Discovery-based selection of lambda (<i>λ</i>).

<p>Discovery-selection by permutation of the response <i>r</i>(<i>t</i>) to identify the minimum lambda necessary to reduce the degrees of freedom to zero. Empirical distribution shows the histogram of minimum <i>λ</i> over 200 repeated permutations and serves as the null distribution. The red arrow denotes the median of the distribution that we designate as the optimal <i>λ</i>.</p

STRF estimated from STA and from GLM.

<p><b>(A</b>) STRF from STA. Stimulus center frequencies ranged from 97 to 11,234 Hz. Spike-times were binned at 1 ms resolution. (<b>B</b>) Evolution of Spike-count STRF from GLM as a function of increasing <i>λ</i> for L1 norm LASSO: (<b>a</b>) very low values of <i>λ</i> lead to noisy estimates, (<b>c</b>) at very high values of <i>λ</i> all covariates are zero valued, (<b>d</b>) at optimal value of <i>λ</i> chosen from discovery-based selection. (<b>C</b>) Evolution of Spike-count STRF from GLM as a function of increasing <i>λ</i> for L1/L2 norm group LASSO: (<b>e</b>) very low, (<b>g</b>) very high, and (<b>h</b>) optimal values of <i>λ</i>. Optimization selects or removes, simultaneously, all the covariates forming a group. Groups are composed of 4x4, adjacent and non-overlapping covariates. <b>(D)</b> Predicted discharge <i>λ</i>_<i>CIF</i>(<i>t</i>|<i>H</i>_<i>t</i>) from representative segment of gammatone stimulus, with and without sparse-group regularization. Group-sparse regularized GLM consistently improved the prediction of validation data over non-regularized GLM prediction of expected spike-counts. Correlation coefficients are 0.133 with regularization (red) and 0.066 without regularization (gray). Neural responses from S178, electrode contact #4.</p

Gammatone stimuli.

<p><b>A</b>) Human cochleotopic map of center frequencies from 100 to 11,234 Hz. <b>B</b>) Gammatone signal at 1 kHz center frequency. <b>C</b>) Gammatone filter bank with 50 channels.</p

Spike-Count History contribution to spike-count and High-<i>γ</i> band power STRFs.

<p>Neural responses from S178, electrode contact #11. Anatomical location shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0137915#pone.0137915.g001" target="_blank">Fig 1</a>. (<b>A</b>) Spike-count STRF estimated with L1/L2 sparsity-inducing norm and group structure GLM with Poisson distribution to link responses to predictors, without and with 350 ms spike-count history. (<b>B</b>) Magnitude of GLM spike-count history coefficients decreases with increasing history (i.e. time elapsed since current spike-count prediction). Shading represents 95% central range of null distribution estimated from permuted random shuffling of responses. (<b>C</b>) Cumulative distribution of p-values testing the contribution of spike-count history to current spike-count activity driven by gammatone stimuli. All p-values were adjusted for false discovery rate. (<b>D</b>) High-<i>γ</i> power STRF estimated with L1/L2 sparsity-inducing norm and group structure GLM with Poisson distribution to link responses to predictors, without and with 350 ms spike-count history. (<b>E</b>) Magnitude of GLM coefficients decreases with increasing spike-count history (i.e. time elapsed since current High-<i>γ</i> band power prediction). (<b>F</b>) Cumulative distribution of p-values testing the contribution of spike-count history to current High-<i>γ</i> power activity driven by gammatone stimuli. All p-values were adjusted for false discovery rate.</p

Locations of electrode recording sites within the superior temporal plane.

<p><b>(A</b>) MRI lateral-view rendering of a typical human left hemisphere. The Sylvian fissure is not visible from the cortical surface. The superior temporal plane was revealed along a section oriented at an oblique horizontal plane (solid red line with razor blade inset). (<b>B</b>) MRI rendering of superior temporal plane viewed from superior aspect. Light blue shading denotes the location of the obliquely oriented Heschl’s gyrus. The estimated locations of four recording sites selected from three different subjects (S140, S151, and S178) were projected to the surface of this illustrative brain and marked with filled red circles. MRI cross-sectional images containing the recording sites were obtained from sections oriented at an oblique frontal plane (solid green lines with razor blade inset), approximately perpendicular to the long axis of Heschl’s gyrus. (<b>C</b>) Line drawings of MRI cross sections show the position of the recording sites within the grey matter of Heschl’s gyrus for individual subjects.</p

Best frequency and bandwidth estimated for sites within Heschl’s gyrus.

<p><b>(Left column</b>) Fourteen recording locations in each subject were projected to the surface and marked with open circles. Solid red line marks the transition from core to non-core fields estimated with click train stimuli. (<b>Middle column</b>) Open circles mark a single or multiple best-frequency (BF) value for each location estimated from spike-count STRF. Bandwidth (BW) is depicted by a solid black line centered on the best-frequency for each location. (<b>Right column</b>) BF and BW mapped using High-<i>γ</i> power STRF.</p

Spike-count and High-<i>γ</i> power STRFs derived with sparse GLM models.

<p>Neural responses from S178 electrode contact #4 used in left column, responses from S140 electrode contact #6 used in middle column and from S151 electrode contact #14 used in right column (See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0137915#pone.0137915.g001" target="_blank">Fig 1</a>). Optimal <i>λ</i> values are shown on insets. (<b>A</b>) Spike-count STRF using L1 sparsity-inducing norm. (<b>B</b>) Spike-count STRF using L1/L2 norm regularization that exploits group structure when covariates are partitioned into neighborhoods, or groups. In this case, optimization selects or removes all the variables forming a group. Groups are composed of 4x4, adjacent and non-overlapping covariates. (<b>C</b>) High-<i>γ</i> (70 to 150 Hz) band power STRF from L1/L2 norm regularization that exploits group structure. Groups are composed of 4x4, adjacent and non-overlapping covariates.</p

Some sites within auditory cortex demonstrate increased HGB activity during self-vocalization compared to playback.

<p>These are four example subjects as labeled (A–D, left column) with the surface rendering of each subject's MRI with the recording site indicated (filled blue circle, right column). In each subject, these brain sites demonstrated increased averaged HGB power responses during SV (red waveforms, middle column) compared to responses obtained during PB (black waveforms, middle column). These HGB responses were ‘sustained’ throughout and beyond the duration of the utterance during SV, while the PB HGB responses were more consistent with an ‘on’ response.</p

Averaged evoked potentials recorded from subject 156 during self-vocalization and playback.

<p>(A) MRI surface rendering of the subject's left hemisphere demonstrating the location of the 96 contact recording array. Filled black circles denote contacts where the AEPs recorded during SV were attenuated (p<.01, 0–500 msec post-stimulus) compared to the AEPs recorded during the PB condition. (B) AEPs recorded from the lateral surface of the cerebral hemisphere during SV. The timing of vocalization onset is represented in each waveform panel by a vertical line. Thick gray lines represent major sulci as labeled on the lateral hemispheric surface in A. (C) AEPs obtained during PB. Two clusters of recording sites with maximal evoked activity are observed at locations along the superior temporal gyrus anterior and posterior to the transverse temporal sulcus. (LF-lateral fissure, STS-superior temporal sulcus, ITS-inferior temporal sulcus, TTS- transverse temporal sulcus).</p

Vocalization-associated changes in auditory responses are not significantly altered by changes in PB intensity.

<p>Different intensities of the PB stimuli were tested in the three subjects shown. Each vertical column displays a recording site location (top, filled blue circle), sound stimulus envelope tracings (middle) and the evoked responses recorded from the selected recording site (bottom) for each subject. (A) Subject 146 perceived the PB stimuli to be both “softer” and “louder” than the SV stimuli despite the fact that the sound stimulus envelope was smaller at both PB intensities than those measured during SV. The AEP waveform is nearly identical for the ‘softer’ and ‘louder’ PB stimuli, and is completely attenuated during SV. The high-gamma (HGB) response shows a ‘sustained’ pattern during SV, and an ‘on’ pattern during both PB conditions, with the early HGB increase seen during PB to be attenuated during SV. Subjects 147 (B) and 149 (C) both perceived the PB stimuli to be both “softer” and “louder” than the SV stimuli yet for these subjects the measured sound stimuli envelopes were greater for both PB intensities compared to that measured during SV. Like subject 146, both subjects demonstrate attenuation of the AEP and HGB power responses during SV compared to both PB intensities, and little difference is seen in AEP and HGB power responses between the PB intensities.</p