Boston University / Center for BioDynamics / Research / Neural Dynamics Research


Neural Dynamics Research

Contents

  1. Dynamics of cortical-like networks
    1. Principles of synchronization: biophysical details matter
    2. Behavior of Rhythmic Networks can be modulated
    3. Long-distance synchronization is different for different rhythms
    4. Propagating waves in cortical networks

  2. Nonlinear dynamics in single neurons
    1. Dendrites of dopaminergic neurons behave like chains of oscillators
    2. Understanding dynamics of layer 1 cells of the neocortex
    3. Dynamics and spatial extent of channel block by zinc

  3. Noise in the nervous system
    1. Noise-enhanced sensory dynamics
    2. Noise-shaping in a population of coupled neurons
    3. Neurons as a model of dynamical systems with intrinsic noise sources

  4. Central Pattern Generators
    1. Synaptic properties can give rise to oscillations in passive cells
    2. Depressing synapses create a dynamical switch
    3. Fast and slow networks interact to create nested rhythms
    4. Decay of inhibition within a local circuit controls phase lags between the circuits
    5. Electrical synapses between cells of different type create unintuitive effects


3. Noise in the nervous system

A. Noise-enhanced sensory dynamics

Stochastic resonance (SR) is a phenomenon wherein the response of a nonlinear system to a weak input signal is optimized by the presence of a particular, non-zero level of noise. Recently, Attila Priplata, James Niemi (Afferent Corp.), Martin Salen, Jason Harry (Afferent Corp.), Lewis A. Lipsitz (Harvard Medical School), and Jim Collins showed that input noise can be used to improve motor control in humans. Specifically, they showed that the postural sway of both young and elderly individuals during quiet standing can be significantly reduced by applying subsensory mechanical noise to the feet. They further demonstrated with input noise a trend towards the reduction of postural sway in elderly subjects to the level of young subjects. These results suggest that noise-based devices, such as randomly vibrating shoe inserts, may enable people to overcome functional difficulties due to age-related sensory loss.

Anthony Scinicariello, J. Timothy Inglis (University of British Columbia), and Jim Collins examined the effects of stochastic monopolar galvanic vestibular stimulation (GVS) on a subject's postural stability during perturbed stance. Specifically, they showed that stochastic cathodal monopolar GVS can enhance the sensitivity of the vestibular system and result in an increase in the relative stability of a subject's postural control system during a time-varying mechanical perturbation. These results demonstrate that increased vestibular activity induced by stochastic cathodal monopolar GVS can lead to enhanced postural stability.

Related Publications
 

K.A. Richardson, T.T. Imhoff, P. Grigg and J.J. Collins (1998) "Using electrical noise to enhance the ability of humans to detect subthreshold mechanical cutaneous stimuli" Chaos,8: 599-603.

Scinicariello A.P., Eaton K., Inglis J.T. and Collins J.J. "Enhancing human balance control with galvanic vestibular stimulation." Biological Cybernetics, 84: 475-480 (2001).

Hasty J., Collins J.J., Wiesenfeld K. and Grigg P. "Wavelets of excitability in sensory neurons." Journal of Neurophysiology, 86 : 2097-2101 (2001).

Liu W., Lipsitz L.A., Montero-Odasso M., Bean J., Kerrigan D.C. and Collins J.J. "Noise-enhanced vibrotactile sensitivity in older adults, patients with stroke and patients with diabetic neuropathy" Archives of Physical Medicine and Rehabilitation, 83: 171-176 (2002).

Dhruv N.T., Niemi J.B., Harry J.D., Lipsitz L.A. and Collins J.J. "Enhancing tactile sensation in older adults with electrical noise stimulation." Neuroreport, 13: 597-600 (2002).

D. Nozaki, D. Mar, P. Grigg and J. Collins demonstrated experimentally that SR-type effects can be obtained in rat sensory neurons with white noise, pink (1/f) noise, or brown noise. For low-frequency input noise, they showed that the optimal noise intensity is the lowest and the output signal-to-noise ratio the highest for conventional white noise. They also showed that under certain circumstances, 1/f noise can be better than white noise for enhancing the response of a neuron to a weak signal. This group has developed a theory to account for these results.

Related Publications
 

D. Nozaki, D.J. Mar, P. Grigg and J.J. Collins (1999) "The many colors of sensory stochastic resonance" Phys. Rev. Lett. 82: 2402-2405.

B. Noise-shaping in a population of coupled neurons

Spectral-noise shaping is a technique used to improved the signal-to-noise ratio in electronic signal processing systems. Biological systems may use a variant of this technique to obtain a system-wide performance improvement. Recently, in a modeling study, D. Mar, C. Chow, W. Gerstner (Swiss Federal Institute of Technology), and R. Adams (Analog Devices Corporation) showed how spectral noise-shaping can be implemented in networks of neurons that are coupled by lateral inhibition. They demonstrated that a network of integrate-and-fire neurons, exhibiting noise-shaping, shows substantial improvement in its dynamic range over a wide bandwidth via limited signal power.

Related Publications
 

D.J. Mar, C.C. Chow, W. Gerstner, R.W. Adams and J.J. Collins "Noise-shaping in populations of coupled model neurons", Proc. Natl. Acad. Sci. USA (1999) 96:10450-10455.

C. Neurons as a model of dynamical systems with intrinsic noise sources

Several related studies examine the effects that noise from ion-channel gating has on neuronal dynamics. Chow and White (1996) developed a simple theoretical model that describes how channel noise can generate spontaneous action potentials in an otherwise silent cell. White, with collaborators R. Klink and A. Alonso (Montreal Neurological Institute) and A. Kay (University of Iowa) used coordinated experimental and computational studies to demonstrate the importance of noise from voltage-gated sodium channels in neurons of the medial entorhinal cortex. S. Lowen (BU Department of Electrical and Computer Engineering), L. Liebovitch (Florida International University), and J. White have examined the effects of long-term correlations in channel state on interspike interval statistics in computational models. Haas and White (2002) examined how neuronal reliability in the entorhinal cortex depends on the frequency content of inputs. Their work suggests that intrinsic noise makes entorhinal neurons unreliable to broadband inputs, but that intrinsic properties make the cells more reliable during conditions of information acquisition and active locomotion, when their inputs are likely to have more energy in the theta (4-12 Hz) band. Ongoing work in White's group concerns the interaction of synaptic noise and noise from voltage-gated channels.

Related Publications
 

White J.A., Rubinstein J.T., and Kay AR (2000) "Channel noise in neurons," Trends in Neurosciences 23: 131-137.

White J.A. and Haas JS (2001) "Noise from voltage-gated ion channels: effects on dynamics and reliability in intrinsically oscillatory neurons, In Handbook of Biological Physics, Vol 4. F. Moss and S. Gielen (Eds.), Elsevier Press, Amsterdam, pp. 257-278.

C.C. Chow and J.A. White, "Spontaneous action potentials due to channel fluctuations", Biophysical J. 1996, 71:3013-3021.

J.A. White, R. Klink, A. Alonso and A.R. Kay, "Noise from voltage-gated ion channels may influence neuronal dynamics in the entorhinal cortex", J. Neurophysiol. 1998, 80:262-269.

S.B. Lowen, L. Liebovitch, and J.A. White, "Fractal ion-channel behavior generates fractal firing patterns in neuronal models" Physical Review E 59 (1999) 5970-5980.

Haas J.S. and White J.A. "Frequency selectivity in layer II cells of the entorhinal cortex" J. Neurophysiol, in press 2002.

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