Age and learning shapes sound representations in auditory cortex during adolescence
- The Edmond and Lily Safra Center for Brain Sciences, Israel
- Department of Neurobiology, The Institute of Life Sciences, The Hebrew University of Jerusalem, Israel
- Department of Neurobiology, Stanford University, United States
- Department of Applied Physics, Stanford University, United States
- Department of Psychiatry and Behavioral Sciences, Stanford University, United States
Figures
Figure 1 with 1 supplement
Adolescent mice exhibit lower performance during self-initiated auditory learning in the ‘Educage’.
(A) Schematic model of the ‘Educage’ (left), the trial structure and trial types (FA, false alarm; CR, correct reject). Created with Biorender.com. (B) Experimental timeline. Total training time was 21 days (±2). (C) The sounds used for training. Light blue: easy task; Dark blue: hard task; Gray: catch-trials. (D) Learning curve examples. Adolescent mouse left, (P20–to–P37); adult mouse right, (P60–to–P77). Vertical dashed lines indicate the easy-hard transition. Horizontal line is d'=1. (E) Number of trials to reach threshold (d’ ≥ 1; adolescents, n=15; adults, n=15; z=–0.1659; p=0.8682, two-sample Wilcoxon rank sum test). (F) Discriminability (d’) of the easy task in adolescent mice at P30 (gray; n=15, d’=2.0001 ± 0.1791; # trials = 8317 ± 712) and adult mice at P70 (black; n=15, d’=2.1986 ± 0.2441; # trials = 13229 ± 514, top: marked by the arrowhead). Dashed lines: mean trials per group (t-stat=–5.6314, df = 28, p=4.9566e-06, two-sample independent t-test, solid vertical line), and mean d’ per age group (z=0.2074; p=0.8357, two-sample Wilcoxon rank sum test, solid horizontal line) (G) Change in discriminability (Δd’) of the easy task before and after the introduction of the hard task (Top: arrowheads; left: adolescent, signed rank = 14, p=0.0067; right: adult, signed rank = 14, p=0.1514, one-sample Wilcoxon signed rank test; Δd’ between adult and adolescent mice: z=–2.0739; p=0.0381, two-sample Wilcoxon rank sum test) (H) Same as ‘G’ for the first 100 and last 100 trials of the experiment in the easy task (adolescent signed rank = 120, p=6.1035e-05; adult signed rank = 120, p=6.1035e-05, one-sample Wilcoxon signed rank test; Δd’ between adult and adolescent mice: z=–1.0370; p=0.2998, two-sample Wilcoxon rank sum test). (I) Same as ‘F’ for the hard task (adolescent-gray; n=15, d’=1.1895 ± 0.1783; # trials = 4163 ± 297; adult-black; n=15, d’=1.8342 ± 0.1743; # trials = 4102 ± 475; mean trials per group: t-stat=0.1306, df = 28, p=0.8970, two-sample independent t-test, solid vertical line; mean d’ per group: z=–2.2398; p=0.0251, two-sample Wilcoxon rank sum test, solid horizontal line). (J) Same as ‘G’ for the hard task. (adolescent signed rank = 73, p=0.4887; adult signed rank = 114, p=8.5449e-04, one-sample Wilcoxon signed rank test; Δd’ between adult and adolescent mice: z=–1.9495; p=0.0512, two-sample Wilcoxon rank sum test).
Figure 1—figure supplement 1
Behavioral criteria of auditory learning.
(A) Learning curves per mouse throughout the experiment (n=5 adolescents, n=4 adults). (B) Discriminability of novice (Nov.; first 100 trials) compared to expert (Exp.; last 100 trials) mice in the adolescent and adult groups (Novice vs Expert — Adolescents, p=0.0625; Adults, p=0.0625, Wilcoxon sign ranked test after Bonferroni correction; Adolescents vs Adults — Novice, p=0.4444, Expert, p=0.5476, Wilcoxon rank sum test after Bonferroni correction). (C) Discriminability (d’) of the easy task at the minimal number of trials (5087 trials) shared between all mice (z=–1.0370; p=0.2998, two-sample Wilcoxon rank sum test). (D) Discriminability (d’) of the easy task at the mean number of trials of adolescent mice (8317 trials) shared between all mice (n=15 per group; z=0.9125; p=0.3615, two-sample Wilcoxon rank sum test). (E) Same as A. but for the mean number of trials (13229 trials) of adult mice (adolescent n=4; adult n=15; z=0.9125; p=0.5304, two-sample Wilcoxon rank sum test).
Figure 2 with 1 supplement
Adolescent mice exhibit lower performance in the head-fixed discrimination task.
(A) Experimental timeline of training followed by recordings. (B) Trial structure during the recording. Solid lines indicate the tone period. Dashed lines show the reward or punishment delay (0.6 s), and the response window (2 sec). (C) Example session. Licks (gray ticks) and trial outcomes (hit = green, false alarm = yellow, miss = red, and correct reject = blue) across all trials in one recording session. (D) Discriminability during training sessions for the easy task (light blue) and hard task (dark blue). (E) Change in d’ after the introduction of the hard task (last 100 trials of the last session of the easy task compared to last 100 trials of the first hard session; adolescent: sign-rank=1, p=0.0625; adult: sign-rank=10, p=0.9998; rank-sum=14, p=0.0381, two-sample Wilcoxon rank sum test). (F) Expert d’ of the last 100 trials during the last training session of the easy task (rank-sum=21, p=0.1255, two-sample Wilcoxon rank sum test). (G) Same as ‘F,’ but for the hard task (rank-sum=17, p=0.0173, two-sample Wilcoxon rank sum test). (H) Behavioral performance (average d’ of the easy and the hard task) per mouse during recording sessions for adolescents (n=13, left) and adults (n=14, right; trials per recording: adolescent: 340.5385±45.0650; adult: 431.1429±30.3367; independent t-test, t-statistic=–203.7581, p=0.1116). (I) Same as ‘H’ but only for the first 148 trials. The color bar shows the p-values between the groups. (J) Average cumulative licks per trial in adolescents (dashed-line) and adults (solid-line) from –200 ms before tone-onset until the reward or punishment delay, 500 ms after tone-offset. (K) Lick latency per trial for adolescent (left) and adult (right) groups during electrophysiological recordings (LME statistics are shown in Supplementary file 1). (J) Same as ‘K’ for the Lick count.
Figure 2—figure supplement 1
Inter-trial interval after different trial outcomes.
(A) Average inter-trial interval (ITI) per mouse to the next trial after a previous hit (z=1.6176; p=0.1057, two-sample Wilcoxon rank sum test). (B) Same as A. after a previous miss hit (z=0.0830; p=0.9339, two-sample Wilcoxon rank sum test). (C) Same as A. after a previous false alarm hit (z=–3.9823; p=6.8241e-05, two-sample Wilcoxon rank sum test). (D) Same A. after a previous correct reject hit (z=0.3733; p=0.7089, two-sample Wilcoxon rank sum test).
Figure 3 with 4 supplements
Adolescent mice exhibit lower performance in the head-fixed discrimination task.
(A) Experimental timeline of training followed by recordings. Created with Biorender.com. (B) Trial structure during the recording. Solid lines indicate the tone period. Dashed lines show the reward or punishment delay (0.6 s), and the response window (2 s). (C) Example session. Licks (gray ticks) and trial outcomes (hit = green, false alarm = yellow, miss = red and correct reject = blue) across all trials in one recording session. (D) Discriminability during training sessions for the easy task (light blue) and hard task (dark blue). (E). Change in d’ after the introduction of the hard task (last 100 trials of the last session of the easy task compared to last 100 trials of the first hard session; adolescent: sign-rank=1, p=0.0625; adult: sign-rank=10, p=0.9998; rank-sum=14; p=0.0381, two-sample Wilcoxon rank sum test). (F) Expert d’ of the last 100 trials during the last training session of the easy task (rank-sum=21; p=0.1255, two-sample Wilcoxon rank sum test). (G) Same as ‘F,’ but for the hard task (rank-sum=17; p=0.0173, two-sample Wilcoxon rank sum test). (H) Behavioral performance (average d’ of the easy and the hard task) per mouse during recording sessions for adolescents (n=13, left) and adults (n=14, right; trials per recording: adolescent: 340.5385±45.0650; adult: 431.1429±30.3367; independent t-test, t-statistic=–203.7581, p=0.1116). (I) Same as ‘H’ but only for the first 148 trials. The color bar shows the p-values between the groups. (J) Average cumulative licks per trial in adolescents (dashed-line) and adults (solid-line) from –200 ms before tone-onset until the reward or punishment delay, 500 ms after tone-offset. (K) Lick latency per trial for adolescent (left) and adult (right) groups during electrophysiological recordings (LME statistics are shown in Supplementary file 1). (J) Same as ‘K’ for the Lick count.
Figure 3—figure supplement 1
Lick bias and impulsivity in adolescent and adult mice during head-fixed recordings.
(A) Average psychometric curve of adult recordings (solid line) and adolescent recordings (dashed line) (B) Lick bias (i.e. criterion bias) per recording (c-bias: z=–2.1366, p=0.0326, Wilcoxon rank sum test). (C) Proportion of licks within inter-trial intervals (ITIs) after False Alarms (FAs) (z=–2.6447, p=0.0082, Wilcoxon rank sum test). (D) Average number of licks during ITIs after FAs(z=–2.7230, p=0.0063, Wilcoxon rank sum test).
Figure 3—figure supplement 2
Auditory Cortex is necessary for task execution in adult mice.
(A) Experimental design for testing the role of ACx during tone discrimination in expert mice (adults only). (B) Protocol for transient optogenetic suppression (light pulse duration was –50 ms from tone onset, to +50 ms from tone offset). Created with Biorender.com. (C) Injection sites and optical fiber implantation for the experimental (GtACR2; top) and control groups (dTomato; bottom). (D) Lick ratio for Go and No-Go stimuli under light-off conditions (gray) as compared to light-on conditions (red) in experimental (GtACR2, n=13; left; Go stimuli: p=0.0001; No-Go stimuli: p=0.0107; one-sample Wilcoxon sign ranked test after Bonferroni correction) and control mice (dTomato, n=8; right; Go stimuli: p=0.4263; No-Go stimuli: p=0.2953; one-sample Wilcoxon sign ranked test after Bonferroni correction). (E) Lick ratio under light-off trials after light-on (red) or light off trials (gray) in experimental (GtACR2, n=13; left; Go stimuli: p=0.3864; No-Go stimuli: p=0.2231; one-sample Wilcoxon sign ranked test after Bonferroni correction) and control (dTomato, n=8; right; Go stimuli: p=0.58341; No-Go stimuli: p=0.3214; one-sample Wilcoxon sign ranked test after Bonferroni correction). (F) Behavioral performance (d’) per session under light-off conditions in easy (light blue) and hard (dark blue) task, as compared to light-on conditions (red) in experimental (GtACR2, n=13; left; easy task: p=0.0010, hard task: p=0.0007, two-sample Wilcoxon rank sum test after Bonferroni correction; light-on p=0.0010; light-off: p=0.0398, one-sample Wilcoxon sign ranked test after Bonferroni correction) and control mice (dTomato, n=8; right, easy task: p=0.9999, hard task: p=0.7422, two-sample Wilcoxon rank sum test after Bonferroni correction; light on p=0.0312; light off: p=0.0234, one-sample Wilcoxon sign ranked test after Bonferroni correction).
Figure 3—figure supplement 3
Verification of GtACR2 expression.
Photomicrograph (left), and reconstruction (right) of the GtACR2 infected area (red) per mouse. Reconstruction followed the coordinates of the Allen-CFF template-atlas. ACx is highlighted in white and GtACR2-expression in red.
Figure 3—figure supplement 4
Adolescent and adult mice performed similarly throughout recordings as well as between the head-fixed configuration and the Educage.
(A) Behavioral performance (d’) in the easy task (light blue) and hard task (dark blue) for adolescent (recording = 13; left) and adult (recording = 14; right) recordings at the behavioral criterion of d’>1 (adolescent mice: signed rank: 91, p=2.4414e-04; adult mice: signed rank: 105, p=1.2207e-04, Wilcoxon sign ranked test). Behavioral threshold of d’=1 highlighted in the dashed line. (B) Behavioral performance (average d’ of the easy and the hard task) for every mouse per recording for adolescent mice (n=5; left; 1st rec.: p=0.8125; 2nd rec.: p=0.9999; 3rd rec.: p=0.9999, Wilcoxon sign ranked test, after Bonferroni correction), and adult mice (n=6; right; 1st rec.: p=0. 8438; 2nd rec.: p=0.9999; 3rd rec.: p=0.9999, Wilcoxon sign ranked test, after Bonferroni correction). Behavioral threshold of d’=1 highlighted in the dashed line. (C) Comparison of behavioral performance in the head-fixed configuration and the Educage for adult mice (left; easy task: p=0.9960; hard task: p=0.2159, Kruskal Wallis test after Bonferroni correction), and adolescent mice (right; easy task: p=0.9973; hard task: p=0.1505, Kruskal Wallis test after Bonferroni correction) in the easy (light blue) and the hard (dark blue) task.
Figure 4 with 2 supplements
Auditory cortex (ACx) neurons in adolescents exhibit lower discriminability in stimulus- and choice- related activity.
(A) Recordings in ACx when the mouse is engaged in the task, using Neuropixels-1 probes. Left: Recordings were performed in AUDd, AUDp, AUDv, and TEa. Right: Fluorescent micrograph of a coronal brain slice showing the probe tracks of three recordings (red = DiI, yellow = DiO). Created with Biorender.com. (B) Top: 3D-Reconstruction of recording sites in adolescents (n=13; gray) and adults (n=14; black). Bottom: distribution of the spike-depth of all excitatory tone-responsive L5/6 neurons in adolescents (n=455; gray) and adults (n=607; black). (C) Normalized PSTH (FR in Hz) and lick-rate (LR in Hz) from –200 ms to +600 ms after tone-onset in adolescents (gray) and adults (black). (D) Spiking activity from one example neuron sorted by trial outcome (hit, miss, false alarm, correct reject). Top: PSTH per trial outcome. Bottom: Heat map of the firing rate (FR) sorted per trial outcome. (E) Discriminability values (AUC) over time (from –200 ms to 600 ms after tone onset) for one example neuron (same neuron as in ‘D’). AUC values are shown for stimulus-related activity (left: easy task, middle: hard task) and choice-related activity (right). Shuffled distribution in all curves is shown in gray. (F) Same as ‘E’ for all neurons. The curves are average (+- STE) neuronal discriminability of adult neurons (solid line) and adolescent neurons (dashed line), for easy (adolescent neurons = 190, mice = 4, recordings = 7; adult n=358, mice = 4, recordings = 8; left) and hard stimulus-related activity (adolescent n=429; adult n=562, mice = 5, recordings = 9; middle), and choice-related activity (adolescent n=429; adult n=562, mice = 5, recordings = 9; right). (G) 3D plots of the onset-latency of discriminability (ms), duration of discriminability (ms), and maximal discriminability (AUC) of all neurons that showed significant discriminability. Left: easy task (adolescent neurons = 178 (93%), mice = 4, recordings = 6; adult n=346 (97%), mice = 4, recordings = 8; left); Center: hard task (adolescent neurons = 399 (93%), mice = 5, recordings = 10; adult n=544 (97%), mice = 6, recordings = 12; middle); Right: choice-related activity (adolescent neurons = 181 (95%), mice = 4, recordings = 9; adult n=339 (95%), mice = 4, recordings = 7; right).
Figure 4—figure supplement 1
Probe reconstruction and activity profile across auditory cortex (ACx) regions.
(A) Example voltage trace during a tone (100 ms) across 11 channels. (B) Example PSTH per depth (50 μm bins) across AUDd, AUDp, AUDv, and TEa (3850 maximal depth μm). (C) 3D-Reconstruction of recording sites in adolescent (n=5; left) and adult (n=6; right) mice. (D) Spike-depth of excitatory tone-responsive L5/6 neurons in AUDd, AUDp, AUDv, and TEa of adolescent (top) and adult (bottom) recordings. (E) Population PSTH from – 200 ms to 600 ms after tone onset in AUDd (blue), AUDp (purple), AUDv (magenta), and TEa (green) for adolescent neurons (dashed line) and adult neurons (solid line).
Figure 4—figure supplement 2
The neuronal discriminability of stimulus- and choice-related activity is similar across auditory sub-regions.
(A) Onset-latency of discriminability (ms), duration of discriminability (ms), and maximal discriminability (AUC) of neurons that showed significant discriminability (exceeded 3 STD of the shuffled distribution) in the easy task (adolescent neurons = 178 (93%), mice = 4, recordings = 6; adult n=346 (97%), mice = 4, recordings = 8; adolescent: onset-latency of discriminability: p=0.5310, duration of discriminability: p=0.5418, maximal discriminability: p=0.7212; adult: onset-latency of discriminability: p=0.3810, duration of discriminability: p=0.6105, maximal discriminability: p=0.9115; Friedman test, correct for multiple comparisons). (B) Same as ‘A,’ but in the hard task (adolescent neurons = 399 (93%), mice = 5, recordings = 10; adult n=544 (97%), mice = 6, recordings = 12; adolescent: onset-latency of discriminability: p=0.9402, duration of discriminability: p=0.3388, maximal discriminability: p=0.6685; adult: onset-latency of discriminability: p=0.2425, duration of discriminability: p=0.5700, maximal discriminability: p=0.1011; Friedman test, correct for multiple comparisons). (C) Same as ‘A,’, but for choice-related activity (adolescent neurons = 181 (95%), mice = 4, recordings = 9; adult n=339 (95%), mice = 4, recordings = 7; adolescent: onset-latency of discriminability: p=0.3975, duration of discriminability: p=0.6823, maximal discriminability: p=0.2866; adult: onset-latency of discriminability: p=0.0881, duration of discriminability: p=0.8185, maximal discriminability: p=0.2501; Friedman test, correct for multiple comparisons), across the AUDd, AUDp, AUDv, TEa.
Figure 5 with 1 supplement
Decoding in adult neuronal populations outperforms decoding in adolescents.
(A) Decoding accuracy for the first 200 ms across all recordings in both adults (black) and adolescents (gray) for the easy task (adolescents compared to adults, p=0.5000, Student’s t-test) and the hard task (adolescents compared to adults, p=0.0300, Student’s t-test). Decoding is better in the easy task for both age groups (adults: p=0.0030; adolescents: p=0.01, paired t-test). (B) Decoding latency for all recordings in the easy task (p=0.0200, Student’s t-test) and the hard task (p=0.0030, Student’s t-test), as well as compared between age groups (easy task, p=0.05400, paired t-test; hard task: p=0.0100). (C) Decoding accuracy over a time window from –0.5 s to 10 s (the response window highlighted in the gray) for the easy task (left) and the hard task (right). (D) Linear discriminant analysis (LDA) separation for easy and hard tasks. Lines represent robust linear regression fits without intercept (Huber loss; robust linear regression, p=0.0001) (E) Single trial variance for easy and hard tasks in adolescent and adult recordings (adults: p=0.0040; adolescents: p=0.0300, paired t-test; easy task: p=0.4500; hard task: p=0.4100, Student’s t-test). (F) Visualization of population representations for the stimuli in easy and hard tasks. Dotted lines indicate decoding dimensions, and ellipses represent the covariance of the representations.
Figure 5—figure supplement 1
Decoding accuracy of the first 200 ms after the response window.
Linear discriminant analysis (LDA) decoding accuracy of the easy and the hard tasks of adolescent and adult mice, 200 ms after the response window.
Figure 6 with 2 supplements
Cortical activity during behavior reflects both age- and learning-induced effects.
(A) Training and recording schedule for novice mice, compared to expert mice. Created with Biorender.com. (B) 3D-Reconstruction of recording sites in novice adolescent (n=6; gray) and novice adult (n=6; black) mice. Bottom: spike-depth of excitatory tone-responsive L5/6 adolescent (n=130; gray) and adult (n=186; black) neurons. (C) Normalized FR and lick rate (LR) PSTH from –200 ms to 600 ms after tone-onset in adolescents (gray) and adults (black). Average +-sem. (D) Single neuron data from novice adolescent mice. Left: Heat map of the firing rate (FR) per trial from one example neuron sorted by trial outcomes. Center: the AUC of the neuron from the left for the easy and hard stimulus pairs (light and dark blue, respectively). Right: Average (+-SEM) AUC of all neurons in the novice group (n=140 neurons). (E–G) Same as ‘D’ for novice adult (n=186 neurons), expert adolescents (n=455 neurons; Easy vs hard), and expert adults (n=604 neurons; Easy vs hard.). (H) Linear regression analysis between the average AUC per recording and the behavioral d’ during the recording (the correlation and p-values are indicated for each plot). (I) Same as ‘I’ for adult mice.
Figure 6—figure supplement 1
Behavioral performance of novice mice.
(A) Behavioral performance (d’) in the easy task (light blue) and hard task (dark blue) for adolescent (n=6; left) and adult (n=6; right) mice at the behavioral criterion of d’>1 (adolescent mice: signed rank: 19, p=0.0938; adult mice: signed rank: 15, p=0.4375, Wilcoxon sign ranked test). Behavioral threshold of d’=1 highlighted in the dashed line. (B) Behavioral performance (average d’ of the easy and the hard task) for every mouse per recording for adult mice (n=3; left; signed rank: 0, p=0.2500 Wilcoxon signed-rank test). adolescent mice (n=3; right; signed rank: 0, p=0.2500, Wilcoxon sign ranked test). Behavioral threshold of d’=1 highlighted in the dashed line.
Figure 6—figure supplement 2
The neuronal discriminability of Easy and Hard Go and No-Go are distributed similar across auditory sub-regions in adolescent and adult novice and expert mice.
Onset-latency of discriminability (ms), duration of discriminability (ms), and maximal discriminability (AUC) of neurons that showed significant discriminability (exceeded 3 STD of the shuffled distribution). Left: easy task (Novice, adolescent n=108 (83%), mice = 3, recording = 6; onset-latency of discriminability: P=0.2422, duration of discriminability: p=0.5639, maximal discriminability: p=0.2062. Novice, adult n=179 (97%), mice = 3, recording = 6, onset-latency of discriminability: p=0.8335, duration of discriminability: p=0.8013, maximal discriminability: p=0.1900. Expert, adolescent n=450 (97%), mice = 5, recording = 13, onset-latency of discriminability: p=0.0918, duration of discriminability: p=0.4020, maximal discriminability: p=0.0698. Expert, adult n=598 (99%), mice = 6, recording = 14, onset-latency of discriminability: p=0.6807, duration of discriminability: p=0.7223, maximal discriminability: p=0.7557; Friedman test, correct for multiple comparisons); Right: hard task (Novice, adolescent n=108 (83%), mice = 3, recording = 6, onset-latency of discriminability: p=0.6294, duration of discriminability: p=0.0693, maximal discriminability: p=0.0858. Novice, adult n=181 (96%), mice = 3, recording = 6, onset-latency of discriminability: p=0.2180, duration of discriminability: p=0.3388, maximal discriminability: p=0.0648. Expert, adolescent n=440 (95%), mice = 5, recording = 13, onset-latency of discriminability: p=0.9911, duration of discriminability: p=0.9939, maximal discriminability: p=0.4058. Expert, adult n=589 (98%), mice = 6, recording = 14, onset-latency of discriminability: p=0.7141, duration of discriminability: p=0.4084, maximal discriminability: p=0.6365; Friedman test, correct for multiple comparisons); across the AUDd, AUDp, AUDv, TEa.
Figure 7 with 1 supplement
Adult mice show greater plasticity after learning.
(A) Schematic showing that for the passive listening protocol, we continued our recording following the session of the engaged task (i.e. in satiated mice) by removing the waterspout. Created with Biorender.com. (B) Example raster plot of a neuron from an adolescent mouse (top) and an adult mouse (bottom). (C) Frequency-response areas (FRA’s) of the neurons shown in ‘B.’ (D) Distribution of best frequencies in our dataset. Values are normalized firing rates calculated at 62 dB SPL. Matrices are sorted by BF for clarity. Dotted line marks the decision boundary. (E) Tuning bandwidth at 62 dB SPL of neurons in adolescents and adults. Side-by-side comparisons of novice versus experts. (adolescents p=0.0882, adults p=0.0001, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons). (F) Same as E. for Population sparseness (adolescents p=0.9549, adults p=0.0013, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons). (G) Same as E. for the distance (in octaves) between the best frequency of each neuron to the easy Go-stimulus (adolescents p=0.0816, adults p=0.6391, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons). (H) Same as E. for the average neuronal d’ of frequencies in the learned frequency spectrum (adolescents p=0.1627, adults p=0.0026, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons).
Figure 7—figure supplement 1
Learning related changes in neuronal tuning properties in primary and secondary auditory cortex.
(A) Tuning bandwidth in AUDp at 62 dB SPL of neurons in adolescents and adults. Side-by-side comparisons of novice versus experts. (adolescents p=0.0438, adults p=0.0001, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons). (B) Same as ‘A’ for the population sparseness in AUDp (adolescents p=0.5724, adults p=0.0066, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons). (C) Same as ‘A’ for the distance (in octaves) between the best frequency of each neuron to the easy Go-stimulus in AUDp (adolescents p=0.0001, adults p=0.0201, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons). (D) Same as ‘A’ for the average neuronal d’ of pairs of frequencies limited to the learned frequency spectrum in AUDp (adolescents p=0.0471, adults p=0.0321, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons). (E–H) Same as A-D but in the AUDv. (E) Adolescents p=0.9982, adults p=0.0427, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons. (F) Adolescents p=0.8841, adults p=0.8031, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons. (G) Adolescents p=0.9910, adults p=0.0042, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons. (H) Adolescents p=0.9438, adults p=0.0108, Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons.
Tables
Table 1
Behavioral differences between adolescent and adult mice are age-, but not sex-related.
Fixed effects of age and sex, and the random effects of co-housing in the ‘Educage’ on the discriminability (mean d’ of the last 100 trials of the easy and hard task to avoid pseudo replication) of all mice (Number of observations=30, Fixed effects coefficients = 3, Random effects coefficients = 7, Covariance parameters = 2). Coefficient estimates, STE, T-statistic, degrees of freedom, p-values (adjusted for multiple comparisons with the Bonferroni method) and the lower and upper Confidence Interval (95%). The model includes random effects coefficients of the Cage ID in each group of co-housed mice (7 cages in total; see methods, equation 7). Model structure: discriminability(d’)~age + sex + (1|cage ID).
| Fixed effects | Estimate | STE | T-statistic | DF | P-value | CI (lower) | CI (upper) |
|---|---|---|---|---|---|---|---|
| Intercept | 1.6001 | 0.2312 | 6.9222 | 27 | 3.8798e-07 | 1.1258 | 2.0744 |
| Age | 0.5994 | 0.2266 | 2.6457 | 27 | 0.0269 | 0.1346 | 1.0643 |
| Sex | –0.0428 | 0.2476 | –0.1729 | 27 | 0.9999 | –0.5509 | 0.4653 |
Table 2
Neuronal discrimination is later, shorter, and less precise in adolescent neurons.
Linear mixed effect models of the neuronal discriminability in adolescence and adulthood per stimulus-related activity in the easy task (Number of observations = 524, Fixed effects coefficients = 2, Random effects coefficients = 10, Covariance parameters = 3), stimulus related activity in the hard task (Number of observations = 943, Fixed effects coefficients = 2, Random effects coefficients = 14), and choice-related activity (Number of observations = 520, Fixed effects coefficients = 2, Random effects coefficients = 10, Covariance parameters = 3). The table shows the fixed effects of the coefficient estimates, STE, T-statistic, degrees of freedom, p-values (corrected for multiple comparisons with Bonferroni-correction) and the upper and lower CI of the effect of age on the onset latency of discrimination, duration of discrimination, and maximal neuronal discrimination (AUC). Each model also included random effect coefficients of each mouse, and recording per mouse. P-values for were adjusted with post-hoc tests using Bonferroni-correction (see methods, equation 9). Model structures: onset latency (ms) ~age + (1|Mouse ID) + (1| Recording ID); duration (ms) ~age + (1|Mouse ID) + (1| Recording ID); maximal discriminability (AUC) ~age + (1|Mouse ID) + (1| Recording ID).
| Stimulus easy | |||||||
|---|---|---|---|---|---|---|---|
| Fixed effects | Estimate | STE | T-statistic | DF | P-value | CI lower | CI upper |
| Intercept | 163.6104 | 7.9457 | 20.591 | 518 | 6.29587E-69 | 148.0009 | 179.2199 |
| Onset (ms) | –29.7978 | 9.7626 | –3.0523 | 518 | 0.00716101 | –48.9765 | –10.6191 |
| Intercept | 216.2921 | 13.2858 | 16.2799 | 518 | 5.15393E-48 | 190.1919 | 242.3924 |
| Duration (ms) | 63.2599 | 16.3499 | 3.8691 | 518 | 0.000369146 | 31.1401 | 95.3796 |
| Intercept | 0.6035 | 0.007 | 85.6404 | 518 | 0.0001 | 0.5897 | 0.6174 |
| Max AUC | 0.0186 | 0.0049 | 3.7564 | 518 | 0.0001 | 0.0088 | 0.02841 |
| Stimulus hard | |||||||
| Fixed Effects | Estimate | STE | T-Statistic | DF | P-Value | CI lower | CI upper |
| Intercept | 151.1905 | 5.4684 | 27.6479 | 535 | 3.6685E-123 | 140.4588 | 161.9222 |
| Onset (ms) | –35.3357 | 7.1998 | –4.9079 | 535 | 3.25392E-06 | –49.4651 | –21.2063 |
| Intercept | 220.614 | 8.4357 | 26.1525 | 535 | 2.8344E-113 | 204.0591 | 237.1689 |
| Duration (ms) | 55.6268 | 11.1065 | 5.0085 | 535 | 1.9647E-06 | 33.8305 | 77.4231 |
| Intercept | 0.5821 | 0.0034 | 170.2777 | 535 | 0.0001 | 0.5754 | 0.5888 |
| Max AUC | 0.02013 | 0.0048 | 4.1119 | 535 | 4.5413e-05 | 0.0105 | 0.0297 |
| Choice | |||||||
| Fixed Effects | Estimate | STE | T-Statistic | DF | P-Value | CI lower | CI upper |
| Intercept | 174.5856 | 8.259 | 21.139 | 518 | 1.6732E-71 | 158.3605 | 190.8108 |
| Onset (ms) | –24.3644 | 10.2288 | –2.3819 | 518 | 0.052746707 | –44.4595 | –4.2693 |
| Intercept | 228.1768 | 12.92 | 17.6607 | 518 | 1.64628E-54 | 202.7947 | 253.5589 |
| Duration (ms) | 82.0002 | 16.0017 | 5.1245 | 518 | 1.26556E-06 | 50.564 | 113.4363 |
| Intercept | 0.5491 | 0.0027 | 200.1358 | 518 | 0.0001 | 0.5437 | 0.5545 |
| Max AUC | 0.01660 | 0.0034 | 4.8959 | 518 | 3.92843E-06 | 0.01 | 0.0233 |
Table 3
The effect of age, learning and task difficulty on the latency, duration, and ability to discriminate tones in ACx neurons.
Linear mixed effect models of the effect of age, learning, and task difficulty on onset-latency of discrimination, duration of discrimination and maximal discriminability (Number of observations = 2590,, Fixed effects coefficients = 8, Random effects coefficients = 20, Covariance parameters = 3). The table shows the fixed effects of the coefficient estimates, STE, T-statistic, degrees of freedom, p-values (corrected for multiple comparisons with Bonferroni-correction), and the upper and lower CI. The model also includes random effects coefficients of each mouse (adolescent novice = 3, adult novice = 3, adolescent expert = 5, adult expert = 6) and recording per mouse (n=3). P-values were adjusted with post-hoc tests using Bonferroni correction (see methods, equation 10). Model structures: onset latency (ms) ~age* learning * difficulty + (1|Mouse ID) + (1| Recording ID); duration (ms) ~age* learning * difficulty + (1|Mouse ID) + (1| Recording ID); maximal discriminability (AUC) ~age* learning * difficulty + (1|Mouse ID) + (1| Recording ID).
| Fixed Effects | |||||||
|---|---|---|---|---|---|---|---|
| Onset latency (ms) | Estimate | STE | T-statistic | DF | P-value | CI lower | CI upper |
| Intercept | 92.6519 | 3.8909 | 23.8125 | 2582 | 5.4024E-113 | 85.0223 | 100.2815 |
| Age | –22.6378 | 5.0624 | –4.4718 | 2582 | 2.42782E-05 | –32.5645 | –12.7111 |
| Learning | 5.6206 | 8.7235 | 0.6443 | 2582 | 0.9999 | –11.4851 | 22.7263 |
| Task difficulty | 0.8813 | 5.4571 | 0.1615 | 2582 | 0.9999 | –9.8194 | 11.5819 |
| Age- Learning | –6.8831 | 11.1114 | –0.6195 | 2582 | 0.9999 | –28.6713 | 14.905 |
| Age - Difficulty | 0.2461 | 7.2185 | 0.0341 | 2582 | 0.9999 | –13.9085 | 14.4006 |
| Learning - Difficulty | –2.5145 | 12.3257 | –0.204 | 2582 | 0.9999 | –26.6837 | 21.6546 |
| Age-Learning-Difficulty | 4.4526 | 15.7691 | 0.2824 | 2582 | 0.9999 | –26.4688 | 35.374 |
| Fixed Effects | |||||||
| Duration of Discrimination(ms) | Estimate | STE | T-Statistic | DF | P-Value | CI lower | CI upper |
| Intercept | 299.7098 | 7.8305 | 38.2747 | 2582 | 8.4469E-254 | 284.3551 | 315.0645 |
| Age | 63.2136 | 9.2513 | 6.833 | 2582 | 3.1017E-11 | 45.0729 | 81.3544 |
| Learning | –88.8699 | 15.9421 | –5.5745 | 2582 | 8.21813E-08 | –120.1306 | –57.6092 |
| Task difficulty | –53.9606 | 9.9745 | –5.4098 | 2582 | 2.06623E-07 | –73.5194 | –34.4017 |
| Age- Learning | –30.6998 | 20.3155 | –1.5112 | 2582 | 0.3926 | –70.5361 | 9.1365 |
| Age - Difficulty | –18.8772 | 13.194 | –1.4307 | 2582 | 0.4579 | –44.749 | 6.9947 |
| Learning - Difficulty | 53.8178 | 22.5289 | 2.3888 | 2582 | 0.0509 | 9.6414 | 97.9943 |
| Age-Learning-Difficulty | 12.9698 | 28.823 | 0.45 | 2582 | 0.9999 | –43.5488 | 69.4884 |
| Fixed Effects | |||||||
| Maximal Discrimination (AUC) | Estimate | STE | T-statistic | DF | P-value | CI lower | CI upper |
| Intercept | 0.6278 | 0.0042 | 148.636 | 2582 | 0.0001 | 0.6195 | 0.6361 |
| Age | 0.024 | 0.0056 | 4.2953 | 2582 | 5.42797E-05 | 0.0131 | 0.035 |
| Learning | –0.0249 | 0.0096 | –2.5859 | 2582 | 0.029303232 | –0.0438 | –0.006 |
| Task difficulty | –0.0438 | 0.006 | –7.24 | 2582 | 1.76807E-12 | –0.0556 | –0.0319 |
| Age- Learning | –0.03 | 0.0123 | –2.4376 | 2582 | 0.0446 | –0.0541 | –0.0059 |
| Age - Difficulty | –0.0023 | 0.008 | –0.2846 | 2582 | 0.9999 | –0.0179 | 0.0134 |
| Learning - Difficulty | 0.0394 | 0.0136 | 2.8893 | 2582 | 0.0116 | 0.0127 | 0.0662 |
| Age-Learning-Difficulty | –0.0094 | 0.0175 | –0.5387 | 2582 | 0.9999 | –0.0437 | 0.0248 |
Additional files
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MDAR checklist
- https://cdn.elifesciences.org/articles/106387/elife-106387-mdarchecklist1-v1.docx
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Supplementary file 1
Adolescent and adult mice exhibit different lick behavior in the task.
Linear mixed-effects models of the fixed effects of lick count (until reward or punishment delay), lick latency, cumulative discriminability (d’) (including the interaction effects of lick count and lick latency, lick count and d’, lick latency and d’, and lick latency, lick count and d’) during the minimal number of trials shared between all mice (148 trials; Number of observations = 1098, Fixed effects coefficients = 8, Random effects coefficients = 14, Covariance parameters = 3). Coefficient estimates, STE, T-statistic, degrees of freedom, p-values (adjusted for post-hoc multiple comparisons with Bonferroni method), lower and higher CI are listed in the table. The model includes random effects coefficients per mouse (11 mice in total) and 3 recordings per mouse (see methods, equation 8). Model structure: Lick Count ~ Group * Lick Latency * dprime + (1|Mouse ID) + (1|Recording ID).
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp1-v1.docx
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Supplementary file 2
Neuronal statistics in expert and novice recordings during task engagement.
Acquired single units, acquired tone-excited units (percentage of tone-excited units relative to total units) in the AUDd, AUDp, AUDv, and TEa of adolescent and adult mice in experts (top) and novice (bottom).
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp2-v1.docx
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Supplementary file 3
Adolescent and adult expert mice have distinct firing properties in different sub-regions.
Mean and standard error, mean effect size (robust Cohen’s D), lower and upper Confidence Interval (CI) and p-value (Wilcoxon rank-sum test, adjusted for multiple comparisons with Bonferroni method) of the average baseline FR (Hz), evoked FR (Hz), coefficient of variance of FR, latency to peak of maximal FR (ms), full-width-half maximum of peak FR (ms), minimal latency of first spike (ms), fraction of responsive trials, lifetime sparseness of all adolescent and adult neurons from tone-onset to 50 ms after tone offset across all stimuli in AUDd, AUDp, and AUDv, and TEa (significant p-values are highlighted in bold).
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp3-v1.docx
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Supplementary file 4
Adolescent and adult firing properties of expert mice are distinct between different sub-regions.
P-values of Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons of the average baseline FR (Hz), evoked FR (Hz), coefficient of variance of FR, latency to peak of maximal FR (ms), full-width-half maximum of peak FR (ms), minimal latency of first spike (ms), fraction of responsive trials, lifetime sparseness of all adolescent and adult neurons from tone-onset to 50 ms after tone offset across all stimuli AUDd – AUDp, AUDd – AUDv, AUDd – TEa, AUDp – AUDv, AUDp – Tea, and AUDv –Tea (significant p-values are highlighted in bold).
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp4-v1.docx
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Supplementary file 5
Novice, adolescent, and adult mice have distinct firing properties in different sub-regions.
Mean and standard error (STE), mean effect size (robust Cohen’s D), lower and upper Confidence Interval (CI) and p-value (Wilcoxon rank-sum test, adjusted for multiple comparisons with Bonferroni method) of the average baseline FR (Hz), evoked FR (Hz), coefficient of variance of FR, latency to peak of maximal FR (ms), full-width-half maximum of peak FR (ms), minimal latency of first spike (ms), fraction of responsive trials, lifetime sparseness of all adolescent and adult neurons from tone-onset to 50 ms after tone offset across all stimuli in AUDd, AUDp, and AUDv, and TEa (significant p-values are highlighted in bold).
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp5-v1.docx
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Supplementary file 6
Adolescent and adult firing properties of novice mice are distinct between different sub-regions.
P-values of Kruskal-Willis Test after Tukey-Kramer correction for multiple comparisons of the average baseline FR (Hz), evoked FR (Hz), coefficient of variance of FR, latency to peak of maximal FR (ms), full-width-half maximum of peak FR (ms), minimal latency of first spike (ms), fraction of responsive trials, lifetime sparseness of all adolescent and adult neurons from tone-onset to 50 ms after tone offset across all stimuli AUDd – AUDp, AUDd – AUDv, AUDd – TEa, AUDp – AUDv, AUDp – Tea, and AUDv –Tea (significant p-values are highlighted in bold).
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp6-v1.docx
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Supplementary file 7
Neuronal statistics during passive FRA protocol in expert and novice mice.
Acquired single units, acquired tone-modulated units, and percentage of modulated units to all acquired units in the AUDd, AUDp, AUDv, and TEa of adolescent and adult mice during passive-listening recordings.
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp7-v1.docx
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Supplementary file 8
Adolescent and adult mice have distinct firing properties across different sub-regions of ACx—passive listening.
Mean and standard error, mean effect size (robust Cohen’s D), lower and upper Confidence Interval (CI) and p-value (Wilcoxon rank-sum test) of the average baseline FR (Hz) (AUDp vs. AUDv: adolescent p = 0.8551; adult p = 0.9711), evoked FR (Hz) (AUDp vs. AUDv: adolescent p = 0.4125; adult p = 0.9954), coefficient of variance of FR (AUDp vs. AUDv: adolescent p = 0.4354; adult p = 0.8800), latency to peak of maximal FR (ms) (AUDp vs. AUDv: adolescent p = 0.5871; adult p = 0.9985), full-width-half maximum of peak FR (ms) (AUDp vs. AUDv: adolescent p = 0.7223; adult p = 0.4628), minimal latency of first spike (ms) (AUDp vs. AUDv: adolescent p = 0.5936; adult p = 0.5669), fraction of responsive trials (AUDp vs. AUDv: adolescent p = 0.3838; adult p = 0.9924), lifetime sparseness (AUDp vs. AUDv: adolescent p = 0.3792; adult p = 0.9341) of all adolescent and adult neurons from tone-onset to 50 ms after tone offset across all stimuli in AUDp, and AUDv (significant p-values are highlighted in bold).
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp8-v1.docx
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Supplementary file 9
Overview of datasets analyzed.Number of mice, recordings, and neurons per learning stage (left: expert, right: novice) for every figure.
- https://cdn.elifesciences.org/articles/106387/elife-106387-supp9-v1.docx
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Age and learning shapes sound representations in auditory cortex during adolescence
eLife 14:RP106387.
https://doi.org/10.7554/eLife.106387.4
