Calibration of the head direction network: a role for symmetric angular head velocity cells

Continuous attractor networks require calibration. Computational models of the head direction (HD) system of the rat usually assume that the connections that maintain HD neuron activity are pre-wired and static. Ongoing activity in these models relies on precise continuous attractor dynamics. It is currently unknown how such connections could be so precisely wired, and how accurate calibration is maintained in the face of ongoing noise and perturbation. Our adaptive attractor model of the HD system that uses symmetric angular head velocity (AHV) cells as a training signal shows that the HD system can learn to support stable firing patterns from poorly-performing, unstable starting conditions. The proposed calibration mechanism suggests a requirement for symmetric AHV cells, the existence of which has previously been unexplained, and predicts that symmetric and asymmetric AHV cells should be distinctly different (in morphology, synaptic targets and/or methods of action on postsynaptic HD cells) due to their distinctly different functions.     

Neural mechanisms of mother–infant bonding and pair bonding: Similarities,differences, and broader implications

This article is part of a Special Issue “Parental Care”.Mother–infant bonding is a characteristic of virtually all mammals. The maternal neural system may have provided the scaffold upon which other types of social bonds in mammals have been built. For example, most mammals exhibit a polygamous mating system, but monogamy and pair bonding between mating partners occur in ~ 5% of mammalian species. In mammals, it is plausible that the neural mechanisms that promote mother–infant bonding have been modified by natural selection to establish the capacity to develop a selective bond with a mate during the evolution of monogamous mating strategies. Here we compare the details of the neural mechanisms that promote mother–infant bonding in rats and other mammals with those that underpin pair bond formation in the monogamous prairie vole. Although details remain to be resolved, remarkable similarities and a few differences between the mechanisms underlying these two types of bond formation are revealed. For example, amygdala and nucleus accumbens–ventral pallidum (NA–VP) circuits are involved in both types of bond formation, and dopamine and oxytocin actions within NA appear to promote the synaptic plasticity that allows either infant or mating partner stimuli to persistently activate NA–VP attraction circuits, leading to an enduring social attraction and bonding. Further, although the medial preoptic area is essential for maternal behavior, its role in pair bonding remains to be determined. Our review concludes by examining the broader implications of this comparative analysis, and evidence is provided that the maternal care system may have also provided the basic neural foundation for other types of strong social relationships, beyond pair bonding, in mammals, including humans.     

A model of head direction and landmark coding in complex environments

Environmental information is required to stabilize estimates of head direction (HD) based on angular path integration. However, it is unclear how this happens in real-world (visually complex) environments. We present a computational model of how visual feedback can stabilize HD information in environments that contain multiple cues of varying stability and directional specificity. We show how combinations of feature-specific visual inputs can generate a stable unimodal landmark bearing signal, even in the presence of multiple cues and ambiguous directional specificity. This signal is associated with the retrosplenial HD signal (inherited from thalamic HD cells) and conveys feedback to the subcortical HD circuitry. The model predicts neurons with a unimodal encoding of the egocentric orientation of the array of landmarks, rather than any one particular landmark. The relationship between these abstract landmark bearing neurons and head direction cells is reminiscent of the relationship between place cells and grid cells. Their unimodal encoding is formed from visual inputs via a modified version of Oja’s Subspace Algorithm. The rule allows the landmark bearing signal to disconnect from directionally unstable or ephemeral cues, incorporate newly added stable cues, support orientation across many different environments (high memory capacity), and is consistent with recent empirical findings on bidirectional HD firing reported in the retrosplenial cortex. Our account of visual feedback for HD stabilization provides a novel perspective on neural mechanisms of spatial navigation within richer sensory environments, and makes experimentally testable predictions.     

Bumblebee Homing: The Fine Structure of Head Turning Movements

Changes in flight direction in flying insects are largely due to roll, yaw and pitch rotations of their body. Head orientation is stabilized for most of the time by counter rotation. Here, we use high-speed video to analyse head- and body-movements of the bumblebee Bombus terrestris while approaching and departing from a food source located between three landmarks in an indoor flight-arena. The flight paths consist of almost straight flight segments that are interspersed with rapid turns. These short and fast yaw turns (“saccades”) are usually accompanied by even faster head yaw turns that change gaze direction. Since a large part of image rotation is thereby reduced to brief instants of time, this behavioural pattern facilitates depth perception from visual motion parallax during the intersaccadic intervals. The detailed analysis of the fine structure of the bees’ head turning movements shows that the time course of single head saccades is very stereotypical. We find a consistent relationship between the duration, peak velocity and amplitude of saccadic head movements, which in its main characteristics resembles the so-called "saccadic main sequence" in humans. The fact that bumblebee head saccades are highly stereotyped as in humans, may hint at a common principle, where fast and precise motor control is used to reliably reduce the time during which the retinal images moves.     

Quantification of the segmental kinematics of spontaneous infant movements

This article introduces a method to capture the movements of the upper and the lower limb of infants using an electromagnetic tracking system and to reliably calculate the segmental kinematics. Analysis of the spontaneous movements of infants is important e.g. in the context of the "General Movement Analysis", which aims at the early diagnosis of motor dysfunctions. Due to special constraints regarding infant anatomy, previous approaches based on optical tracking could only gather position data of the infant' segments, whereas with this method in addition relative segment angles can be calculated. The spontaneous movements of the infant and simple calibration movements of the hand and the foot are used to calculate the joint centers and the joint axes of a multi-segmental chain model. The quality of the calibration movements is assessed at calibration time by calculating the root mean square deviation from the total least squares regression plane. The general accuracy of the recording is evaluated by the difference between recorded and estimated sensor positions and the difference between recorded and estimated sensor orientations. Movements of 20 infants between term and 3 months post term age were recorded and processed. A first application illustrates how abnormal movement patterns are manifested in the segmental kinematics. The results show that the presented method is a practicable and reliable way to record spontaneous infant movements and to calculate the segmental kinematics.     

Basal ganglia neural mechanisms of natural movement sequences

Natural rodent grooming and other instinctive behavior serves as a natural model of complex movement sequences. Rodent grooming has syntactic (rule-driven) sequences and more random movement patterns. Both incorporate the same movements--only the serial structure differs. Recordings of neural activity in the dorsolateral striatum and the substantia nigra pars reticulata indicate preferential activation during syntactic sequences over more random sequences. Neurons that are responsive during syntactic grooming sequences are often unresponsive or have reverse activation profiles during kinematically similar movements that occur in flexible or random grooming sequences. Few neurons could be categorized as strictly movement related--instead they were activated only in the context of particular sequential patterns of movements. Particular sequential patterns included "syntactic chain" grooming sequences of paw, head, and body movements and also "warm-up" sequences, which consist of head and body/limb movements that precede locomotion after a period of quiet resting (Golani 1992). Activation during warm-up was less intense and less frequent than during grooming sequences, but both sequences activated neurons above baseline levels, and the same neurons sometimes responded to both sequences. The fact that striatal neurons code 2 natural sequences which are made up of different constituent movements suggests that the basal ganglia may have a generalized role in sequence control. The basal ganglia are modulated by the context of the sequence and may play an executive function in the complex natural patterns of sequenced behaviour.     

Intrinsic and synaptic plasticity in the vestibular system

The vestibular system provides an attractive model for understanding how changes in cellular and synaptic activity influence learning and memory in a quantifiable behavior, the vestibulo-ocular reflex. The vestibulo-ocular reflex produces eye movements that compensate for head motion; simple yet powerful forms of motor learning calibrate the circuit throughout life. Learning in the vestibulo-ocular reflex depends initially on the activity of Purkinje cells in the cerebellar flocculus, but consolidated memories appear to be stored downstream of Purkinje cells, probably in the vestibular nuclei. Recent studies have demonstrated that the neurons of the vestibular nucleus possess the capacity for both synaptic and intrinsic plasticity. Mechanistic analyses of a novel form of firing rate potentiation in neurons of the vestibular nucleus have revealed new rules of plasticity that could apply to spontaneously firing neurons in other parts of the brain.     

Influence of closed skill and open skill warm-ups on the performance of speed, change of direction speed, vertical jump, and reactive agility in team sport athletes

In this study, we evaluated the efficacy of two different dynamic warm-up conditions, one that was inclusive of open skills (i.e., reactive movements) and one that included only preplanned dynamic activities (i.e., closed skills) on the performance of speed, change of direction speed, vertical jump, and reactive agility in team sport athletes. Fourteen (six male, eight female) junior (mean +/- SD age, 16.3 +/- 0.7 year) basketball players participated in this study. Testing was conducted on 2 separate days using a within-subjects cross-over study design. Each athlete performed a standardized 7-minute warm-up consisting of general dynamic movements and stretching. After the general warm-up, athletes were randomly allocated into one of two groups that performed a dynamic 15-minute warm-up consisting entirely of open or closed skills. Each of the warm-up conditions consisted of five activities of 3 minute duration. At the completion of the warm-up protocol, players completed assessments of reactive agility, speed (5-, 10-, and 20-m sprints), change of direction speed (T-test), and vertical jump. No significant differences (p > 0.05) were detected among warm-up conditions for speed, vertical jump, change of direction speed, and reactive agility performances. The results of this study demonstrate that either open skill or closed skill warm-ups can be used effectively for team sport athletes without compromising performance on open skill and closed skill tasks.     

Gastrulation dynamics: cells move into focus

During vertebrate gastrulation, a relatively limited number of blastodermal cells undergoes a stereotypical set of cellular movements that leads to formation of the three germ layers: ectoderm, mesoderm and endoderm. Gastrulation, therefore, provides a unique developmental system in which to study cell movements in vivo in a fairly simple cellular context. Recent advances have been made in elucidating the cellular and molecular mechanisms that underlie cell movements during zebrafish gastrulation. These findings can be compared with observations made in other model systems to identify potential general mechanisms of cell migration during development.     

Variables Contributing to the Coordination of Rapid Eye/Head Gaze Shifts

In this article results of several published studies are synthesized in order to address the neural system for the determination of eye and head movement amplitudes of horizontal eye/head gaze shifts with arbitrary initial head and eye positions. Target position, initial head position, and initial eye position span the space of physical parameters for a planned eye/head gaze saccade. The principal result is that a functional mechanism for determining the amplitudes of the component eye and head movements must use the entire space of variables. Moreover, it is shown that amplitudes cannot be determined additively by summing contributions from single variables. Many earlier models calculate amplitudes as a function of one or two variables and/or restrict consideration to best-fit linear formulae. Our analysis systematically eliminates such models as candidates for a system that can generate appropriate movements for all possible initial conditions. The results of this study are stated in terms of properties of the response system. Certain axiom sets for the intrinsic organization of the response system obey these properties. We briefly provide one example of such an axiomatic model. The results presented in this article help to characterize the actual neural system for the control of rapid eye/head gaze shifts by showing that, in order to account for behavioral data, certain physical quantities must be represented in and used by the neural system. Our theoretical analysis generates predictions and identifies gaps in the data. We suggest needed experiments.     

Calibration of a Hall effect displacement measurement system for complex motion analysis using a neural network

Biomechanics studies often require the analysis of position and orientation. Although a variety of transducer and camera systems can be utilized, a common inexpensive alternative is the Hall effect sensor. Hall effect sensors have been used extensively for one-dimensional position analysis but their non-linear behavior and cross-talk effects make them difficult to calibrate for effective and accurate two- and three-dimensional position and orientation analysis. The aim of this study was to develop and calibrate a displacement measurement system for a hydraulic-actuation joystick used for repetitive motion analysis of heavy equipment operators. The system utilizes an array of four Hall effect sensors that are all active during any joystick movement. This built-in redundancy allows the calibration to utilize fully connected feed forward neural networks in conjunction with a Microscribe 3D digitizer. A fully connected feed forward neural network with one hidden layer containing five neurons was developed. Results indicate that the ability of the neural network to accurately predict the x, y and z coordinates of the joystick handle was good with r(2) values of 0.98 and higher. The calibration technique was found to be equally as accurate when used on data collected 5 days after the initial calibration, indicating the system is robust and stable enough to not require calibration every time the joystick is used. This calibration system allowed an infinite number of joystick orientations and positions to be found within the range of joystick motion.     

Integrated mechanisms of anticipation and rate-of-change computations in cortical circuits

Local neocortical circuits are characterized by stereotypical physiological and structural features that subserve generic computational operations. These basic computations of the cortical microcircuit emerge through the interplay of neuronal connectivity, cellular intrinsic properties, and synaptic plasticity dynamics. How these interacting mechanisms generate specific computational operations in the cortical circuit remains largely unknown. Here, we identify the neurophysiological basis of both the rate of change and anticipation computations on synaptic inputs in a cortical circuit. Through biophysically realistic computer simulations and neuronal recordings, we show that the rate-of-change computation is operated robustly in cortical networks through the combination of two ubiquitous brain mechanisms: short-term synaptic depression and spike-frequency adaptation. We then show how this rate-of-change circuit can be embedded in a convergently connected network to anticipate temporally incoming synaptic inputs, in quantitative agreement with experimental findings on anticipatory responses to moving stimuli in the primary visual cortex. Given the robustness of the mechanism and the widespread nature of the physiological machinery involved, we suggest that rate-of-change computation and temporal anticipation are principal, hard-wired functions of neural information processing in the cortical microcircuit.     

Robust spatial working memory through homeostatic synaptic scaling in heterogeneous cortical networks

The concept of bell-shaped persistent neural activity represents a cornerstone of the theory for the internal representation of analog quantities, such as spatial location or head direction. Previous models, however, relied on the unrealistic assumption of network homogeneity. We investigate this issue in a network model where fine tuning of parameters is destroyed by heterogeneities in cellular and synaptic properties. Heterogeneities result in the loss of stored spatial information in a few seconds. Accurate encoding is recovered when a homeostatic mechanism scales the excitatory synapses to each cell to compensate for the heterogeneity in cellular excitability and synaptic inputs. Moreover, the more realistic model produces a wide diversity of tuning curves, as commonly observed in recordings from prefrontal neurons. We conclude that recurrent attractor networks in conjunction with appropriate homeostatic mechanisms provide a robust, biologically plausible theoretical framework for understanding the neural circuit basis of spatial working memory.     

Plasticity of functional connectivity in the adult spinal cord

This paper emphasizes several characteristics of the neural control of locomotion that provide opportunities for developing strategies to maximize the recovery of postural and locomotor functions after a spinal cord injury (SCI). The major points of this paper are: (i) the circuitry that controls standing and stepping is extremely malleable and reflects a continuously varying combination of neurons that are activated when executing stereotypical movements; (ii) the connectivity between neurons is more accurately perceived as a functional rather than as an anatomical phenomenon; (iii) the functional connectivity that controls standing and stepping reflects the physiological state of a given assembly of synapses, where the probability of these synaptic events is not deterministic; (iv) rather, this probability can be modulated by other factors such as pharmacological agents, epidural stimulation and/or motor training; (v) the variability observed in the kinematics of consecutive steps reflects a fundamental feature of the neural control system and (vi) machine-learning theories elucidate the need to accommodate variability in developing strategies designed to enhance motor performance by motor training using robotic devices after an SCI.     

The neural circuits and synaptic mechanisms underlying motor initiation in C. elegans

C. elegans is widely used to dissect how neural circuits and genes generate behavior. During locomotion, worms initiate backward movement to change locomotion direction spontaneously or in response to sensory cues; however, the underlying neural circuits are not well defined. We applied a multidisciplinary approach to map neural circuits in freely behaving worms by integrating functional imaging, optogenetic interrogation, genetic manipulation, laser ablation, and electrophysiology. We found that a disinhibitory circuit and a stimulatory circuit together promote initiation of backward movement and that circuitry dynamics is differentially regulated by sensory cues. Both circuits require glutamatergic transmission but depend on distinct glutamate receptors. This dual mode of motor initiation control is found in mammals, suggesting that distantly related organisms with anatomically distinct nervous systems may adopt similar strategies for motor control. Additionally, our studies illustrate how a multidisciplinary approach facilitates dissection of circuit and synaptic mechanisms underlying behavior in a genetic model organism.     

Cranial neural crest migration: New rules for an old road

The neural crest serve as an excellent model to better understand mechanisms of embryonic cell migration. Cell tracing studies have shown that cranial neural crest cells (CNCCs) emerge from the dorsal neural tube in a rostrocaudal manner and are spatially distributed along stereotypical, long distance migratory routes to precise targets in the head and branchial arches. Although the CNCC migratory pattern is a beautifully choreographed and programmed invasion, the underlying orchestration of molecular events is not well known. For example, it is still unclear how single CNCCs react to signals that direct their choice of direction and how groups of CNCCs coordinate their interactions to arrive at a target in an ordered manner. In this review, we discuss recent cellular and molecular discoveries of the CNCC migratory pattern. We focus on events from the time when CNCCs encounter the tissue adjacent to the neural tube and their travel through different microenvironments and into the branchial arches. We describe the patterning of discrete cell migratory streams that emerge from the hindbrain, rhombomere (r) segments r1-r7, and the signals that coordinate directed migration. We propose a model that attempts to unify many complex events that establish the CNCC migratory pattern, and based on this model we integrate information between cranial and trunk neural crest development.     

A neural network model of the vestibulo-ocular reflex using a local synaptic learning rule.

Vertebrates use the vestibulo-ocular reflex to maintain clear vision during head movements. This reflex requires eye-velocity commands from the semicircular canals to be integrated (mathematically) to produce eye-position commands for the extraocular muscles. This is accomplished by a neural network in the caudal pons. A model of this network is proposed using positive feedback via lateral inhibition. The model has been adapted to a learning network. We have developed a synaptic learning rule using only local information to make the model more physiological.     

Effect of cyclic AMP on the excitation and response of command neurons responsible for the snail defensive behavior caused by sensory stimulation]

Extraneuronal application of db-cAMP or intraneuronal injection of cAMP were found to increase the neural membrane excitability and synaptic facilitation in neural responses to sensory stimulation of Lpl1 and Rpl1 neurones. The db-cAMP exerted no effects on neural responses to tactile stimulation of the snail foot or mantle. The intraneuronal injection of cAMP produced synaptic facilitation only in neural responses to quinine application to the snail head. The findings suggest the cAMP selective involvement in postsynaptic mechanisms of inducing the long-term facilitation transient stage.