Dean Buonomano

Dean Buonomano

Professor, Neurobiology, University of California Los Angeles

310-794-5012

UC Profile
http://www.buonomanolab.com/
Buonomano Lab

The ability to tell time is among the most important functions the brain performs. Tasks such as, understanding speech, performing the complex movements necessary to catch a prey, and predicting when external events will occur, all rely on the brain’s ability to tell time. We have hypothesized that timing and temporal processing is such an important computation, that most neural circuits are capable of telling time on the scale of milliseconds and seconds. Our research suggests that how the brain tells time has little to do with how man-made clocks tell time (by counting the ticks of an oscillator), our hypothesis is that the brain tells time through the intrinsic dynamics of neurons and neural circuits. Our research focuses on how neural circuits learn and perform complex computations--such as telling time and temporal processing. Towards this goal our lab uses electrophysiological, optogenetic, computational, and psychophysical techniques.

Interests

Time, Neurocomputation, neural dynamics, synaptic plasticity, Learning and Memory, microcircuits, Temporal processing

Publications

  1. Buonomano DV, Buzsáki G, Davachi L, Nobre AC. Time for Memories.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2023.
  2. Kourdougli N, Suresh A, Liu B, Juarez P, Lin A, Chung DT, Graven Sams A, 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, 2023.
  3. 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.
  4. Liu B, Seay MJ, Buonomano DV. Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2022.
  5. Soldado-Magraner S, Seay MJ, Laje R, Buonomano DV. Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules.. Proceedings of the National Academy of Sciences of the United States of America, 2022.
  6. Zhou S, Buonomano DV. Neural population clocks: Encoding time in dynamic patterns of neural activity.. Behavioral neuroscience, 2022.
  7. Zhou S, Masmanidis SC, Buonomano DV. Encoding time in neural dynamic regimes with distinct computational tradeoffs.. PLoS computational biology, 2022.
  8. 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.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2021.
  9. Sosa JLR, Buonomano D, Izquierdo A. The orbitofrontal cortex in temporal cognition.. Behavioral neuroscience, 2021.
  10. 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.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2020.
  11. Zhou S, Masmanidis SC, Buonomano DV. Neural Sequences as an Optimal Dynamical Regime for the Readout of Time.. Neuron, 2020.
  12. Motanis H, Buonomano D. Decreased reproducibility and abnormal experience-dependent plasticity of network dynamics in Fragile X circuits.. Scientific reports, 2020.
  13. 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, 2020.
  14. Hardy NF, Goudar V, Romero-Sosa JL, Buonomano DV. A model of temporal scaling correctly predicts that motor timing improves with speed.. Nature communications, 2018.
  15. Motanis H, Seay MJ, Buonomano DV. Short-Term Synaptic Plasticity as a Mechanism for Sensory Timing.. Trends in neurosciences, 2018.
  16. Paton JJ, Buonomano DV. The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions.. Neuron, 2018.
  17. Goudar V, Buonomano DV. Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.. eLife, 2018.
  18. Hardy NF, Buonomano DV. Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.. Neural computation, 2017.
  19. Bakhurin KI, Goudar V, Shobe JL, Claar LD, Buonomano DV, Masmanidis SC. Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2017.
  20. Goel A, Buonomano DV. Temporal Interval Learning in Cortical Cultures Is Encoded in Intrinsic Network Dynamics.. Neuron, 2016.
  21. Hardy NF, Buonomano DV. Neurocomputational Models of Interval and Pattern Timing.. Current opinion in behavioral sciences, 2016.
  22. Finnerty GT, Shadlen MN, Jazayeri M, Nobre AC, Buonomano DV. Time in Cortical Circuits.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2015.
  23. Motanis H, Buonomano D. Delayed in vitro development of Up states but normal network plasticity in Fragile X circuits.. The European journal of neuroscience, 2015.
  24. Motanis H, Buonomano DV. Neural coding: time contraction and dilation in the striatum.. Current biology : CB, 2015.
  25. Shtrahman M, Aharoni DB, Hardy NF, Buonomano DV, Arisaka K, Otis TS. Multifocal fluorescence microscope for fast optical recordings of neuronal action potentials.. Biophysical journal, 2015.
  26. 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.. Journal of neurophysiology, 2014.
  27. Goudar V, Buonomano DV. Useful dynamic regimes emerge in recurrent networks.. Nature neuroscience, 2014.
  28. Goel A, Buonomano DV. Timing as an intrinsic property of neural networks: evidence from in vivo and in vitro experiments.. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2014.
  29. Buonomano DV. Neural dynamics based timing in the subsecond to seconds range.. Advances in experimental medicine and biology, 2014.
  30. Buonomano D. Neuroscience: Brain projects need stronger foundation.. Nature, 2013.
  31. Laje R, Buonomano DV. Robust timing and motor patterns by taming chaos in recurrent neural networks.. Nature neuroscience, 2013.
  32. Goel A, Buonomano DV. Chronic electrical stimulation homeostatically decreases spontaneous activity, but paradoxically increases evoked network activity.. Journal of neurophysiology, 2013.
  33. Lee TP, Buonomano DV. Unsupervised formation of vocalization-sensitive neurons: a cortical model based on short-term and homeostatic plasticity.. Neural computation, 2012.
  34. Chen WX, Buonomano DV. Developmental shift of short-term synaptic plasticity in cortical organotypic slices.. Neuroscience, 2012.
  35. Laje R, Cheng K, Buonomano DV. Learning of temporal motor patterns: an analysis of continuous versus reset timing.. Frontiers in integrative neuroscience, 2011.
  36. Carvalho TP, Buonomano DV. A novel learning rule for long-term plasticity of short-term synaptic plasticity enhances temporal processing.. Frontiers in integrative neuroscience, 2011.
  37. Buonomano DV, Laje R. Population clocks: motor timing with neural dynamics.. Trends in cognitive sciences, 2010.
  38. Johnson HA, Goel A, Buonomano DV. Neural dynamics of in vitro cortical networks reflects experienced temporal patterns.. Nature neuroscience, 2010.
  39. Liu JK, Buonomano DV. Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2009.
  40. Buonomano DV. Harnessing chaos in recurrent neural networks.. Neuron, 2009.
  41. Buonomano DV, Bramen J, Khodadadifar M. Influence of the interstimulus interval on temporal processing and learning: testing the state-dependent network model.. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2009.
  42. Carvalho TP, Buonomano DV. Differential effects of excitatory and inhibitory plasticity on synaptically driven neuronal input-output functions.. Neuron, 2009.
  43. Buonomano DV, Maass W. State-dependent computations: spatiotemporal processing in cortical networks.. Nature reviews. Neuroscience, 2009.
  44. Johnson HA, Buonomano DV. A method for chronic stimulation of cortical organotypic cultures using implanted electrodes.. Journal of neuroscience methods, 2008.
  45. van Wassenhove V, Buonomano DV, Shimojo S, Shams L. Distortions of subjective time perception within and across senses.. PloS one, 2008.
  46. Buonomano DV. The biology of time across different scales.. Nature chemical biology, 2007.
  47. Johnson HA, Buonomano DV. Development and plasticity of spontaneous activity and Up states in cortical organotypic slices.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2007.
  48. Karmarkar UR, Buonomano DV. Timing in the absence of clocks: encoding time in neural network states.. Neuron, 2007.
  49. Karmarkar UR, Buonomano DV. Different forms of homeostatic plasticity are engaged with distinct temporal profiles.. The European journal of neuroscience, 2006.
  50. Eagleman DM, Tse PU, Buonomano D, Janssen P, Nobre AC, Holcombe AO. Time and the brain: how subjective time relates to neural time.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2005.
  51. Buonomano DV. A learning rule for the emergence of stable dynamics and timing in recurrent networks.. Journal of neurophysiology, 2005.
  52. Dong HW, Buonomano DV. A technique for repeated recordings in cortical organotypic slices.. Journal of neuroscience methods, 2005.
  53. Marder CP, Buonomano DV. Timing and balance of inhibition enhance the effect of long-term potentiation on cell firing.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2004.
  54. Mauk MD, Buonomano DV. The neural basis of temporal processing.. Annual review of neuroscience, 2004.
  55. Buonomano DV. Timing of neural responses in cortical organotypic slices.. Proceedings of the National Academy of Sciences of the United States of America, 2003.
  56. Karmarkar UR, Buonomano DV. Temporal specificity of perceptual learning in an auditory discrimination task.. Learning & memory (Cold Spring Harbor, N.Y.), 2003.
  57. Marder CP, Buonomano DV. Differential effects of short- and long-term potentiation on cell firing in the CA1 region of the hippocampus.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2003.
  58. Karmarkar UR, Buonomano DV. A model of spike-timing dependent plasticity: one or two coincidence detectors?. Journal of neurophysiology, 2002.
  59. Buonomano DV. Decoding temporal information: A model based on short-term synaptic plasticity.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2000.
  60. Buonomano DV. Distinct functional types of associative long-term potentiation in neocortical and hippocampal pyramidal neurons.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 1999.
  61. Buonomano DV, Merzenich M. A neural network model of temporal code generation and position-invariant pattern recognition.. Neural computation, 1999.
  62. Buonomano DV, Merzenich MM. Net interaction between different forms of short-term synaptic plasticity and slow-IPSPs in the hippocampus and auditory cortex.. Journal of neurophysiology, 1998.
  63. Buonomano DV, Merzenich MM. Cortical plasticity: from synapses to maps.. Annual review of neuroscience, 1998.
  64. Buonomano DV, Hickmott PW, Merzenich MM. Context-sensitive synaptic plasticity and temporal-to-spatial transformations in hippocampal slices.. Proceedings of the National Academy of Sciences of the United States of America, 1997.
  65. Wright BA, Buonomano DV, Mahncke HW, Merzenich MM. Learning and generalization of auditory temporal-interval discrimination in humans.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 1997.
  66. Buonomano DV, Merzenich MM. Associative synaptic plasticity in hippocampal CA1 neurons is not sensitive to unpaired presynaptic activity.. Journal of neurophysiology, 1996.
  67. Buonomano DV, Merzenich MM. Temporal information transformed into a spatial code by a neural network with realistic properties.. Science (New York, N.Y.), 1995.
  68. Buonomano DV, Cleary LJ, Byrne JH. Inhibitory neuron produces heterosynaptic inhibition of the sensory-to-motor neuron synapse in Aplysia.. Brain research, 1992.
  69. Byrne JH, Baxter DA, Buonomano DV, Cleary LJ, Eskin A, Goldsmith JR, McClendon E, Nazif FA, Noel F, Scholz KP. Neural and molecular bases of nonassociative and associative learning in Aplysia.. Annals of the New York Academy of Sciences, 1991.
  70. Buonomano DV, Byrne JH. Long-term synaptic changes produced by a cellular analog of classical conditioning in Aplysia.. Science (New York, N.Y.), 1990.
  71. Byrne JH, Baxter DA, Buonomano DV, Raymond JL. Neuronal and network determinants of simple and higher-order features of associative learning: experimental and modeling approaches.. Cold Spring Harbor symposia on quantitative biology, 1990.