Spectrotemporal response properties of inferior colliculus neurons in alert monkey

Abstract

Because of its central position in the ascending auditory pathway, its large number of converging auditory brainstem inputs, and its fundamental role as a relay to auditory cortex and midbrain superior colliculus, the mammalian inferior colliculus (IC) is regarded pivotal for the integration of acoustic spectral-temporal cues to mediate sound-evoked behavior. However, detailed quantitative analyses of spectrotemporal neural responses are scarce. Moreover, most studies have been performed in anesthetized preparations, and it is unclear how to extrapolate findings to awake and behaving animals. Here, we characterize spectrotemporal receptive fields (STRFs) of single units in alert monkey IC by using a variety of broadband sounds with rippled amplitude spectra. We measured the response sensitivity to the ripple parameters density, Omega (cycles/octave), velocity, w (hertz), and direction selectivity, D. We observed a variety of dynamic STRFs, with a strong preference for low ripple densities, and a generally weak direction selectivity. Most cells preferred dynamic rippled stimuli above pure amplitude modulated noise (i.e., Omega = 0). Half of the cells could be characterized by good spectral-temporal separability, in which the ripple transfer function can be written as T(w, Omega) = F(w) x G(Omega). Inseparability could be attributed to a difference in responses to up and downward direction with respect to both amplitude and temporal phase. We tested linearity of IC neurons by using the STRF to predict neural responses to natural stimuli and broadband noise and discuss our results in the light of findings obtained from auditory cortex.

Figure 1.

Spectra of ripple stimuli as used in experiment. A, Ripple with upward sweep direction, velocity w = 4 Hz, and density Ω = −1.2 cyc/oct. B, Ripple with downward sweep direction, w = 8 Hz, and Ω = 0.4 cyc/oct. C, Ripple with flat spectrum: amplitude-modulating stimulus, w = 4 Hz, and Ω = 0 cyc/oct.

Figure 2.

Paradigm to derive STRF from responses to ripples varied in full velocity–density range. A, Spike events of IC neuron responding to ripples with densities of 0.4–2 cycles/octave and velocities of 8 to 40 Hz. Responses are shown for downward sweep direction (Ω > 0). B, Period histograms derived from responses as shown in A. Histograms are shown for responses to all stimuli (both sweep directions and Ω = 0). Phases in degrees are shown above each histogram. C, Magnitude and phase of ripple transfer function. D, STRF: descriptor of the response to spectrotemporal envelope modulations. It can be considered a time-dependent frequency filter or a frequency-dependent impulse response.

Figure 3.

Ripple transfer functions (magnitude), corresponding STRFs, and tone responses of four different cells. A, Example of low best ripple velocity and high best ripple density: best w = 16 Hz; best Ω = 1.6 cyc/oct; direction selectivity D = −0.11; ripple/AM response ratio = 2.61. B, Example of high best ripple velocity and low best ripple density: best w = 32 Hz; best Ω = 0.4 cyc/oct; direction selectivity D = 0.03; ripple/AM response ratio = 3.50. C, Example of asymmetric transfer function with preference for upward direction: best w = 16 Hz; best Ω = 0.4 cyc/oct; direction selectivity D = 0.23; ripple/AM response ratio = 4.60. D, Example of preference for amplitude modulation (Ω = 0) above ripple: best w = 24 Hz; best Ω = 0 cyc/oct; direction selectivity D = −0.18; ripple/AM response ratio = 0.43.

Figure 4.

Distributions of ripple parameters derived from the magnitude of ripple transfer functions. A, Distribution of best ripple velocity; B, best ripple density; C, distribution of direction selectivity; D, combined distribution of best ripple velocity versus best ripple density. The size of the data points reflect the number of neurons.

Figure 5.

Ratio of responses to moving ripple (Ω ≠ 0) and AM (Ω = 0) as a function of best Ω and the corresponding distribution of ripple/AM response ratio. Bin size, bs, is chosen according to bs = range/√n with range computed over data without outliers.

Figure 6.

Best frequency derived from STRF as a function of BF derived from tone responses. The solid line represents y = x, and the dotted lines represent differences of half octave (y = x − 0.5; y = x + 0.5). For 42 of 68 neurons (62%), the difference is <0.25 octave. There is no bias in the difference (mean difference, 0.04 octave; not significantly different from 0; t test, p > 0.1).

Figure 7.

SVD of ripple transfer functions (magnitude and phase), shown for downward ripple direction (Ω > 0). Eigenvalues in this example (normalized with respect to λ₁) are λ₁ = 1, λ₂ = 0.13, λ₃ = 0.07, λ₄ = 0.04, λ₅ = 0.02, and the inseparability index α = 0.02. A, Recorded transfer function in IC neuron. B, Separated spectral and temporal transfer functions corresponding to λ₁. C, An STRF is reconstructed by multiplying separated transfer functions (B) according to Equation 5. The reconstructed STRF (right) is compared with original STRF (left). The correlation between the STRFs has an r of 0.97.

Figure 8.

Separated transfer functions of four different neurons: magnitude (spikes per seconds) and phase (radians) versus ripple density and ripple velocity. Solid curves represent functions for downward sweep direction (Ω > 0), and dashed curves represent functions for upward direction (Ω < 0). Dotted curves represent AM transfer functions (Ω = 0) for three cells that yielded significant responses (q₅₀ > 0.376). Note that, for comparison purposes, the spectral data for Ω < 0 are shown along the positive Ω axis. Inseparability indices α were as follows, with α_down for downward, α_up for upward sweep direction, and α_total for total transfer function (downward, upward, and Ω = 0). A, α_down = 0.03; α_up = 0.02; α_total = 0.04. B, α_down = 0.08; α_up = 0.08; α_total = 0.13. C, α_down = 0.05; α_up = 0.16; α_total = 0.16. D, α_down = 0.14; α_up = 0.34; α_total = 0.18. The corresponding complete transfer functions are shown in Figures 2 and 3.

Figure 9.

Distributions of inseparability indices α. A, Quadrant separabilities α_up versus α_down. B, α_total, for total transfer function.

Figure 10.

A, Magnitude of ripple transfer function T(w, Ω) of IC unit and corresponding STRF. T(w, Ω) was recorded in full typical w–Ω range between 8 and 40 Hz with 8 Hz steps and between −2 and 2 cyc/oct with 0.4 cyc/oct steps (as in Fig. 3). B, Magnitude of ripple transfer functions F(w) at Ω = 0.4 cyc/oct and G(Ω) at w = 32 Hz of same unit. The ranges are 8–80 Hz with 8 Hz steps and −2 to 2 cyc/oct with 0.2 cyc/oct steps. C, Full transfer function computed according to Equation 5 and the corresponding STRF. Because the w range has been doubled compared with the recording in A, the temporal bin size of the STRF is halved, and, because the Ω step size has been halved, the frequency range is doubled.

Figure 11.

A, Phase functions of neuron shown in Figure 2. Phase, derived from SVD (see Fig. 7B), plotted as a function of velocity and density. For both directions, slopes correspond to temporal position (group delay) and spectral position (BF), see Equation 7. Phases for downward/upward sweep directions, χ_down and χ_up, consist of temporal and spectral parts, θ and ϕ (Eq. 8). In this example, χ_down = 0.88π − 0.81π = 0.07π and χ_up = −(−0.51π − 1.19π + 2π) = −0.30π, thus ϕ = (χ_up + χ_down)/2 = −0.36 = −21° and θ = (χ_up - χ_down)/2 = −0.57 = −33°. B, Temporal positions, or group delays, for upward versus those for downward sweep direction. C, Differences of group delays for upward and downward as shown in B, as a function of direction selectivity D. D, Spectral positions for upward versus those for downward sweep direction. The spectral positions are between −1.25 and 1.25 octave. When the difference between the two positions is >1.25 octave, a 2.5 octave correction is made. The diagonal in B and C represents the y = x line. E, Distribution of temporal phase constant θ (−180° < θ < 180°). F, Distribution of spectral phase constant ϕ (−90° < ϕ < 90°).

Figure 12.

Spatial distributions of response parameters. A, Map of best ripple density along lateromedial and anteroposterior axis. To allow a combined map for the two monkeys, anteroposterior coordinates are given relative to the center of the overlying motor SC. Sites with neurons not responding to ripple stimuli are indicated with x. B, Direction selectivity along anteroposterior axis.

Figure 13.

Prediction of response R(t) according to Equation 9. A, STRF and spectrogram of stimulus, S (in this example: macaque vocalization, grunt). The STRF is spectrally positioned around the best response (here, 1 kHz). The stimulus spectrogram is shown in the frequency range of the STRF (here, 0.5–2.8 kHz). B, Response spectrogram obtained by convolution along temporal dimension of STRF and stimulus spectrogram. C, Predicted response, R(t), obtained by sum along spectral dimension of response spectrogram. The black curve represents the prediction, and the gray curve represents the actual neural response to the vocalization. The average spontaneous spike rate (here, 16 spikes/s) is subtracted from the response. The amplitude of the predicted response is scaled to the actual response. The correlation between prediction and response is 0.50.

Figure 14.

Predictions of responses to noise stimuli or vocalizations according to Equation 9 compared with the actual responses for four different IC neurons. The left column shows the STRFs of the neuron, and the middle column shows either response spectrograms as in Figure 13B (A, B) or stimulus spectrograms (C, D), and the right column shows the predicted (black curve) and recorded (gray curve) responses. A, Neuron with low BF (1.2 kHz) responding to noise stimulus. B, Neuron with double-peak STRF (6 and 11 kHz). C, Neuron with low BF (1 kHz) responding to an undulating macaque scream. D, Neuron with medium-high BF (6 kHz) and inhibition preceding excitation responding to a bird song (northern oriole).

Figure 15.

Correlations of predicted with recorded responses. A, Correlations versus strength of predicted response. The prediction strength is computed by taking the root mean square of the predicted response (which is both positive and negative; see black curves in Fig. 14). The curves represent running averages over 12 data points. Sound levels of noise and vocalizations were 60 dB SPL. Responses to three different noise samples were recorded in 44 cells in Gi and 16 cells in Br; responses to six different vocalizations were recorded in 19 cells in Br. B, Correlations versus BF of the neuron for 60 IC neurons in monkey Gi (circles; n = 44) and Br (squares; n = 16). For each neuron, the largest of correlations found for three different noise stimuli at 60 dB SPL is shown. C, Correlations versus BF for vocalization responses for 19 IC neurons in monkey Br. For each neuron, the largest of correlations found for six different vocalizations at three sound levels (40, 50, and 60 dB SPL) is shown.