Cover ArticleResearch Articles, Systems/Circuits

Effective Regulation of Auditory Processing by Parvalbumin Interneurons in the Tail of the Striatum

Xuan Li, Jiapeng You, Yidi Pan, Changbao Song, Haifu Li, Xuying Ji and Feixue Liang
Journal of Neuroscience 31 January 2024, 44 (5) e1171232023; https://doi.org/10.1523/JNEUROSCI.1171-23.2023

Abstract

Parvalbumin (PV) interneurons in the auditory cortex (AC) play a crucial role in shaping auditory processing, including receptive field formation, temporal precision enhancement, and gain regulation. PV interneurons are also the primary inhibitory neurons in the tail of the striatum (TS), which is one of the major descending brain regions in the auditory nervous system. However, the specific roles of TS-PV interneurons in auditory processing remain elusive. In this study, morphological and slice recording experiments in both male and female mice revealed that TS-PV interneurons, compared with AC-PV interneurons, were present in fewer numbers but exhibited longer projection distances, which enabled them to provide sufficient inhibitory inputs to spiny projection neurons (SPNs). Furthermore, TS-PV interneurons received dense auditory input from both the AC and medial geniculate body (MGB), particularly from the MGB, which rendered their auditory responses comparable to those of AC-PV interneurons. Optogenetic manipulation experiments demonstrated that TS-PV interneurons were capable of bidirectionally regulating the auditory responses of SPNs. Our findings suggest that PV interneurons can effectively modulate auditory processing in the TS and may play a critical role in auditory-related behaviors.

Significance Statement

Parvalbumin (PV) interneurons are one of the main inhibitory cell types in the tail of the striatum (TS), even though they are relatively scarce. Currently, it remains unclear whether or to what extent these neurons contribute to auditory processing in the TS. Here, we demonstrated that optogenetic manipulation of PV neuron activity significantly altered the auditory responses of spiny projection neurons (SPNs), providing valuable insights into the role of the TS-PV interneurons in auditory processing and their potential role in auditory-related behaviors.

Introduction

The striatum is the main structure of the basal ganglia, receiving cortical and subcortical input and modulating behavior in response to this integrated information (Kemp and Powell, 1971; Buchwald et al., 1973; Berendse and Groenewegen, 1990; Zheng and Wilson, 2002). As an additional domain of the dorsal striatum (Valjent and Gangarossa, 2021), the tail of the auditory striatum (TS) plays a critical role in auditory information discrimination (Chen et al., 2022), decision making (Chang et al., 2002), and defensive behavior (Z. Li et al., 2021), which receives auditory input from both the thalamus and auditory cortex (AC; Chen et al., 2019; Ponvert and Jaramillo, 2019).

In the striatum, the SPNs account for 95% of all neurons as the only output neurons (Ding et al., 2008; Rothwell et al., 2015). In addition, the striatum contains various interneurons, such as parvalbumin (PV)-expressing fast-spiking interneurons (FSIs), low-threshold spiking interneurons (LTSIs), and cholinergic neurons (ChINs). PV interneurons constitute only 1% of all striatal neurons, but they are critical for inhibitory control over striatal output since they provide feedforward inhibition of SPNs through divergent output and mutual electrotonic coupling (Gerfen et al., 1985; Koós and Tepper, 1999; Kita et al., 1990; Sciamanna et al., 2015). Research has recently focused on the participation of the majority of striatal PV interneurons in motor-related processes, and malfunction of these neurons is associated with numerous motor diseases, including Tourette’s syndrome, dystonia, and Huntington’s disease (Plotkin and Surmeier, 2015; Xu et al., 2016).

Cortical PV interneurons play a critical function in information processing, especially in the AC, affecting the information generated and transmitted within and between cortical neuronal populations (Yuste, 2015). PV interneurons exhibit a strong response to sound onset, providing rapid, transient inhibitory signals to pyramidal neurons (PNs) that modulate frequency tuning (Natan et al., 2017; Liang et al., 2019). However, the role of PV interneurons in the TS in sensory information processing, particularly auditory processing, remains unknown.

In this study, we first compared the distribution and anatomical features of PV interneurons in the TS (TS-PV interneurons) and AC (AC-PV interneurons). The results showed that TS-PV interneurons were sparsely distributed but had longer nerve fibers. The patch clamp results confirmed that TS-PV interneurons could form synaptic connections with a wider range of SPNs, and PV interneurons received auditory input from two upstream auditory nuclei: the MGB (the main input source) and the AC. Subsequently, through optogenetics combined with in vivo electrophysiological recordings, we found that TS-PV interneurons exhibit high-fidelity auditory responses similar to those of AC-PV interneurons. Furthermore, TS-PV interneurons can influence striatal auditory output by providing inhibitory regulation of SPN activity. Our research suggests the potential of TS-PV interneurons in auditory processing and behavior.

Materials and Methods

Animals

All experimental procedures in this study were approved by the Institutional Animal Care and Use Committee of the Southern Medical University. Male and female wild-type C57BL/6J and transgenic, PV-Cre, PV-Cre::Ai14, and PV-Cre::Ai14::Ai32 mice from Jackson Laboratory were used in this study. The animals were kept in a vivarium with a 12 h light/dark cycle.

Viral injection

Viral injections were performed as we previously described (Liang et al., 2015; Wu et al., 2023). Adult PV-Cre and PV-Cre::Ai14 mice were anesthetized with 1.5% isoflurane. A small incision was made on the skin covering the TS (AP: 1.58 mm, ML: 3.2 mm, DV: 2.6 mm, relative to the bregma), AC (AP: 3.0 mm, ML: 4.5 mm, DV: 0.6 mm, relative to the bregma), or MGB (AP: 3.16 mm, ML: 1.99 mm, DV: 2.5 mm, relative to the bregma), and a craniotomy of a small hole (0.5 mm diameter) was drilled. Specific adeno-associated viruses (AAVs) encoding ChR2 or ArchT were applied depending on the purpose of the experiments and mouse strain: AAV-EF1a-hChR2(H134R)-EYFP (WZ Biosciences, t ≥ 1013 vg/ml), AAV-EF1a-DIO-hChR2(H134R)-EYFP (WZ Biosciences, t ≥ 1013 vg/ml), or AAV-EF1a-DIO-ArchT-EYFP (WZ Biosciences, t ≥ 1013 vg/ml). The virus was delivered using a beveled glass micropipette (tip diameter: ∼30–40 µm) attached to a microsyringe pump (World Precision Instruments). Each injection consisted of a 100 nl volume of virus delivered at a rate of 20 nl/min. After each injection, the pipette was left in place for 5 min before being withdrawn, and the scalp was sutured. After the surgery, a subcutaneous injection of 0.1 mg/kg buprenorphine was administered. Mice were allowed to recover for at least 3 weeks.

Awake animal preparation for recordings

For awake recordings, mice were anesthetized with 1.5% isoflurane (vol/vol), and screws were fixed to the skull surface with dental cement. After recovering from anesthesia, the mouse was trained to become habituated to head fixation. A specifically designed post holder was used to firmly secure the head by tightening the screw. On the recording day, the mouse was briefly anesthetized with isoflurane. A craniotomy was then performed over the TS or AC region. The animal was given at least 1 h to recover from the effects of the anesthesia before the recording sessions began. Each recording session lasted ∼4 h and took place in a soundproof room. The animal received drops of 5% glucose through a pipette each hour.

Sound generation

The sound stimulation software used in the study was specifically developed using LabVIEW (National Instruments, http://www.ni.com; RRID: SCR_014325). Pure-tone stimuli (2–64 kHz spaced at 0.1 octave, 50 ms duration, 3 ms ramp, 0–70 dB SPL spaced at 10 dB, in pseudorandom sequence, 3 repetitions, 0.5 s interstimulus interval) were delivered through a calibrated speaker (Tucker-Davis Technologies) to the contralateral ear.

In vivo loose-patch recordings

Loose-patch recordings were conducted using an Axopatch 200B amplifier (Molecular Devices) as previously described (Li et al., 2019; Liang et al., 2019; H. Li et al., 2021). For AC recordings, our main focus was on the primary AC. To premap AC and to locate A1, multiunit spikes were recorded with parylene-coated tungsten microelectrodes (2 MΩ; FHC) at 500–600 µm below the pia. The preliminary tonal receptive field (TRF) was plotted online to identify the characteristic frequency (CF) of the recording site, and A1 location was determined by the anterior–posterior tonotopic gradient (from high to low frequency). For TS recordings, the recording site was determined by the brain atlas. The patch pipette, controlled by a micromanipulator (Siskiyou), was inserted into the TS or the AC at the same angle as in multiunit recordings. The patch pipette, with a resistance of 5−7 MΩ, was filled with artificial cerebral spinal fluid (ACSF; 124 mM NaCl, 1.2 mM NaH2PO4, 2.5 mM KCl, 25 mM NaHCO3, 20 mM glucose, 2 mM CaCl2, 1 mM MgCl2). A seal with a resistance of 100–250 MΩ was formed on the targeted neuron. The pipette capacitance was fully compensated, and spikes were recorded under voltage-clamp mode with a ,nd potential applied to achieve a zero-baseline current. Signals were recorded in voltage-clamp mode at a sampling rate of 20 kHz. Neurons that did not display spontaneous spikes within a 10 min period were excluded from further recording.

Optogenetically guided in vivo cell-attached recordings from PV interneurons

To record TS-PV interneurons, an optical fiber (NA = 0.6, RWD) connected to an LED light source (470 nm, Thorlabs) was implanted 0.9 mm below the cortical surface (AP: 1.58 mm, ML: 4.15 mm), and the fiber was positioned at a 50° angle relative to the horizontal plane to maximize the light stimulation range of the TS. The implantations were performed in mice anesthetized with 1.5% isoflurane, and fibers were mounted to the head-fixation apparatus with dental cement. Similarly, to record AC-PV interneurons, an optic fiber connected to a blue LED source was positioned close to the cortical surface of the recording site. On the day of recording, loose-patch recordings using pipettes were performed in the TS (AP: 1.58 mm, ML: 3.2 mm, DV: ranging from 2.8 mm to 3.1 mm relative to the bregma) or AC (AP: 3.0 mm, ML: 4.5 mm, DV: ranging from 0 mm to 1.0 mm relative to the bregma). TS-PV and AC-PV interneurons were identified by inducing spikes through ChR2 activation. By placing a 470 nm optical fiber in the recording region, PV neurons could be stimulated to generate spikes during loose-patch recording with blue light stimulation (Liang et al., 2019).

Optogenetically suppressing or activating TS-PV interneurons

The suppression and activation of PV interneurons were performed in different animals. Suppression of PV interneurons was performed with mice expressing an AAV encoding ArchT. The fiberoptic patch cord (200 mm, Thorlabs) was implanted on the surface of the TS, with the fiber angled at 50° relative to the horizontal plane (as mentioned above), and PV interneurons were inhibited with amber LED light (565 nm, 500 ms duration). Activation of PV interneurons was performed in mice expressing AAV encoding ChR2. Blue LED light (470 nm) was delivered through the fiberoptic patch cord (200 mm, Thorlabs) to stimulate PV interneurons. After the experiment, brain slices were imaged using a fluorescence microscope (A1R-si, Nikon) to verify virus expression with reference to the Stereotaxic Brain Atlas of Mice. Only the data with accurate expression were included in further analysis.

Slice preparation

Virus-injected mice were anesthetized with pelltobarbitalum natricum. After decapitation, the brain was rapidly removed and placed into ice-cold oxygenated dissection buffer (60 mM NaCl, 3 mM KCl, 1.25 mM NaH2PO4, 25 mM NaHCO3, 115 mM sucrose, 10 mM glucose, 7 mM MgCl2, 0.5 mM CaCl2; bubbled with 95% O2 and 5% CO2; pH = 7.4). Brain slices containing the TS or AC regions were cut in the coronal plane using a vibrating microtome (Leica VT1200 s) to a thickness of 300 µm. After incubation for more than 30 min in warmed ACSF (35°C), the slice was transferred to the recording chamber at room temperature.

Electrophysiological recording

Recording was conducted using an upright fluorescence microscope (Eclipse FN1, Nikon) equipped with an infrared light source. Before slice recording, the confirmation of ChR2 expression location was achieved by applying 470 nm blue light to A1 under a 4× objective to observe the fluorescence expression of A1. Brain slices with accurate expression locations were selected for recording. Whole-cell voltage-clamp recordings were selectively performed on PV interneurons and SPNs in the TS or PNs in the AC using epifluorescence imaging and a 60× objective. Fluorescence-labeled PV interneurons were identified in the recordings of PV-Cre::Ai14 mice. SPNs were identified due to their widespread distribution and distinct firing characteristics, which differ significantly from the fast spiking of PV interneurons. During recording, tetrodotoxin (TTX; a sodium channel blocker, 1 µM) and 4-aminopyridine (a potassium channel blocker, 1 mM) were applied in the bath solution to isolate monosynaptic responses. The glass pipette (7–10 MΩ impedance) used for recording was filled with a potassium-based internal solution (125 mM K+-gluconate, 10 mM HEPES, 10 mM EGTA, 4 mM Mg-ATP, 0.3 mM GTP, 2 mM KCl, 0.1 mM CaCl2, 8 mM phosphocreatine sodium; pH = 7.2). Excitatory postsynaptic currents (EPSCs) and inhibitory postsynaptic currents (IPSCs) were recorded by clamping the membrane potential of the cell at −70 and 0 Mv, respectively. Signals were recorded with an Axopatch 700B amplifier (Molecular Devices), filtered at 2.8 kHz and sampled at 10 kHz. Multiple neurons were recorded in each slice. The morphologies of recorded cells were reconstructed through histological procedures including biocytin labeling. To investigate the input from PV interneurons to SPNs at different depths within the TS, we first determined the full depth of the TS in the brain slice by micromanipulator measurement (Sutter) and then measured the depth of the recording neuron in the TS after recording. To compare multiple brain slices, we normalized these values by dividing by the total length of the TS in the recorded brain slices and calculated the depth of recorded neurons after normalization to obtain the SPN response distribution. To achieve flexible adjustment of spot size and stimulation position, the Polygon 400 (Mightex Systems) was employed. It serves as a high-precision spatial illuminator with a built-in 470 nm LED, providing not only full-field light stimulation but also the ability to adjust the size of the light stimulus at any desired location within the field of view (Lee et al., 2013; De Marco et al., 2015; Tuncdemir et al., 2016).

Channelrhodopsin-assisted circuit mapping

In channelrhodopsin-assisted circuit mapping (CRACM) experiments, we utilized a Polygon 400 to deliver a 470 nm blue light stimulus. The 470 nm stimulus spot was set to a size of 150 × 100 µm and was moved along the vertical column of the TS or AC where the recorded cell body was located, with no gap between the light spots. The IPSCs of the same neuron were recorded at different vertical depths in the TS or AC. The total area of stimulation was set to 150 × 1,800 µm for the TS and 150 × 1,000 µm for the AC, ensuring that the entire vertical region of the TS or AC was stimulated. The LED intensity remained constant at each stimulus location throughout the experiment. A 5 ms LED pulse was utilized, resulting in an effective power of 2.3 mW/mm. Each stimulus was repeated 10 times, with a 30 s interval between trials.

Histology

During whole-cell recording, 0.1% biocytin was added to the internal solution, and stable recordings were obtained for at least 15–20 min. The slices were immersed in 4% PFA at 4°C overnight. Then, the slices were washed 3 times in PBS, placed in PBS with 0.3% Triton X-100 for 3 h, and agitated at room temperature. After being washed 3 times in PBS, each brain slice was immersed in 500 µl of streptavidinCy3 (dilution ratio of 1:200) overnight. Slices were placed into glass slides and sealed with transparent nail polish.

Morphological quantification

Individual high-magnification images of AC-PV and TS-PV interneurons were morphologically reconstructed by Photoshop. The Simple Neurite Tracer plugin and region function of ImageJ (Fiji, https://fiji.sc/; RRID: SCR_002285) were used to elucidate the cell morphology of these neurons (Longair et al., 2011), including calculation of soma area, number of branches, and Sholl analysis metrics (Sholl, 1953).

Data analysis

We utilized MATLAB (http://www.mathworks.com/; RRID: SCR_001622), with a custom-developed script, to conduct our data analysis. To quantify evoked firing rates, the average baseline firing rate was calculated within a 50 ms window preceding the onset of sounds and subtracted from recordings during sound stimulus presentation. Evoked responses were defined as firing rates exceeding the average baseline firing rate by 3 standard deviations. The evoked firing rates were compared between LED-on and LED-off conditions at 70 dB. Linear regression fitting was used to analyze the evoked firing rates in each group with and without activity manipulation based on the average measurements across the neurons. For tone-driven spike rates, the frequency–intensity space was upsampled 3 times along the frequency and intensity dimensions only for visualization purposes. The measurements of TRF parameters were made from the raw data. Boundaries of the spike TRF were determined following previous studies. The bandwidth of the TRF was determined as the total frequency range for effective tones at 60 dB. Neurons that did not exhibit evoked spiking responses were excluded from the analysis.

Statistical analysis

Our statistical analysis was performed in Origin (Origin Lab). Error bars in all figures represent the standard error of the mean (SEM). If unpaired data were normally distributed (according to the Shapiro‒Wilk test), a two-sample t test was employed to compare the data between two groups. Otherwise, the Mann‒Whitney U test was used to compare unpaired data between the two groups. Comparisons of normally distributed data recorded in pairs were between groups performed using a paired sample t test. Comparisons between nonnormally data recorded in pairs between groups were performed using the Wilcoxon signed-rank test. The significance was set at p < 0.05.

Results

Distribution quantity and morphological properties of TS-PV and AC-PV interneurons

To compare the distribution quantity and morphology of PV interneurons between the TS and AC, we first established PV-Cre::Ai14 mice to label PV interneurons with tdTomato (Fig. 1A,B). Fluorescence images revealed that PV interneurons in the TS were much sparser than those in the AC (Fig. 1A–C). By comparing the distribution density of PV interneurons in different layers of the AC (Fig. 1C, right), we found that more PV interneurons are present in layer 2/3 and layer 4. Therefore, our recordings of AC-PV interneurons were mainly performed in the supragranular layers. In Figure 1D (left panel), we presented examples of action potential patterns in TS-PV and AC-PV interneurons following current injection. By analyzing the relationship between the injected current and firing rate (Fig. 1D, right), we observed that, under the same injection current conditions, AC-PV interneurons exhibited higher firing rates overall (Fig. 1D, 100 pA: Z = −4.6274, p < 0.0001, Mann‒Whitney U test; 150 pA: Z = −4.25004, p < 0.0001, Mann‒Whitney U test; 200 pA: Z = −3.93913, p < 0.0001, Mann‒Whitney U test; 250 pA: Z = −3.9202, p < 0.0001, Mann‒Whitney U test; 300 pA: Z = −3.16832, p = 0.00153, Mann‒Whitney U test). Compared with pyramidal cells, PV interneurons had a shorter spike half-width (Fig. 1D, bottom right inset). We next utilized biocytin to reconstruct the morphology of PV interneurons in both brain regions with double confirmation by tdTomato labeling, as shown in Figure E. The processes and branches refer to dendrites. The morphology of PV interneurons between the TS and AC, in terms of the overall anatomical structure (Fig. 1E) and cell body area (Fig. 1G; t = −2.03989, p = 0.06761, two-sample t test), was very similar, while more branches and longer dendrites were observed in TS-PV interneurons compared with those in AC-PV interneurons (Fig. 1H,I; number of branches: t = 2.295205, p = 0.042388; dendritic length: t = 2.339, p = 0.039; two-sample t test). To provide a simplified quantification of the innervating range of TS-PV and AC-PV interneurons, we performed a Sholl analysis to investigate the dendritic differences by plotting the number of intersections with circles centered around the soma against the distance from the cell body (see Methods; Fig. 1F). The number of intersections in TS-PV interneurons was significantly greater than that in AC-PV interneurons (Fig. 1J).

Figure 1.
Figure 1.

Comparing the distribution density and morphological characteristics of PV interneurons between TS and AC. A, B, Fluorescence images show tdTomato-labeled PV interneurons (red) in TS (A) and AC (B). Scale bar, 100 µm. C, Left, distribution density of TS-PV (red) across coronal sections compared with that of AC-PV (black). Right, distribution density of AC-PV along cortical depth. Dotted lines indicate estimated boundaries between layers. D, Left, representative firing of TS-PV (top) and AC-PV (bottom) in response to increasing depolarizing currents (−50, 0, 150, and 250 pA). Right, summary plot of averaging firing rate per current step amplitude from TS-PV (red) and AC-PV (black), and an example of an AP recorded from a PV (red) and PN (gray) neurons. E, Biocytin-recovered morphologies of TS-PV (top) and AC-PV (bottom). Scale bar, 50 µm. F, Sholl analysis for an example TS-PV (top) and AC-PV (bottom). G, Comparison of the soma area between TS-PV (red) and AC-PV (black; TS-PV, 164.45 ± 9.77 µm2; AC-PV, 188.87 ± 6.91 µm2; p = 0.06761, two-sample t test, n = 7 and 6 cells, respectively). H, Comparison of the number of branches between TS-PV (red) and AC-PV (black; TS-PV, 26.57 ± 3.21; AC-PV, 18.17 ± 1.53; *p < 0.05, two-sample t test, n = 7 and 6 cells, respectively). I, Comparison of the dendritic length between TS-PV (red) and AC-PV (black; TS-PV, 217.00 ± 27.98 µm; AC-PV, 143.05 ± 9.36 µm; *p < 0.05, two-sample t test, n = 7 and 6 cells, respectively). J, Number of intersections from Sholl analysis plotted as a function of soma distance for TS-PV (red) and AC-PV (black), respectively. Error bar indicates SEM.

PV interneurons in the TS provide extensive inhibition to SPNs

Previous studies have shown that PV interneurons are the primary providers of feedforward and feedback inhibition in the AC (Li et al., 2014). However, considering the sparsely distributed nature of such neurons in the TS, it remains unclear whether PV interneurons can provide sufficient inhibitory input to SPNs. To address this question, we utilized adeno-associated virus (AAV) encoding Cre-dependent channelrhodopsin 2 (ChR2) in the TS of PV-Cre mice (Fig. 2A). In brain slice preparations, we performed whole-cell voltage-clamp recordings from putative SPNs in the TS (Fig. 2A) while simultaneously exposing the entire TS to blue light to optogenetically stimulate PV interneurons. We recorded monosynaptic inhibitory currents in response to the stimulation of PV interneurons. A 5 ms pulse of blue light elicited a clear inhibitory current in SPNs (Fig. 2B, SPNs: 50/53). We recorded SPNs at different depths in the TS, normalized values by dividing by the total length of the TS in the recorded brain slices, and calculated the depth of recorded neurons after normalization to obtain SPNs response distribution at different depths within the TS. SPNs within the standardized depth range of 0.45–0.85 exhibited more pronounced IPSC responses (Fig. 2C). Therefore, for subsequent experiments, we selected neurons located within this range for recording.

Figure 2.
Figure 2.

Innervation from PV interneurons to principal neurons in TS and AC. A, Schematic graph showing AAV-DIO-ChR2 injection into TS to label PV interneurons (left) and recordings from putative SPNs (right) in slices from PV-Cre mice. Blue light was applied onto the entire TS to stimulate PV interneurons with ChR2 expression. B, Left, fluorescence image of labeled PV interneurons in TS of a PV-Cre mouse. Scale,100 µm. Right, representative light-evoked monosynaptic inhibitory postsynaptic currents (IPSCs) by photoactivating PV interneurons recorded in SPNs of TS, a blue tick marks the onset of LED illumination (top). Scale bar, 20 pA and 25 ms. Pie graphs showing fraction of SPNs exhibiting light-evoked responses (bottom). C, Distribution of IPSCs peak amplitudes along normalized depth of TS. Each data point represents one neuron (n = 50 SPNs from four mice). The blue area inside the dashed line represents the primary response area, which is also the area for subsequent records. D, Schematic graph showing the distance-specific activation of PV interneurons in TS. Whole-cell voltage-clamp recording was made from putative SPNs, while stimulation with a series of 110 × 150 µm rectangular blue spot covers the TS region of the vertical cell body with no gaps between adjacent stimuli (top left). Representative traces (bottom left) and its topographic map (right) form an example putative SPN responses to the LED stimulation at different distance from the soma. Triangle showing the soma location of the recorded SPN. Dashed lines represent the boundaries of each stimulus. Scale bar, 20 pA and 30 ms. E, Similar to D but for PV-pyramidal innervation in AC. Top left, fluorescence image of labeled PV interneurons in AC of a PV-Cre mouse. Scale bar, 50 pA and 30 ms. F, Normalized peak amplitudes of light-evoked IPSCs plotted as a function of distance from the soma for putative SPNs in TS (red) and pyramidal neurons in AC (black), respectively. Error bar indicates SEM. G–I, Comparison of the distance of the 20% cutoff of IPSCs (H), peak amplitude of the maximum IPSC (I), and half-peak duration of the maximum IPSC (J) between recorded neurons of TS and those of AC (H: TS, 396.2 ± 20.91 µm, AC, 132.63 ± 9.78 µm,***p < 0.0001, two-sample t test, n = 10 and 11 cells, respectively; I: TS, 92.01 ± 15.39 pA, AC, 464.39 ± 58.56 pA, ***p < 0.0001, two-sample t test, n = 14 and 11 cells, respectively; J: TS, 61.71 ± 6.45 ms, AC, 26.71 ± 1.94 ms, ***p < 0.0001, two-sample t test, n = 14 and 11 cells, respectively).

We next investigated the distance of synaptic locations through which SPNs can receive inhibitory input from PV interneurons. Using a subcellular ChR2-assisted circuit diagram (sCRACM; Petreanu et al., 2009; Suter and Shepherd, 2015), we mapped the intensity of PV inhibitory innervation over the distance of the recorded SPNs in the TS. As a control, the same sCRACM was performed for PNs in the AC. For SPNs in the TS, the global map showed that PV inhibitory innervation was primarily concentrated in the soma of the recorded SPN, with a gradual decrease toward the distal part of the neuron (Fig. 2D). For the PNs in the AC, PV inhibitory innervation was also primarily concentrated in the soma but sharply decayed with distance (Fig. 2E). At the population level, the amplitude of IPSCs of both SPNs in the TS and PNs in the AC exhibited a monotonic decrease with increasing distance. However, the decay rate of IPSC amplitude in PNs was much higher than that in SPNs (Fig. 2F). This was further confirmed by the 20% cutoff value of the amplitude –distance curve (Fig. 2G; t = 11.774362, p < 0.0001, two-sample t test). In addition, the IPSC amplitude in SPNs was significantly lower than that in PNs (Fig. 2H; t = −7.112297, p < 0.0001, two-sample t test), while the half-peak duration of IPSCs exhibited the opposite pattern (Fig. 2I; t = 4.98163, p < 0.0001, two-sample t test). These results suggest that there are effective synaptic connections from PV interneurons to SPNs in the TS.

TS-PV interneurons receive more auditory input from the MGB than from the AC

Previous studies have indicated that the TS receives intensive innervation from both the MGB and AC (Chen et al., 2019). To investigate whether TS-PV interneurons receive auditory input from the MGB and AC, we first injected AAV-ChR2 into the AC of PV-Cre::Ai14 mice (Fig. 3A,B), verifying that the projection fibers received by the TS fully expressed ChR2 3–4 weeks after injection (Fig. 3C). We then performed whole-cell recording of tdTomato-labeled TS-PV interneurons in slice preparations while optogenetically activating the AC axon terminals with a 5 ms blue light pulse (Fig. 3D). As control experiments, we also examined the light-evoked response of putative SPNs in close vicinity (intersomatic distance <150 µm; Fig. 3D) and compared the firing pattern of PV interneurons and SPNs (Fig. 3E). Reliable EPSC responses were recorded in both SPNs and PV interneurons. Most SPNs received input from the AC (Fig. 3F, 80%, n = 24/30), while only some PV interneurons demonstrated this response (Fig. 3F, 47%, 15/32). Moreover, the amplitude of light-evoked EPSCs in PV interneurons were significantly smaller than that in SPNs in ACSF (Fig. 3F, Z = 2.34533, p = 0.01901, Mann‒Whitney U test). A monosynaptic response was obtained by applying TTX and 4-AP, resulting in a significant reduction in the response amplitude in both SPNs and PV interneurons (Fig. 3G,H; PV: Z = −2.9823, p = 0.00134, Wilcoxon signed-rank test; SPN: t = −3.62772, p = 0.0463, paired sample t test). Following the addition of TTX and 4-AP, the excitatory input provided by the AC to PV interneurons was weaker than that to SPNs, which aligns with the findings observed in ACSF (Fig. 3I; Z = 2.80899, p = 0.00497, Mann‒Whitney U test, PV: 33%, 22/66; SPN: 66%, 36/54).

Figure 3.
Figure 3.

Distribution of cortical axons and functional examination of AC-TS innervation. A, Schematic of AAV-CamkII-ChR2-EYFP injection in AC of a PV-Cre::Ai14 mouse. B, Fluorescence image showing AAV-ChR2-EYFP expression at the injection site. Scale bar, 100 µm. C, Left, EYFP-labeled AC axons in TS. Right, enlarged image of TS showing the fluorescent cortical axons (top) and the tdTomato-expressing PV neurons (bottom). Scale bar, 100 µm. D, Left, schematic of whole-cell recording from putative SPNs (blue) and PV interneurons (red) in TS with photoactivation of AC glutamatergic axons in a slice preparation. Right, image showing fluorescence of labeled PV (top) and unlabeled putative SPN (bottom) in TS. E, Fire frequency of PV interneurons (red) and SPNs (blue) elicited across a range of current injections (−150–550 pA), respectively. F, Left, comparison of peak EPSC amplitude of recorded neurons with ACSF between PV interneurons and SPNs (PV, 75.82 ± 15.73 pA, SPN, 160.57 ± 26.37 pA, **p < 0.01, Mann–Whitney U test, n = 32 and 30 cells, respectively). Right, pie graphs showing fraction of PV interneurons (left) and SPNs (right) exhibiting light-evoked responses with ACSF. G, EPSCs of example PV interneurons (top) and SPNs (bottom) evoked by a 5 ms pulse of blue light, recorded in the normal external solution and after perfusing in TTX and 4-AP. Scale bar, 100 pA and 20 ms. H, Comparison of peak EPSC amplitude of recorded PV interneurons and SPNs between before and after TTX and 4-AP perfusion, respectively (PV: before, 86.07 ± 22.63 pA, after, 31.83 ± 11.85 pA, **p < 0.01, Wilcoxon signed-rank test, n = 17 cells; SPN: before, 159.54 ± 38.66 pA, after, 105.89 ± 31.13 pA, **p < 0.01, paired sample t test, n = 11 cells). I, Left, comparison of peak EPSC amplitude of recorded neurons after TTX and 4-AP perfusion between PV interneurons and SPNs (PV, 43.25 ± 8.17 pA, SPN, 94.28 ± 15.55 pA, **p < 0.01, Mann–Whitney U test, n = 66 and 54 cells, respectively). Right, pie graphs showing fraction of PV interneurons (left) and SPNs (right) exhibiting light-evoked responses after TTX and 4-AP perfusion.

To explore MGB input to TS-PV interneurons, we next expressed ChR2 in MGB axons of PV-Cre::Ai14 mice (Fig. 4A–C) and performed whole-cell recording from both PV interneurons and SPNs in slice preparations (Fig. 4D–E). In ACSF, both SPNs and PV interneurons received excitatory input from the AC, and there was no significant difference in the response amplitudes between the two (Fig. 4F, Z = 0.02826, p = 0.97745, Mann‒Whitney U test; PV: 80%, 21/26; SPN: 88%, 22/25). Consistent with this result, after the addition of TTX and 4-AP, although the amplitude of monosynaptic EPSC responses decreased (Fig. 4G,H; PV: Z = −3.15219, p = 0.00162, Wilcoxon signed-rank test; SPN: Z = −2.86531, p = 0.00171, Wilcoxon signed-rank test), both types of neurons still received excitatory input from the AC and did not significantly differ (Fig. 4I; Z = 0.54671 p = 0.58458, Mann‒Whitney U test; PV: 72%, 50/69; SPN: 74%, 47/63). These results indicate that compared with AC-PV interneurons, more TS-PV interneurons receive input from the MGB.

Figure 4.
Figure 4.

Distribution of cortical axons and functional examination of MGB-TS innervation. A, Schematic of AAV-CamkII-ChR2-EYFP injection in MGB of a PV-Cre::Ai14 mouse. B, Fluorescence image showing AAV-ChR2-EYFP expression at the injection site. Scale bar, 100 µm. C, Left, EYFP-labeled MGB axons in TS. Right, enlarged image of TS showing the fluorescent cortical axons (top) and the tdTomato-expressing PV interneurons (bottom). Scale bar, 100 µm. D, Schematic of whole-cell recording from putative SPNs (blue) and PV interneurons (red) in TS with photoactivation of MGB glutamatergic axons in a slice preparation. E, Left, image showing fluorescence of labeled PV (top) and unlabeled putative SPN (bottom) in the TS. Right, biocytin-recovered morphologies of an example PV interneuron (top) and SPN (bottom). Scale bar, 50 µm. F, Left, comparison of peak EPSC amplitude of recorded neurons with ACSF between PV interneurons and SPNs (PV, 119.11 ± 18.54 pA, SPN, 122.55 ± 19.67 pA, p = 0.97745, Mann–Whitney U test, n = 26 and 25 cells, respectively). Right, pie graphs showing fraction of PV interneurons (left) and SPNs (right) exhibiting light-evoked responses with ACSF. G, EPSCs of example PV interneurons (top) and SPNs (bottom) evoked by a 5 ms pulse of blue light, recorded in the normal external solution and after perfusing in TTX and 4-AP. Scale bar, 50 pA and 20 ms. H, Comparison of peak EPSC amplitude of recorded PV interneurons and SPNs between before and after TTX and 4-AP perfusion, respectively (PV: before, 76.29 ± 14.89 pA, after, 35.55 ± 10.80 pA, ***p < 0.001, paired sample t test, n = 15 cells; SPN: before, 94.83 ± 23.04 pA, after, 51.55 ± 16.24 pA, **p < 0.01, Wilcoxon signed-rank test, n = 13 cells). I, Comparison of peak EPSC amplitude of recorded neurons after TTX and 4-AP perfusion between PV interneurons and SPNs (PV, 43.34 ± 5.13 pA, SPN, 56.50 ± 7.70 pA, p = 0.558458, Mann–Whitney U test, n = 69 and 63 cells, respectively). Right, pie graphs showing fraction of PV interneurons (left) and SPNs (right) exhibiting light-evoked responses after TTX and 4-AP perfusion.

The auditory response characteristics of PV interneurons were similar in the TS and AC

Since PV interneurons receive projections from upstream auditory nuclei, we proceeded to examine the auditory response characteristics of TS-PV interneurons. As a control, the auditory response characteristics of PV interneurons in the AC were also studied. We used PV-Cre mice crossed with Ai32 (Cre-dependent ChR2) and Ai14 (Cre-dependent tdTomato) reporter strains to optogenetically identify TS-PV interneurons with loose-patch recording (Fig. 5A,B). PV interneurons were identified based on their spike responses to pulses of blue LED light (see Methods; (Fig. 5C). To distinguish the spike waveforms of PV interneurons, we compared the spike waveforms of TS-PV interneurons, AC-PV interneurons, TS-SPNs, and AC-PNs. We found that both TS-PV interneurons and AC-PV interneurons exhibited comparable spike waveforms, which were significantly narrower than the spike waveforms of TS-SPNs and AC-PNs (Fig. 5D). We examined the tone-evoked spike responses of PV interneurons by presenting a range of pure-tone stimuli of varying frequencies and intensities (50 ms, 2–64 kHz, 0–70 dB SPL). The TRF and temporal response patterns of representative PV interneurons are shown in Figure 5E. The TRFs of both groups were broad, consistent with our previous observations (H. Li et al., 2021). A total of 33 out of 35 TS-PV interneurons and 65 out of 70 AC-PV interneurons exhibited a clear TRF (Fig. 5F), and similar evoked firing rates (Fig. 5G; Z = 0.53509, p = 0.804071, Mann‒Whitney U test), spontaneous firing rates (Fig. 5H; Z = −0.545001, p = 0.585753, Mann‒Whitney U test), BW20 (bandwidth at 20 dB above the intensity threshold; Fig. 5I; t = 1.343641, p = 0.182265, two-sample t test), and intensity thresholds (Fig. 5J; Z = −0.124401, p = 0.900998, Mann‒Whitney U test) were observed between the two groups. These characteristics indicate that the auditory response of TS-PV interneurons is comparable to that of AC-PV interneurons.

Figure 5.
Figure 5.

Auditory response in TS-PV and AC-PV. A, Schematic of optogenetics-guided TS-PV electrophysiological recording in vivo. B, Fluorescence image showing tdTomato-labeled PV interneurons (red) and the expression of ChR2-YFP (green) in a representative slice of a PV-Cre::Ai14::Ai32 mouse. Scale bar, 100 µm. C, Raster plot and PSTH for spike responses of a representative PV interneuron to 10 pulses of blue LED stimulation (marked by blue vertical lines). D, Plot of peak/trough amplitude ratio versus trough-to-peak interval for the spike waveforms (top inset) of recorded TS-PV (red), AC-PV (black), TS-SPN (blue), and AC-PN (gray), respectively. Each data point represents one cell. Scale bar, 0.5 ms. E, Color maps of TRF (top) and PSTHs (bottom) for best-tone-evoked spikes of example TS-PV (left two) and AC-PV (right two), respectively. Inset, spike waveform of the corresponding cell. Scale bar, 1 ms. F, Pie graphs showing proportion of TS-PV (top) and AC-PV (bottom) responding to tones. G–J, Comparison of evoked firing rate (G), spontaneous firing rate (H), TRF bandwidth at 20 dB above the intensity threshold (I), and intensity threshold (J) between TS-PV (red) and AC-PV (black; G: TS-PV, 115.23 ± 12.25 Hz, AC-PV, 115.35 ± 10.44 Hz, p = 0.804071, Mann–Whitney U test, n = 33 and 65 cells, respectively; H: TS-PV, 13.59 ± 2.19 Hz, AC-PV, 13.57 ± 1.33 Hz, p = 0.585753, Mann–Whitney U test, n = 33 and 65 cells, respectively; I: TS-PV, 2.36 ± 0.10, AC-PV, 2.18 ± 0.07, p = 0.182265, Mann–Whitney U test, n = 33 and 65 cells, respectively; J: TS-PV, 21.21 ± 2.49 dB, AC-PV, 20.15 ± 1.58 dB, p = 0.900998, Mann–Whitney U test, n = 33 and 65 cells, respectively).

TS-PV interneurons were sufficient to regulate the auditory response of SPNs

According to previous research, PV interneurons in the AC play a significant role in regulating cortical auditory processing (Li et al., 2014). Although PV interneurons constitute only a small proportion of neurons in the TS, they are extremely important for controlling the activity of SPNs (Tomkins et al., 2013). Therefore, we investigated whether TS-PV interneurons can effectively regulate auditory information processing in SPNs. To manipulate TS-PV activity, we injected an AAV encoding Cre-dependent ArchT or ChR2 into the TS of adult PV-Cre mice and implanted an optical fiber 50° from the horizontal above the TS for optogenetic stimulation (see Methods). To investigate the impact of TS-PV regulation on auditory information processing in SPNs, we delivered green light (530 nm) to silence ArchT-expressing TS-PV interneurons or blue light (470 nm) to activate ChR2-expressing TS-PV interneurons (Fig. 6A,B). When TS-PV interneurons were silenced, the auditory response of SPNs was significantly increased (Fig. 6C,D). In general, we observed that SPNs had a higher evoked FR (Fig. 6E; Z = −3.823007, p = 0.000132, Wilcoxon signed-rank test), higher spontaneous FR (Fig. 6F; Z = −3.04541, p = 0.002324, Wilcoxon signed-rank test), broader TRF (Fig. 6G; Z = −3.824169, p = 0.000131, Wilcoxon signed-rank test), and lower intensity threshold (Fig. 6H; Z = −3.787314, p = 0.000152, Wilcoxon signed-rank test) when TS-PV interneurons were optogenetically suppressed. In contrast, the TRF of SPNs was significantly decreased by activating TS-PV interneurons (Fig. 6I,J). In general, the evoked FR (Fig. 6K; Z = −2.80306, p = 0.005062, Wilcoxon signed-rank test) and spontaneous FR (Fig. 6L; Z = −2.60634, p = 0.00915, Wilcoxon signed-rank test) were lower, the TRF (Fig. 6M; Z = −2.66557, p = 0.007686, Wilcoxon signed-rank test) was narrower, and the intensity threshold was higher (Fig. 6N; Z = 1.44338, p = 0.14891, Wilcoxon signed-rank test) when TS-PV interneurons were optogenetically activated. The slope of the FR of frequency tuning at 70 dB in the light-off and light-on conditions further confirmed these results (Fig. 6O). These results suggest that the frequency tuning of SPNs is bidirectionally modulated by TS-PV interneurons, similar to the role of PV interneurons in the AC. Finally, we compared the tuning properties of PV interneurons and SPNs in the TS. In general, PV interneurons had a broader TRF (Fig. 6P; t = −3.89615, p = 0.00025, two-sample t test) and lower intensity threshold (Fig. 6Q; Z = 3.47642, p = 0.00051, Mann‒Whitney U test) than SPNs. These properties indicate that PV interneurons exhibit higher responsiveness.

Figure 6.
Figure 6.

Manipulations of the auditory responses of SPNs by optogenetics inactivating or activating PV interneurons in TS. A, Schematic of injection of AAV-DIO-ArchT-EYFP or AAV-DIO-ChR2-EYFP into TS and loose-patch recording for putative SPNs. LED light is applied to TS through an implanted fiber 50° diagonally above TS. B, Fluorescence images showing tdTomato-labeled PV interneurons (red) and the expression of ArchT-EYFP (green) in a representative slice of a PV-Cre::Ai14 mouse. Scale bar, 100 µm. C, Tonal receptive field (TRF) of an example SPNs without (left) and with (right) optogenetic silencing of TS-PV. Color scale indicates evoked firing rate. D, Plot of normalized firing rates evoked by effective tones (at 70 dB SPL) with versus without PV neuronal silencing. Red line is the best fit linear regression line. E–H, Comparison of normalized evoked firing rate (E), normalized spontaneous firing rate (F), normalized TRF bandwidth at 20 dB above the intensity threshold (G), and intensity threshold (H) of SPNs between without (black) and with (red) TS-PV neuronal silencing (E: before, 1, after, 1.65 ± 0.55, ***p < 0.001, Wilcoxon signed-rank test, n = 19 cells; F: before, 1, after, 1.23 ± 0.30, **p < 0.01, Wilcoxon signed-rank test, n = 19 cells; G: before, 1, after, 1.29 ± 0.23, ***p < 0.001, Wilcoxon signed-rank test, n = 19 cells; H: before, 32.63 ± 12.84 dB, after, 21.05 ± 12.86 dB, ***p < 0.001, Wilcoxon signed-rank test, n = 19 cells). I–N, Similar to C–H but for optogenetics activating TS-PV (K: before, 1, after, 0.62 ± 0.20, **p < 0.01, Wilcoxon signed-rank test, n = 10 cells; L: before, 1, after, 0.48 ± 0.25, **p < 0.01, Wilcoxon signed-rank test, n = 10 cells; M: before, 1, after, 0.77 ± 0.13, **p < 0.01, Wilcoxon signed-rank test, n = 10 cells; N: before, 34 ± 13.49 dB, after, 31 ± 14.49 dB, p = 0.14891, Wilcoxon signed-rank test, n = 10 cells). O, Summary of slope of linear fitting for all neurons in the PV neuronal silencing (ArchT) and activation (ChR2) groups. P, Comparison of TRF bandwidth at 20 dB above the intensity threshold between TS-PV (red) and TS-SPN (blue; TS-PV, 2.36 ± 0.10, TS-SPN, 1.75 ± 0.11 Hz, ***p < 0.001, Mann–Whitney U test, n = 33 and 29 cells, respectively). Q, Comparison of intensity threshold between TS-PV (red) and TS-SPN (blue; TS-PV, 21.21 ± 2.49 dB, TS-SPN, 33.10 ± 2.22 dB, ***p < 0.001, Mann–Whitney U test, n = 33 and 29 cells, respectively).

Discussion

In this study, we found that although there are few PV interneurons in the TS, they form inhibitory synapses with a wide range of SPNs. We also demonstrated that PV interneurons receive input primarily from the MGB and have high-fidelity tuning properties. Furthermore, by using optogenetics to regulate the activity of PV interneurons, we showed that the auditory processing of SPNs can be bidirectionally modulated within the TS, which is important for auditory-related behavior.

Effective synaptic connections from the PV to SPNs in the TS

PV interneurons, as the largest subpopulation of GABAergic interneurons in the cortex, have been extensively studied in the AC. As they account for a large proportion of AC neurons (∼40%; Tsodyks et al., 1997; Xu et al., 2010) and have dense axonal processes that synapse at the somas and proximal dendrites of excitatory neurons, they are capable of providing fast and powerful inhibition to the surrounding neurons, playing an important role in auditory information processing, including receptive field formation, improved temporal precision, and gain control (Kisvarday et al., 2000; Kuhlman et al., 2011; Moore and Wehr, 2013). However, the contribution of PV interneurons to auditory processing in the TS is still unclear. Our research indicates that the morphological characteristics of PV interneurons in the TS are distinctly different from those in the AC; TS-PV interneurons have a lower distribution density (Fig. 1C, average density: TS-PV: 48.06 ± 2.11; AC-PV: 335.46 ± 21.63), more diffuse morphology, more dendritic branches, and higher dendritic coverage (Tepper et al., 2004; Gittis et al., 2010; Planert et al., 2010). The differences in morphology and density of these two groups of PV interneurons indicate that they have different functional characteristics. Unlike AC-PV interneurons, which innervate the soma and proximal dendrites (Ferguson and Gao, 2018), the synapses formed by TS-PV interneurons can be distributed farther away from the cell body of the main neuron, and a TS-PV interneuron can innervate hundreds of neurons (Plenz, 2003; Gittis et al., 2011). Therefore, as PV interneurons are sparsely distributed in the TS, can they provide enough inhibitory input to SPNs? Our results showed that PV interneurons can form effective synaptic connections with SPNs in the TS (Fig. 2B,C). In addition, as the principal neurons in the TS and AC, SPNs and PNs are differentially regulated by PV interneurons. The synaptic connections between AC-PNs and PV interneurons are mainly concentrated near the cell body (Fig. 2D), while the synaptic connections formed by SPNs are more widespread (Fig. 2E). This supports previous studies (Plenz, 2003; Gittis et al., 2011) and indicates that PV interneurons can provide effective inhibitory input for SPNs. Therefore, there is a structural basis for PV interneurons to participate in auditory processing in the TS.

The auditory input and output responses of TS-PV interneurons

The TS is a special part of the striatum, which receives various sensory information inputs, including auditory input (Hintiryan et al., 2016). Recent studies have shown that auditory input to the TS mainly comes from the AC and MGB (Chen et al., 2019). Both PV interneurons and SPNs in the TS receive dense auditory input from both the AC and MGB, and this finding supports that of previous studies demonstrating that the MGB is a critical relay station through which sensory information reaches the cortex and other downstream regions (Ji et al., 2016). However, there was a higher rate of projections from the MGB to PV interneurons (response ratio: MGB to PV, N = 21/26; AC to PV, N = 15/32) and from the AC to SPNs (response ratio: MGB to SPN, N = 22/25; AC to SPN, N = 24/30; Figs. 3F, 4F). This indicates that PV interneurons and SPNs have different sources of auditory input, with PV interneurons mainly receiving auditory input from the MGB and SPNs mainly receiving auditory input from the AC. It is worth noting that because the MGB receives information faster than the AC, TS-PV interneurons may provide faster auditory inhibition than SPNs (Szydlowski et al., 2013; Johansson and Silberberg, 2020).This asynchronous excitatory and inhibitory input may cause greater variability in the firing probability and firing time of postsynaptic neurons (Haider et al., 2006), significantly influencing the excitability and function of principle neurons, indicating that TS-PV interneurons may play a special role in auditory information processing.

Our research indicates that TS-PV and AC-PV interneurons demonstrate similar tuning properties. Previous studies have revealed that TS-PV interneurons exhibit tone-evoked spike responses with clear tone-receptive fields (TRF) and broad frequency tuning curves, comparable to the auditory responses of AC-PV interneurons (Li et al., 2019), although the TS and AC receive input from different pathways, with the TS receiving input from the MGv (in the driver pathway; Lee and Sherman, 2010) and the AC receiving input from the MGd (in the modulator pathway; Chen et al., 2019). TS-PV interneurons also receive input from the AC and other auditory-related brain areas (Vasquez-Lopez et al., 2017). This integration of auditory information from various brain areas allows TS-PV interneurons to adjust their frequency characteristics. Moreover, previous studies have shown that the projecting neurons both in the AC and MGB that project to the striatum have similar frequency tuning bandwidths (Ponvert and Jaramillo, 2019), suggesting that both pathways can convey frequency information to the TS with comparable fidelity (Ponvert and Jaramillo, 2019), Consequently, TS-PV interneurons exhibit similar high-fidelity tuning characteristics to AC-PV interneurons. Therefore, when sound stimuli appear, these auditory responses are sufficient to allow TS-PV interneurons to regulate the auditory function of the TS by providing inhibitory input to SPNs, indicating that TS-PV interneurons play a fundamental role in auditory information processing. Furthermore, the auditory responses of TS-PV interneurons are modulated by the acoustic features of sound stimuli, such as frequency and intensity, suggesting that these neurons play a critical role in the processing of auditory information.

The role of TS-PV interneurons in auditory information processing

Based on the above results, we believe that TS-PV interneurons participate in striatal auditory processing, as confirmed by optogenetic studies. Specifically, the activation of TS-PV interneurons leads to the inhibition of SPNs, while the inactivation of these neurons leads to the excitation of SPNs (Fig. 6). This indicates that TS-PV interneurons can bidirectionally regulate the auditory responses of SPNs. In our study, we found that the regulation of principal neurons by TS-PV interneurons is comparable to that by AC-PV interneurons. PV interneurons are recruited by feedforward circuits and can rapidly provide extensive inhibitory tuning following excitation (Li et al., 2015). Their peak activity occurs earlier than that of SPNs (Fig. 5D), leading to more efficient input –output conversion (Wu et al., 2008). Therefore, manipulating the activity of TS-PV interneurons, as observed in the AC (Liang et al., 2019), results in corresponding changes in the frequency tuning and intensity threshold characteristics of SPNs. It is worth noting that when TS-PV interneurons are activated, the auditory response of SPNs is partially rather than completely suppressed (Fig. 6I). This is in contrast to the effects of AC-PV interneurons, which are the primary inhibitory input source in the AC because they account for a large proportion of neurons in the AC and provide strong inhibitory input to the local excitatory neurons. Thus, activating PV interneurons is sufficient to silence the entire AC (Xiong et al., 2015). How PV properties may lead to the tuning modulation on SPN? By analyzing the toning characteristics of PV interneurons and SPNs, we find that PV interneurons had broader TRFs and a lower intensity threshold, as shown in Figure 6P,Q. These properties indicate that PV inhibitory neurons exhibit higher responsiveness, while their similar tuning properties also contribute to the broad regulation of inhibitory signaling initiation (Li et al., 2014, 2015). This suggests that TS-PV interneurons can influence striatal auditory output by providing inhibitory regulation of SPN activity and, moreover, the bidirectional regulation of auditory responses of SPNs by TS-PV interneurons, which is essential for auditory-related behaviors (Kalanithi et al., 2005; Gittis et al., 2011; Burguiere et al., 2013).

In conclusion, the present study provides novel insights into the role of PV interneurons in the AC and TS. Our results demonstrates that TS-PV interneurons can inhibit SPNs across a wider range than previously reported, suggesting that they play a more critical role in auditory processing than previously thought. Our study highlights the potential of TS-PV interneurons to contribute to auditory processing and behavior. Further studies are needed to fully understand the mechanisms underlying TS-PV activity and their overall contribution to auditory processing and behavior. By elucidating the role of TS-PV interneurons, our work illuminates new avenues for research and has promising implications for the development of novel therapeutic interventions for auditory-related disorders. It is worth noting that the AC consists of multiple major components, including A1, A2, and AAF. Due to the limitations in experimental techniques, it is challenging to separately investigate the impact of these brain regions on TS function. Our findings primarily focus on the primary AC, while the impact of other parts of the AC on TS in terms of structure and function requires further investigation in future studies.

Footnotes

  • This work was supported by grants from the National Natural Science Foundation of China (32271061), the Natural Science Funds for Distinguished Young Scholar of Guangdong Province (2019B151502033), the STI2030-major projects (2021ZD0202600), and the Science and Technology Plan Project of Guangzhou (202206060004) to F.L.; from the National Natural Science Foundation of China (31600849) and the Natural Science Foundation of Guangdong (2017A030313186) to X.J.; and from the National Natural Science Foundation of China (32000699) and the Guangdong Basic and Applied Basic Research Foundation (2019A1515110804) to H.L.

  • ↵* X.L. and J.Y. contributed equally to this work.

  • The authors declare that they have no conflicts of interest.

  • Correspondence should be addressed to Xuying Ji at jixuying{at}163.com or Feixue Liang at liangfx{at}smu.edu.cn.

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Effective Regulation of Auditory Processing by Parvalbumin Interneurons in the Tail of the Striatum
Xuan Li, Jiapeng You, Yidi Pan, Changbao Song, Haifu Li, Xuying Ji, Feixue Liang
Journal of Neuroscience 31 January 2024, 44 (5) e1171232023; DOI: 10.1523/JNEUROSCI.1171-23.2023
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