Browsing by Author "Klein, David J."
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Item The Case of the Missing Pitch Templates: How Harmonic Templates Emerge in the Early Auditory System(1999) Shamma, Shihab; Klein, David J.; ISRPeriodicity pitch is the most salient and important of all pitch percepts.Psycho-acoustical models of this percept have long postulated the existenceof internalized harmonic templates against which incoming resolved spectracan be compared, and pitch determined according to the best matchingtemplates cite{goldstein:pitch}.However, it has been a mystery where andhow such harmonic templates can come about. Here we present a biologicallyplausible model for how such templates can form in the early stages of theauditory system. The model demonstrates that {it any} broadband stimulussuch as noise or random click trains, suffices for generating thetemplates, and that there is no need for any delay-lines, oscillators, orother neural temporal structures.
The model consists of two key stages:cochlear filtering followed by coincidence detection. The cochlear stageprovides responses analogous to those seen on the auditory-nerve andcochlear nucleus. Specifically, it performs moderately sharp frequencyanalysis via a filter-bank with tonotopically ordered center frequencies(CFs); the rectified and phase-locked filter responses are further enhancedtemporally to resemble the synchronized responses of cells in the cochlearnucleus.
The second stage is a matrix of coincidence detectors thatcompute the average pair-wise instantaneous correlation (or product)between responses from all CFs across the channels. Model simulations showthat for any broadband stimulus, high coincidences occur between cochlearchannels that are exactly harmonic distances apart. Accumulatingcoincidences over time results in the formation of harmonic templates forall fundamental frequencies in the phase-locking frequency range.
Themodel explains the critical role played by three subtle but importantfactors in cochlear function: the nonlinear transformations following thefiltering stage; the rapid phase-shifts of the traveling wave near itsresonance; and the spectral resolution of the cochlear filters. Finally, wediscuss the physiological correlates and location of such a process and itsresulting templates.
Item Dynamics of Neural Responses in Ferret Primary Auditory Cortex: I. Spectro-Temporal Response Field Characterization by Dynamic Ripple Spectra(1999) Depireux, Didier A.; Simon, J.Z.; Klein, David J.; Shamma, S.A.; ISR; CAARTo understand the neural representation of broadband, dynamic sounds in Primary Auditory Cortex (AI), we characterize responses using the Spectro-Temporal Response Field (STRF). The STRF describes and predicts the linear response of neurons to sounds with rich spectro-temporal envelopes. It is calculated here from the responses to elementary "ripples," a family of sounds with drifting, sinusoidal, spectral envelopes--the complex spectro-temporal envelope of any broadband, dynamic sound can expressed as the linear sum of individual ripples.The collection of responses to all elementary ripples is the spectro-temporal transfer function. Previous experiments using ripples with downward drifting spectra suggested that the transfer function is separable, i.e., it is reducible into a product of purely temporal and purely spectral functions.
Here we compare the responses to upward and downward drifting ripples, assuming separability within each direction, to determine if the total bi-directional transfer function is fully separable. In general, the combined transfer function for two directions is not symmetric, and hence units in AI are not, in general, fully separable. Consequently, many AI units have complex response properties such as sensitivity to direction of motion, though most inseparable units are not strongly directionally selective.
We show that for most neurons the lack of full separability stems from differences between the upward and downward spectral cross-sections, not from the temporal cross-sections; this places strong constraints on the neural inputs of these AI units.
Item Linear stimulus-invariant processing and spectrotemporal reverse correlation in primary auditory cortex(2003) Klein, David J.; Simon, Jonathan Z.; Depireux, Didier A.; Shamma, Shihab A.; Shamma, Shihab A.; ISR; CAARThe spectrotemporal receptive field (STRF) provides a versatile and integrated (spectral and temporal) functional characterization of single cells in primary auditory cortex (AI). We explore in this paper the origin and relationship between several different ways of measuring and analyzing the STRF. Specifically, we demonstrate that STRFs measured using a spectrotemporally diverse array of broadband stimuli --- such as dynamic ripples, spectrotemporally white noise (STWN), and temporally orthogonal ripple combinations (TORCs) --- are very similar, confirming earlier findings that the STRF is a robust linear descriptor of the cell. We also present a new deterministic analysis framework that employs the Fourier series to describe the spectrotemporal modulation frequency content of the stimuli and responses. Additional insights into the STRF measurements, including the nature and interpretation of measurement errors, is presented using the Fourier transform, coupled to singular-value decomposition (SVD), and variability analyses including bootstrap. The results promote the utility of the STRF as a core functional descriptor of neurons in AI.Item Racial and Ethnic Health Disparities among Fifth-Graders in Three Cities(2012) Schuster, Mark A.; Elliott, Marc N.; Kanouse, David E.; Wallander, Jan L.; Tortolero, Susan R.; Ratner, Jessica A.; Klein, David J.; Cuccaro, Paula M.; Davies, Susan L.; Banspach, Stephen W.Item Robust Spectro-Temporal Reverse Correlation for the Auditory System: Optimizing Stimulus Design(1999) Klein, David J.; Depireux, Didier A.; Simon, J.Z.; Shamma, S.A.; ISR; CAARThe spectro-temporal receptive field (STRF) is a functionaldescriptor of the linear processing of time-varying acoustic spectra by theauditory system. By cross-correlating sustained neuronal activity with the"dynamic spectrum" of a spectro-temporally rich stimulus ensemble, oneobtains an estimate of the STRF.In this paper, the relationship betweenthe spectro-temporal structure of any given stimulus and the quality ofthe STRF estimate is explored and exploited. Invoking the Fouriertheorem, arbitrary dynamic spectra are described as sums of basicsinusoidal components, i.e., "moving ripples." Accurate estimation isfound to be especially reliant on the prominence of components whosespectral and temporal characteristics are of relevance to the auditorylocus under study, and is sensitive to the phase relationships betweencomponents with identical temporal signatures.
These and otherobservations have guided the development and use of stimuli withdeterministic dynamic spectra composed of the superposition of many"temporally orthogonal" moving ripples having a restricted, relevant rangeof spectral scales and temporal rates.
The method, termedsum-of-ripples, is similar in spirit to the "white-noise approach," butenjoys the same practical advantages--which equate to faster and moreaccurate estimation--attributable to the time-domain sum-of-sinusoidsmethod previously employed in vision research. Application of the methodis exemplified with both modeled data and experimental data from ferretprimary auditory cortex (AI).