Articles

  1. Zhou S, Buonomano DV. Unified control of temporal and spatial scales of sensorimotor behavior through neuromodulation of short-term synaptic plasticity Science Advances 10 , 2024 PDF
  2. Dobler Z, Suresh A, Chari T, Mula S, Tran A, Buonomano DV, Portera-Cailliau C. Adapting and facilitating responses in mouse somatosensory cortex are dynamic and shaped by experience Current Biology 34 3506-3521, 2024 PDF
  3. Buonomano DV, Buzsáki G, Davachi L, Nobre AC. Time for Memories The Journal of Neuroscience 43 7565-7574, 2023 PDF
  4. Kourdougli N, Suresh A, Liu B, Juarez P, Lin A, Chung DT, Sams AG, Gandal MJ, Martínez-Cerdeño V, Buonomano DV, Hall BJ, Mombereau C, Portera-Cailliau C. Improvement of sensory deficits in fragile X mice by increasing cortical interneuron activity after the critical period Neuron 111 2863-2880, 2023 PDF
  5. Buonomano DV, Rovelli C. Bridging the Neuroscience and Physics of Time Time and Science (World Scientific) , 2023 PDF
  6. Zhou S, Seay M, Taxidis J, Golshani P, Buonomano DV. Multiplexing working memory and time in the trajectories of neural networks Nature Human Behaviour , 2023 PDF
  7. Liu B, Seay M, Buonomano DV. Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation J. Neurosci 43 82-92, 2023 PDF
  8. Soldado-Magraner S, Seay M, Laje R, Buonomano DV. Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules PNAS 119 , 2022 PDF
  9. Chinoy R, Tanwar A, Buonomano DV. A Recurrent Neural Network Model Accounts for Both Timing and Working Memory Components of an Interval Discrimination Task Brill , 2022 PDF
  10. Zhou S, Buonomano DV. Neural population clocks: Encoding time in dynamic patterns of neural activity. Behavioral Neuroscience 136 , 2022 PDF
  11. Zhou S, Masmanidis H, Buonomano DV. Encoding Time in Neural Dynamic Regimes with Distinct Computational Tradeoffs PLoS Computational Biology 18 , 2022 PDF
  12. Romero-Sosa JL, Motanis H, Buonomano DV. Differential Excitability of PV and SST Neurons Results in Distinct Functional Roles in Inhibition Stabilization of Up States J. Neurosci. 41 7182-7196, 2021 PDF
  13. Romero-Sosa JL, Buonomano DV, Izquierdo A. The Orbitofrontal Cortex in Temporal Cognition Behavioral Neuroscience 135 154-164, 2021 PDF
  14. Seay MJ, Natan RG, Geffen MN, Buonomano DV. Differential Short-Term Plasticity of PV and SST Neurons Accounts for Adaptation and Facilitation of Cortical Neurons to Auditory Tones J. Neurosci. 40 9210-9223, 2020 PDF
  15. Zhou S, Masmanidis SC, Buonomano DV. Neural Sequences as an Optimal Dynamical Regime for the Readout of Time Neuron 108 1-8, 2020 PDF
  16. Motanis H, Buonomano DV. Decreased reproducibility and abnormal experience‐dependent plasticity of network dynamics in Fragile X circuits Scientific Reports 10 14535, 2020 PDF
  17. Slayton MA, Romero-Sosa JL, Shore K, Buonomano DV, Viskontas IV. Musical expertise generalizes to superior temporal scaling in a Morse code tapping task PLOS ONE 15: e0221000, 2020 PDF
  18. Hardy NF, Goudar V, Romero-Sosa JL, Buonomano DV. A model of temporal scaling correctly predicts that motor timing improves with speed Nature Communications 9: 4732, 2018 PDF
  19. Motanis H, Seay MJ, Buonomano DV. Short-Term Synaptic Plasticity as a Mechanism for Sensory Timing Trends in Neurosciences 41: 701-711, 2018 PDF
  20. Paton JJ, Buonomano DV. The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions Neuron 98: 687-705, 2018 PDF
  21. Goudar V, Buonomano DV. Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks eLife 7: e31134, 2018 PDF
  22. Hardy N, Buonomano DV. Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model Neural Computation 30: 378-396, 2018 PDF
  23. Bakhurin KI, Goudar V, Shobe JL, Claar LD, Buonomano DV, Masmanidis SC. Differential Encoding of Time by Prefrontal and Striatal Network Dynamics J Neurosci 37: 854-870, 2017 PDF
  24. Goel A, Buonomano DV. Temporal Interval Learning in Cortical Cultures Is Encoded in Intrinsic Network Dynamics Neuron 91: 320-327, 2016 PDF
  25. Hardy NF, Buonomano DV. Neurocomputational models of interval and pattern timing. Current Opinion in Behavioral Sciences 8: 250-257, 2016 PDF
  26. Finnerty GT, Shadlen MN, Jazayeri M, Nobre AC, Buonomano DV. Time in Cortical Circuits. J Neurosci 35: 13912-13916, 2015 PDF
  27. Motanis H, Buonomano DV. Delayed in vitro Development of Up States but Normal Network Plasticity in Fragile X Circuits. Eur J Neurosci. 42: 2312-21, 2015 PDF
  28. Motanis H, Buonomano DV. Neural coding: time contraction and dilation in the striatum. Curr Biol 25: R374-376, 2015 PDF
  29. Shtrahman M, Aharoni DB, Hardy NF, Buonomano DV, Arisaka K, Otis TS. Multifocal fluorescence microscope for fast optical recordings of neuronal action potentials. Biophys J 108: 520-529, 2015 PDF
  30. Goudar V, Buonomano DV. A model of order-selectivity based on dynamic changes in the balance of excitation and inhibition produced by short-term synaptic plasticity. J. Neurophysiol. 113: 509-523, 2015 PDF
  31. Bueti D, Buonomano DV. Temporal Perceptual Learning. Timing & Time Perception 2: 261-289, 2014 PDF
  32. Goudar V, Buonomano DV. Useful dynamic regimes emerge in recurrent networks. Nat Neurosci 17: 487-489., 2014 PDF
  33. Goel A, Buonomano DV. Timing as an intrinsic property of neural networks: evidence from in vivo and in vitro experiments. Philos Trans R Soc Lond B Biol Sci 369: 20120460, 2014 PDF
  34. Laje R, Buonomano DV. Robust timing and motor patterns by taming chaos in recurrent neural networks. Nat. Neurosci. 16: 925-933., 2013 PDF
  35. Goel A, Buonomano DV. Chronic electrical stimulation homeostatically decreases spontaneous activity, but paradoxically increases evoked network activity. J. Neurophys. 109: 1824-1836., 2013 PDF
  36. Lee TP, Buonomano DV Unsupervised formation of vocalization-sensitive neurons: a cortical model based on short-term and homeostatic plasticity. Neural Comput. 24: 2579-2603., 2012 PDF
  37. Chen WX, Buonomano DV Developmental shift of short-term plasticity in cortical organotypic slices. Neurosci. 213: 38-46, 2012 PDF
  38. Laje R, Cheng K, Buonomano, DV. Learning of temporal motor patterns: an analysis of continuous versus reset timing. Frontiers Integrative Neurosci 5: 61, 2011 PDF
  39. Carvalho, T.P. and Buonomano, D.V. A novel learning rule for long-term plasticity of short-term synaptic plasticity enhances temporal procesing. Frontiers Integrative Neurosci 5: 20, 2011 PDF
  40. Buonomano, D.V. and Laje, R. Population clocks: motor timing with neural dynamics. Trends in Cognitive Science. 14: 520-527, 2010 PDF
  41. Johnson HA, Goel A, Buonomano DV. Neural dynamics of in vitro cortical networks reflects experienced temporal patterns. Nature Neurosci 13: 917-919, 2010 PDF
  42. Liu, J.K., Buonomano, D.V. Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner. J. Neurosci. 29: 13172-13181, 2009 PDF
  43. Buonomano, D.V. Harnessing chaos in recurrent neural networks. Neuron 63: 423-425, 2009 PDF
  44. Buonomano DV, Bramen J, Khodadadifar M. Influence of the interstimulus interval on temporal processing and learning: testing the state-dependent network model. Phil. Trans. R. Soc. B 364: 1865-1873, 2009 PDF
  45. Carvalho, T.P. and Buonomano, D.V. Differential effects of excitatory and inhibitory plasticity on synaptically driven neuronal input-output function. Neuron 61: 774-785, 2009 PDF
  46. Buonomano D.V. and Maass W. State-dependent Computations: Spatiotemporal Processing in Cortical Networks. Nat. Rev. Neurosci. 10: 113-125, 2009 PDF
  47. Johnson, H.A. and Buonomano, D.V. A method for chronic stimulation of cortical organotypic cultures using implanted electrodes. J. Neurosci. Methods 176: 136-143, 2009 PDF
  48. van Wassenhove V, Buonomano DV, Shimojo S, Shams L. Distortions of Subjective Time Perception Within and Across Senses. PLoS ONE 3: e1437, 2008 PDF
  49. Buonomano, D.V. The biology of time across different scales. Nat. Chem. Bio. 3: 594-597, 2007 PDF
  50. Johnson, H.A. and Buonomano, D.V. Development and plasticity of spontaneous activity and UP states in cortical organotypic slices. J. Neuroscience 27: 5915-5925, 2007 PDF
  51. Karmarkar, U.R. and Buonomano, D.V. Timing in the absence of clocks: Encoding time in neural network states. Neuron 53: 427-438, 2007 PDF
  52. Karmarkar, U.R. and Buonomano, D.V. Bi-directional homeostatic inhibitory plasticity. European. J. Neuroscience 23: 1575-1584, 2006 PDF
  53. Eagleman DM, Tse PU, Janssen P, Nobre AC, Buonomano D, Holcombe AO. Time and the brain: how subjective time relates to neural time. J. Neuroscience 25: 10369–10371,, 2005 PDF
  54. Buonomano, D.V. A Learning Rule for the Emergence of Stable Dynamics and Timing in Recurrent Networks. J. Neurophysiol. 94: 2275-2283, 2005 PDF
  55. Dong, H. and Buonomano, D.V. A technique for repeated recordings from cortical organotypic slices. J. Neurosci. Methods 146: 69-75, 2005 PDF
  56. Marder, C.P. and Buonomano D.V. Timing and Balance of Inhibition Enhance the Effect of LTP on Cell Firing. J. Neurosci. 24: 8873-8884,, 2004 PDF
  57. Mauk M.D. and Buonomano D.V. The Neural Basis of Temporal Processing. Annual Rev. Neuroscience. 27: 304-340, 2004 PDF
  58. Buonomano, D.V. Timing of Neural Responses in Cortical Organotypic Slices. Proc. Natl. Acad. Sci. USA. 100: 4897-4902, 2003 PDF
  59. Karmarkar, U. and Buonomano D.V. Temporal specificity of perceptual learning in an auditory discrimination task. Learning & Memory 10: 141-147, 2003 PDF
  60. Marder, C.P. and Buonomano D.V. Differential effects of short- and long-term potentiation on cell firing in the CA1 region of the hippocampus. J. Neurosci. 23: 112-121, 2003 PDF
  61. Karmarkar, U.R. Najarian, M.T. and Buonomano, D.V. Mechanisms and significance of spike-timing dependent plasticity. Biol. Cybernetics 87: 373-382, 2002 PDF
  62. Buonomano, D.V. and Karmarkar, U.R. How do we tell time? Neuroscientist 8: 42- 51, 2002 PDF
  63. Karmarkar, U.R. and Buonomano, D.V. A Model of Spike-Timing Dependent Plasticity: One or Two Coincidence Detectors? J. Neurophysiol. 88: 507-513, 2002 PDF
  64. Buonomano, D.V. Decoding temporal information: a model based on short-term synaptic plasticity. J. Neurosci. 20: 1129-1141,, 2000 PDF
  65. Buonomano, D.V. Distinct functional types of associative long-term potentiation in neocortical and hippocampal pyramidal neurons. J. Neurosci. 19: 6748-6754, 1999 PDF
  66. Buonomano, D.V. and Merzenich, M.M. A neural network model of temporal code generation of position invariant pattern recognition. Neural Computation 11: 103-116, 1999 PDF
  67. Buonomano, D.V. and Merzenich M.M. Cortical plasticity: from synapses to maps. Annual Rev. Neuroscience 21: 149-186, 1998 PDF
  68. Buonomano, D.V. and Merzenich, M.M. Net interaction between different forms of short-term synaptic plasticity and slow-IPSPs in the hippocampus and auditory cortex. J. Neurophysiol. 80: 1765-1774, 1998 PDF
  69. Buonomano, D.V., Hickmott, P.W., and Merzenich, M.M. Temporal to spatial transformations and context-sensitive plasticity in hippocampal slices. Proc. Natl. Acad. Sci. USA. 94: 10403-10408, 1997 PDF
  70. Wright, B.A., Buonomano, D.V., Mahncke, H.W., Merzenich, M.M. Learning and generalization of auditory temporal-interval discrimination in humans. J. Neurosci. 17: 3956-3963, 1997 PDF
  71. Buonomano, D.V. and Merzenich, M.M. Associative synaptic plasticity in hippocampal CA1 neurons is not sensitive to unpaired presynaptic activity. J. Neurophysiol. 76: 631-636,, 1996 PDF
  72. Buonomano, D.V. and Merzenich, M.M. Temporal information transformed into a spatial code by a neural network with realistic properties. Science 267: 1028-1030, 1995 PDF
  73. Buonomano, D.V. and Mauk, M.D. Neural network model of the cerebellum: temporal discrimination and the timing of motor responses. Neural Computation 6: 38-55, 1994 PDF
  74. Buonomano, D.V., Cleary, L.J. and Byrne, J.H. Inhibitory neuron produces heterosynaptic inhibition of the sensory-to-motor neuron in Aplysia. Brain Res. 577: 147 -150, 1992 PDF
  75. Raymond, J.L., Baxter, D.A., Buonomano, D.V. and Byrne J.H. A learning rule based on empirically-derived activity-dependent neuromodulation supports operant conditioning in a small network. Neural Networks 5: 789-803, 1992 PDF
  76. Buonomano, D.V, D.A. Baxter and Byrne, J.H. Simulations of small networks based on empirically derived adaptive elements predict some higher-order features of classical conditioning. Neural Networks 3: 507-527, 1990 PDF
  77. Buonomano, D.V. and Byrne, J.H. Long-term synaptic changes produced by a cellular analog of classical conditioning in Aplysia. Science 249: 421-422, 1990 PDF

Books

  1. Buonomano, D.V. Brain Bugs: How the brain's flaws shape our lives. Norton 2011 WEBSITE
  2. Buonomano, D.V. Your Brain is a Time Machine: The Neuroscience and Physics of Time. Norton 2018 WEBSITE

Chapters

  1. Soldado-Magraner, S. and Buonomano, D.V. Neural Sequences and the Encoding of Time.. In Neurobiology of Interval Timing , 2024
  2. Buonomano, D.V. and Laje, R. Population Clocks: Motor Timing with Neural Dynamics.. In Space, Time and Number in the Brain , 2011
  3. Buonomano, D.V. and Carvalho T.P. Spike Timing Dependent Plasticity. In New Encyclopedia of Neuroscience. , 2008
  4. Buonomano, D.V. and Johnson H.A. Cortical Plasticity: Mechanisms and Models. In New Encyclopedia of Neuroscience. , 2008
  5. Raymond, J.L., Byrne, J.H. and Buonomano, D.V. Conditioning, Cellular and Network Schemes for Higher Order Features of Classical Conditioning.. In Encyclopedia of Learning and Memory. , 2003
  6. Buonomano, D.V. and Merzenich. M.M. Temporal Information processing: A Computational role for Paired-pulse Facilitation and Slow Inhibition.. In Neural-Network Models of Complex Behavior: Biobehavioral Foundations. , 1997
  7. Baxter, D.A., Buonomano, D.V., Raymond, J.L., Cook, D.G., Kuenzi, F.M, Carew, T.J. and Byrne, J.H. Empirically derived adaptive elements and networks simulate associative learning.. In Quantitative Analyses of Behavior: Neural Networks of Conditioning and Action , 1991
  8. Byrne, J.H., Baxter, D.A., Buonomano, D.V., Cleary, L.J., Eskin, A., Goldsmith, J.R., McClendon, E., Nazif, F.A., Noel, F. and Scholz, K.P. Neural and molecular bases of nonassociative and associative learning in Aplysia,. In Ann. N.Y. Acad. Sci. , 1991
  9. Byrne, J.H., Baxter, D.A., Buonomano, D.V. and Raymond, J.L. Neuronal and network determinants of simple and higher-order features of associative learning: Experimental and modeling approaches.. In Cold Spring Harbor Symposium on Quantitative Biology , 1991