Morphological basis for the evolution of acoustic diversity in oscine songbirds

Acoustic properties of vocalizations arise through the interplay of neural control with the morphology and biomechanics of the sound generating organ, but in songbirds it is assumed that the main driver of acoustic diversity is variation in telencephalic motor control. Here we show, however, that variation in the composition of the vibrating tissues, the labia, underlies diversity in one acoustic parameter, fundamental frequency (F0) range. Lateral asymmetry and arrangement of fibrous proteins in the labia into distinct layers is correlated with expanded F0 range of species. The composition of the vibrating tissues thus represents an important morphological foundation for the generation of a broad F0 range, indicating that morphological specialization lays the foundation for the evolution of complex acoustic repertoires.     

Abnormal Electrophysiological Motor Responses in Huntington’s Disease: Evidence of Premanifest Compensation

Background

Huntington''s disease (HD) causes progressive motor dysfunction through characteristic atrophy. Changes to neural structure begin in premanifest stages yet individuals are able to maintain a high degree of function, suggesting involvement of supportive processing during motor performance. Electroencephalography (EEG) enables the investigation of subtle impairments at the neuronal level, and possible compensatory strategies, by examining differential activation patterns. We aimed to use EEG to investigate neural motor processing (via the Readiness Potential; RP), premotor processing and sensorimotor integration (Contingent Negative Variation; CNV) during simple motor performance in HD.

Methods

We assessed neural activity associated with motor preparation and processing in 20 premanifest (pre-HD), 14 symptomatic HD (symp-HD), and 17 healthy controls. Participants performed sequential tapping within two experimental paradigms (simple tapping; Go/No-Go). RP and CNV potentials were calculated separately for each group.

Results

Motor components and behavioural measures did not distinguish pre-HD from controls. Compared to controls and pre-HD, symp-HD demonstrated significantly reduced relative amplitude and latency of the RP, whereas controls and pre-HD did not differ. However, early CNV was found to significantly differ between control and pre-HD groups, due to enhanced early CNV in pre-HD.

Conclusions

For the first time, we provide evidence of atypical activation during preparatory processing in pre-HD. The increased activation during this early stage of the disease may reflect ancillary processing in the form of recruitment of additional neural resources for adequate motor preparation, despite atrophic disruption to structure and circuitry. We propose an early adaptive compensation mechanism in pre-HD during motor preparation.     

The role of primary motor cortex in goal-directed movements: insights from neurophysiological studies on non-human primates

Neurophysiological studies on non-human primates have provided a large body of information on the response patterns of neurons in primary motor cortex during volitional motor tasks. Rather than finding a single simple pattern of activity in primary motor cortex neurons, these studies illustrate that neural activity in this area reflects many different types of information, including spatial goals, hand motion, joint motion, force output and electromyographic activity. This richness in the response characteristics of neurons makes estimates of any single variable on motor performance from population signals imprecise and prone to errors. It initially seems puzzling that so many different types of information are represented in primary motor cortex. However, such richness in neural responses reflects its important role in converting high-level behavioral goals generated in other cortical regions into complex spatiotemporal patterns to control not only alpha-motoneuron activity but also other features of spinal processing.     

Two-phase strategy of controlling motor coordination determined by task performance optimality

A quantitative model of optimal coordination between hand transport and grip aperture has been derived in our previous studies of reach-to-grasp movements without utilizing explicit knowledge of the optimality criterion or motor plant dynamics. The model’s utility for experimental data analysis has been demonstrated. Here we show how to generalize this model for a broad class of reaching-type, goal-directed movements. The model allows for measuring the variability of motor coordination and studying its dependence on movement phase. The experimentally found characteristics of that dependence imply that execution noise is low and does not affect motor coordination significantly. From those characteristics it is inferred that the cost of neural computations required for information acquisition and processing is included in the criterion of task performance optimality as a function of precision demand for state estimation and decision making. The precision demand is an additional optimized control variable that regulates the amount of neurocomputational resources activated dynamically. It is shown that an optimal control strategy in this case comprises two different phases. During the initial phase, the cost of neural computations is significantly reduced at the expense of reducing the demand for their precision, which results in speed-accuracy tradeoff violation and significant inter-trial variability of motor coordination. During the final phase, neural computations and thus motor coordination are considerably more precise to reduce the cost of errors in making a contact with the target object. The generality of the optimal coordination model and the two-phase control strategy is illustrated on several diverse examples.     

Lessons for circuit function from large insects: towards understanding the neural basis of motor flexibility

Motor behaviors result from information processing that occurs in multiple neural networks acting at all levels from the initial selection of the behavior to its final generation. A long-standing research interest is how single neural networks can help generate different motor behaviors, that is, the origin of motor flexibility. Modern experimental techniques allow studying neural network activity during the production of multiple motor behaviors. Recent data provide strong evidence that the neural networks controlling insect legs are individually modified in task-dependent and finely tuned fashions. Understanding the mechanistic basis of these neural network modifications will be of particular interest in the upcoming years.     

A neural network model for the intersensory coordination involved in goal-directed movements

A neural network model for a sensorimotor system, which was developed to simulate oriented movements in man, is presented. It is composed of a formal neural network comprising two layers: a sensory layer receiving and processing sensory inputs, and a motor layer driving a simulated arm. The sensory layer is an extension of the topological network previously proposed by Kohonen (1984). Two kinds of sensory modality, proprioceptive and exteroceptive, are used to define the arm position. Each sensory cell receives proprioceptive inputs provided by each arm-joint together with the exteroceptive inputs. This sensory layer is therefore a kind of associative layer which integrates two separate sensory signals relating to movement coding. It is connected to the motor layer by means of adaptive synapses which provide a physical link between a motor activity and its sensory consequences. After a learning period, the spatial map which emerges in the sensory layer clearly depends on the sensory inputs and an associative map of both the arm and the extra-personal space is built up if proprioceptive and exteroceptive signals are processed together. The sensorimotor transformations occuring in the junctions linking the sensory and motor layers are organized in such a manner that the simulated arm becomes able to reach towards and track a target in extra-personal space. Proprioception serves to determine the final arm posture adopted and to correct the ongoing movement in cases where changes in the target location occur. With a view to developing a sensorimotor control system with more realistic salient features, a robotic model was coupled with the formal neural network. This robotic implementation of our model shows the capacity of formal neural networks to control the displacement of mechanical devices.     

Involving the motor system in decision making

The control of behaviour is usually understood in terms of three distinct components: sensory processing, decision making and movement control. Recently, this view has been questioned on the basis of physiological and behavioural data, blurring the distinction between these three stages. This raises the question to what extent the motor system itself can contribute to the interpretation of behavioural situations. To investigate this question we use a neural model of sensory motor integration applied to a behaving mobile robot performing a navigation task. We show that the population response of the motor system provides a substrate for the categorization of behavioural situations. This categorization allows for the assessment of the complexity of a behavioural situation and regulates whether higher-level decision making is required to resolve behavioural conflicts. Our model lends credence to an emerging reconceptualization of behavioural control where the motor system can be considered as part of a high-level perceptual system.     

Mapping information flow in sensorimotor networks

Biological organisms continuously select and sample information used by their neural structures for perception and action, and for creating coherent cognitive states guiding their autonomous behavior. Information processing, however, is not solely an internal function of the nervous system. Here we show, instead, how sensorimotor interaction and body morphology can induce statistical regularities and information structure in sensory inputs and within the neural control architecture, and how the flow of information between sensors, neural units, and effectors is actively shaped by the interaction with the environment. We analyze sensory and motor data collected from real and simulated robots and reveal the presence of information structure and directed information flow induced by dynamically coupled sensorimotor activity, including effects of motor outputs on sensory inputs. We find that information structure and information flow in sensorimotor networks (a) is spatially and temporally specific; (b) can be affected by learning, and (c) can be affected by changes in body morphology. Our results suggest a fundamental link between physical embeddedness and information, highlighting the effects of embodied interactions on internal (neural) information processing, and illuminating the role of various system components on the generation of behavior.     

Integrating neuromorphic action-oriented perceptual inputs to generate a navigation behaviour for a robot

We use neural networks with pointer map architectures to provide simple attentional processing in a robotic task. A pointer map comprises a map of neurons that encode a stimulus. Besides global feedback inhibition, the map receives feedback excitation via a small group of pointer neurons that encode the location of a salient stimulus on the map as a vectorial representation. The pointer neurons are able to apply selective processing to a particular region of the network. The robot uses these properties to manoeuver in relation to an attended object. We implemented a controller composed of two pointer maps, and a motor map. The first pointer map reports the direction of a salient obstacle in a one-dimensional map of distance derived from infrared sensors. The second pointer map reports the direction to potential obstacles in a two-dimensional edge-enhanced image derived from a forward looking CCD-camera. These outputs are applied to a motor map, where they bias the motor control signals issued to the robots wheels, according to navigational intentions.     

New moves in motor control

Motor behaviour results from information processing across multiple neural networks acting at all levels from initial selection of the behaviour to its final generation. Understanding how motor behaviour is produced requires identifying the constituent neurons of these networks, their cellular properties, and their pattern of synaptic connectivity. Neural networks have been traditionally studied with neurophysiological and neuroanatomical approaches. These approaches have been highly successful in particularly suitable 'model' preparations, typically ones in which the numbers of neurons in the networks were relatively small, neural network composition was unvarying across individual animals, and the preparations continued to produce fictive motor patterns in?vitro. However, analysing networks without these characteristics, and analysing the complete ensemble of networks that cooperatively generate behaviours, is difficult with these approaches. Recently developed molecular and neurogenetic tools provide additional avenues for analysing motor networks by allowing individual or groups of neurons within networks to be manipulated in novel ways and allowing experiments to be performed not only in?vitro but also in?vivo. We review here some of the new insights into motor network function that these advances have provided and indicate how these advances might bridge gaps in our understanding of motor control. To these ends, we first review motor neural network organisation highlighting cross-phylum principles. We then use prominent examples from the field to show how neurogenetic approaches can complement classical physiological studies, and identify additional areas where these approaches could be advantageously applied.     

The auditory behaviour of primates: a neuroethological perspective

The ethological approach has already provided rich insights into the auditory neurobiology of a number of different taxa (e.g. birds, frogs and insects). Understanding the ethology of primates is likely to yield similar insights into the specializations of this taxa's auditory system for processing species-specific vocalisations. Here, we review the recent advances made in our understanding of primate vocal perception and its neural basis.     

Acetylcholinesterase in central vocal control nuclei of the zebra finch (<Emphasis Type="Italic">Taeniopygia guttata</Emphasis>)

The distribution of acetylcholinesterase (AChE) in the central vocal control nuclei of the zebra finch was studied using enzyme histochemistry. AChE fibres and cells are intensely labelled in the forebrain nucleus area X, strongly labelled in high vocal centre (HVC) perikarya, and moderately to lightly labelled in the somata and neuropil of vocal control nuclei robust nucleus of arcopallium (RA), medial magnocellular nucleus of the anterior nidopallium (MMAN) and lateral magnocellular nucleus of the anterior nidopallium (LMAN). The identified sites of cholinergic and/or cholinoceptive neurons are similar to the cholinergic presence in vocal control regions of other songbirds such as the song sparrow, starling and another genus of the zebra finch (Poephila guttata), and to a certain extent in parallel vocal control regions in vocalizing birds such as the budgerigar. AChE presence in the vocal control system suggests innervation by either afferent projecting cholinergic systems and/or local circuit cholinergic neurons. Co-occurrence with choline acetyltransferase (ChAT) indicates efferent cholinergic projections. The cholinergic presence in parts of the zebra finch vocal control system, such as the area X, that is also intricately wired with parts of the basal ganglia, the descending fibre tracts and brain stem nuclei could underlie this circuitry’s involvement in sensory processing and motor control of song.     

Information processing in neural networks by means of controlled dynamic regimes

This paper is concerned with the modeling of neural systems regarded as information processing entities. I investigate the various dynamic regimes that are accessible in neural networks considered as nonlinear adaptive dynamic systems. The possibilities of obtaining steady, oscillatory or chaotic regimes are illustrated with different neural network models. Some aspects of the dependence of the dynamic regimes upon the synaptic couplings are examined. I emphasize the role that the various regimes may play to support information processing abilities. I present an example where controlled transient evolutions in a neural network, are used to model the regulation of motor activities by the cerebellar cortex.     

Rhythmic cortical neurons increase their oscillations and sculpt basal ganglia signaling during motor learning

The function and modulation of neural circuits underlying motor skill may involve rhythmic oscillations (Feller, 1999 ; Marder and Goaillard, 2006 ; Churchland et al., 2012 ). In the proposed pattern generator for birdsong, the cortical nucleus HVC, the frequency and power of oscillatory bursting during singing increases with development (Crandall et al., 2007 ; Day et al., 2009 ). We examined the maturation of cellular activity patterns that underlie these changes. Single unit ensemble recording combined with antidromic identification (Day et al., 2011 ) was used to study network development in anesthetized zebra finches. Autocovariance quantified oscillations within single units. A subset of neurons oscillated in the theta/alpha/mu/beta range (8–20 Hz), with greater power in adults compared to juveniles. Across the network, the normalized oscillatory power in the 8–20 Hz range was greater in adults than juveniles. In addition, the correlated activity between rhythmic neuron pairs increased with development. We next examined the functional impact of the oscillators on the output neurons of HVC. We found that the firing of oscillatory neurons negatively correlated with the activity of cortico‐basal ganglia neurons (HVC_Xs), which project to Area X (the song basal ganglia). If groups of oscillators work together to tonically inhibit and precisely control the spike timing of adult HVC_Xs with coordinated release from inhibition, then the activity of HVC_Xs in juveniles should be decreased relative to adults due to uncorrelated, tonic inhibition. Consistent with this hypothesis, HVC_Xs had lower activity in juveniles. These data reveal network changes that shape cortical‐to‐basal ganglia signaling during motor learning. © 2013 Wiley Periodicals, Inc. Develop Neurobiol 73: 754–768, 2013     

A functional role for modality-specific perceptual systems in conceptual representations

Theories of embodied cognition suggest that conceptual processing relies on the same neural resources that are utilized for perception and action. Evidence for these perceptual simulations comes from neuroimaging and behavioural research, such as demonstrations of somatotopic motor cortex activations following the presentation of action-related words, or facilitation of grasp responses following presentation of object names. However, the interpretation of such effects has been called into question by suggestions that neural activation in modality-specific sensorimotor regions may be epiphenomenal, and merely the result of spreading activations from "disembodied", abstracted, symbolic representations. Here, we present two studies that focus on the perceptual modalities of touch and proprioception. We show that in a timed object-comparison task, concurrent tactile or proprioceptive stimulation to the hands facilitates conceptual processing relative to control stimulation. This facilitation occurs only for small, manipulable objects, where tactile and proprioceptive information form part of the multimodal perceptual experience of interacting with such objects, but facilitation is not observed for large, nonmanipulable objects where such perceptual information is uninformative. Importantly, these facilitation effects are independent of motor and action planning, and indicate that modality-specific perceptual information plays a functionally constitutive role in our mental representations of objects, which supports embodied assumptions that concepts are grounded in the same neural systems that govern perception and action.     

Cortical activation induced by intraoral stimulation with water in humans

Studies of gustatory processing frequently utilize water as a control stimulus. However, the neural representations of intraoral stimulation with water have received little attention. We report a series of positron emission tomography studies involving intraoral stimulation with deionized distilled water. Attempting to taste water produced large, bilateral activations in insular, opercular, Rolandic and cerebellar cortices relative to resting with eyes closed or 'smelling' odorless air. The magnitude and volume of activation was substantially reduced when tasting water was contrasted with voluntary swallowing. This indicates that much of the activity induced by water reflects intraoral somatosensory or motor processing. Nevertheless, portions of the insula, operculum, post-central gyrus and cerebellum remained significantly activated in the contrast between 'tasting' water and swallowing. This activity appears to represent a specific neural correlate of fluid stimulation, and may reflect aspects of trigeminal, gustatory or thermal coding. These findings emphasize the large volume of cortex dedicated to intraoral processing, and highlight the importance of controlling for nongustatory factors in studies of gustation.     

Neuropsychological studies of perception and visuomotor control.

According to recent conceptualizations, there are two separate cortical visual systems--each with its own distinctive cortical and subcortical links--and these two systems respectively serve the functions of perception and of motor control. These ideas have been arrived at through a confluence of neuroanatomical, electrophysiological, behavioural, and neuropsychological research. It is proposed that this distinction between two broad purposes of vision and their neural bases can provide useful working procedures for analysing both: (i) the nature of visuomotor processing in the normal brain; and also (ii) the abnormal patterns of visual processing that are seen in certain neurological conditions.     

Insect–machine hybrid system for understanding and evaluating sensory-motor control by sex pheromone in Bombyx mori

To elucidate the dynamic information processing in a brain underlying adaptive behavior, it is necessary to understand the behavior and corresponding neural activities. This requires animals which have clear relationships between behavior and corresponding neural activities. Insects are precisely such animals and one of the adaptive behaviors of insects is high-accuracy odor source orientation. The most direct way to know the relationships between neural activity and behavior is by recording neural activities in a brain from freely behaving insects. There is also a method to give stimuli mimicking the natural environment to tethered insects allowing insects to walk or fly at the same position. In addition to these methods an ‘insect–machine hybrid system’ is proposed, which is another experimental system meeting the conditions necessary for approaching the dynamic processing in the brain of insects for generating adaptive behavior. This insect–machine hybrid system is an experimental system which has a mobile robot as its body. The robot is controlled by the insect through its behavior or the neural activities recorded from the brain. As we can arbitrarily control the motor output of the robot, we can intervene at the relationship between the insect and the environmental conditions.     

Comparative approaches to avian song system function: insights into auditory and motor processing

Many fundamental advances in our understanding of basic neural function have been made using bird song learning and performance as a model system. These advances have included a greater understanding of higher-order neural processing, developmental and hormonal influences on behavior, and the realization that neurogenesis plays an important role in normal adult brain function. The great diversity of passerine birds and song-related behaviors they exhibit suggest that oscine songbirds are ideally suited for comparative studies. While the comparative approach has been used successfully in the past to study song-related phenomena at anatomical and behavioral levels, it has been underutilized in addressing questions at the neurophysiological level. Most neurophysiological studies of songbird auditory and motor processing have been performed in one species, the zebra finch (Taeniopygia guttata). We present and compare neurophysiological studies we have performed in zebra finches and song sparrows (Melospiza melodia), species that differ markedly in their singing behavior and song repertoire characteristics. Interspecific similarities, and striking differences, in song neural processing are apparent. While preliminary, these data suggest that comparative neurophysiological studies of species carefully chosen for their vocal repertoire and singing behavior will contribute significantly to our understanding of vertebrate sensory and motor neural processing.     

Adult bengalese finches (Lonchura striata var. domestica) require real-time auditory feedback to produce normal song syntax

Songbirds develop their songs by imitating songs of adults. For song learning to proceed normally, the bird's hearing must remain intact throughout the song development process. In many species, song learning takes place during one period early in life, and no more new song elements are learned thereafter. In these so-called close-ended learners, it has long been assumed that once song development is complete, audition is no longer necessary to maintain the motor patterns of full song. However, many of these close-ended learners maintain plasticity in overall song organization; the number and the sequence of song elements included in a song of an individual vary from one utterance to another, although no new song elements are added or lost in adulthood. It is conceivable that these species rely on continued auditory feedback to produce normal song syntax. The Bengalese finch is a close-ended learner that produces considerably variable songs as an adult. In the present study, we found that Bengalese finches require real-time auditory feedback for motor control even after song learning is complete; deafening adult finches resulted in development of abnormal song syntax in as little as 5 days. We also found that there was considerable individual variation in the degree of song deterioration after deafening. The neural mechanisms underlying adult song production in different species of songbirds may be more diverse than has been traditionally considered. © 1997 John Wiley & Sons, Inc. J Neurobiol 33: 343–356, 1997