Abstract
Perceptual decisions are based on the activity of sensory cortical neurons, but how organisms learn to transform this activity into appropriate actions remains unknown. Projections from the auditory cortex to the auditory striatum carry information that drives decisions in an auditory frequency discrimination task1. To assess the role of these projections in learning, we developed a channelrhodopsin-2-based assay to probe selectively for synaptic plasticity associated with corticostriatal neurons representing different frequencies. Here we report that learning this auditory discrimination preferentially potentiates corticostriatal synapses from neurons representing either high or low frequencies, depending on reward contingencies. We observe frequency-dependent corticostriatal potentiation in vivo over the course of training, and in vitro in striatal brain slices. Our findings suggest a model in which the corticostriatal synapses made by neurons tuned to different features of the sound are selectively potentiated to enable the learned transformation of sound into action.
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Acknowledgements
We thank B. Burbach for technical help, R. Eifert for mechanical material support, and J. Cohen for training the rats. AAV-CAGGS-ChR2–Venus was provided by K. Svoboda. We thank U. Livneh and A. Reid for discussions. This work was supported by grants (R01DC012565 and R01NS088649) from the National Institutes of Health and the Swartz Foundation (A.M.Z.).
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Q.X., P.Z., and A.M.Z. designed the experiments; Q.X. performed the experiments; Q.X., P.Z., and A.M.Z. analysed the data and wrote the manuscript.
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Extended data figures and tables
Extended Data Figure 1 Corticostriatal projections from auditory cortex to striatum.
a, Coronal view for the location in the striatum that receives auditory cortical inputs. b, Confocal image of auditory cortical axon terminals expressing ChR2–Venus in the striatum. Scale bars, 2 mm.
Extended Data Figure 2 Slope measurement for ChR2-LFP and GABAergic (γ-aminobutyric-acid-mediated) synaptic transmission does not contribute to the CHR2-LFP slope in vivo.
a, Raw ChR2-LFP traces (left) were normalized to the amplitude of their corresponding early component (Ai). The normalization factor Ai was determined as the peak of the raw trace in the time window (W1) between 0.5 and 1.2 ms after light stimulation onset. b, The rising phase of the late component of ChR2-LFP (in a time window W2 defined by rise from 10% to 90% of the peak P) was fitted linearly, and the slope of the fit was used for the quantification of ChR2-LFP. c, Left: ChR2-LFP before (black traces) and after (orange traces) picrotoxin application (20 mM, 5 μl). Raw traces are averaged traces from 60–80 trials at each condition (upper row). Normalized traces are raw traces normalized to their peaks of first components (as illustrated in a). Right: slopes measured from normalized traces in control and picrotoxin conditions for each recording before and after picrotoxin application (P = 0.8, paired signed-rank test). Data are presented as mean ± s.e.m.
Extended Data Figure 3 ChR2-LFP depends on the presence of ChR2-expressing axons.
To rule out the possibility that the TTX-insensitive component of the light-evoked response resulted from a photoelectric or other artefact, rather than from ChR2-evoked currents, we assessed light-evoked responses in brain regions that did not express ChR2. a, Four independent recordings in the auditory striatum (red traces) which receives auditory cortical input (ChR2-expressing axons are present), and the overlying somatosensory cortex (black traces) which lacks auditory cortical input (ChR2-expressing axons are absent). Each pair of recordings is from the same tetrode/fibre bundle. The recordings indicate that the light artefact was negligible under our conditions. b, Comparison of the first component amplitude from each recording pair.
Extended Data Figure 4 Normalization procedure corrects for variation in light power in vivo (for in vitro data see Fig. 4d, e).
a, Example of ChR2-LFP recorded at different light levels. b, Normalized ChR2-LFP, the same example as in a. c, Slopes from five example recordings across 1–10 mW light level range (coloured symbols are examples shown in a and b). Grey lines are drawn from the mean values of each group. Together with the data shown in Fig. 4e, the normalization procedure thus minimizes fluctuations in the response arising from artefactual changes in the number of recruited fibres, but preserves changes arising from actual increases or decreases in synaptic efficacy.
Extended Data Figure 5 Quantification of corticostriatal projection topography.
a, Normalized red and green fluorescence intensities measured across the tonotopic axis from the image shown in Fig. 4a. b, Mean red:green intensity ratio across the tonotopic axis (n = 3 sections from two rats). Shading, s.e.m.
Extended Data Figure 6 ChR2-LFP slope does not vary systematically across the tonotopic axis in naive rats.
a, ChR2-LFP slope map from three striatal slices (n = 3 rats). b, Quantification of the ChR2-LFP slope across the tonotopic axis. Data are mean ± s.e.m.
Extended Data Figure 7 Gradient of ChR2-LFP across the dorsoventral (non-tonotopic) axis showed no difference between the two training groups.
a, Averaged ChR2-LFP slopes with position along the tonotopic axis for LowRight and LowLeft groups (seven rats from each group). b, Individual gradients of ChR2-LFP across the dorsoventral axis from LowRight and LowLeft groups (P = 0.22, paired t-test).
Extended Data Figure 8 Model showing how corticostriatal potentiation could mediate task acquisition.
a, In the naive rat, the strength of corticostriatal connections does not depend on their frequency preference. b, Training to associate low stimuli with rightward choices and high stimuli with leftward choices (LowRight) selectively potentiates corticostriatal synapses tuned to low frequencies in the left hemisphere and corticostriatal synapses tuned to high frequencies in the right hemisphere. Thus, in the trained rat, low stimuli drive rightward choices and high stimuli drive leftward choices.
Extended Data Figure 9 To exclude the possibility that spiking responses affected the ChR2-LFP measurement, we analysed the data after median or lowpass filtering.
a, Single trial (upper rows) and average (bottom row) examples of unfiltered, median filtered, and Butterworth lowpass filtered responses. Average traces are presented as mean values (black traces) with 95% confidence intervals (grey shading). b, ChR2-LFP examples in Fig. 2a with different filter settings. c, ChR2-LFP measurements from examples shown in Fig. 2a at different filter settings.
Extended Data Figure 10 Changes in ChR2-LFP could result from variation in response timing precision.
To rule out this possibility we compared slopes measured from single trial and mean responses. a, Single trial responses (left) and slopes measured from individual trials and mean response (right) at a weakly light-responsive site. b, An example robustly responsive site. c, Comparison of mean slopes from single trial responses and slopes quantified from mean responses.
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Xiong, Q., Znamenskiy, P. & Zador, A. Selective corticostriatal plasticity during acquisition of an auditory discrimination task. Nature 521, 348–351 (2015). https://doi.org/10.1038/nature14225
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DOI: https://doi.org/10.1038/nature14225
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