Distinct neuron populations for simple and compound calls in the primary auditory cortex of awake marmosets

Unique Cortical and Subcortical Activation Patterns for Different Conspecific Calls in Marmosets

The common marmoset (Callithrix jacchus) is known for its highly vocal nature, displaying a diverse range of calls. Functional imaging in marmosets has shown that the processing of conspecific calls activates a brain network that includes fronto-temporal areas. It is currently unknown whether different call types activate the same or different networks. In this study, nine adult marmosets (four females) were exposed to four common vocalizations (phee, chatter, trill, and twitter), and their brain responses were recorded using event-related functional magnetic resonance imaging at 9.4 T. We found robust activations in the auditory cortices, encompassing core, belt, and parabelt regions, and in subcortical areas like the inferior colliculus, medial geniculate nucleus, and amygdala in response to these calls. Although a common network was engaged, distinct activity patterns were evident for different vocalizations that could be distinguished by a 3D convolutional neural network, indicating unique neural processing for each vocalization. Our findings also indicate the involvement of the cerebellum and medial prefrontal cortex in distinguishing particular vocalizations from others.

Sparse representation of neurons for encoding complex sounds in the auditory cortex

Listening in complex sound environments requires rapid segregation of different sound sources, e.g., having a conversation with multiple speakers or other environmental sounds. Efficient processing requires fast encoding of inputs to adapt to target sounds and identify relevant information from past experiences. This adaptation process represents an early phase of implicit learning of the sound statistics to form auditory memory. The auditory cortex (ACtx) plays a crucial role in this implicit learning process, but the underlying circuits are unknown. In awake mice, we recorded neuronal responses in different ACtx subfields using in vivo 2-photon imaging of excitatory and inhibitory (parvalbumin; PV) neurons. We used a paradigm adapted from human studies that induced rapid implicit learning from passively presented complex sounds and imaged A1 Layer 4 (L4), A1 L2/3, and A2 L2/3. In this paradigm, a frozen spectro-temporally complex 'Target' sound randomly re-occurred within a stream of other random complex sounds. All ACtx subregions contained distinct groups of cells specifically responsive to complex acoustic sequences, indicating that even thalamocortical input layers (A1 L4) respond to complex sounds. Subgroups of excitatory and inhibitory cells in all subfields showed decreased responses for re-occurring Target sounds, indicating that ACtx is highly involved in the early implicit learning phase. At the population level, activity was more decorrelated to Target sounds independent of the duration of frozen token, subregions, and cell type. These findings suggest that ACtx and its input layers contribute to the early phase of auditory memory for complex sounds, suggesting a parallel strategy across ACtx areas and between excitatory and inhibitory neurons.

Representation of conspecific vocalizations in amygdala of awake marmosets

Human speech and animal vocalizations are important for social communication and animal survival. Neurons in the auditory pathway are responsive to a range of sounds, from elementary sound features to complex acoustic sounds. For social communication, responses to distinct patterns of vocalization are usually highly specific to an individual conspecific call, in some species. This includes the specificity of sound patterns and embedded biological information. We conducted single-unit recordings in the amygdala of awake marmosets and presented calls used in marmoset communication, calls of other species and calls from specific marmoset individuals. We found that some neurons (47/262) in the amygdala distinguished 'Phee' calls from vocalizations of other animals and other types of marmoset vocalizations. Interestingly, a subset of Phee-responsive neurons (22/47) also exhibited selectivity to one out of the three Phees from two different 'caller' marmosets. Our findings suggest that, while it has traditionally been considered the key structure in the limbic system, the amygdala also represents a critical stage of socially relevant auditory perceptual processing.

The neurobiology of vocal communication in marmosets

An increasingly popular animal model for studying the neural basis of social behavior, cognition, and communication is the common marmoset (Callithrix jacchus). Interest in this New World primate across neuroscience is now being driven by their proclivity for prosociality across their repertoire, high volubility, and rapid development, as well as their amenability to naturalistic testing paradigms and freely moving neural recording and imaging technologies. The complement of these characteristics set marmosets up to be a powerful model of the primate social brain in the years to come. Here, we focus on vocal communication because it is the area that has both made the most progress and illustrates the prodigious potential of this species. We review the current state of the field with a focus on the various brain areas and networks involved in vocal perception and production, comparing the findings from marmosets to other animals, including humans.

A vocalization-processing network in marmosets

Vocalizations play an important role in the daily life of primates and likely form the basis of human language. Functional imaging studies have demonstrated that listening to voices activates a fronto-temporal voice perception network in human participants. Here, we acquired whole-brain ultrahigh-field (9.4 T) fMRI in awake marmosets (Callithrix jacchus) and demonstrate that these small, highly vocal New World primates possess a similar fronto-temporal network, including subcortical regions, that is activated by the presentation of conspecific vocalizations. The findings suggest that the human voice perception network has evolved from an ancestral vocalization-processing network that predates the separation of New and Old World primates.

Sound localization acuity of the common marmoset (Callithrix jacchus)

The common marmoset (Callithrix jacchus) is a small arboreal New World primate which has emerged as a promising model in auditory neuroscience. One potentially useful application of this model system is in the study of the neural mechanism underlying spatial hearing in primate species, as the marmosets need to localize sounds to orient their head to events of interest and identify their vocalizing conspecifics that are not visible. However, interpretation of neurophysiological data on sound localization requires an understanding of perceptual abilities, and the sound localization behavior of marmosets has not been well studied. The present experiment measured sound localization acuity using an operant conditioning procedure in which marmosets were trained to discriminate changes in sound location in the horizontal (azimuth) or vertical (elevation) dimension. Our results showed that the minimum audible angle (MAA) for horizontal and vertical discrimination was 13.17° and 12.53°, respectively, for 2 to 32 kHz Gaussian noise. Removing the monaural spectral cues tended to increase the horizontal localization acuity (11.31°). Marmosets have larger horizontal MAA (15.54°) in the rear than the front. Removing the high-frequency (> 26 kHz) region of the head-related transfer function (HRTF) affected vertical acuity mildly (15.76°), but removing the first notch (12-26 kHz) region of HRTF substantially reduced the vertical acuity (89.01°). In summary, our findings indicate that marmosets' spatial acuity is on par with other species of similar head size and field of best vision, and they do not appear to use monaural spectral cues for horizontal discrimination but rely heavily on first notch region of HRTF for vertical discrimination.

Auditory memory of complex sounds in sparsely distributed, highly correlated neurons in the auditory cortex

Listening in complex sound environments requires rapid segregation of different sound sources e.g., speakers from each other, speakers from other sounds, or different instruments in an orchestra, and also adjust auditory processing on the prevailing sound conditions. Thus, fast encoding of inputs and identifying and adapting to reoccurring sounds are necessary for efficient and agile sound perception. This adaptation process represents an early phase of developing implicit learning of sound statistics and thus represents a form of auditory memory. The auditory cortex (ACtx) is known to play a key role in this encoding process but the underlying circuits and if hierarchical processing exists are not known. To identify ACtx regions and cells involved in this process, we simultaneously imaged population of neurons in different ACtx subfields using in vivo 2-photon imaging in awake mice. We used an experimental stimulus paradigm adapted from human studies that triggers rapid and robust implicit learning to passively present complex sounds and imaged A1 Layer 4 (L4), A1 L2/3, and A2 L2/3. In this paradigm, a frozen spectro-temporally complex 'Target' sound would be randomly re-occurring within a stream of random other complex sounds. We find distinct groups of cells that are specifically responsive to complex acoustic sequences across all subregions indicating that even the initial thalamocortical input layers (A1 L4) respond to complex sounds. Cells in all imaged regions showed decreased response amplitude for reoccurring Target sounds indicating that a memory signature is present even in the thalamocortical input layers. On the population level we find increased synchronized activity across cells to the Target sound and that this synchronized activity was more consistent across cells regardless of the duration of frozen token within Target sounds in A2, compared to A1. These findings suggest that ACtx and its input layers play a role in auditory memory for complex sounds and suggest a hierarchical structure of processes for auditory memory.

Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.

Constructing the hierarchy of predictive auditory sequences in the marmoset brain

Our brains constantly generate predictions of sensory input that are compared with actual inputs, propagate the prediction-errors through a hierarchy of brain regions, and subsequently update the internal predictions of the world. However, the essential feature of predictive coding, the notion of hierarchical depth and its neural mechanisms, remains largely unexplored. Here, we investigated the hierarchical depth of predictive auditory processing by combining functional magnetic resonance imaging (fMRI) and high-density whole-brain electrocorticography (ECoG) in marmoset monkeys during an auditory local-global paradigm in which the temporal regularities of the stimuli were designed at two hierarchical levels. The prediction-errors and prediction updates were examined as neural responses to auditory mismatches and omissions. Using fMRI, we identified a hierarchical gradient along the auditory pathway: midbrain and sensory regions represented local, shorter-time-scale predictive processing followed by associative auditory regions, whereas anterior temporal and prefrontal areas represented global, longer-time-scale sequence processing. The complementary ECoG recordings confirmed the activations at cortical surface areas and further differentiated the signals of prediction-error and update, which were transmitted via putative bottom-up γ and top-down β oscillations, respectively. Furthermore, omission responses caused by absence of input, reflecting solely the two levels of prediction signals that are unique to the hierarchical predictive coding framework, demonstrated the hierarchical top-down process of predictions in the auditory, temporal, and prefrontal areas. Thus, our findings support the hierarchical predictive coding framework, and outline how neural networks and spatiotemporal dynamics are used to represent and arrange a hierarchical structure of auditory sequences in the marmoset brain.