Sound-identity processing in early areas of the auditory ventral stream in the macaque

An Emergent Population Code in Primary Auditory Cortex Supports Selective Attention to Spectral and Temporal Sound Features

Textbook descriptions of primary sensory cortex (PSC) revolve around single neurons' representation of low-dimensional sensory features, such as visual object orientation in primary visual cortex (V1), location of somatic touch in primary somatosensory cortex (S1), and sound frequency in primary auditory cortex (A1). Typically, studies of PSC measure neurons' responses along few (one or two) stimulus and/or behavioral dimensions. However, real-world stimuli usually vary along many feature dimensions and behavioral demands change constantly. In order to illuminate how A1 supports flexible perception in rich acoustic environments, we recorded from A1 neurons while rhesus macaques (one male, one female) performed a feature-selective attention task. We presented sounds that varied along spectral and temporal feature dimensions (carrier bandwidth and temporal envelope, respectively). Within a block, subjects attended to one feature of the sound in a selective change detection task. We found that single neurons tend to be high-dimensional, in that they exhibit substantial mixed selectivity for both sound features, as well as task context. We found no overall enhancement of single-neuron coding of the attended feature, as attention could either diminish or enhance this coding. However, a population-level analysis reveals that ensembles of neurons exhibit enhanced encoding of attended sound features, and this population code tracks subjects' performance. Importantly, surrogate neural populations with intact single-neuron tuning but shuffled higher-order correlations among neurons fail to yield attention- related effects observed in the intact data. These results suggest that an emergent population code not measurable at the single-neuron level might constitute the functional unit of sensory representation in PSC.SIGNIFICANCE STATEMENT The ability to adapt to a dynamic sensory environment promotes a range of important natural behaviors. We recorded from single neurons in monkey primary auditory cortex (A1), while subjects attended to either the spectral or temporal features of complex sounds. Surprisingly, we found no average increase in responsiveness to, or encoding of, the attended feature across single neurons. However, when we pooled the activity of the sampled neurons via targeted dimensionality reduction (TDR), we found enhanced population-level representation of the attended feature and suppression of the distractor feature. This dissociation of the effects of attention at the level of single neurons versus the population highlights the synergistic nature of cortical sound encoding and enriches our understanding of sensory cortical function.

Sexual Dimorphism Within Brain Regions Controlling Speech Production

Neural processing of speech production has been traditionally attributed to the left hemisphere. However, it remains unclear if there are structural bases for speech functional lateralization and if these may be partially explained by sexual dimorphism of cortical morphology. We used a combination of high-resolution MRI and speech-production functional MRI to examine cortical thickness of brain regions involved in speech control in healthy males and females. We identified greater cortical thickness of the left Heschl's gyrus in females compared to males. Additionally, rightward asymmetry of the supramarginal gyrus and leftward asymmetry of the precentral gyrus were found within both male and female groups. Sexual dimorphism of the Heschl's gyrus may underlie known differences in auditory processing for speech production between males and females, whereas findings of asymmetries within cortical areas involved in speech motor execution and planning may contribute to the hemispheric localization of functional activity and connectivity of these regions within the speech production network. Our findings highlight the importance of consideration of sex as a biological variable in studies on neural correlates of speech control.

Intrinsic Connections of the Core Auditory Cortical Regions and Rostral Supratemporal Plane in the Macaque Monkey

In the ventral stream of the primate auditory cortex, cortico-cortical projections emanate from the primary auditory cortex (AI) along 2 principal axes: one mediolateral, the other caudorostral. Connections in the mediolateral direction from core, to belt, to parabelt, have been well described, but less is known about the flow of information along the supratemporal plane (STP) in the caudorostral dimension. Neuroanatomical tracers were injected throughout the caudorostral extent of the auditory core and rostral STP by direct visualization of the cortical surface. Auditory cortical areas were distinguished by SMI-32 immunostaining for neurofilament, in addition to established cytoarchitectonic criteria. The results describe a pathway comprising step-wise projections from AI through the rostral and rostrotemporal fields of the core (R and RT), continuing to the recently identified rostrotemporal polar field (RTp) and the dorsal temporal pole. Each area was strongly and reciprocally connected with the areas immediately caudal and rostral to it, though deviations from strictly serial connectivity were observed. In RTp, inputs converged from core, belt, parabelt, and the auditory thalamus, as well as higher order cortical regions. The results support a rostrally directed flow of auditory information with complex and recurrent connections, similar to the ventral stream of macaque visual cortex.

Hierarchical differences in population coding within auditory cortex

Most models of auditory cortical (AC) population coding have focused on primary auditory cortex (A1). Thus our understanding of how neural coding for sounds progresses along the cortical hierarchy remains obscure. To illuminate this, we recorded from two AC fields: A1 and middle lateral belt (ML) of rhesus macaques. We presented amplitude-modulated (AM) noise during both passive listening and while the animals performed an AM detection task ("active" condition). In both fields, neurons exhibit monotonic AM-depth tuning, with A1 neurons mostly exhibiting increasing rate-depth functions and ML neurons approximately evenly distributed between increasing and decreasing functions. We measured noise correlation (r_noise) between simultaneously recorded neurons and found that whereas engagement decreased average r_noise in A1, engagement increased average r_noise in ML. This finding surprised us, because attentive states are commonly reported to decrease average r_noise We analyzed the effect of r_noise on AM coding in both A1 and ML and found that whereas engagement-related shifts in r_noise in A1 enhance AM coding, r_noise shifts in ML have little effect. These results imply that the effect of r_noise differs between sensory areas, based on the distribution of tuning properties among the neurons within each population. A possible explanation of this is that higher areas need to encode nonsensory variables (e.g., attention, choice, and motor preparation), which impart common noise, thus increasing r_noise Therefore, the hierarchical emergence of r_noise-robust population coding (e.g., as we observed in ML) enhances the ability of sensory cortex to integrate cognitive and sensory information without a loss of sensory fidelity.NEW & NOTEWORTHY Prevailing models of population coding of sensory information are based on a limited subset of neural structures. An important and under-explored question in neuroscience is how distinct areas of sensory cortex differ in their population coding strategies. In this study, we compared population coding between primary and secondary auditory cortex. Our findings demonstrate striking differences between the two areas and highlight the importance of considering the diversity of neural structures as we develop models of population coding.

Divergent Human Cortical Regions for Processing Distinct Acoustic-Semantic Categories of Natural Sounds: Animal Action Sounds vs. Vocalizations

A major gap in our understanding of natural sound processing is knowledge of where or how in a cortical hierarchy differential processing leads to categorical perception at a semantic level. Here, using functional magnetic resonance imaging (fMRI) we sought to determine if and where cortical pathways in humans might diverge for processing action sounds vs. vocalizations as distinct acoustic-semantic categories of real-world sound when matched for duration and intensity. This was tested by using relatively less semantically complex natural sounds produced by non-conspecific animals rather than humans. Our results revealed a striking double-dissociation of activated networks bilaterally. This included a previously well described pathway preferential for processing vocalization signals directed laterally from functionally defined primary auditory cortices to the anterior superior temporal gyri, and a less well-described pathway preferential for processing animal action sounds directed medially to the posterior insulae. We additionally found that some of these regions and associated cortical networks showed parametric sensitivity to high-order quantifiable acoustic signal attributes and/or to perceptual features of the natural stimuli, such as the degree of perceived recognition or intentional understanding. Overall, these results supported a neurobiological theoretical framework for how the mammalian brain may be fundamentally organized to process acoustically and acoustic-semantically distinct categories of ethologically valid, real-world sounds.

Neural Correlates of Vocal Production and Motor Control in Human Heschl's Gyrus

The present study investigated how pitch frequency, a perceptually relevant aspect of periodicity in natural human vocalizations, is encoded in Heschl's gyrus (HG), and how this information may be used to influence vocal pitch motor control. We recorded local field potentials from multicontact depth electrodes implanted in HG of 14 neurosurgical epilepsy patients as they vocalized vowel sounds and received brief (200 ms) pitch perturbations at 100 Cents in their auditory feedback. Event-related band power responses to vocalizations showed sustained frequency following responses that tracked voice fundamental frequency (F0) and were significantly enhanced in posteromedial HG during speaking compared with when subjects listened to the playback of their own voice. In addition to frequency following responses, a transient response component within the high gamma frequency band (75-150 Hz) was identified. When this response followed the onset of vocalization, the magnitude of the response was the same for the speaking and playback conditions. In contrast, when this response followed a pitch shift, its magnitude was significantly enhanced during speaking compared with playback. We also observed that, in anterolateral HG, the power of high gamma responses to pitch shifts correlated with the magnitude of compensatory vocal responses. These findings demonstrate a functional parcellation of HG with neural activity that encodes pitch in natural human voice, distinguishes between self-generated and passively heard vocalizations, detects discrepancies between the intended and heard vocalization, and contains information about the resulting behavioral vocal compensations in response to auditory feedback pitch perturbations.

SIGNIFICANCE STATEMENT

The present study is a significant contribution to our understanding of sensor-motor mechanisms of vocal production and motor control. The findings demonstrate distinct functional parcellation of core and noncore areas within human auditory cortex on Heschl's gyrus that process natural human vocalizations and pitch perturbations in the auditory feedback. In addition, our data provide evidence for distinct roles of high gamma neural oscillations and frequency following responses for processing periodicity in human vocalizations during vocal production and motor control.

Causal contribution of primate auditory cortex to auditory perceptual decision-making

Auditory perceptual decisions are thought to be mediated by the ventral auditory pathway. However, the specific and causal contributions of different brain regions in this pathway, including the middle-lateral (ML) and anterolateral (AL) belt regions of the auditory cortex, to auditory decisions have not been fully identified. To identify these contributions, we recorded from and microstimulated ML and AL sites while monkeys decided whether an auditory stimulus contained more low-frequency or high-frequency tone bursts. Both ML and AL neural activity was modulated by the frequency content of the stimulus. But, only the responses of the most stimulus-sensitive AL neurons were systematically modulated by the monkeys' choices. Consistent with this observation, microstimulation of AL, but not ML, systematically biased the monkeys' behavior toward the choice associated with the preferred frequency of the stimulated site. Together, these findings suggest that AL directly and causally contributes sensory evidence to form this auditory decision.

Perceptual elements in brain mechanisms of acoustic communication in humans and nonhuman primates

Ackermann et al. outline a model for elaboration of subcortical motor outputs as a driving force for the development of the apparently unique behaviour of language in humans. They emphasize circuits in the striatum and midbrain, and acknowledge, but do not explore, the importance of the auditory perceptual pathway for evolution of verbal communication. We suggest that understanding the evolution of language will also require understanding of vocalization perception, especially in the auditory cortex.

Functional MRI of the vocalization-processing network in the macaque brain

Using functional magnetic resonance imaging in awake behaving monkeys we investigated how species-specific vocalizations are represented in auditory and auditory-related regions of the macaque brain. We found clusters of active voxels along the ascending auditory pathway that responded to various types of complex sounds: inferior colliculus (IC), medial geniculate nucleus (MGN), auditory core, belt, and parabelt cortex, and other parts of the superior temporal gyrus (STG) and sulcus (STS). Regions sensitive to monkey calls were most prevalent in the anterior STG, but some clusters were also found in frontal and parietal cortex on the basis of comparisons between responses to calls and environmental sounds. Surprisingly, we found that spectrotemporal control sounds derived from the monkey calls (“scrambled calls”) also activated the parietal and frontal regions. Taken together, our results demonstrate that species-specific vocalizations in rhesus monkeys activate preferentially the auditory ventral stream, and in particular areas of the antero-lateral belt and parabelt.

Anatomic organization of the auditory cortex

The auditory cortex is a network of areas in the part of the brain that receives inputs from the subcortical auditory pathways in the brainstem and thalamus. Through an elaborate network of intrinsic and extrinsic connections, the auditory cortex is thought to bring about the conscious perception of sound and provide a basis for the comprehension and production of meaningful utterances. In this chapter, the organization of auditory cortex is described with an emphasis on its anatomic features and the flow of information within the network. These features are then used to introduce key neurophysiologic concepts that are being intensively studied in humans and animal models. The discussion is presented in the context of our working model of the primate auditory cortex and extensions to humans. The material is presented in the context of six underlying principles, which reflect distinct, but related, aspects of anatomic and physiologic organization: (1) the division of auditory cortex into regions; (2) the subdivision of regions into areas; (3) tonotopic organization of areas; (4) thalamocortical connections; (5) serial and parallel organization of connections; and (6) topographic relationships between auditory and auditory-related areas. Although the functional roles of the various components of this network remain poorly defined, a more complete understanding is emerging from ongoing studies that link auditory behavior to its anatomic and physiologic substrates.

Hierarchical effects of task engagement on amplitude modulation encoding in auditory cortex

We recorded from middle lateral belt (ML) and primary (A1) auditory cortical neurons while animals discriminated amplitude-modulated (AM) sounds and also while they sat passively. Engagement in AM discrimination improved ML and A1 neurons' ability to discriminate AM with both firing rate and phase-locking; however, task engagement affected neural AM discrimination differently in the two fields. The results suggest that these two areas utilize different AM coding schemes: a "single mode" in A1 that relies on increased activity for AM relative to unmodulated sounds and a "dual-polar mode" in ML that uses both increases and decreases in neural activity to encode modulation. In the dual-polar ML code, nonsynchronized responses might play a special role. The results are consistent with findings in the primary and secondary somatosensory cortices during discrimination of vibrotactile modulation frequency, implicating a common scheme in the hierarchical processing of temporal information among different modalities. The time course of activity differences between behaving and passive conditions was also distinct in A1 and ML and may have implications for auditory attention. At modulation depths ≥ 16% (approximately behavioral threshold), A1 neurons' improvement in distinguishing AM from unmodulated noise is relatively constant or improves slightly with increasing modulation depth. In ML, improvement during engagement is most pronounced near threshold and disappears at highly suprathreshold depths. This ML effect is evident later in the stimulus, and mainly in nonsynchronized responses. This suggests that attention-related increases in activity are stronger or longer-lasting for more difficult stimuli in ML.

Auditory connections and functions of prefrontal cortex

The functional auditory system extends from the ears to the frontal lobes with successively more complex functions occurring as one ascends the hierarchy of the nervous system. Several areas of the frontal lobe receive afferents from both early and late auditory processing regions within the temporal lobe. Afferents from the early part of the cortical auditory system, the auditory belt cortex, which are presumed to carry information regarding auditory features of sounds, project to only a few prefrontal regions and are most dense in the ventrolateral prefrontal cortex (VLPFC). In contrast, projections from the parabelt and the rostral superior temporal gyrus (STG) most likely convey more complex information and target a larger, widespread region of the prefrontal cortex. Neuronal responses reflect these anatomical projections as some prefrontal neurons exhibit responses to features in acoustic stimuli, while other neurons display task-related responses. For example, recording studies in non-human primates indicate that VLPFC is responsive to complex sounds including vocalizations and that VLPFC neurons in area 12/47 respond to sounds with similar acoustic morphology. In contrast, neuronal responses during auditory working memory involve a wider region of the prefrontal cortex. In humans, the frontal lobe is involved in auditory detection, discrimination, and working memory. Past research suggests that dorsal and ventral subregions of the prefrontal cortex process different types of information with dorsal cortex processing spatial/visual information and ventral cortex processing non-spatial/auditory information. While this is apparent in the non-human primate and in some neuroimaging studies, most research in humans indicates that specific task conditions, stimuli or previous experience may bias the recruitment of specific prefrontal regions, suggesting a more flexible role for the frontal lobe during auditory cognition.

Natural variability in species-specific vocalizations constrains behavior and neural activity

A listener's capacity to discriminate between sounds is related to the amount of acoustic variability that exists between these sounds. However, a full understanding of how this natural variability impacts neural activity and behavior is lacking. Here, we tested monkeys' ability to discriminate between different utterances of vocalizations from the same acoustic class (i.e., coos and grunts), while neural activity was simultaneously recorded in the anterolateral belt region (AL) of the auditory cortex, a brain region that is a part of a pathway that mediates auditory perception. Monkeys could discriminate between coos better than they could discriminate between grunts. We also found AL activity was more informative about different coos than different grunts. This difference could be attributed, in part, to our finding that coos had more acoustic variability than grunts. Thus, intrinsic acoustic variability constrained the discriminability of AL spike trains and the ability of rhesus monkeys to discriminate between vocalizations.

Feedforward and feedback projections of caudal belt and parabelt areas of auditory cortex: refining the hierarchical model

Our working model of the primate auditory cortex recognizes three major regions (core, belt, parabelt), subdivided into thirteen areas. The connections between areas are topographically ordered in a manner consistent with information flow along two major anatomical axes: core-belt-parabelt and caudal-rostral. Remarkably, most of the connections supporting this model were revealed using retrograde tracing techniques. Little is known about laminar circuitry, as anterograde tracing of axon terminations has rarely been used. The purpose of the present study was to examine the laminar projections of three areas of auditory cortex, pursuant to analysis of all areas. The selected areas were: middle lateral belt (ML); caudomedial belt (CM); and caudal parabelt (CPB). Injections of anterograde tracers yielded data consistent with major features of our model, and also new findings that compel modifications. Results supporting the model were: (1) feedforward projection from ML and CM terminated in CPB; (2) feedforward projections from ML and CPB terminated in rostral areas of the belt and parabelt; and (3) feedback projections typified inputs to the core region from belt and parabelt. At odds with the model was the convergence of feedforward inputs into rostral medial belt from ML and CPB. This was unexpected since CPB is at a higher stage of the processing hierarchy, with mainly feedback projections to all other belt areas. Lastly, extending the model, feedforward projections from CM, ML, and CPB overlapped in the temporal parietal occipital area (TPO) in the superior temporal sulcus, indicating significant auditory influence on sensory processing in this region. The combined results refine our working model and highlight the need to complete studies of the laminar inputs to all areas of auditory cortex. Their documentation is essential for developing informed hypotheses about the neurophysiological influences of inputs to each layer and area.

Selectivity for space and time in early areas of the auditory dorsal stream in the rhesus monkey

The respective roles of ventral and dorsal cortical processing streams are still under discussion in both vision and audition. We characterized neural responses in the caudal auditory belt cortex, an early dorsal stream region of the macaque. We found fast neural responses with elevated temporal precision as well as neurons selective to sound location. These populations were partly segregated: Neurons in a caudomedial area more precisely followed temporal stimulus structure but were less selective to spatial location. Response latencies in this area were even shorter than in primary auditory cortex. Neurons in a caudolateral area showed higher selectivity for sound source azimuth and elevation, but responses were slower and matching to temporal sound structure was poorer. In contrast to the primary area and other regions studied previously, latencies in the caudal belt neurons were not negatively correlated with best frequency. Our results suggest that two functional substreams may exist within the auditory dorsal stream.

Interaction between dorsal and ventral processing streams: where, when and how?

The execution of complex visual, auditory, and linguistic behaviors requires a dynamic interplay between spatial ('where/how') and non-spatial ('what') information processed along the dorsal and ventral processing streams. However, while it is acknowledged that there must be some degree of interaction between the two processing networks, how they interact, both anatomically and functionally, is a question which remains little explored. The current review examines the anatomical, temporal, and behavioral evidence regarding three potential models of dual stream interaction: (1) computations along the two pathways proceed independently and in parallel, reintegrating within shared target brain regions; (2) processing along the separate pathways is modulated by the existence of recurrent feedback loops; and (3) information is transferred directly between the two pathways at multiple stages and locations along their trajectories.

Coding of vocalizations by single neurons in ventrolateral prefrontal cortex

Neuronal activity in single prefrontal neurons has been correlated with behavioral responses, rules, task variables and stimulus features. In the non-human primate, neurons recorded in ventrolateral prefrontal cortex (VLPFC) have been found to respond to species-specific vocalizations. Previous studies have found multisensory neurons which respond to simultaneously presented faces and vocalizations in this region. Behavioral data suggests that face and vocal information are inextricably linked in animals and humans and therefore may also be tightly linked in the coding of communication calls in prefrontal neurons. In this study we therefore examined the role of VLPFC in encoding vocalization call type information. Specifically, we examined previously recorded single unit responses from the VLPFC in awake, behaving rhesus macaques in response to 3 types of species-specific vocalizations made by 3 individual callers. Analysis of responses by vocalization call type and caller identity showed that ∼19% of cells had a main effect of call type with fewer cells encoding caller. Classification performance of VLPFC neurons was ∼42% averaged across the population. When assessed at discrete time bins, classification performance reached 70 percent for coos in the first 300 ms and remained above chance for the duration of the response period, though performance was lower for other call types. In light of the sub-optimal classification performance of the majority of VLPFC neurons when only vocal information is present, and the recent evidence that most VLPFC neurons are multisensory, the potential enhancement of classification with the addition of accompanying face information is discussed and additional studies recommended. Behavioral and neuronal evidence has shown a considerable benefit in recognition and memory performance when faces and voices are presented simultaneously. In the natural environment both facial and vocalization information is present simultaneously and neural systems no doubt evolved to integrate multisensory stimuli during recognition. This article is part of a Special Issue entitled "Communication Sounds and the Brain: New Directions and Perspectives".

Differences between primary auditory cortex and auditory belt related to encoding and choice for AM sounds

We recorded from middle-lateral (ML) and primary (A1) auditory cortex while macaques discriminated amplitude-modulated (AM) noise from unmodulated noise. Compared with A1, ML had a higher proportion of neurons that encoded increasing AM depth by decreasing their firing rates ("decreasing" neurons), particularly with responses that were not synchronized to the modulation. Choice probability (CP) analysis revealed that A1 and ML activity were different during the first half of the test stimulus. In A1, significant CP began before the test stimulus, remained relatively constant (or increased slightly) during the stimulus, and increased greatly within 200 ms of lever release. Neurons in ML behaved similarly, except that significant CP disappeared during the first half of the stimulus and reappeared during the second half and prerelease periods. CP differences between A1 and ML depend on neural response type. In ML (but not A1), when activity was lower during the first half of the stimulus in nonsynchronized, decreasing neurons, the monkey was more likely to report AM. Neurons that both increased firing rate with increasing modulation depth ("increasing" neurons) and synchronized their responses to AM had similar choice-related activity dynamics in ML and A1. These results suggest that, when ascending the auditory system, there is a transformation in coding AM from primarily synchronized increasing responses in A1 to nonsynchronized and dual (increasing/decreasing) coding in ML. This sensory transformation is accompanied by changes in the timing of activity related to choice, suggesting functional differences between A1 and ML related to attention and/or behavior.

Effect of acoustic similarity on short-term auditory memory in the monkey

Recent evidence suggests that the monkey's short-term memory in audition depends on a passively retained sensory trace as opposed to a trace reactivated from long-term memory for use in working memory. Reliance on a passive sensory trace could render memory particularly susceptible to confusion between sounds that are similar in some acoustic dimension. If so, then in delayed matching-to-sample, the monkey's performance should be predicted by the similarity in the salient acoustic dimension between the sample and subsequent test stimulus, even at very short delays. To test this prediction and isolate the acoustic features relevant to short-term memory, we examined the pattern of errors made by two rhesus monkeys performing a serial, auditory delayed match-to-sample task with interstimulus intervals of 1 s. The analysis revealed that false-alarm errors did indeed result from similarity-based confusion between the sample and the subsequent nonmatch stimuli. Manipulation of the stimuli showed that removal of spectral cues was more disruptive to matching behavior than removal of temporal cues. In addition, the effect of acoustic similarity on false-alarm response was stronger at the first nonmatch stimulus than at the second one. This pattern of errors would be expected if the first nonmatch stimulus overwrote the sample's trace, and suggests that the passively retained trace is not only vulnerable to similarity-based confusion but is also highly susceptible to overwriting.

Comparison of neural responses to cat meows and human vowels in the anterior and posterior auditory field of awake cats

For humans and animals, the ability to discriminate speech and conspecific vocalizations is an important physiological assignment of the auditory system. To reveal the underlying neural mechanism, many electrophysiological studies have investigated the neural responses of the auditory cortex to conspecific vocalizations in monkeys. The data suggest that vocalizations may be hierarchically processed along an anterior/ventral stream from the primary auditory cortex (A1) to the ventral prefrontal cortex. To date, the organization of vocalization processing has not been well investigated in the auditory cortex of other mammals. In this study, we examined the spike activities of single neurons in two early auditory cortical regions with different anteroposterior locations: anterior auditory field (AAF) and posterior auditory field (PAF) in awake cats, as the animals were passively listening to forward and backward conspecific calls (meows) and human vowels. We found that the neural response patterns in PAF were more complex and had longer latency than those in AAF. The selectivity for different vocalizations based on the mean firing rate was low in both AAF and PAF, and not significantly different between them; however, more vocalization information was transmitted when the temporal response profiles were considered, and the maximum transmitted information by PAF neurons was higher than that by AAF neurons. Discrimination accuracy based on the activities of an ensemble of PAF neurons was also better than that of AAF neurons. Our results suggest that AAF and PAF are similar with regard to which vocalizations they represent but differ in the way they represent these vocalizations, and there may be a complex processing stream between them.