728 x 90

Neural basis of compositional control – Nature

Neural basis of compositional control – Nature

Gordon, J. et al. The road towards understanding embodied decisions. Neurosci. Biobehav. Rev. 131, 722–736 (2021).Thank you for reading this post, don’t forget to subscribe! Article  PubMed  PubMed Central  Google Scholar  Maselli, A. et al. Beyond simple laboratory studies: developing sophisticated models to study rich behavior. Phys. Life Rev. 46, 220–244 (2023). Article  ADS  PubMed 

  • Gordon, J. et al. The road towards understanding embodied decisions. Neurosci. Biobehav. Rev. 131, 722–736 (2021).

    Thank you for reading this post, don't forget to subscribe!

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Maselli, A. et al. Beyond simple laboratory studies: developing sophisticated models to study rich behavior. Phys. Life Rev. 46, 220–244 (2023).

    Article 
    ADS 
    PubMed 

    Google Scholar 

  • Yoo, S. B. M., Hayden, B. Y. & Pearson, J. M. Continuous decisions. Philos. Trans. R. Soc. B 376, 20190664 (2021).

    Article 

    Google Scholar 

  • Merel, J., Botvinick, M. & Wayne, G. Hierarchical motor control in mammals and machines. Nat. Commun. 10, 5489 (2019).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cisek, P. Making decisions through a distributed consensus. Curr. Opin. Neurobiol. 22, 927–936 (2012).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Gallivan, J. P., Chapman, C. S., Wolpert, D. M. & Flanagan, J. R. Decision-making in sensorimotor control. Nat. Rev. Neurosci. 19, 519–534 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Yoo, S. B. M., Tu, J. C., Piantadosi, S. T. & Hayden, B. Y. The neural basis of predictive pursuit. Nat. Neurosci. 23, 252–259 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Fabian, S. T., Sumner, M. E., Wardill, T. J., Rossoni, S. & Gonzalez-Bellido, P. T. Interception by two predatory fly species is explained by a proportional navigation feedback controller. J. R. Soc. Interface. 15, 20180466 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sridhar, V. H. et al. The geometry of decision-making in individuals and collectives. Proc. Natl Acad. Sci. USA 118, e2102157118 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Yang, Q. et al. Monkey plays Pac-Man with compositional strategies and hierarchical decision-making. eLife 11, e74500 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Bertsekas, D. P. in Encyclopedia of Optimization (eds Pardalos, P. M. & Prokopyev, O. A.) 1–6 (Springer, 2025).

  • Sutton, R. S. & Barto, A. G. Reinforcement Learning: An Introduction (MIT Press, 1998).

  • Theodorou, E. A., Buchli, J. & Schaal, S. A generalized path integral control approach to reinforcement learning. J. Mach. Learn. Res. 11, 3137–3181 (2010).

    MathSciNet 

    Google Scholar 

  • Dvijotham, K. & Todorov, E. in Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (eds Lewis. F. L. & Liu, D.) 119–141 (Wiley, 2012).

  • Wolpert, D. M. & Kawato, M. Multiple paired forward and inverse models for motor control. Neural Netw. 11, 1317–1329 (1998).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Lake, B. & Baroni, M. Generalization without systematicity: on the compositional skills of sequence-to-sequence recurrent networks. In Proc. 35th International Conference on Machine Learning (eds. Dy, J. & Krause, A.) 2873–2882 (PMLR, 2018).

  • Todorov, E. Compositionality of optimal control laws. In Advances in Neural Information Processing Systems 22 (eds Bengio, Y. et al.) (NeurIPS, 2009).

  • Kurth-Nelson, Z. et al. Replay and compositional computation. Neuron 111, 454–469 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Whittington, J. C. R., McCaffary, D., Bakermans, J. J. W. & Behrens, T. E. J. How to build a cognitive map. Nat. Neurosci. 25, 1257–1272 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Eichenbaum, H. & Cohen, N. J. Can we reconcile the declarative memory and spatial navigation views on hippocampal function? Neuron 83, 764–770 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Behrens, T. E. J. et al. What is a cognitive map? Organizing knowledge for flexible behavior. Neuron 100, 490–509 (2018).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Kay, K. et al. Constant sub-second cycling between representations of possible futures in the hippocampus. Cell 180, 552–567.e25 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Park, S. A., Miller, D. S., Nili, H., Ranganath, C. & Boorman, E. D. Map making: constructing, combining, and inferring on abstract cognitive maps. Neuron 107, 1226–1238.e8 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sanders, H., Wilson, M. A. & Gershman, S. J. Hippocampal remapping as hidden state inference. eLife 9, e51140 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Rushworth, M. F. S., Noonan, M. P., Boorman, E. D., Walton, M. E. & Behrens, T. E. Frontal cortex and reward-guided learning and decision-making. Neuron 70, 1054–1069 (2011).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Wikenheiser, A. M. & Schoenbaum, G. Over the river, through the woods: cognitive maps in the hippocampus and orbitofrontal cortex. Nat. Rev. Neurosci. 17, 513–523 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Yeung, N. & Summerfield, C. Metacognition in human decision-making: confidence and error monitoring. Philos. Trans. R. Soc. B 367, 1310–1321 (2012).

    Article 

    Google Scholar 

  • Eppinger, B., Goschke, T. & Musslick, S. Meta-control: From psychology to computational neuroscience. Cogn. Affect. Behav. Neurosci. 21, 447–452 (2021).

    Article 
    PubMed 

    Google Scholar 

  • Musslick, S., Cohen, J. D. & Goschke, T. in Encyclopedia of the Human Brain (ed. Grafman, J. H.) 269–285 (Elsevier, 2025).

  • Alexander, W. H. & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nat. Neurosci. 14, 1338–1344 (2011).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Kennerley, S. W., Walton, M. E., Behrens, T. E. J., Buckley, M. J. & Rushworth, M. F. S. Optimal decision making and the anterior cingulate cortex. Nat. Neurosci. 9, 940–947 (2006).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Kolling, N., Behrens, T., Wittmann, M. & Rushworth, M. Multiple signals in anterior cingulate cortex. Curr. Opin. Neurobiol. 37, 36–43 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Shenhav, A., Botvinick, M. M. & Cohen, J. D. The expected value of control: an integrative theory of anterior cingulate cortex function. Neuron 79, 217–240 (2013).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Akam, T. et al. The anterior cingulate cortex predicts future states to mediate model-based action selection. Neuron 109, 149–163.e7 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Heilbronner, S. R. & Hayden, B. Y. Dorsal anterior cingulate cortex: a bottom-up view. Annu. Rev. Neurosci. 39, 149–170 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sarafyazd, M. & Jazayeri, M. Hierarchical reasoning by neural circuits in the frontal cortex. Science 364, eaav8911 (2019).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Padoa-Schioppa, C. Neurobiology of economic choice: a good-based model. Annu. Rev. Neurosci. 34, 333–359 (2011).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Hunt, L. T. et al. Triple dissociation of attention and decision computations across prefrontal cortex. Nat. Neurosci. 21, 1471–1481 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wilson, R. C., Takahashi, Y. K., Schoenbaum, G. & Niv, Y. Orbitofrontal cortex as a cognitive map of task space. Neuron 81, 267–279 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Elston, T. W. & Wallis, J. D. Context-dependent decision-making in the primate hippocampal–prefrontal circuit. Nat. Neurosci. 28, 374–382 (2025).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Yoo, S. B. M., Tu, J. C. & Hayden, B. Y. Multicentric tracking of multiple agents by anterior cingulate cortex during pursuit and evasion. Nat. Commun. 12, 1985 (2021).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wilson, R. C. & Collins, A. G. E. Ten simple rules for the computational modeling of behavioral data. eLife 8, e49547 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Khona, M. & Fiete, I. R. Attractor and integrator networks in the brain. Nat. Rev. Neurosci. 23, 744–766 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Hayden, B. Y., Pearson, J. M. & Platt, M. L. Neuronal basis of sequential foraging decisions in a patchy environment. Nat. Neurosci. 14, 933–939 (2011).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Anderson, D. J. & Perona, P. Toward a science of computational ethology. Neuron 84, 18–31 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Brown, A. E. X. & de Bivort, B. Ethology as a physical science. Nat. Phys. 14, 653–657 (2018).

    Article 
    CAS 

    Google Scholar 

  • Milner, D. & Goodale, M. The Visual Brain in Action (Oxford Univ. Press, 2006).

  • Gershman, S. J. & Niv, Y. Learning latent structure: carving nature at its joints. Curr. Opin. Neurobiol. 20, 251–256 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Zutshi, I. et al. Hippocampal neuronal activity is aligned with action plans. Nature 639, 153–161 (2025).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • Shadmehr, R. & Krakauer, J. W. A computational neuroanatomy for motor control. Exp. Brain Res. 185, 359–381 (2008).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Bakkour, A. et al. The hippocampus supports deliberation during value-based decisions. eLife 8, e46080 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Stachenfeld, K. L., Botvinick, M. M. & Gershman, S. J. The hippocampus as a predictive map. Nat. Neurosci. 20, 1643–1653 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Vikbladh, O. M. et al. Hippocampal contributions to model-based planning and spatial memory. Neuron 102, 683–693.e4 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Edelson, M. G. & Hare, T. A. Goal-dependent hippocampal representations facilitate self-control. J. Neurosci. 43, 7822–7830 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cohen, J. D., Botvinick, M. & Carter, C. S. Anterior cingulate and prefrontal cortex: who’s in control?. Nat. Neurosci. 3, 421–423 (2000).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Verguts, T. Binding by random bursts: a computational model of cognitive control. J. Cogn. Neurosci. 29, 1103–1118 (2017).

    Article 
    PubMed 

    Google Scholar 

  • Silvetti, M., Vassena, E., Abrahamse, E. & Verguts, T. Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner. PLoS Comput. Biol. 14, e1006370 (2018).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Friedman, A. et al. A corticostriatal path targeting striosomes controls decision-making under conflict. Cell 161, 1320–1333 (2015).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Kane, G. A. et al. Rat anterior cingulate cortex continuously signals decision variables in a patch foraging task. J. Neurosci. 42, 5730–5744 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Botvinick, M. M., Niv, Y. & Barto, A. G. Hierarchically organized behavior and its neural foundations: A reinforcement learning perspective. Cognition 113, 262–280 (2009).

    Article 
    PubMed 

    Google Scholar 

  • Franch, M. et al. A population code for semantics in human hippocampus. Preprint at bioRxiv https://doi.org/10.1101/2025.02.21.639601 (2025).

  • Chaure, F. J., Rey, H. G. & Quian Quiroga, R. A novel and fully automatic spike-sorting implementation with variable number of features. J. Neurophysiol. 120, 1859–1871 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Groppe, D. M. et al. iELVis: An open source MATLAB toolbox for localizing and visualizing human intracranial electrode data. J. Neurosci. Methods 281, 40–48 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Jenkinson, M. & Smith, S. A global optimisation method for robust affine registration of brain images. Med. Image Anal. 5, 143–156 (2001).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Jenkinson, M., Bannister, P., Brady, M. & Smith, S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17, 825–841 (2002).

    Article 
    PubMed 

    Google Scholar 

  • Joshi, A. et al. Unified framework for development, deployment and robust testing of neuroimaging algorithms. Neuroinformatics 9, 69–84 (2011).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Dale, A. M., Fischl, B. & Sereno, M. I. Cortical surface-based analysis. Neuroimage 9, 179–194 (1999).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Yang, A. I. et al. Localization of dense intracranial electrode arrays using magnetic resonance imaging. Neuroimage 63, 157–165 (2012).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Magnotti, J. F., Wang, Z. & Beauchamp, M. S. RAVE: Comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data. Neuroimage 223, 117341 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wang, Z., Magnotti, J. F., Zhang, X. & Beauchamp, M. S. YAEL: your advanced electrode localizer. eNeuro 10, ENEURO.0328-23.2023 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Chericoni, A. et al. Neural geometry in the human hippocampus enables generalization across spatial position and gaze. Preprint at arXiv https://doi.org/10.48550/arXiv.2603.04747 (2026).

  • Gómez, V., Kappen, H. J., Peters, J. & Neumann, G. in Machine Learning and Knowledge Discovery in Databases (eds Calders, T. et al.) 482–497 (2014).

  • Peng, X. Bin, Chang, M., Zhang, G., Abbeel, P. & Levine, S. MCP: learning composable hierarchical control with multiplicative compositional policies. In Advances in Neural Information Processing Systems 32 (eds Wallach, H. et al.) (NeurIPS, 2019).

  • Matsuo, Y. et al. Deep learning, reinforcement learning, and world models. Neural Netw. 152, 267–275 (2022).

    Article 
    ADS 
    PubMed 

    Google Scholar 

  • Murphy, K. P. Probabilistic Machine Learning: An Introduction (The MIT Press, 2022).

  • Wood, S. N. Generalized additive models. Annu. Rev. Stat. Appl. 12, 497–526 (2025).

    Article 
    MathSciNet 

    Google Scholar 

  • Seabold, S. & Perktold, J. Statsmodels: econometric and statistical modeling with Python. In Proc. 9th Python in Science Conference (SciPy 2010) https://doi.org/10.25080/Majora-92bf1922-011 (SciPy, 2010).

  • Balzani, E., Lakshminarasimhan, K., Angelaki, D. & Savin, C. Efficient estimation of neural tuning during naturalistic behavior. In Advances in Neural Information Processing Systems 33 (eds. Larochelle, H. et al.) (NeurIPS, 2020).

  • Wood, S. N. Generalized Additive Models: An Introduction with R (CRC Press/Taylor & Francis Group, 2017).

  • Gelman, A., Hwang, J. & Vehtari, A. Understanding predictive information criteria for Bayesian models. Stat. Comput. 24, 997–1016 (2014).

    Article 
    MathSciNet 

    Google Scholar 

  • Kriegeskorte, N. & Wei, X.-X. Neural tuning and representational geometry. Nat. Rev. Neurosci. 22, 703–718 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Kobak, D. et al. Demixed principal component analysis of neural population data. eLife 5, e10989 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Chericoni, A. Dataset for: Neural basis of compositional control. Figshare https://doi.org/10.6084/m9.figshare.32572764.v3 (2026).

  • Check back often for more exciting news!

    Posts Carousel

    Latest Posts

    Top Authors

    Most Commented

    Featured Videos

    Thank you for reading this post, don't forget to subscribe!