Analysis of dynamic spectra in ferret primary auditory cortex. I. Characteristics of single-unit responses to moving ripple spectra

Abstract

1. Auditory stimuli referred to as moving ripples are used to characterize the responses of both single and multiple units in the ferret primary auditory cortex. Moving ripples are broadband complex sounds with a sinusoidal spectral profile that drift along the logarithmic frequency axis at a constant velocity. 2. Neuronal responses to moving ripples are locked to the phase of the ripple, i.e., they exhibit the same periodicity as that of the moving ripple profile. Neural responses are characterized as a function of ripple velocity (temporal property) and ripple frequency (spectral property). Transfer functions describing the response to these temporal and spectral modulations are constructed. Temporal transfer functions are inverse Fourier transformed to obtain impulse response functions that reflect the cell's temporal characteristics. Ripple transfer functions are inverse Fourier transformed to obtain the response field, a measure analogous to the cell's response area. These operations assume linearity in the cell's response to moving ripples. 3. Transfer functions and other response functions are shown to be fairly independent on the overall level or depth of modulation of the ripple stimuli. Only downward moving ripples were used in this study. 4. The temporal and ripple transfer functions are found to be separable, in that their shapes remain unchanged for different test parameters. Thus ripple transfer functions and response fields remain statistically similar in shape (to within an overall scale factor) regardless of the ripple velocity or whether stationary or moving ripples are used in the measurement. The same stability in shape holds for the temporal transfer functions and the impulse response functions measured with different ripple frequencies. Separability implies that the combined spectrotemporal transfer function of a cell can be written as the product of a purely ripple and a purely temporal transfer functions, and thus that the neuron can be computationally modeled as processing spectral and temporal information in two separate and successive stages. 5. The ripple parameters that characterize cortical cells are distributed somewhat evenly, with the characteristic ripple frequencies ranging from 0.2 to > 2 cycles/octave and the characteristic angular frequency typically ranging from 2 to 20 Hz. 6. Many responses exhibit periodicities in the spectral envelope of the stimulus. These periodicities are of two types. Slow rebounds, not found in the spectral envelope, and with a period of approximately 150 ms, appear with various strengths in approximately 30% of the cells. Fast regular firings with interspike intervals of approximately 10 ms are much less common and appear to correspond to interactions between the component tones that make up a ripple.

Stimulus-invariant processing and spectrotemporal reverse correlation in primary auditory cortex

“…For the dynamic-ripple stimuli (Kowalski et al, 1996a;Depireux et al, 2001) shown in Figure 2A, each stimulus is composed of a single spectrotemporal modulation frequency (Fourier component). It can therefore be considered the auditory equivalent to the drifting sinusoidal luminance gratings used in visual neuroscience (Valois and Valois, 1990).…”

Spectral integration plasticity in cat auditory cortex induced by perceptual training

“…The spatial organization of tuning to broad-band ripple spectra should be related to sharpness of tuning assessed with pure-tones since both reflect aspects of spectral filtering (Calhoun and Schreiner, 1998;Wang and Shamma, 1995). However, there is only sparse experimental evidence for spatial organization of ripple transfer functions Kowalski et al, 1996). In this study, care was taken to sample the targeted frequency region evenly to avoid spatial biases due to sharpness of tuning clusters.…”

“…broad-band stimuli with sinusoidal spectral envelopes similar to the structure of vowels, have been used to characterize spectral integration properties of central auditory neurons (e.g., Schreiner and Calhoun, 1994;Shamma et al, 1995;Klein et al, 2000;Miller et al, 2002;Escabi and Schreiner, 2002). Cat and ferret cortical neurons respond preferentially to a narrow range of formant ratios or spectral envelope frequencies (Calhoun and Schreiner, 1998;Klein et al, 2000;Kowalski et al, 1996;Schreiner and Calhoun, 1994;Shamma et al, 1995). Receptive field properties determined with broad-band acoustic gratings and pure tones appear to be related, although the precise nature of that relationship is still debated (Calhoun and Schreiner, 1998;Linden et al, 2003).…”

Cortico‐cortical connectivity within ferret auditory cortex

“…The presence of multiple auditory cortical areas on the ectosylvian gyrus (EG) of this species was first demonstrated by using 2‐deoxyglucose autoradiography (Wallace et al, 1997) and subsequently confirmed by using optical imaging of intrinsic signals (Nelken et al, 2004) and single‐unit recording (Kelly et al, 1986; Kelly and Judge, 1994; Kowalski et al, 1995; Bizley et al, 2005). Although most electrophysiological recording studies have focused on the primary auditory cortex (A1) (Phillips et al, 1988; Kowalski et al, 1996; Schnupp et al, 2001; Fritz et al, 2003; Rabinowitz et al, 2011; Keating et al, 2013), the nonprimary auditory fields in this species are now receiving increasing attention (Nelken et al, 2008; Bizley et al, 2009, 2010, 2013; Walker et al, 2011; Atiani et al, 2014). …”