Spectro-temporal receptive fields of midbrain auditory neurons in the rat obtained with frequency modulated stimulation

Electrical Stimulation of the Auricular Branch Vagus Nerve Using Random and Alternating Frequencies Triggers a Rapid Onset and Pronounced Antihyperalgesia via Peripheral Annexin A1-Formyl Peptide Receptor 2/ALX Pathway in a Mouse Model of Persistent Inflammatory Pain

This study evaluated the antihyperalgesic and anti-inflammatory effects of percutaneous vagus nerve electrical stimulation (pVNS) by comparing the effects of alternating and random frequencies in an animal model of persistent inflammatory hyperalgesia. The model was induced by Freund's complete adjuvant (CFA) intraplantar (i.pl.) injection. Mice were treated with different protocols of time (10, 20, or 30 min), ear laterality (right, left or both), and frequency (alternating or random). Mechanical hyperalgesia was evaluated, and some groups received i.pl. WRW4 (FPR2/ALX antagonist) to determine the involvement. Edema, paw surface temperature, and spontaneous locomotor activity were evaluated. Interleukin-1β, IL-6, IL-10, and IL4 levels were verified by enzyme-linked immunosorbent assay. AnxA1, FPR2/ALX, neutrophil, M1 and M2 phenotype macrophage, and apoptotic cells markers were identified using western blotting. The antihyperalgesic effect pVNS with alternating and random frequency effect is depending on the type of frequency, time, and ear treated. The pVNS random frequency in the left ear for 10 min had a longer lasting antihyperalgesic effect, superior to classical stimulation using alternating frequency and the FPR2/ALX receptor was involved in this effect. There was a reduction in the levels of pro-inflammatory cytokines and an increase in the immunocontent of AnxA1 and CD86 in mice paw. pVNS with a random frequency in the left ear for 10 min showed to be optimal for inducing an antihyperalgesic effect. Thus, the random frequency was more effective than the alternating frequency. Therefore, pVNS may be an important adjunctive treatment for persistent inflammatory pain.

Natural Statistics as Inference Principles of Auditory Tuning in Biological and Artificial Midbrain Networks

Bats provide a powerful mammalian model to explore the neural representation of complex sounds, as they rely on hearing to survive in their environment. The inferior colliculus (IC) is a central hub of the auditory system that receives converging projections from the ascending pathway and descending inputs from auditory cortex. In this work, we build an artificial neural network to replicate auditory characteristics in IC neurons of the big brown bat. We first test the hypothesis that spectro-temporal tuning of IC neurons is optimized to represent the natural statistics of conspecific vocalizations. We estimate spectro-temporal receptive fields (STRFs) of IC neurons and compare tuning characteristics to statistics of bat calls. The results indicate that the FM tuning of IC neurons is matched with the statistics. Then, we investigate this hypothesis on the network optimized to represent natural sound statistics and to compare its output with biological responses. We also estimate biomimetic STRFs from the artificial network and correlate their characteristics to those of biological neurons. Tuning properties of both biological and artificial neurons reveal strong agreement along both spectral and temporal dimensions, and suggest the presence of nonlinearity, sparsity, and complexity constraints that underlie the neural representation in the auditory midbrain. Additionally, the artificial neurons replicate IC neural activities in discrimination of social calls, and provide simulated results for a noise robust discrimination. In this way, the biomimetic network allows us to infer the neural mechanisms by which the bat’s IC processes natural sounds used to construct the auditory scene.

Sublaminar Subdivision of Mouse Auditory Cortex Layer 2/3 Based on Functional Translaminar Connections

The cerebral cortex is subdivided into six layers based on morphological features. The supragranular layers 2/3 (L2/3) contain morphologically and genetically diverse populations of neurons, suggesting the existence of discrete classes of cells. In primates and carnivores L2/3 can be subdivided morphologically, but cytoarchitectonic divisions are less clear in rodents. Nevertheless, discrete classes of cells could exist based on their computational requirement, which might be linked to their associated functional microcircuits. Through in vitro slice recordings coupled with laser-scanning photostimulation we investigated whether L2/3 of male mouse auditory cortex contains discrete subpopulations of cells with specific functional microcircuits. We use hierarchical clustering on the laminar connection patterns to reveal the existence of multiple distinct classes of L2/3 neurons. The classes of L2/3 neurons are distinguished by the pattern of their laminar and columnar inputs from within A1 and their location within L2/3. Cells in superficial L2 show more extensive columnar integration than deeper L3 cells. Moreover, L3 cells receive more translaminar input from L4. In vivo imaging in awake mice revealed that L2 cells had higher bandwidth than L3 cells, consistent with the laminar differences in columnar integration. These results suggest that similar to higher mammals, rodent L2/3 is not a homogenous layer but contains several parallel microcircuits.SIGNIFICANCE STATEMENT Layer 2/3 of auditory cortex is functionally diverse. We investigated whether L2/3 cells form classes based on their functional connectivity. We used in vitro whole-cell patch-clamp recordings with laser-scanning photostimulation and performed unsupervised clustering on the resulting excitatory and inhibitory connection patterns. Cells within each class were located in different sublaminae. Superficial cells showed wider integration along the tonotopic axis and the amount of L4 input varied with sublaminar location. To identify whether sensory responses varied with sublaminar location, we performed in vivo Ca2+ imaging and found that L2 cells were less frequency-selective than L3 cells. Our results show that the diversity of receptive fields in L2/3 is likely due to diversity in the underlying functional circuits.

Matching Pursuit Analysis of Auditory Receptive Fields' Spectro-Temporal Properties

Gabor filters have long been proposed as models for spectro-temporal receptive fields (STRFs), with their specific spectral and temporal rate of modulation qualitatively replicating characteristics of STRF filters estimated from responses to auditory stimuli in physiological data. The present study builds on the Gabor-STRF model by proposing a methodology to quantitatively decompose STRFs into a set of optimally matched Gabor filters through matching pursuit, and by quantitatively evaluating spectral and temporal characteristics of STRFs in terms of the derived optimal Gabor-parameters. To summarize a neuron's spectro-temporal characteristics, we introduce a measure for the “diagonality,” i.e., the extent to which an STRF exhibits spectro-temporal transients which cannot be factorized into a product of a spectral and a temporal modulation. With this methodology, it is shown that approximately half of 52 analyzed zebra finch STRFs can each be well approximated by a single Gabor or a linear combination of two Gabor filters. Moreover, the dominant Gabor functions tend to be oriented either in the spectral or in the temporal direction, with truly “diagonal” Gabor functions rarely being necessary for reconstruction of an STRF's main characteristics. As a toy example for the applicability of STRF and Gabor-STRF filters to auditory detection tasks, we use STRF filters as features in an automatic event detection task and compare them to idealized Gabor filters and mel-frequency cepstral coefficients (MFCCs). STRFs classify a set of six everyday sounds with an accuracy similar to reference Gabor features (94% recognition rate). Spectro-temporal STRF and Gabor features outperform reference spectral MFCCs in quiet and in low noise conditions (down to 0 dB signal to noise ratio).

Multiscale mapping of frequency sweep rate in mouse auditory cortex

Functional organization is a key feature of the neocortex that often guides studies of sensory processing, development, and plasticity. Tonotopy, which arises from the transduction properties of the cochlea, is the most widely studied organizational feature in auditory cortex; however, in order to process complex sounds, cortical regions are likely specialized for higher order features. Here, motivated by the prevalence of frequency modulations in mouse ultrasonic vocalizations and aided by the use of a multiscale imaging approach, we uncover a functional organization across the extent of auditory cortex for the rate of frequency modulated (FM) sweeps. In particular, using two-photon Ca²⁺ imaging of layer 2/3 neurons, we identify a tone-insensitive region at the border of AI and AAF. This central sweep region behaves fundamentally differently from nearby neurons in AI and AII, responding preferentially to fast FM sweeps but not to tones or bandlimited noise. Together these findings define a second dimension of organization in the mouse auditory cortex for sweep rate complementary to that of tone frequency.

Modeling complex responses of FM-sensitive cells in the auditory midbrain using a committee machine

Frequency modulation (FM) is an important building block of complex sounds that include speech signals. Exploring the neural mechanisms of FM coding with computer modeling could help understand how speech sounds are processed in the brain. Here, we modeled the single unit responses of auditory neurons recorded from the midbrain of anesthetized rats. These neurons displayed spectral temporal receptive fields (STRFs) that had multiple-trigger features, and were more complex than those with single-trigger features. Their responses have not been modeled satisfactorily with simple artificial neural networks, unlike neurons with simple-trigger features. To improve model performance, here we tested an approach with the committee machine. For a given neuron, the peri-stimulus time histogram (PSTH) was first generated in response to a repeated random FM tone, and peaks in the PSTH were segregated into groups based on the similarity of their pre-spike FM trigger features. Each group was then modeled using an artificial neural network with simple architecture, and, when necessary, by increasing the number of neurons in the hidden layer. After initial training, the artificial neural networks with their optimized weighting coefficients were pooled into a committee machine for training. Finally, the model performance was tested by prediction of the response of the same cell to a novel FM tone. The results showed improvement over simple artificial neural networks, supporting that trigger-feature-based modeling can be extended to cells with complex responses. This article is part of a Special Issue entitled Neural Coding 2012. This article is part of a Special Issue entitled Neural Coding 2012.

Modeling frequency modulated responses of midbrain auditory neurons based on trigger features and artificial neural networks

Frequency modulation (FM) is an important building block of communication signals for animals and human. Attempts to predict the response of central neurons to FM sounds have not been very successful, though achieving successful results could bring insights regarding the underlying neural mechanisms. Here we proposed a new method to predict responses of FM-sensitive neurons in the auditory midbrain. First we recorded single unit responses in anesthetized rats using a random FM tone to construct their spectro-temporal receptive fields (STRFs). Training of neurons in the artificial neural network to respond to a second random FM tone was based on the temporal information derived from the STRF. Specifically, the time window covered by the presumed trigger feature and its delay time to spike occurrence were used to train a finite impulse response neural network (FIRNN) to respond to this random FM. Finally we tested the model performance in predicting the response to another similar FM stimuli (third random FM tone). We found good performance in predicting the time of responses if not also the response magnitudes. Furthermore, the weighting function of the FIRNN showed temporal 'bumps' suggesting temporal integration of synaptic inputs from different frequency laminae. This article is part of a Special Issue entitled: Neural Coding.

Differential roles of GABAergic and glycinergic input on FM selectivity in the inferior colliculus of the pallid bat

Multiple mechanisms have been shown to shape frequency-modulated (FM) selectivity within the central nucleus of the inferior colliculus (IC) in the pallid bat. In this study we focus on the mechanisms associated with sideband inhibition. The relative arrival time of inhibition compared with excitation can be used to predict FM responses as measured with a two-tone inhibition paradigm. An early-arriving low-frequency inhibition (LFI) prevents responses to upward sweeps and thus shapes direction selectivity. A late-arriving high-frequency inhibition (HFI) suppresses slow FM sweeps and thus shapes rate selectivity for downward sweeps. Iontophoretic application of gabazine (GBZ) to block GABA(A) receptors or strychnine (Strych) to block glycine receptors was used to assess the effects of removal of inhibition on each form of FM selectivity. GBZ and Strych had a similar effect on FM direction selectivity, reducing selectivity in up to 86% of neurons when both drugs were coapplied. FM rate selectivity was more resistant to drug application with less than 38% of neurons affected. In addition, only Strych could eliminate FM rate selectivity, whereas GBZ alone was ineffective. The loss of FM selectivity was directly correlated to a loss of the respective inhibitory sideband that shapes that form of selectivity. The elimination of LFI correlated to a loss of FM direction selectivity, whereas elimination of HFI correlated to a loss of FM rate selectivity. Results indicate that 1) although the majority of FM direction selectivity is created within the IC, the majority of rate selectivity is inherited from lower levels of the auditory system, 2) a loss of LFI corresponds to a loss of FM direction selectivity and is created through either GABAergic or glycinergic input, and 3) a loss of HFI corresponds to a loss of FM rate selectivity and is created mainly through glycinergic input.

Should spikes be treated with equal weightings in the generation of spectro-temporal receptive fields?

Knowledge on the trigger features of central auditory neurons is important in the understanding of speech processing. Spectro-temporal receptive fields (STRFs) obtained using random stimuli and spike-triggered averaging allow visualization of trigger features which often appear blurry in the time-versus-frequency plot. For a clearer visualization we have previously developed a dejittering algorithm to sharpen trigger features in the STRF of FM-sensitive cells. Here we extended this algorithm to segregate spikes, based on their dejitter values, into two groups: normal and outlying, and to construct their STRF separately. We found that while the STRF of the normal jitter group resembled full trigger feature in the original STRF, those of the outlying jitter group resembled a different or partial trigger feature. This algorithm allowed the extraction of other weaker trigger features. Due to the presence of different trigger features in a given cell, we proposed that in the generation of STRF, the evoked spikes should not be treated indiscriminately with equal weightings.

Spatial and temporal jitter distort estimated functional properties of visual sensory neurons

The functional properties of neural sensory cells or small neural ensembles are often characterized by analyzing response-conditioned stimulus ensembles. Many widely used analytical methods, like receptive fields (RF), Wiener kernels or spatio-temporal receptive fields (STRF), rely on simple statistics of those ensembles. They also tend to rely on simple noise models for the residuals of the conditional ensembles. However, in many cases the response-conditioned stimulus set has more complex structure. If not taken explicitly into account, it can bias the estimates of many simple statistics, and lead to erroneous conclusions about the functionality of a neural sensory system. In this article, we consider sensory noise in the visual system generated by small stimulus shifts in two dimensions (2 spatial or 1-space 1-time jitter). We model this noise as the action of a set of translations onto the stimulus that leave the response invariant. The analysis demonstrates that the spike-triggered average is a biased estimator of the model mean, and provides a de-biasing method. We apply this approach to observations from the stimulus/response characteristics of cells in the cat visual cortex and provide improved estimates of the structure of visual receptive fields. In several cases the new estimates differ substantially from the classic receptive fields, to a degree that may require re-evaluation of the functional description of the associated cells.

Responses of inferior collicular cells to species-specific vocalizations in normal and enucleated rats

The inferior colliculus (IC) is an obligatory relay for the ascending and descending auditory pathways. Cells in this brainstem structure not only analyze auditory stimuli but they also play a major role in multi-modal integration of auditory and visual information. The aim of the present study was to determine whether cells in the central nucleus of the inferior colliculus (CNIC) of normal rats respond selectively to complex auditory signals, such as species-specific vocalizations, and compare their responses to those obtained in neonatal bilateral enucleated (P2-P3) adult rats. Extra-cellular recordings were carried out in anesthetized normal and enucleated rats using auditory stimuli (pure tones, broadband noise and vocalizations) presented in free field in a semi-anechoic chamber. The results indicate that most cells in the CNIC of both groups respond selectively to species-specific vocalizations better than to the same but inverted sounds. No significant differences were found between the normal and enucleated rat groups in their responses to broadband noise and pure tones.

Frequency-modulation encoding in the primary auditory cortex of the awake owl monkey

Many communication sounds, such as New World monkey twitter calls, contain frequency-modulated (FM) sweeps. To determine how this prominent vocalization element is represented in the auditory cortex we examined neural responses to logarithmic FM sweep stimuli in the primary auditory cortex (AI) of two awake owl monkeys. Using an implanted array of microelectrodes we quantitatively characterized neuronal responses to FM sweeps and to random tone-pip stimuli. Tone-pip responses were used to construct spectrotemporal receptive fields (STRFs). Classification of FM sweep responses revealed few neurons with high direction and speed selectivity. Most neurons responded to sweeps in both directions and over a broad range of sweep speeds. Characteristic frequency estimates from FM responses were highly correlated with estimates from STRFs, although spectral receptive field bandwidth was consistently underestimated by FM stimuli. Predictions of FM direction selectivity and best speed from STRFs were significantly correlated with observed FM responses, although some systematic discrepancies existed. Last, the population distributions of FM responses in the awake owl monkey were similar to, although of longer temporal duration than, those in the anesthetized squirrel monkeys.

Spectrotemporal receptive fields in the inferior colliculus revealing selectivity for spectral motion in conspecific vocalizations

Frequency modulations are a prominent feature of animal vocalizations and human speech. Here we investigated how neurons in the inferior colliculus (IC) of Mexican free-tailed bats respond to the frequency-modulated (FM) direction and velocity of complex signals by extracting their spectrotemporal receptive fields (STRFs) using a family of upward- and downward-moving ripple stimuli. STRFs were obtained in more than half of the cells that were sampled. To verify the validity of each STRF, we compared their features both with tone-evoked responses and by convolving the STRF with several conspecific calls. We show that responses to tones are in close agreement with the STRF and that the responses predicted by convolutions compare favorably with responses evoked by those calls. The high predictability showed that the STRF captured most of the excitatory and inhibitory properties of IC cells. Most neurons were selective for the direction and velocity of spectral motion with a majority favoring the downward FM direction, and most had spectrum-time inseparability that correlated with their direction selectivity. Furthermore, blocking inhibition significantly reduced the directional selectivity of these neurons, suggesting that inhibition shapes FM direction selectivity in the IC. Finally, we decomposed the natural calls into their ripple components and show that most species-specific calls have downward-sweeping FM components with sweep velocities that correspond with the preferred sweep velocities of IC neurons. This close quantitative correspondence among features of signals and responses suggests that IC cells are tuned by inhibition to respond optimally to spectral motion cues present in their conspecific vocalizations.

Target representation of naturalistic echolocation sequences in single unit responses from the inferior colliculus of big brown bats

Echolocating big brown bats (Eptesicus fuscus) emit trains of frequency-modulated (FM) biosonar signals whose duration, repetition rate, and sweep structure change systematically during interception of prey. When stimulated with a 2.5-s sequence of 54 FM pulse-echo pairs that mimic sounds received during search, approach, and terminal stages of pursuit, single neurons (N = 116) in the bat's inferior colliculus (IC) register the occurrence of a pulse or echo with an average of < 1 spike/sound. Individual IC neurons typically respond to only a segment of the search or approach stage of pursuit, with fewer neurons persisting to respond in the terminal stage. Composite peristimulus-time-histogram plots of responses assembled across the whole recorded population of IC neurons depict the delay of echoes and, hence, the existence and distance of the simulated biosonar target, entirely as on-response latencies distributed across time. Correlated changes in pulse duration, repetition rate, and pulse or echo amplitude do modulate the strength of responses (probability of the single spike actually occurring for each sound), but registration of the target itself remains confined exclusively to the latencies of single spikes across cells. Modeling of echo processing in FM biosonar should emphasize spike-time algorithms to explain the content of biosonar images.

Functional Organization of Squirrel Monkey Primary Auditory Cortex: Responses to Frequency-Modulation Sweeps

The squirrel monkey twitter call is an exemplar of a broad class of species-specific vocalizations that contain naturally voiced frequency-modulated (FM) sweeps. To investigate how this prominent communication call element is represented in primary auditory cortex (AI), neuronal receptive field properties to pure-tone and synthetic, logarithmically spaced FM-sweep stimuli in 3 barbiturate-anesthetized squirrel monkeys are studied. Responses to pure tones are assessed by using standard measures of frequency response areas, whereas responses to FM sweeps are classified according to direction selectivity, best speed, and speed tuning preferences. Most neuronal clusters respond to FM sweeps in both directions and over a range of FM speeds. Center frequencies calculated from the average of high and low trigger frequency edges of FM response profiles are highly correlated with pure-tone characteristic frequencies (CFs). However, bandwidth estimates are only weakly correlated with their pure-tone counterparts. CF and direction selectivity are negatively correlated. Best speed maps reveal idiosyncratically positioned spatial aggregation of similar values. In contrast, direction selectivity maps show unambiguous spatial organization. Neuronal clusters selective for upward-directed FM sweeps are located in ventral–caudal AI, where CFs range from 0.5 to 1 kHz. Combinations of pure-tone and FM response parameters form 2 significant factors to account for response variations. These results are interpreted in the context of earlier FM investigations and neuronal encoding of dynamic sounds.

A new method for adjusting neural response jitter in the STRF obtained by spike-trigger averaging

Sensitivity of central auditory neurons to frequency modulated (FM) sound is often characterized based on spectro-temporal receptive field (STRF), which is generated by spike-trigger averaging a random stimulus. Due to the inherent property of time variability in neural response, this method erroneously represents the response jitter as stimulus jitter in the STRF. To reveal the trigger features more clearly, we have implemented a method that minimizes this error. Neural spikes from the brainstem of urethane-anesthetized rats were first recorded in response to two sets of FM stimuli: (a) a random FM tone for the generation of STRF and (b) a family of linear FM ramps for the determination of FM 'trigger point'. Based on the first dataset, STRFs were generated using spike-trigger averaging. Individual modulating waveforms were then matched with respect to their mean waveform at time-windows of a systematically varied length. A stable or optimal variance time profile was found at a particular window length. At this optimal window length, we performed delay adjustments. A marked sharpening in the FM bands in the STRF was found. Results were consistent with the FM 'trigger point' as estimated by the linear FM ramps. We concluded that the present approach of adjusting response jitter was effective in delineating FM trigger features in the STRF.

Responses of central auditory neurons modeled with finite impulse response (FIR) neural networks

To simulate central auditory responses to complex sounds, a computational model was implemented. It consists of a multi-scale classification process, and an artificial neural network composed of two modules of finite impulse response (FIR) neural networks connected to a maximum network. Electrical activities of single auditory neurons were recorded at the rat midbrain in response to a repetitive pseudo-random frequency modulated (FM) sound. The multi-scale classification process divides the training dataset into either strong or weak response using a multiple-scale Gaussian filter that based on response probability. Two modules of FIR neural network are then independently trained to model the two types of responses. This caters for the possible differences in neuronal circuitry and transmission delay. Their outputs are connected to a maximum network to generate the final output. After training, we use a different set of FM responses collected from the same neuron to test the performance of the model. Two criteria are adopted for assessment. One measures the matching of the modeled output to the actual output on a point-to-point basis. Another measures the matching of bulk responses between the two. Results show that the proposed model predicts the responses of central auditory neurons satisfactorily.

Topography and synaptic shaping of direction selectivity in primary auditory cortex

The direction of frequency-modulated (FM) sweeps is an important temporal cue in animal and human communication. FM direction-selective neurons are found in the primary auditory cortex (A1), but their topography and the mechanisms underlying their selectivity remain largely unknown. Here we report that in the rat A1, direction selectivity is topographically ordered in parallel with characteristic frequency (CF): low CF neurons preferred upward sweeps, whereas high CF neurons preferred downward sweeps. The asymmetry of 'inhibitory sidebands', suppressive regions flanking the tonal receptive field (TRF) of the spike response, also co-varied with CF. In vivo whole-cell recordings showed that the direction selectivity already present in the synaptic inputs was enhanced by cortical synaptic inhibition, which suppressed the synaptic excitation of the non-preferred direction more than that of the preferred. The excitatory and inhibitory synaptic TRFs had identical spectral tuning, but with inhibition delayed relative to excitation. The spectral asymmetry of the synaptic TRFs co-varied with CF, as had direction selectivity and sideband asymmetry, and thus suggested a synaptic mechanism for the shaping of FM direction selectivity and its topographic ordering.

Spectrotemporal organization of excitatory and inhibitory receptive fields of cat posterior auditory field neurons

The excitatory and inhibitory frequency/intensity response areas (FRAs) and spectrotemporal receptive fields (STRFs) of posterior auditory cortical field (PAF) single neurons were investigated in barbiturate anesthetized cats. PAF neurons' pure-tone excitatory FRAs (eFRAs) exhibited a diversity of shapes, including some with very broad frequency tuning and some with multiple distinct excitatory frequency ranges (i.e., multipeaked eFRAs). Excitatory FRAs were analyzed after selectively excluding spikes on the basis of spike response times relative to stimulus onset. This analysis indicated that spikes with shorter response times were confined to narrow regions of the eFRAs, while spikes with longer response times were more broadly distributed over the eFRA. First-spike latencies in higher threshold response peaks of multipeaked eFRAs were approximately 10 ms longer, on average, than latencies in lower threshold response peaks. STRFs were constructed to examine the dynamic frequency tuning of neurons. More than half of the neurons (51%) had STRFs with "sloped" response maxima, indicating that the excitatory frequency range shifted with time. A population analysis demonstrated that the median first-spike latency varied systematically as a function of frequency with a median slope of approximately 12 ms per octave. Inhibitory frequency response areas were determined by simultaneous two-tone stimulation. As in primary auditory cortex (A1), a diversity of inhibitory band structures was observed. The largest class of neurons (25%) had an inhibitory band flanking each eFRA edge, i.e., one lower and one upper inhibitory band in a "center-surround" organization. However, in comparison to a previous report of inhibitory structure in A1 neurons, PAF exhibited a higher incidence of neurons with more complex inhibitory band structure (for example, >2 inhibitory bands). As was the case with eFRAs, spikes with longer response times contributed to the complexity of inhibitory FRAs. These data indicate that PAF neurons integrate temporally varying excitatory and inhibitory inputs from a broad spectral extent and, compared with A1, may be suited to analyzing acoustic signals of greater spectrotemporal complexity than was previously thought.