Is the MSB hypothesis (music as a coevolved system for social bonding) testable in the Popperian sense?

"Music As a Coevolved System for Social Bonding" (MSB) is a brilliant synthesis and appealing hypothesis offering insights into the evolution and social bonding of musicality, but is so broad and sweeping it will be challenging to test, prove or falsify in the Popperian sense (Popper, 1959). After general comments, I focus my critique on underlying neurobiological mechanisms, and offer some suggestions for experimental tests of MSB.

Dorsal prefrontal and premotor cortex of the ferret as defined by distinctive patterns of thalamo-cortical projections.

Recent studies of the neurobiology of the dorsal frontal cortex (FC) of the ferret have illuminated its key role in the attention network, top-down cognitive control of sensory processing, and goal directed behavior. To elucidate the neuroanatomical regions of the dorsal FC, and delineate the boundary between premotor cortex (PMC) and dorsal prefrontal cortex (dPFC), we placed retrograde tracers in adult ferret dorsal FC anterior to primary motor cortex and analyzed thalamo-cortical connectivity. Cyto- and myeloarchitectural differences across dorsal FC and the distinctive projection patterns from thalamic nuclei, especially from the subnuclei of the medial dorsal (MD) nucleus and the ventral thalamic nuclear group, make it possible to clearly differentiate three separate dorsal FC fields anterior to primary motor cortex: polar dPFC (dPFCpol), dPFC, and PMC. Based on the thalamic connectivity, there is a striking similarity of the ferret's dorsal FC fields with other species. This possible homology opens up new questions for future comparative neuroanatomical and functional studies.

Dynamics and Hierarchical Encoding of Non-compact Acoustic Categories in Auditory and Frontal Cortex.

Categorical perception is a fundamental cognitive function enabling animals to flexibly assign sounds into behaviorally relevant categories. This study investigates the nature of acoustic category representations, their emergence in an ascending series of ferret auditory and frontal cortical fields, and the dynamics of this representation during passive listening to task-relevant stimuli and during active retrieval from memory while engaging in learned categorization tasks. Ferrets were trained on two auditory Go-NoGo categorization tasks to discriminate two non-compact sound categories (composed of tones or amplitude-modulated noise). Neuronal responses became progressively more categorical in higher cortical fields, especially during task performance. The dynamics of the categorical responses exhibited a cascading top-down modulation pattern that began earliest in the frontal cortex and subsequently flowed downstream to the secondary auditory cortex, followed by the primary auditory cortex. In a subpopulation of neurons, categorical responses persisted even during the passive listening condition, demonstrating memory for task categories and their enhanced categorical boundaries.

What can animal communication teach us about human language?

Language has been considered by many to be uniquely human. Numerous theories for how it evolved have been proposed but rarely tested. The articles in this theme issue consider the extent to which aspects of language, such as vocal learning, phonology, syntax, semantics, intentionality, cognition and neurobiological adaptations, are shared with other animals. By adopting a comparative approach, insights into the mechanisms and origins of human language can be gained. While points of agreement exist among the authors, conflicting viewpoints are expressed on several issues, such as the presence of proto-syntax in animal communication, the neural basis of the Merge operation, and the neurogenetic changes necessary for vocal learning. Future comparative research in animal communication has the potential to teach us even more about the evolution, neurobiology and cognitive basis of human language. This article is part of the theme issue 'What can animal communication teach us about human language?'

Adaptive Efficient Coding of Correlated Acoustic Properties.

Natural sounds such as vocalizations often have covarying acoustic attributes, resulting in redundancy in neural coding. The efficient coding hypothesis proposes that sensory systems are able to detect such covariation and adapt to reduce redundancy, leading to more efficient neural coding. Recent psychoacoustic studies have shown the auditory system can rapidly adapt to efficiently encode two covarying dimensions as a single dimension, following passive exposure to sounds in which temporal and spectral attributes covaried in a correlated fashion. However, these studies observed a cost to this adaptation, which was a loss of sensitivity to the orthogonal dimension. Here we explore the neural basis of this psychophysical phenomenon by recording single-unit responses from the primary auditory cortex in awake ferrets exposed passively to stimuli with two correlated attributes, similar in stimulus design to the psychoacoustic experiments in humans. We found: (1) the signal-to-noise ratio of spike-rate coding of cortical responses driven by sounds with correlated attributes remained unchanged along the exposure dimension, but was reduced along the orthogonal dimension; (2) performance of a decoder trained with spike data to discriminate stimuli along the orthogonal dimension was equally reduced; (3) correlations between neurons tuned to the two covarying attributes decreased after exposure; and (4) these exposure effects still occurred if sounds were correlated along two acoustic dimensions, but varied randomly along a third dimension. These neurophysiological results are consistent with the efficient coding hypothesis and may help deepen our understanding of how the auditory system encodes and represents acoustic regularities and covariance.SIGNIFICANCE STATEMENT The efficient coding (EC) hypothesis (Attneave, 1954; Barlow, 1961) proposes that the neural code in sensory systems efficiently encodes natural stimuli by minimizing the number of spikes to transmit a sensory signal. Results of recent psychoacoustic studies in humans are consistent with the EC hypothesis in that, following passive exposure to stimuli with correlated attributes, the auditory system rapidly adapts so as to more efficiently encode the two covarying dimensions as a single dimension. In the current neurophysiological experiments, using a similar stimulus design and the experimental paradigm to the psychoacoustic studies of Stilp et al. (2010) and Stilp and Kluender (2011, 2012, 2016), we recorded responses from single neurons in the auditory cortex of the awake ferret, showing adaptive efficient neural coding of two correlated acoustic attributes.

Computational Neural Modeling of Auditory Cortical Receptive Fields.

Previous studies have shown that the auditory cortex can enhance the perception of behaviorally important sounds in the presence of background noise, but the mechanisms by which it does this are not yet elucidated. Rapid plasticity of spectrotemporal receptive fields (STRFs) in the primary (A1) cortical neurons is observed during behavioral tasks that require discrimination of particular sounds. This rapid task-related change is believed to be one of the processing strategies utilized by the auditory cortex to selectively attend to one stream of sound in the presence of mixed sounds. However, the mechanism by which the brain evokes this rapid plasticity in the auditory cortex remains unclear. This paper uses a neural network model to investigate how synaptic transmission within the cortical neuron network can change the receptive fields of individual neurons. A sound signal was used as input to a model of the cochlea and auditory periphery, which activated or inhibited integrate-and-fire neuron models to represent networks in the primary auditory cortex. Each neuron in the network was tuned to a different frequency. All neurons were interconnected with excitatory or inhibitory synapses of varying strengths. Action potentials in one of the model neurons were used to calculate the receptive field using reverse correlation. The results were directly compared to previously recorded electrophysiological data from ferrets performing behavioral tasks that require discrimination of particular sounds. The neural network model could reproduce complex STRFs observed experimentally through optimizing the synaptic weights in the model. The model predicts that altering synaptic drive between cortical neurons and/or bottom-up synaptic drive from the cochlear model to the cortical neurons can account for rapid task-related changes observed experimentally in A1 neurons. By identifying changes in the synaptic drive during behavioral tasks, the model provides insights into the neural mechanisms utilized by the auditory cortex to enhance the perception of behaviorally salient sounds.

State-dependent encoding of sound and behavioral meaning in a tertiary region of the ferret auditory cortex.

In higher sensory cortices, there is a gradual transformation from sensation to perception and action. In the auditory system, this transformation is revealed by responses in the rostral ventral posterior auditory field (VPr), a tertiary area in the ferret auditory cortex, which shows long-term learning in trained compared to naïve animals, arising from selectively enhanced responses to behaviorally relevant target stimuli. This enhanced representation is further amplified during active performance of spectral or temporal auditory discrimination tasks. VPr also shows sustained short-term memory activity after target stimulus offset, correlated with task response timing and action. These task-related changes in auditory filter properties enable VPr neurons to quickly and nimbly switch between different responses to the same acoustic stimuli, reflecting either spectrotemporal properties, timing, or behavioral meaning of the sound. Furthermore, they demonstrate an interaction between the dynamics of short-term attention and long-term learning, as incoming sound is selectively attended, recognized, and translated into action.

Laminar profile of task-related plasticity in ferret primary auditory cortex.

Rapid task-related plasticity is a neural correlate of selective attention in primary auditory cortex (A1). Top-down feedback from higher-order cortex may drive task-related plasticity in A1, characterized by enhanced neural representation of behaviorally meaningful sounds during auditory task performance. Since intracortical connectivity is greater within A1 layers 2/3 (L2/3) than in layers 4-6 (L4-6), we hypothesized that enhanced representation of behaviorally meaningful sounds might be greater in A1 L2/3 than L4-6. To test this hypothesis and study the laminar profile of task-related plasticity, we trained 2 ferrets to detect pure tones while we recorded laminar activity across a 1.8 mm depth in A1. In each experiment we analyzed high-gamma local field potentials (LFPs) and multi-unit spiking in response to identical acoustic stimuli during both passive listening and active task performance. We found that neural responses to auditory targets were enhanced during task performance, and target enhancement was greater in L2/3 than in L4-6. Spectrotemporal receptive fields (STRFs) computed from both high-gamma LFPs and multi-unit spiking showed similar increases in auditory target selectivity, also greatest in L2/3. Our results suggest that activity within intracortical networks plays a key role in the underlying neural mechanisms of selective attention.

Implicit Memory for Complex Sounds in Higher Auditory Cortex of the Ferret.

Responses of auditory cortical neurons encode sound features of incoming acoustic stimuli and also are shaped by stimulus context and history. Previous studies of mammalian auditory cortex have reported a variable time course for such contextual effects ranging from milliseconds to minutes. However, in secondary auditory forebrain areas of songbirds, long-term stimulus-specific neuronal habituation to acoustic stimuli can persist for much longer periods of time, ranging from hours to days. Such long-term habituation in the songbird is a form of long-term auditory memory that requires gene expression. Although such long-term habituation has been demonstrated in avian auditory forebrain, this phenomenon has not previously been described in the mammalian auditory system. Utilizing a similar version of the avian habituation paradigm, we explored whether such long-term effects of stimulus history also occur in auditory cortex of a mammalian auditory generalist, the ferret. Following repetitive presentation of novel complex sounds, we observed significant response habituation in secondary auditory cortex, but not in primary auditory cortex. This long-term habituation appeared to be independent for each novel stimulus and often lasted for at least 20 min. These effects could not be explained by simple neuronal fatigue in the auditory pathway, because time-reversed sounds induced undiminished responses similar to those elicited by completely novel sounds. A parallel set of pupillometric response measurements in the ferret revealed long-term habituation effects similar to observed long-term neural habituation, supporting the hypothesis that habituation to passively presented stimuli is correlated with implicit learning and long-term recognition of familiar sounds.SIGNIFICANCE STATEMENT Long-term habituation in higher areas of songbird auditory forebrain is associated with gene expression and is correlated with recognition memory. Similar long-term auditory habituation in mammals has not been previously described. We studied such habituation in single neurons in the auditory cortex of awake ferrets that were passively listening to repeated presentations of various complex sounds. Responses exhibited long-lasting habituation (at least 20 min) in the secondary, but not primary auditory cortex. Habituation ceased when stimuli were played backward, despite having identical spectral content to the original sound. This long-term neural habituation correlated with similar habituation of ferret pupillary responses to repeated presentations of the same stimuli, suggesting that stimulus habituation is retained as a long-term behavioral memory.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.