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The phase of cortical oscillations contains rich information and is valuable for encoding sound stimuli. Here we hypothesized that oscillatory phase modulation, instead of amplitude modulation, is a neural correlate of auditory streaming. Our behavioral evaluation provided compelling evidences for the first time that rats are able to organize auditory stream. Local field potentials (LFPs) were investigated in the cortical layer IV or deeper in the primary auditory cortex of anesthetized rats. In response to ABA- sequences with different inter-tone intervals and frequency differences, neurometric functions were characterized with phase locking as well as the band-specific amplitude evoked by test tones. Our results demonstrated that under large frequency differences and short inter-tone intervals, the neurometric function based on stimulus phase locking in higher frequency bands, particularly the gamma band, could better describe van Noorden's perceptual boundary than the LFP amplitude. Furthermore, the gamma-band neurometric function showed a build-up-like effect within around 3 seconds from sequence onset. These findings suggest that phase locking and amplitude have different roles in neural computation, and support our hypothesis that temporal modulation of cortical oscillations should be considered to be neurophysiological mechanisms of auditory streaming, in addition to forward suppression, tonotopic separation, and multi-second adaptation.
Pubmed ID: 24376715 RIS Download
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NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
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