ROBUST TIMING AND MOTOR PATTERNS BY TAMING CHAOS IN RECURRENT NEURAL NETWORKS

The brain's ability to tell time and produce complex spatiotemporal motor patterns is critical for anticipating the next ring of a telephone or playing a musical instrument. One class of models proposes that these abilities emerge from dynamically changing patterns of neural activity generated in recurrent neural networks. However, the relevant dynamic regimes of recurrent networks are highly sensitive to noise; that is, chaotic. We developed a firing rate model that tells time on the order of seconds and generates complex spatiotemporal patterns in the presence of high levels of noise. This is achieved through the tuning of the recurrent connections. The network operates in a dynamic regime that exhibits coexisting chaotic and locally stable trajectories. These stable patterns function as 'dynamic attractors' and provide a feature that is characteristic of biological systems: the ability to 'return' to the pattern being generated in the face of perturbations.

• Publication year

  2012

• Venue

  Nature Neuroscience

• Publication date

  2012-10-07

• Fields of study

  Biology, Medicine, Physics, Computer Science

• Identifiers
  DOI 10.1038/nn.3405arXiv 1210.2104PMID 23708144PMCID 3753043
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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• Neural population dynamics during reaching

  2012cited by this paper
• Dynamic Flux Tubes Form Reservoirs of Stability in Neuronal Circuits

  2012cited by this paper
• Learning about time: plastic changes and interindividual brain differences.

  2012cited by this paper
• Transferring Learning from External to Internal Weights in Echo-State Networks with Sparse Connectivity

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  2012cited by this paper
• Time Scale Hierarchies in the Functional Organization of Complex Behaviors

  2011cited by this paper
• Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making

  2011cited by this paper
• A Model of Interval Timing by Neural Integration

  2011cited by this paper
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  2011cited by this paper
• Measuring time with different neural chronometers during a synchronization-continuation task

  2011cited by this paper
• Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time

  2011influential reference
• Learned timing of motor behavior in the smooth eye movement region of the frontal eye fields.

  2011cited by this paper
• Stimulus onset quenches neural variability: a widespread cortical phenomenon

  2010cited by this paper
• Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex

  2010cited by this paper
• Support for a synaptic chain model of neuronal sequence generation

  2010cited by this paper
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  2010cited by this paper
• Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity.

  2010cited by this paper
• Population clocks: motor timing with neural dynamics.

  2010cited by this paper
• Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex

  2009cited by this paper
• Stimulus onset quenches neural variability: a widespread cortical phenomenon

  2009cited by this paper
• Stimulus-dependent suppression of chaos in recurrent neural networks.

  2009cited by this paper
• Very long transients, irregular firing, and chaotic dynamics in networks of randomly connected inhibitory integrate-and-fire neurons.

  2009cited by this paper
• State-dependent computations: spatiotemporal processing in cortical networks

  2009influential reference
• Generating Coherent Patterns of Activity from Chaotic Neural Networks

  2009influential reference
• Embedding Multiple Trajectories in Simulated Recurrent Neural Networks in a Self-Organizing Manner

  2009cited by this paper
• Memory without feedback in a neural network.

  2009cited by this paper
• Computational significance of transient dynamics in cortical networks

  2008cited by this paper
• Dynamical Constraints on Using Precise Spike Timing to Compute in Recurrent Cortical Networks

  2008influential reference
• Transient Dynamics for Neural Processing

  2008cited by this paper
• Dissociating explicit timing from temporal expectation with fMRI.

  2008cited by this paper
• Large-scale model of mammalian thalamocortical systems

  2008cited by this paper
• Memory traces in dynamical systems

  2008influential reference
• Dedicated and intrinsic models of time perception.

  2008cited by this paper
• Internally Generated Cell Assembly Sequences in the Rat Hippocampus

  2008cited by this paper
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  2007cited by this paper
• Sensory Experience Alters Cortical Connectivity and Synaptic Function Site Specifically

  2007cited by this paper
• Timing in the absence of clocks: encoding time in neural network states.

  2007cited by this paper
• Computational significance of transient dynamics in cortical networks

  2007cited by this paper
• Clustering in complex directed networks.

  2006cited by this paper
• Glucocorticoid-induced leucine zipper (GILZ)/NF-κB interaction: role of GILZ homo-dimerization and C-terminal domain

  2006cited by this paper
• Polychronization: Computation with Spikes

  2006cited by this paper
• Homeostatic synaptic plasticity can explain post-traumatic epileptogenesis in chronically isolated neocortex.

  2005cited by this paper
• A learning rule for the emergence of stable dynamics and timing in recurrent networks.

  2005cited by this paper
• Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits

  2005cited by this paper
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  2005cited by this paper
• What makes us tick? Functional and neural mechanisms of interval timing

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  2005cited by this paper
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  2005cited by this paper
• Dissociation of the lateral and medial cerebellum in movement timing and movement execution

  2004cited by this paper
• Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication

  2004influential reference
• The neural basis of temporal processing.

  2004influential reference
• Intensity versus identity coding in an olfactory system.

  2003cited by this paper
• Basic mechanisms for graded persistent activity: discrete attractors, continuous attractors, and dynamic representations.

  2003cited by this paper
• Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons.

  2003cited by this paper
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  2003cited by this paper
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  2002cited by this paper
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  2002cited by this paper
• An ultra-sparse code underlies the generation of neural sequences in a songbird

  2002cited by this paper
• The''echo state''approach to analysing and training recurrent neural networks

  2001influential reference
• Synaptic reverberation underlying mnemonic persistent activity.

  2001cited by this paper
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  2001cited by this paper
• Dynamical encoding by networks of competing neuron groups: winnerless competition.

  2001cited by this paper
• Computer simulation of cerebellar information processing

  2000cited by this paper
• Neurocomputational models of working memory

  2000cited by this paper
• Timing Mechanisms in the Cerebellum: Testing Predictions of a Large-Scale Computer Simulation

  2000cited by this paper
• Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons.

  2000influential reference
• Decoding Temporal Information: A Model Based on Short-Term Synaptic Plasticity

  2000cited by this paper
• Neural Network Model of the Cerebellum: Temporal Discrimination and the Timing of Motor Responses

  1999cited by this paper
• Conflict monitoring versus selection-for-action in anterior cingulate cortex

  1999cited by this paper
• Collective dynamics of ‘small-world’ networks

  1998cited by this paper
• Stable Chaos in the Asteroid Belt

  1997cited by this paper
• A model of Pavlovian eyelid conditioning based on the synaptic organization of the cerebellum.

  1997cited by this paper
• Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex.

  1997cited by this paper
• Adaptive Filter Theory

  1996cited by this paper
• Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity

  1996influential reference
• Temporal information transformed into a spatial code by a neural network with realistic properties

  1995cited by this paper
• Application of scalar timing theory to individual trials.

  1994cited by this paper
• Learning long-term dependencies with gradient descent is difficult

  1994cited by this paper
• A robust method to estimate the maximal Lyapunov exponent of a time series

  1994cited by this paper
• Bifurcations in the learning of recurrent neural networks

  1992cited by this paper
• An example of stable chaos in the Solar System

  1992cited by this paper
• The Storage of Time Intervals Using Oscillating Neurons

  1989cited by this paper
• Modeling brain function: the world of attractor neural networks, 1st Edition

  1989cited by this paper
• Chaos in random neural networks.

  1988cited by this paper
• How brains make chaos in order to make sense of the world

  1987cited by this paper
• Determining Lyapunov exponents from a time series

  1985cited by this paper
• Strange attractors that are not chaotic

  1984cited by this paper
• Crises, sudden changes in chaotic attractors, and transient chaos

  1983cited by this paper
• Neural networks and physical systems with emergent collective computational abilities.

  1982cited by this paper
• Circuits and systems

  1980cited by this paper
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