Neuroscience Colloquia, New York University
Additional Information, Fall 1998
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| Speaker: | Larry Abbott |
|---|---|
| Title: | Circuit Models of Simple and Complex Cells in Primary Visual Cortex |
| Abstract: |
Although the majority of cortical synapses carry excitation between nearby
neurons, it has proven difficult to find a clear role for local recurrent
excitation in cortical processing. For example, inactivation of primary
visual cortex does not significantly modify the orientation selectivity of
simple cells. Correlation measurements indicate that the strongest
recurrent connections in primary visual cortex are between complex cells,
and we propose that these are responsible for the spatial phase invariance
of complex cell responses. I will present a cortical circuit model in
which recurrent connections selectively amplify neuronal responses. When
the cortical amplification is weak, the neurons in this network exhibit
simple cell responses, and when it is strong they respond as complex cells.
This suggests that simple and complex cells are the low and high gain
limits of the same basic cortical circuit, and that manipulations that
modify cortical gain should induce transitions between simple and complex
cell behavior.
Many models of simple and complex cells adequately describe their spatial selectivity but fail to account for their temporal response properties. These models act as low-pass temporal filters while neurons in primary visual cortex have bandpass characteristics. I will discuss how including realistic synaptic dynamics, in particular short-term depression, corrects this problem and leads to models with realistic frequency-response curves, nonlinear temporal summation, and direction selectivity. |
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| Speaker: | Shihab Shamma |
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| Title: | The Representaion of Dynamic Spectra in the Responses of Primary Auditory Cortex |
| Abstract: |
Natural sounds are usually characterized by their pitch, timbre, loudness, forms of
modulation, and onset/offset instants. These descriptions of sound quality have a
close relationship to the instantaneous spectral properties of the
sound waves. Physiological, psychoacoustical, and computational studies reveal that the
central auditory system has developed elegant mechanisms to extract and
represent this spectro-temporal information. For instance, the
primary auditory cortex (AI) employs a multiscale representation in which the dynamic
spectrum is repeatedly represented in AI at various degrees of spectral and
temporal resolution. This is accomplished by cells whose
responses are selective to a range of spectro-temporal parameters such as the local
bandwidth and asymmetry of spectral peaks, and their onset and offset transition
rates.
To explore these representations, neurophysiological experiments were designed employing new techniques to measure the spectral and dynamic properties of response areas in the primary cortical areas. The stimuli and techniques apply linear system theory to measure the response area of cortical units. In one method, the stimuli used are broadband spectra with sinusoidally modulated spectral envelopes against the logarithmic frequency axis - also called ripples. By varying the density (or frequency), amplitude, phase, and the drifting velocity of the ripple one can measure a ripple transfer function, and from it by an inverse Fourier transform, obtain a spectrotemporal response function, or effectively, an impulse response function of the cells. In another method, the impulse responses are measured using stimuli with random and dynamic spectral profiles that are cross-correlated with the responses (also known as the reverse-correlation method). In this talk, we will the application of these methods to the characterization of AI unit responses, and the perceptual and technological implications of these cortical representations. |
| Speaker: | Ken Johnson |
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| Title: |
Spatial and Temporal Structure of Receptive Fields in Area 3B of the Alert Monkey |
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