Active neural coordination of motor behaviors with internal states.

The brain continuously coordinates skeletomuscular movements with internal physiological states like arousal, but how is this coordination achieved? One possibility is that the brain simply reacts to changes in external and/or internal signals. Another possibility is that it is actively coordinating both external and internal activities. We used functional ultrasound imaging to capture a large medial section of the brain, including multiple cortical and subcortical areas, in marmoset monkeys while monitoring their spontaneous movements and cardiac activity. By analyzing the causal ordering of these different time series, we found that information flowing from the brain to movements and heart-rate fluctuations were significantly greater than in the opposite direction. The brain areas involved in this external versus internal coordination were spatially distinct, but also extensively interconnected. Temporally, the brain alternated between network states for this regulation. These findings suggest that the brain's dynamics actively and efficiently coordinate motor behavior with internal physiology.

A mechanism for punctuating equilibria during mammalian vocal development.

Evolution and development are typically characterized as the outcomes of gradual changes, but sometimes (states of equilibrium can be punctuated by sudden change. Here, we studied the early vocal development of three different mammals: common marmoset monkeys, Egyptian fruit bats, and humans. Consistent with the notion of punctuated equilibria, we found that all three species undergo at least one sudden transition in the acoustics of their developing vocalizations. To understand the mechanism, we modeled different developmental landscapes. We found that the transition was best described as a shift in the balance of two vocalization landscapes. We show that the natural dynamics of these two landscapes are consistent with the dynamics of energy expenditure and information transmission. By using them as constraints for each species, we predicted the differences in transition timing from immature to mature vocalizations. Using marmoset monkeys, we were able to manipulate both infant energy expenditure (vocalizing in an environment with lighter air) and information transmission (closed-loop contingent parental vocal playback). These experiments support the importance of energy and information in leading to punctuated equilibrium states of vocal development.

Arousal dynamics drive vocal production in marmoset monkeys.

Vocal production is the result of interacting cognitive and autonomic processes. Despite claims that changes in one interoceptive state (arousal) govern primate vocalizations, we know very little about how it influences their likelihood and timing. In this study we investigated the role of arousal during naturally occurring vocal production in marmoset monkeys. Throughout each session, naturally occurring contact calls are produced more quickly, and with greater probability, during higher levels of arousal, as measured by heart rate. On average, we observed a steady increase in heart rate 23 s before the production of a call. Following call production, there is a sharp and steep cardiac deceleration lasting ∼8 s. The dynamics of cardiac fluctuations around a vocalization cannot be completely predicted by the animal's respiration or movement. Moreover, the timing of vocal production was tightly correlated to the phase of a 0.1-Hz autonomic nervous system rhythm known as the Mayer wave. Finally, a compilation of the state space of arousal dynamics during vocalization illustrated that perturbations to the resting state space increase the likelihood of a call occurring. Together, these data suggest that arousal dynamics are critical for spontaneous primate vocal production, not only as a robust predictor of the likelihood of vocal onset but also as scaffolding on which behavior can unfold.

Cooperative vocal control in marmoset monkeys via vocal feedback.

Humans adjust speech amplitude as a function of distance from a listener; we do so in a manner that would compensate for such distance. This ability is presumed to be the product of high-level sociocognitive skills. Nonhuman primates are thought to lack such socially related flexibility in vocal production. Using predictions from a simple arousal-based model whereby vocal feedback from a conspecific modulates the drive to produce a vocalization, we tested whether another primate exhibits this type of cooperative vocal control. We conducted a playback experiment with marmoset monkeys and simulated "far-away" and "nearby" conspecifics using contact calls that differed in sound intensity. We found that marmoset monkeys increased the amplitude of their contact calls and produced such calls with shorter response latencies toward more distant conspecifics. The same was not true in response to changing levels of background noise. To account for how simulated conspecific distance can change both the amplitude and timing of vocal responses, we developed a model that incorporates dynamic interactions between the auditory system and limbic "drive" systems. Overall, our data show that, like humans, marmoset monkeys cooperatively control the acoustics of their vocalizations according to changes in listener distance, increasing the likelihood that a conspecific will hear their call. However, we propose that such cooperative vocal control is a system property that does not necessitate any particularly advanced sociocognitive skill. At least in marmosets, this vocal control can be parsimoniously explained by the regulation of arousal states across two interacting individuals via vocal feedback.

Facial expressions and the evolution of the speech rhythm.

In primates, different vocalizations are produced, at least in part, by making different facial expressions. Not surprisingly, humans, apes, and monkeys all recognize the correspondence between vocalizations and the facial postures associated with them. However, one major dissimilarity between monkey vocalizations and human speech is that, in the latter, the acoustic output and associated movements of the mouth are both rhythmic (in the 3- to 8-Hz range) and tightly correlated, whereas monkey vocalizations have a similar acoustic rhythmicity but lack the concommitant rhythmic facial motion. This raises the question of how we evolved from a presumptive ancestral acoustic-only vocal rhythm to the one that is audiovisual with improved perceptual sensitivity. According to one hypothesis, this bisensory speech rhythm evolved through the rhythmic facial expressions of ancestral primates. If this hypothesis has any validity, we expect that the extant nonhuman primates produce at least some facial expressions with a speech-like rhythm in the 3- to 8-Hz frequency range. Lip smacking, an affiliative signal observed in many genera of primates, satisfies this criterion. We review a series of studies using developmental, x-ray cineradiographic, EMG, and perceptual approaches with macaque monkeys producing lip smacks to further investigate this hypothesis. We then explore its putative neural basis and remark on important differences between lip smacking and speech production. Overall, the data support the hypothesis that lip smacking may have been an ancestral expression that was linked to vocal output to produce the original rhythmic audiovisual speech-like utterances in the human lineage.

A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data.

Statistical inference of functional magnetic resonance imaging (fMRI) data is an important tool in neuroscience investigation. One major hypothesis in neuroscience is that the presence or not of a psychiatric disorder can be explained by the differences in how neurons cluster in the brain. Therefore, it is of interest to verify whether the properties of the clusters change between groups of patients and controls. The usual method to show group differences in brain imaging is to carry out a voxel-wise univariate analysis for a difference between the mean group responses using an appropriate test and to assemble the resulting 'significantly different voxels' into clusters, testing again at cluster level. In this approach, of course, the primary voxel-level test is blind to any cluster structure. Direct assessments of differences between groups at the cluster level seem to be missing in brain imaging. For this reason, we introduce a novel non-parametric statistical test called analysis of cluster structure variability (ANOCVA), which statistically tests whether two or more populations are equally clustered. The proposed method allows us to compare the clustering structure of multiple groups simultaneously and also to identify features that contribute to the differential clustering. We illustrate the performance of ANOCVA through simulations and an application to an fMRI dataset composed of children with attention deficit hyperactivity disorder (ADHD) and controls. Results show that there are several differences in the clustering structure of the brain between them. Furthermore, we identify some brain regions previously not described to be involved in the ADHD pathophysiology, generating new hypotheses to be tested. The proposed method is general enough to be applied to other types of datasets, not limited to fMRI, where comparison of clustering structures is of interest.

Vocal communication is multi-sensorimotor coordination within and between individuals.

Speech is an exquisitely coordinated interaction among effectors both within and between individuals. No account of human communication evolution that ignores its foundational multisensory characteristics and cooperative nature will be satisfactory. Here, we describe two additional capacities - rhythmic audiovisual speech and cooperative communication - and suggest that they may utilize the very same or similar circuits as those proposed for vocal learning.

Active Sampling in Primate Vocal Interactions.

Active sensing is a behavioral strategy for exploring the environment. In this study, we show that contact vocal behaviors can be an active sensing mechanism that uses sampling to gain information about the social environment, in particular, the vocal behavior of others. With a focus on the realtime vocal interactions of marmoset monkeys, we contrast active sampling to a vocal accommodation framework in which vocalizations are adjusted simply to maximize responses. We conducted simulations of a vocal accommodation and an active sampling policy and compared them with real vocal exchange data. Our findings support active sampling as the best model for marmoset monkey vocal exchanges. In some cases, the active sampling model was even able to predict the distribution of vocal durations for individuals. These results suggest a new function for primate vocal interactions in which they are used by animals to seek information from social environments.

Prenatal development of neonatal vocalizations.

Human and non-human primates produce rhythmical sounds as soon as they are born. These early vocalizations are important for soliciting the attention of caregivers. How they develop remains a mystery. The orofacial movements necessary for producing these vocalizations have distinct spatiotemporal signatures. Therefore, their development could potentially be tracked over the course of prenatal life. We densely and longitudinally sampled fetal head and orofacial movements in marmoset monkeys using ultrasound imaging. We show that orofacial movements necessary for producing rhythmical vocalizations differentiate from a larger movement pattern that includes the entire head. We also show that signature features of marmoset infant contact calls emerge prenatally as a distinct pattern of orofacial movements. Our results establish that aspects of the sensorimotor development necessary for vocalizing occur prenatally, even before the production of sound.

Much like human babies, newborn monkeys cry and coo to get their caregiver's attention. They all produce these sounds in the same way. They push air from the lungs to vibrate the vocal cords, and adjust the movement of their jaws, lips, tongue and other muscles to create different kinds of sounds. Ultrasounds show that human fetuses begin making crying-like mouth movements during the last trimester of pregnancy. Yet the prenatal development of this crucial skill remains unclear, as most studies of early primate vocalization take place after birth. To explore this question, Narayanan et al. focused on a small species of monkeys known as marmosets. Regular ultrasounds were performed on four pregnant marmosets, starting on the first day the fetuses' faces became visible and ending the day before delivery. The developing marmosets acquired the ability to independently move their mouth from their head over time, a skill crucial for feeding and vocalizing. By the end of pregnancy, a subset of fetal mouth movements were nearly identical to those produced when baby marmosets call for their caregivers after birth. Human ultrasound studies are needed to confirm whether vocal development follows a similar trajectory in our species.This is likely given the developmental similarities between both species. If so, work in marmosets could be helpful to understand how conditions such as cerebral palsy interfere with this process, and to potentially develop early interventions.

Information theoretic interpretation of frequency domain connectivity measures.

In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.

Domestication Phenotype Linked to Vocal Behavior in Marmoset Monkeys.

The domestication syndrome refers to a set of traits that are the by-products of artificial selection for increased tolerance toward humans [1-3]. One hypothesis is that some species, like humans and bonobos, "self-domesticated" and have been under selection for that same suite of domesticated phenotypes [4-8]. However, the evidence for this has been largely circumstantial. Here, we provide evidence that, in marmoset monkeys, the size of a domestication phenotype-a white facial fur patch-is linked to their degree of affiliative vocal responding. During development, the amount of parental vocal feedback experienced influences the rate of growth of this facial white patch, and this suggests a mechanistic link between the two phenotypes, possibly via neural crest cells. Our study provides evidence for links between vocal behavior and the development of morphological phenotypes associated with domestication in a nonhuman primate.

Author Correction: Vocal state change through laryngeal development.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Frequency domain connectivity identification: an application of partial directed coherence in fMRI.

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity.

Vocal Learning: Shaping by Social Reinforcement.

Animals modulate their behavior by interacting with others. Nevertheless, popular theories of vocal learning frequently overlook the role of ongoing social interactions. New research suggests that a social feedback loop between young male zebra finches and adult females guides the process of song learning.

Vocal and locomotor coordination develops in association with the autonomic nervous system.

In adult animals, movement and vocalizations are coordinated, sometimes facilitating, and at other times inhibiting, each other. What is missing is how these different domains of motor control become coordinated over the course of development. We investigated how postural-locomotor behaviors may influence vocal development, and the role played by physiological arousal during their interactions. Using infant marmoset monkeys, we densely sampled vocal, postural and locomotor behaviors and estimated arousal fluctuations from electrocardiographic measures of heart rate. We found that vocalizations matured sooner than postural and locomotor skills, and that vocal-locomotor coordination improved with age and during elevated arousal levels. These results suggest that postural-locomotor maturity is not required for vocal development to occur, and that infants gradually improve coordination between vocalizations and body movement through a process that may be facilitated by arousal level changes.

Vocal state change through laryngeal development.

Across vertebrates, progressive changes in vocal behavior during postnatal development are typically attributed solely to developing neural circuits. How the changing body influences vocal development remains unknown. Here we show that state changes in the contact vocalizations of infant marmoset monkeys, which transition from noisy, low frequency cries to tonal, higher pitched vocalizations in adults, are caused partially by laryngeal development. Combining analyses of natural vocalizations, motorized excised larynx experiments, tensile material tests and high-speed imaging, we show that vocal state transition occurs via a sound source switch from vocal folds to apical vocal membranes, producing louder vocalizations with higher efficiency. We show with an empirically based model of descending motor control how neural circuits could interact with changing laryngeal dynamics, leading to adaptive vocal development. Our results emphasize the importance of embodied approaches to vocal development, where exploiting biomechanical consequences of changing material properties can simplify motor control, reducing the computational load on the developing brain.

Animal Communication: Chit-Chat in Meerkats.

Coordinated behaviors are the hallmark of animal societies. General mechanisms for the emergence of social group dynamics are still unknown. New research suggests that a vocal feedback loop explains the appearance of coordinated vocal exchanges in large groups of meerkats.

[Brief cognitive evaluation of patients attended in a general neurological outpatient clinic]. / Avaliação cognitiva breve de pacientes atendidos em ambulatórios de neurologia geral.

INTRODUCTION: Cognitive evaluation is usually performed in the assessment of patients with suspected dementia, but is not generally performed in patients with other neurological diseases. OBJECTIVE: To investigate the relevance of a systematic cognitive examination in patients with different neurological conditions. METHOD: One-hundred and five patients consecutively attended over a one-year period in a general Neurology outpatient clinic from a public-affiliated hospital, with no complaints of cognitive changes, were submitted to the following cognitive tests: Mini-Mental State Examination (MMSE), digit span (forward and backward), delayed recall of ten simple figures, category fluency and clock drawing. Whenever possible, the cut-off scores were adjusted as function of educational level. RESULTS: Nearly 2/3 of the patients presented impaired performance in at least one of the tests. The MMSE was altered in 20% of the patients. Performance at digit span was impaired in 50.4% of cases (29.5% forward and 20.9% backward), delayed recall in 14.2% of the patients, category fluency in 27.6% and clock drawing in 40.0%. CONCLUSION: These results reinforce the need of including cognitive evaluation as a routine part of the neurological examination, independently of the presence of specific complaints in this domain.

A Statistical Method to Distinguish Functional Brain Networks.

One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001).

Vocal Learning via Social Reinforcement by Infant Marmoset Monkeys.

For over half a century now, primate vocalizations have been thought to undergo little or no experience-dependent acoustic changes during development [1]. If any changes are apparent, then they are routinely (and quite reasonably) attributed to the passive consequences of growth. Indeed, previous experiments on squirrel monkeys and macaque monkeys showed that social isolation [2, 3], deafness [2], cross-fostering [4] and parental absence [5] have little or no effect on vocal development. Here, we explicitly test in marmoset monkeys-a very vocal and cooperatively breeding species [6]-whether the transformation of immature into mature contact calls by infants is influenced by contingent parental vocal feedback. Using a closed-loop design, we experimentally provided more versus less contingent vocal feedback to twin infant marmoset monkeys over their first 2 months of life, the interval during which their contact calls transform from noisy, immature calls to tonal adult-like "phee" calls [7, 8]. Infants who received more contingent feedback had a faster rate of vocal development, producing mature-sounding contact calls earlier than the other twin. The differential rate of vocal development was not linked to genetics, perinatal experience, or body growth; nor did the amount of contingency influence the overall rate of spontaneous vocal production. Thus, we provide the first experimental evidence for production-related vocal learning during the development of a nonhuman primate.