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Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

By Maoz Shamir, Oded Ghitza, Steven Epstein and Nancy Kopell


Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp

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    1. (2002). A computational role for slow conductances: single-neuron models that measure duration.
    2. (2005). Active listening: task-dependent plasticity of spectrotemporal receptive fields in primary auditory cortex.
    3. (2005). An oscillatory hierarchy controlling neuronal excitability and stimulus processing in the auditory cortex.
    4. (2005). Background gamma rhythmicity and attention in cortical local circuits: a computational study.
    5. (1994). Connectionist Speech Recognition: A Hybrid Approach.
    6. (2002). Cortical representation of auditory space: information-bearing features of spike patterns.
    7. (2007). Cross-frequency coupling between neuronal oscillations.
    8. (2000). Decoding temporal information: a model based on short-term synaptic plasticity.
    9. (2005). Dejittered spike-conditioned stimulus waveforms yield improved estimates of neuronal feature selectivity and spike-timing precision of sensory interneurons.
    10. (1998). Detection of n:m phase locking from noisy data: application to magnetoencephalography.
    11. (1953). Discharge patterns and functional organization of mammalian retina.
    12. (2003). Early cortical orientation selectivity: how fast inhibition decodes the order of spike latencies.
    13. (2001). Effects of syllable affiliation and consonant voicing on temporal adjustment in a repetitive speech-production task.
    14. (2004). Encoding for computation: recognizing brief dynamical patterns by exploiting effects of weak rhythms on action-potential timing.
    15. (2005). Encoding stimulus information by spike numbers and mean response time in primary auditory cortex.
    16. (2007). Endogenous cortical rhythms determine cerebral specialization for speech perception and production.
    17. (1999). Fast global oscillations in networks of integrate-andfire neurons with low firing rates.
    18. (1998). Fine structure of neural spiking and synchronization in the presence of conduction delays.
    19. (2007). First-spike latency information in single neurons increases when referenced to population onset.
    20. (1998). Gaa ´l G
    21. (2005). Hidden conditional random fields for phone classification.
    22. (2006). High gamma power is phase-locked to theta oscillations in human neocortex.
    23. (1996). High-frequency gamma electroencephalogram activity in association with sleep-wake states and spontaneous behaviors in the rat.
    24. (2006). How noise affects the synchronization properties of recurrent networks of inhibitory neurons.
    25. (2008). Induced electroencephalogram oscillations during source memory: familiarity is reflected in the gamma band, recollection in the theta band.
    26. (1995). Jando ´G ,N a ´dasdy
    27. (2004). Learning and production of movement sequences: behavioral, neurophysiological, and modeling perspectives.
    28. (2001). Model of cellular and network mechanisms for odor-evoked temporal patterning in the locust antennal lobe.
    29. (2001). Model of transient oscillatory synchronization in the locust antennal lobe.
    30. (1991). Neuronal Networks of the Hippocampus.
    31. (2003). New roles for the gamma rhythm: population tuning and preprocessing for the Beta rhythm.
    32. (2007). Olfactory bulb gamma oscillations are enhanced with task demands.
    33. (1998). Optimizing sound features for cortical neurons.
    34. (1997). Oscillatory gamma-band (30–70 Hz) activity induced by a visual search task in humans.
    35. (2006). Oscillatory neuronal dynamics during language comprehension.
    36. (2005). Phase synchrony among neuronal oscillations in the human cortex.
    37. (2006). Polychronization: computation with spikes.
    38. (2001). Rate coding versus temporal order coding: what the retinal ganglion cells tell the visual cortex.
    39. (2002). Real-time computing without stable states: a new framework for neural computation based on perturbations.
    40. (2006). Samengo I
    41. (1992). Segment-based stochastic models of spectral dynamics for continuous speech recognition.
    42. (1999). Speaking in shorthand—a syllable-centric perspective for understanding pronunciation variation.
    43. (2000). Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds.
    44. (2005). Spike times make sense.
    45. (1989). Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex.
    46. (2004). Task-related coupling from high- to low-frequency signals among visual cortical areas in human subdural recordings.
    47. (2007). Temporal coding of time varying stimuli. Neural Comput
    48. (1996). Temporal representations of odors in an olfactory network.
    49. (2006). Temporal structure in zebra finch song: implications for motor coding.
    50. (2008). The consequences of response nonlinearities for interpretation of spectrotemporal receptive fields.
    51. (1938). The response of single optic nerve fibers of the vertebrate eye to illumination of the retina.
    52. (2001). The role of spike timing in the coding of stimulus location in rat somatosensory cortex.
    53. (1983). The symmetric time-warping problem: from continuous to discrete. In:
    54. (2006). The tempotron: a neuron that learns spike timing-based decisions.
    55. (2005). Theta rhythm of navigation: link between path integration and landmark navigation, episodic and semantic memory.
    56. (2004). Time course of information about motion direction in visual area MT of macaque monkeys.
    57. (2007). Towards predicting consonant confusions of degraded speech.

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