and the evolution of brain architecture for optimal function. He received the Sloan Fellowship in Theoretical Neuroscience from 1998 to 2001 and the NIH Director's Transformative Research Award in 2018.[2][3]

Koulakov's research has been featured in media outlets, including Physics Today,[4] Wired,[5] Nautilus Magazine,[6] Medical Xpress,[7] Long Island Business News,[8] and 'Scientific Inquirer.[9]

Education and early career

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Koulakov earned an Engineer-physicist degree (equivalent to an MS) in Applied Mathematics and Physics from the Moscow Institute of Physics and Technology in 1990. From 1988 to 1993, he worked as an Engineer in the Theoretical Department at the Institute of Nuclear Energy in Troitsk, Moscow region. He then pursued a PhD in Theoretical Physics at the University of Minnesota, completing it in 1998. Following his doctoral studies, he engaged in a postdoctoral fellowship in Neuroscience in the Sloan Center for Theoretical Neurobiology at the Salk Institute for Biological Studies in La Jolla, California, where he conducted research from 1998 to 2001.[10][11]

Career

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Koulakov joined the Department of Physics at the University of Utah as an Assistant Professor in 2001. In 2003, he moved to Cold Spring Harbor Laboratory as an Assistant Professor, became an Associate Professor in 2008, and then was promoted to Professor in 2012. He held that role until 2021, when he became the Charles Robertson Professor.[1]

Koulakov has served as the Director of the Swartz Center for Computational Neuroscience at Cold Spring Harbor Laboratory.[12] He has organized workshops, including the Cosyne workshop in March 2018, which focused on exploring causal links between neural responses and behavior, and another, on computational olfaction, in March 2005 at Snowbird, Utah.[13]

Research

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Koulakov is most known for his contributions to condensed matter physics, computational neuroscience, brain evolution, neural development, olfactory coding, neural stem cells, machine learning, and artificial intelligence. He and his team have studied neural computation, brain development and evolution, including how neurons process information, how brain networks assemble during development, and how brain architecture evolved to facilitate its function.[14][15]

Contributions to neuroscience

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Computational principles of neural development

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Koulakov and his colleagues developed a predictive quantitative model of neural development that integrated the effects of molecular guidance cues and activity-dependent neural plasticity (learning). This model explained the effects of genetic, surgical, and pharmacological manipulations on neural connectivity across species. Refined for the visual system, it predicted connectivity changes in genetically modified animals and was generalizable to other forms of connectivity.[16][17]

Principles of cortical evolution

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Koulakov's research has focused on quantitative models of brain evolution, including theoretical models of cortical maps,[18][19] the development of cortical areas and their connectivity,[19] and the influence of the genomic bottleneck on cortical network evolution.[18][20][21]

Disposable neural stem cell hypothesis

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Examining the decline in hippocampal neurogenesis with age, Koulakov's quantitative analysis revealed that this decline was due to the depletion of the neural stem cell pool, which occurred as these cells were activated to generate new neurons. Activated stem cells underwent asymmetric divisions to produce neurons and eventually matured into astrocytes. His team proposed a "disposable stem cell" model which explains the age-related decrease in stem cells as resulting from production of new neurons.[22][23]

Olfactory coding

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In collaboration with his colleagues, Koulakov devised theories for olfactory coding that helped build an understanding of olfactory information processing. These included theories for temporal processing in the early olfactory system,[24] such as the primacy theory,[25] structured connectivity theory,[26][25] and sparse representations in the early olfactory system.[27]

Decision making and meta-cognition

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Koulakov's team has developed theories of decision-making in collaboration with experimental groups.[28][29] They have formulated a theory of decision confidence that has been experimentally tested.[30]

Reinforcement learning and motivated behavior

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Koulakov and his colleagues established a deep neural network-based reinforcement learning model of motivational salience, allowing agents to quickly adapt their behavior to changing rewards based on dynamic needs.[31] This approach improved the interpretability of behavioral data by inferring motivational dynamics in the brain. By linking sequential decision-making theories—including the marginal value theorem, reinforcement learning, and Bayesian methods—his research team proposed an optimal decision rule for stay-or-leave choices in natural environments.[32]

Attractor dynamics is short- and long-term memory

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Through joint efforts, Koulakov formulated theories of robust short-term (working) memory systems using attractor neural networks,[33][34][35] and discovered that attractor states can be stabilized in networks exhibiting long-term synaptic plasticity, a phenomenon that may result from memory consolidation.[36]

NeuroAI

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Spanning 2019 to 2024, Koulakov worked at the intersection of neuroscience and AI, aiming to use insights from nervous system studies to develop improved AI algorithms.[37][18][32][31][38]

Contributions to theoretical physics

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Koulakov and his colleagues theoretically identified a new quantum state of electrons in quantum Hall samples under weak magnetic fields, resembling a liquid crystal phase, which they described as "Quantum Hall Nematics". This theoretical discovery was later confirmed experimentally.[39][40] Within mesoscopic physics, they contributed to understanding the properties of small particles, such as quantum dots with a few electrons and superconducting vortex cores.[41][42][43]

Awards and honors

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  • 2018 – NIH Director's Transformative Research Award, NIH[2]

Selected articles

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  • Koulakov, A. A., Fogler, M. M., & Shklovskii, B. I. (1996). Charge density wave in two-dimensional electron liquid in weak magnetic field. Physical review letters, 76(3), 499.
  • Fogler, M. M., Koulakov, A. A., & Shklovskii, B. I. (1996). Ground state of a two-dimensional electron liquid in a weak magnetic field. Physical Review B, 54(3), 1853.
  • Koulakov, A. A., Raghavachari, S., Kepecs, A., & Lisman, J. E. (2002). Model for a robust neural integrator. Nature neuroscience, 5(8), 775-782.
  • Chklovskii, D. B., & Koulakov, A. A. (2004). Maps in the brain: what can we learn from them?. Annu. Rev. Neurosci., 27(1), 369-392.
  • Encinas, J. M., Michurina, T. V., Peunova, N., Park, J. H., Tordo, J., Peterson, D. A., ... & Enikolopov, G. (2011). Division-coupled astrocytic differentiation and age-related depletion of neural stem cells in the adult hippocampus. Cell stem cell, 8(5), 566-579.

References

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  1. ^ a b "Alexei Koulakov - Faculty Profile".
  2. ^ a b "NIH Director's Transformative Research Award".
  3. ^ "What's that smell? Neuroscientists are figuring it out". 2 October 2018.
  4. ^ "Microwaves Induce Vanishing Resistance in Two-Dimensional Electron Systems".
  5. ^ Harrison, Sara. "Now the Machines Are Learning How to Smell". Wired.
  6. ^ "The Doctor Will Sniff You Now". 3 February 2021.
  7. ^ "Mapping the path from smell to perception".
  8. ^ "Simons donates $50M to Cold Spring Harbor Lab". 7 July 2014.
  9. ^ "How the brain interprets smells continues to hold mysteries". 30 November 2019.
  10. ^ "NIH Director's Transformative Research Award - 2018 Awardees".
  11. ^ "Frontiers in Physics Colloquium Series - February 2002" (PDF).
  12. ^ "Swartz Foundation".
  13. ^ "If you thought all neuroscientists work with neurons, you're wrong".
  14. ^ "Alexei Koulakov - Faculty Profile - RESEARCH INTERESTS".
  15. ^ "Alexei Koulakov - Google Scholar".
  16. ^ Triplett, J. W.; Pfeiffenberger, C.; Yamada, J.; Stafford BK; Sweeney, N. T.; Litke, A. M.; Sher, A.; Koulakov, A. A.; Feldheim, D. A. (2011). "Competition is a driving force in topographic mapping". Proceedings of the National Academy of Sciences of the United States of America. 108 (47): 19060–19065. Bibcode:2011PNAS..10819060T. doi:10.1073/pnas.1102834108. PMC 3223436. PMID 22065784.
  17. ^ Wei, Y.; Tsigankov, D.; Koulakov, A. (2013). "The molecular basis for the development of neural maps". Annals of the New York Academy of Sciences. 1305 (1): 44–60. Bibcode:2013NYASA1305...44W. doi:10.1111/nyas.12324. PMID 24329485.
  18. ^ a b c Koulakov, Alexei; Shuvaev, Sergey; Lachi, Divyansha; Zador, Anthony (2022). "Encoding innate ability through a genomic bottleneck". doi:10.1101/2021.03.16.435261.
  19. ^ a b Ferrante, Daniel D.; Wei, Yi; Koulakov, Alexei A. (2016). "Mathematical Model of Evolution of Brain Parcellation". Frontiers in Neural Circuits. 10: 43. doi:10.3389/fncir.2016.00043. PMC 4909755. PMID 27378859.
  20. ^ Chklovskii, D. B.; Koulakov, A. A. (2004). "Maps in the brain: what can we learn from them?". Annual Review of Neuroscience. 27: 369–392. doi:10.1146/annurev.neuro.27.070203.144226. PMID 15217337.
  21. ^ Koulakov, Alexei A.; Chklovskii, Dmitri B. (February 2001). "Orientation Preference Patterns in Mammalian Visual Cortex: A Wire Length Minimization Approach". Neuron. 29 (2): 519–527. doi:10.1016/S0896-6273(01)00223-9. PMID 11239440.
  22. ^ Mineyeva, Olga A.; Enikolopov, Grigori; Koulakov, Alexei A. (2018). "Spatial geometry of stem cell proliferation in the adult hippocampus". Scientific Reports. 8 (1): 3444. Bibcode:2018NatSR...8.3444M. doi:10.1038/s41598-018-21078-6. PMC 5821870. PMID 29467395.
  23. ^ Encinas, J. M.; Michurina, T. V.; Peunova, N.; Park, J. H.; Tordo, J.; Peterson, D. A.; Fishell, G.; Koulakov, A.; Enikolopov, G. (2011). "Division-coupled astrocytic differentiation and age-related depletion of neural stem cells in the adult hippocampus". Cell Stem Cell. 8 (5): 566–579. doi:10.1016/j.stem.2011.03.010. PMC 3286186. PMID 21549330.
  24. ^ Koulakov, Alexei A.; Kolterman, B. E.; Enikolopov, A. G.; Rinberg, D. (2011). "In search of the structure of human olfactory space". Frontiers in Systems Neuroscience. 5: 65. doi:10.3389/fnsys.2011.00065. PMC 3173711. PMID 21954378.
  25. ^ a b Wilson, C. D.; Serrano, G. O.; Koulakov, A. A.; Rinberg, D. (2017). "A primacy code for odor identity". Nature Communications. 8 (1): 1477. Bibcode:2017NatCo...8.1477W. doi:10.1038/s41467-017-01432-4. PMC 5684307. PMID 29133907.
  26. ^ Chen, Y.; Chen, X.; Baserdem, B.; Zhan, H.; Li, Y.; Davis, M. B.; Kebschull, J. M.; Zador, A. M.; Koulakov, A. A.; Albeanu, D. F. (2022). "High-throughput sequencing of single neuron projections reveals spatial organization in the olfactory cortex". Cell. 185 (22): 4117–4134.e28. doi:10.1016/j.cell.2022.09.038. PMC 9681627. PMID 36306734.
  27. ^ Koulakov, A. A.; Rinberg, D. (2011). "Sparse incomplete representations: a potential role of olfactory granule cells". Neuron. 72 (1): 124–136. doi:10.1016/j.neuron.2011.07.031. PMC 3202217. PMID 21982374.
  28. ^ Rinberg, D.; Koulakov, A.; Gelperin, A. (2006). "Speed-accuracy tradeoff in olfaction". Neuron. 51 (3): 351–358. doi:10.1016/j.neuron.2006.07.013. PMID 16880129.
  29. ^ Shuvaev, Sergey; Amelchenko, Evgeny; Smagin, Dmitry; Kudryavtseva, Natalia; Enikolopov, Grigori; Koulakov, Alexei (2023). "A normative theory of social conflict". arXiv:2303.04285 [q-bio.NC].
  30. ^ Lak, A.; Costa, G. M.; Romberg, E.; Koulakov, A. A.; Mainen, Z. F.; Kepecs, A. (2014). "Orbitofrontal cortex is required for optimal waiting based on decision confidence". Neuron. 84 (1): 190–201. doi:10.1016/j.neuron.2014.08.039. PMC 4364549. PMID 25242219.
  31. ^ a b Shuvaev, Sergey A.; Tran, Ngoc B.; Stephenson-Jones, Marcus; Li, Bo; Koulakov, Alexei A. (2021). "Neural Networks With Motivation". Frontiers in Systems Neuroscience. 14. doi:10.3389/fnsys.2020.609316. PMC 7848953. PMID 33536879.
  32. ^ a b "R-learning in actor-critic model offers a biologically relevant mechanism for sequential decision-making". 2020. pp. 18872–18882.
  33. ^ Nikitchenko, M.; Koulakov, A. (2008). "Neural integrator: a sandpile model". Neural Computation. 20 (10): 2379–2717. doi:10.1162/neco.2008.12-06-416. PMC 2814182. PMID 18533820.
  34. ^ Koulakov, A.A. (2001). "Properties of synaptic transmission and the global stability of delayed activity states". Network: Computation in Neural Systems. 12 (1): 47–74. doi:10.1080/net.12.1.47.74. PMID 11254082.
  35. ^ Koulakov, A. A.; Raghavachari, S.; Kepecs, A.; Lisman, J. E. (2002). "Model for a robust neural integrator". Nature Neuroscience. 5 (8): 775–782. doi:10.1038/nn893. PMID 12134153.
  36. ^ Wei, Y.; Koulakov, A. A. (2014). "Long-Term Memory Stabilized by Noise-Induced Rehearsal". The Journal of Neuroscience. 34 (47): 15804–15815. doi:10.1523/JNEUROSCI.3929-12.2014. PMC 4236406. PMID 25411507.
  37. ^ Zador, Anthony; Escola, Sean; Richards, Blake; Ölveczky, Bence; Bengio, Yoshua; Boahen, Kwabena; Botvinick, Matthew; Chklovskii, Dmitri; Churchland, Anne; Clopath, Claudia; Dicarlo, James; Ganguli, Surya; Hawkins, Jeff; Körding, Konrad; Koulakov, Alexei; Lecun, Yann; Lillicrap, Timothy; Marblestone, Adam; Olshausen, Bruno; Pouget, Alexandre; Savin, Cristina; Sejnowski, Terrence; Simoncelli, Eero; Solla, Sara; Sussillo, David; Tolias, Andreas S.; Tsao, Doris (2023). "Catalyzing next-generation Artificial Intelligence through NeuroAI". Nature Communications. 14 (1): 1597. Bibcode:2023NatCo..14.1597Z. doi:10.1038/s41467-023-37180-x. PMC 10033876. PMID 36949048.
  38. ^ "NeuroAI".
  39. ^ Fogler, M. M.; Koulakov, A. A.; Shklovskii, B. I. (1996). "Ground state of a two-dimensional electron liquid in a weak magnetic field". Physical Review B. 54 (3): 1853–1871. arXiv:cond-mat/9601110. Bibcode:1996PhRvB..54.1853F. doi:10.1103/PhysRevB.54.1853. PMID 9986033.
  40. ^ Koulakov, A. A.; Fogler, M. M.; Shklovskii, B. I. (1996). "Charge Density Wave in Two-Dimensional Electron Liquid in Weak Magnetic Field". Physical Review Letters. 76 (3): 499–502. arXiv:cond-mat/9508017. Bibcode:1996PhRvL..76..499K. doi:10.1103/PhysRevLett.76.499. PMID 10061472.
  41. ^ Koulakov, A. A.; Pikus, F. G.; Shklovskii, B. I. (1997). "Statistics of the charging spectrum of a two-dimensional Coulomb-glass island". Physical Review B. 55 (15): 9223–9226. arXiv:cond-mat/9612236. Bibcode:1997PhRvB..55.9223K. doi:10.1103/PhysRevB.55.9223.
  42. ^ Koulakov, A. A.; Shklovskii, B. I. (1998). "Charging spectrum of a small Wigner crystal island". Philosophical Magazine B. 77 (5): 1235–1247. arXiv:cond-mat/9705030. doi:10.1080/13642819808205015.
  43. ^ Koulakov, A. A.; Larkin, A. I. (1999). "Vortex-mediated microwave absorption in superclean layered superconductors". Physical Review B. 59 (18): 12021–12032. arXiv:cond-mat/9802002. Bibcode:1999PhRvB..5912021K. doi:10.1103/PhysRevB.59.12021.
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