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Showing 1–12 of 12 results
Advanced filters: Author: Dean Buonomano Clear advanced filters

  • Most models of sensory processing consider the spatial and temporal aspects of sensory stimuli separately. Here, Buonomano and Maass describe a framework in which spatiotemporal computations emerge from the interaction between incoming stimuli and the internal dynamic state of neural networks.

    • Dean V. Buonomano
    • Wolfgang Maass
    Reviews
    Nature Reviews Neuroscience
    Volume: 10, P: 113-125

  • Achieving the same robustness of biological networks in neuromorphic systems remains a challenge due to the variability in their analogue components. Here, the authors apply a biologically-plausible cross-homeostatic rule to balance neuromorphic implementations of spiking recurrent networks.

    • Maryada
    • Saray Soldado-Magraner
    • Giacomo Indiveri
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-13

  • Because the ability to tell time and make predictions anchor much of cognition, it has been proposed that they are computational primitives. Here, authors directly demonstrated that this is the case by showing that neocortical circuits ex vivo can learn to tell time and make simple predictions.

    • Benjamin Liu
    • Dean V. Buonomano
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-13

  • The internal dynamics of recurrent cortical circuits is crucial to brain function. We now learn that simply increasing the strengths of recurrent connections shifts neural dynamics to a potentially powerful computational regime.

    • Vishwa Goudar
    • Dean V Buonomano
    News & Views
    Nature Neuroscience
    Volume: 17, P: 487-489

  • Animals time events on scales that span from microseconds to days. In contrast to the technologies devised by humans to keep track of time, biology has developed vastly different mechanisms for timing across these different scales.

    • Dean V Buonomano
    Comments & Opinion
    Nature Chemical Biology
    Volume: 3, P: 594-597

  • Humans can perform complex motor movements at varying speeds. Here, the authors show that a recurrent neural network can be trained to exhibit temporal scaling obeying Weber’s law as well as validate a prediction of the model of improved precision of movements at faster speeds.

    • Nicholas F. Hardy
    • Vishwa Goudar
    • Dean V. Buonomano
    ResearchOpen Access
    Nature Communications
    Volume: 9, P: 1-14

  • Here the authors describe a recurrent neural network model that tells time on the order of seconds and generates complex spatiotemporal motor patterns in the presence of high levels of noise. Robustness is achieved through the tuning of the recurrent connections, which produces stable patterns in the face of perturbations.

    • Rodrigo Laje
    • Dean V Buonomano
    Research
    Nature Neuroscience
    Volume: 16, P: 925-933

  • Theories of consciousness have a long and controversial history. One well-known proposal — integrated information theory — has recently been labeled as ‘pseudoscience’, which has caused a heated open debate. Here we discuss the case and argue that the theory is indeed unscientific because its core claims are untestable even in principle.

    • Derek H. Arnold
    • Mark G. Baxter
    • Joel S. Snyder
    Comments & Opinion
    Nature Neuroscience
    Volume: 28, P: 689-693