Impaired motor facilitation during action observation in individuals with autism spectrum disorder

It has been suggested that social impairments observed in individuals with autism spectrum disorder (ASD) can be partly explained by an abnormal mirror neuron system (MNS) 1., 2.. Studies on monkeys have shown that mirror neurons are cells in premotor area F5 that discharge when a monkey executes or sees a specific action or when it hears the corresponding action-related sound 3., 4., 5.. Evidence for the presence of a MNS in humans comes in part from studies using transcranial magnetic stimulation (TMS), where a change in the amplitude of the TMS-induced motor-evoked potentials (MEPs) during action observation has been demonstrated 6., 7., 8., 9.. These data suggest that actions are understood when the representation of that action is mapped onto the observer's own motor structures [10]. To determine if the neural mechanism matching action observation and execution is anomalous in individuals with ASD, TMS was applied over the primary motor cortex (M1) during observation of intransitive, meaningless finger movements. We show that overall modulation of M1 excitability during action observation is significantly lower in individuals with ASD compared with matched controls. In addition, we find that basic motor cortex abnormalities do not underlie this impairment.     

Efficient and robust coding in heterogeneous recurrent networks

Cortical networks show a large heterogeneity of neuronal properties. However, traditional coding models have focused on homogeneous populations of excitatory and inhibitory neurons. Here, we analytically derive a class of recurrent networks of spiking neurons that close to optimally track a continuously varying input online, based on two assumptions: 1) every spike is decoded linearly and 2) the network aims to reduce the mean-squared error between the input and the estimate. From this we derive a class of predictive coding networks, that unifies encoding and decoding and in which we can investigate the difference between homogeneous networks and heterogeneous networks, in which each neurons represents different features and has different spike-generating properties. We find that in this framework, ‘type 1’ and ‘type 2’ neurons arise naturally and networks consisting of a heterogeneous population of different neuron types are both more efficient and more robust against correlated noise. We make two experimental predictions: 1) we predict that integrators show strong correlations with other integrators and resonators are correlated with resonators, whereas the correlations are much weaker between neurons with different coding properties and 2) that ‘type 2’ neurons are more coherent with the overall network activity than ‘type 1’ neurons.     

The mirror mechanism: recent findings and perspectives

Mirror neurons are a specific type of visuomotor neuron that discharge both when a monkey executes a motor act and when it observes a similar motor act performed by another individual. In this article, we review first the basic properties of these neurons. We then describe visual features recently investigated which indicate that, besides encoding the goal of motor acts, mirror neurons are modulated by location in space of the observed motor acts, by the perspective from which the others’ motor acts are seen, and by the value associated with the object on which others’ motor acts are performed. In the last part of this article, we discuss the role of the mirror mechanism in planning actions and in understanding the intention underlying the others’ motor acts. We also review some human studies suggesting that motor intention in humans may rely, as in the monkey, on the mirror mechanism.     

Frequency and topography in monkey electroencephalogram during action observation: possible neural correlates of the mirror neuron system

The observation of actions executed by others results in desynchronization of electroencephalogram (EEG) in the alpha and beta frequency bands recorded from the central regions in humans. On the other hand, mirror neurons, which are thought to be responsible for this effect, have been studied only in macaque monkeys, using single-cell recordings. Here, as a first step in a research programme aimed at understanding the parallels between human and monkey mirror neuron systems (MNS), we recorded EEG from the scalp of two monkeys during action observation. The monkeys were trained to fixate on the face of a human agent and subsequently to fixate on a target upon which the agent performed a grasping action. We found that action observation produced desynchronization in the 19–25 Hz band that was strongest over anterior and central electrodes. These results are in line with human data showing that specific frequency bands within the power spectrum of the ongoing EEG may be modulated by observation of actions and therefore might be a specific marker of MNS activity.     

The mirror system and its role in social cognition

Experiments in monkeys have shown that coding the goal of the motor acts is a fundamental property of the cortical motor system. In area F5, goal-coding motor neurons are also activated by observing motor acts done by others (the 'classical' mirror mechanism); in area F2 and area F1, some motor neurons are activated by the mere observation of goal-directed movements of a cursor displayed on a computer screen (a 'mirror-like' mechanism). Experiments in humans and monkeys have shown that the mirror mechanism enables the observer to understand the intention behind an observed motor act, in addition to the goal of it. Growing evidence shows that a deficit in the mirror mechanism underlies some aspects of autism.     

Human motor cortex excitability during the perception of others' action

Neuroscience research during the past ten years has fundamentally changed the traditional view of the motor system. In monkeys, the finding that premotor neurons also discharge during visual stimulation (visuomotor neurons) raises new hypotheses about the putative role played by motor representations in perceptual functions. Among visuomotor neurons, mirror neurons might be involved in understanding the actions of others and might, therefore, be crucial in interindividual communication. Functional brain imaging studies enabled us to localize the human mirror system, but the demonstration that the motor cortex dynamically replicates the observed actions, as if they were executed by the observer, can only be given by fast and focal measurements of cortical activity. Transcranial magnetic stimulation enables us to instantaneously estimate corticospinal excitability, and has been used to study the human mirror system at work during the perception of actions performed by other individuals. In the past ten years several TMS experiments have been performed investigating the involvement of motor system during others' action observation. Results suggest that when we observe another individual acting we strongly 'resonate' with his or her action. In other words, our motor system simulates underthreshold the observed action in a strictly congruent fashion. The involved muscles are the same as those used in the observed action and their activation is temporally strictly coupled with the dynamics of the observed action.     

How Lateral Connections and Spiking Dynamics May Separate Multiple Objects Moving Together

Over successive stages, the ventral visual system of the primate brain develops neurons that respond selectively to particular objects or faces with translation, size and view invariance. The powerful neural representations found in Inferotemporal cortex form a remarkably rapid and robust basis for object recognition which belies the difficulties faced by the system when learning in natural visual environments. A central issue in understanding the process of biological object recognition is how these neurons learn to form separate representations of objects from complex visual scenes composed of multiple objects. We show how a one-layer competitive network comprised of ‘spiking’ neurons is able to learn separate transformation-invariant representations (exemplified by one-dimensional translations) of visual objects that are always seen together moving in lock-step, but separated in space. This is achieved by combining ‘Mexican hat’ functional lateral connectivity with cell firing-rate adaptation to temporally segment input representations of competing stimuli through anti-phase oscillations (perceptual cycles). These spiking dynamics are quickly and reliably generated, enabling selective modification of the feed-forward connections to neurons in the next layer through Spike-Time-Dependent Plasticity (STDP), resulting in separate translation-invariant representations of each stimulus. Variations in key properties of the model are investigated with respect to the network’s ability to develop appropriate input representations and subsequently output representations through STDP. Contrary to earlier rate-coded models of this learning process, this work shows how spiking neural networks may learn about more than one stimulus together without suffering from the ‘superposition catastrophe’. We take these results to suggest that spiking dynamics are key to understanding biological visual object recognition.     

The role of ventral premotor cortex in action execution and action understanding

The human ventral premotor cortex overlaps, at least in part, with Broca's region in the dominant cerebral hemisphere, that is known to mediate the production of language and contributes to language comprehension. This region is constituted of Brodmann's areas 44 and 45 in the inferior frontal gyrus. We summarize the evidence that the motor related part of Broca's region is localized in the opercular portion of the inferior frontal cortex, mainly in area 44 of Brodmann. According to our own data, there seems to be a homology between Brodmann area 44 in humans and the monkey area F5. The non-language related motor functions of Broca's region comprise complex hand movements, associative sensorimotor learning and sensorimotor integration. Brodmann's area 44 is also a part of a specialized parieto-premotor network and interacts significantly with the neighbouring premotor areas. In the ventral premotor area F5 of monkeys, the so called mirror neurons have been found which discharge both when the animal performs a goal-directed hand action and when it observes another individual performing the same or a similar action. More recently, in the same area mirror neurons responding not only to the observation of mouth actions, but also to sounds characteristic to actions have been found. In humans, through an fMRI study, it has been shown that the observation of actions performed with the hand, the mouth and the foot leads to the activation of different sectors of Broca's area and premotor cortex, according to the effector involved in the observed action, following a somatotopic pattern which resembles the classical motor cortex homunculus. On the other hand the evidence is growing that human ventral premotor cortex, especially Brodmann's area 44, is involved in polymodal action processing. These results strongly support the existence of an execution-observation matching system (mirror neuron system). It has been proposed that this system is involved in polymodal action recognition and might represent a precursor of language processing. Experimental evidence in favour of this hypothesis both in the monkey and humans is shortly reviewed.     

Schema design and implementation of the grasp-related mirror neuron system

 Mirror neurons within a monkey's premotor area F5 fire not only when the monkey performs a certain class of actions but also when the monkey observes another monkey (or the experimenter) perform a similar action. It has thus been argued that these neurons are crucial for understanding of actions by others. We offer the hand-state hypothesis as a new explanation of the evolution of this capability: the basic functionality of the F5 mirror system is to elaborate the appropriate feedback – what we call the hand state– for opposition-space based control of manual grasping of an object. Given this functionality, the social role of the F5 mirror system in understanding the actions of others may be seen as an exaptation gained by generalizing from one's own hand to an other's hand. In other words, mirror neurons first evolved to augment the “canonical” F5 neurons (active during self-movement based on observation of an object) by providing visual feedback on “hand state,” relating the shape of the hand to the shape of the object. We then introduce the MNS1 (mirror neuron system 1) model of F5 and related brain regions. The existing Fagg–Arbib–Rizzolatti–Sakata model represents circuitry for visually guided grasping of objects, linking the anterior intraparietal area (AIP) with F5 canonical neurons. The MNS1 model extends the AIP visual pathway by also modeling pathways, directed toward F5 mirror neurons, which match arm–hand trajectories to the affordances and location of a potential target object. We present the basic schemas for the MNS1 model, then aggregate them into three “grand schemas”– visual analysis of hand state, reach and grasp, and the core mirror circuit – for each of which we present a useful implementation (a non-neural visual processing system, a multijoint 3-D kinematics simulator, and a learning neural network, respectively). With this implementation we show how the mirror system may learnto recognize actions already in the repertoire of the F5 canonical neurons. We show that the connectivity pattern of mirror neuron circuitry can be established through training, and that the resultant network can exhibit a range of novel, physiologically interesting behaviors during the process of action recognition. We train the system on the basis of final grasp but then observe the whole time course of mirror neuron activity, yielding predictions for neurophysiological experiments under conditions of spatial perturbation, altered kinematics, and ambiguous grasp execution which highlight the importance of the timingof mirror neuron activity. Received: 6 August 2001 / Accepted in revised form: 5 February 2002     

The role of the cerebellum in modulating voluntary limb movement commands

We recorded the activity of cerebellar Purkinje cells (PCs), primary motor cortical (M1) neurons, and limb EMG signals while monkeys executed a sequential reaching and button pressing task. PC simple spike discharge generally correlated well with the activity of one or more forelimb muscles. Surprisingly, given the inhibitory projection of PCs, only about one quarter of the correlations were negative. The largest group of neurons burst during movement and were positively correlated with EMG signals, while another significant group burst and were negatively correlated. Among the PCs that paused during movement most were negatively correlated with EMG. The strength of these various correlations was somewhat weaker, on average, than equivalent correlations between M1 neurons and EMG signals. On the other hand, there were no significant differences in the timing of the onset of movement related discharge among these groups of PCs, or between the PCs and M1 neurons. PC discharge was modulated largely in phase, or directly out of phase, with muscle activity. The nearly synchronous activation of PCs and muscles yielded positive correlations, despite the fact that the synaptic effect of the PC discharge is inhibitory. The apparent function of this inhibition is to restrain activity in the limb premotor network, shaping it into a spatiotemporal pattern that is appropriate for controlling the many muscles that participate in this task. The observed timing suggests that the cerebellar cortex learns to modulate PC discharge predictively. Through the cerebellar nucleus, this PC signal is combined with an underlying cerebral cortical signal. In this manner the cerebellum refines the descending command as compared with the relatively crude version generated when the cerebellum is damaged.     

Predicting Agenesis of the Mandibular Second Premolar from Adjacent Teeth

Early diagnosis of agenesis of the mandibular second premolar (P2) enhances management of the dental arch in the growing child. The aim of this study was to explore the relationship in the development of the mandibular first molar (M1) and first premolar (P1) at early stages of P2 (second premolar). Specifically, we ask if the likelihood of P2 agenesis can be predicted from adjacent developing teeth. We selected archived dental panoramic radiographs with P2 at crown formation stages (N = 212) and calculated the likelihood of P2 at initial mineralisation stage ‘Ci’ given the tooth stage of adjacent teeth. Our results show that the probability of observing mandibular P2 at initial mineralisation stage ‘Ci’ decreased as both the adjacent P1 and M1 matured. The modal stage at P2 ‘Ci’ was P1 ‘Coc’ (cusp outline complete) and M1 ‘Crc’ (crown complete). Initial mineralisation of P2 was observed up to P1 ‘Crc’ and M1 stage ‘R½’ (root half). The chance of observing P2 at least ‘Coc’ (coalescence of cusps) was considerably greater prior to these threshold stages compared to later stages of P1 and M1. These findings suggest that P2 is highly unlikely to develop if P1 is beyond ‘Crc’ and M1 is beyond ‘R½’.     

Blind demixing methods for recovering dense neuronal morphology from barcode imaging data

Cellular barcoding methods offer the exciting possibility of ‘infinite-pseudocolor’ anatomical reconstruction—i.e., assigning each neuron its own random unique barcoded ‘pseudocolor,’ and then using these pseudocolors to trace the microanatomy of each neuron. Here we use simulations, based on densely-reconstructed electron microscopy microanatomy, with signal structure matched to real barcoding data, to quantify the feasibility of this procedure. We develop a new blind demixing approach to recover the barcodes that label each neuron, and validate this method on real data with known barcodes. We also develop a neural network which uses the recovered barcodes to reconstruct the neuronal morphology from the observed fluorescence imaging data, ‘connecting the dots’ between discontiguous barcode amplicon signals. We find that accurate recovery should be feasible, provided that the barcode signal density is sufficiently high. This study suggests the possibility of mapping the morphology and projection pattern of many individual neurons simultaneously, at high resolution and at large scale, via conventional light microscopy.     

Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection

The external globus pallidus (GPe) is a key nucleus within basal ganglia circuits that are thought to be involved in action selection. A class of computational models assumes that, during action selection, the basal ganglia compute for all actions available in a given context the probabilities that they should be selected. These models suggest that a network of GPe and subthalamic nucleus (STN) neurons computes the normalization term in Bayes’ equation. In order to perform such computation, the GPe needs to send feedback to the STN equal to a particular function of the activity of STN neurons. However, the complex form of this function makes it unlikely that individual GPe neurons, or even a single GPe cell type, could compute it. Here, we demonstrate how this function could be computed within a network containing two types of GABAergic GPe projection neuron, so-called ‘prototypic’ and ‘arkypallidal’ neurons, that have different response properties in vivo and distinct connections. We compare our model predictions with the experimentally-reported connectivity and input-output functions (f-I curves) of the two populations of GPe neurons. We show that, together, these dichotomous cell types fulfil the requirements necessary to compute the function needed for optimal action selection. We conclude that, by virtue of their distinct response properties and connectivities, a network of arkypallidal and prototypic GPe neurons comprises a neural substrate capable of supporting the computation of the posterior probabilities of actions.     

Suffixation influences receivers' behaviour in non-human primates

Compared to humans, non-human primates have very little control over their vocal production. Nonetheless, some primates produce various call combinations, which may partially offset their lack of acoustic flexibility. A relevant example is male Campbell''s monkeys (Cercopithecus campbelli), which give one call type (‘Krak’) to leopards, while the suffixed version of the same call stem (‘Krak-oo’) is given to unspecific danger. To test whether recipients attend to this suffixation pattern, we carried out a playback experiment in which we broadcast naturally and artificially modified suffixed and unsuffixed ‘Krak’ calls of male Campbell''s monkeys to 42 wild groups of Diana monkeys (Cercopithecus diana diana). The two species form mixed-species groups and respond to each other''s vocalizations. We analysed the vocal response of male and female Diana monkeys and overall found significantly stronger vocal responses to unsuffixed (leopard) than suffixed (unspecific danger) calls. Although the acoustic structure of the ‘Krak’ stem of the calls has some additional effects, subject responses were mainly determined by the presence or the absence of the suffix. This study indicates that suffixation is an evolved function in primate communication in contexts where adaptive responses are particularly important.     

Hebbian learning and predictive mirror neurons for actions,sensations and emotions

Spike-timing-dependent plasticity is considered the neurophysiological basis of Hebbian learning and has been shown to be sensitive to both contingency and contiguity between pre- and postsynaptic activity. Here, we will examine how applying this Hebbian learning rule to a system of interconnected neurons in the presence of direct or indirect re-afference (e.g. seeing/hearing one''s own actions) predicts the emergence of mirror neurons with predictive properties. In this framework, we analyse how mirror neurons become a dynamic system that performs active inferences about the actions of others and allows joint actions despite sensorimotor delays. We explore how this system performs a projection of the self onto others, with egocentric biases to contribute to mind-reading. Finally, we argue that Hebbian learning predicts mirror-like neurons for sensations and emotions and review evidence for the presence of such vicarious activations outside the motor system.     

An isomorphic mapping hypothesis of the grid representation

We introduce a grid cell microcircuit hypothesis. We propose the ‘grid in the world’ (evident in grid cell discharges) is generated by a ‘grid in the cortex’. This cortical grid is formed by patches of calbindin-positive pyramidal neurons in layer 2 of medial entorhinal cortex (MEC). Our isomorphic mapping hypothesis assumes three types of isomorphism: (i) metric correspondence of neural space (the two-dimensional cortical sheet) and the external two-dimensional space within patches; (ii) isomorphism between cellular connectivity matrix and firing field; (iii) isomorphism between single cell and population activity. Each patch is a grid cell lattice arranged in a two-dimensional map of space with a neural : external scale of approximately 1 : 2000 in the dorsal part of rat MEC. The lattice behaves like an excitable medium with neighbouring grid cells exciting each other. Spatial scale is implemented as an intrinsic scaling factor for neural propagation speed. This factor varies along the dorsoventral cortical axis. A connectivity scheme of the grid system is described. Head direction input specifies the direction of activity propagation. We extend the theory to neurons between grid patches and predict a rare discharge pattern (inverted grid cells) and the relative location and proportion of grid cells and spatial band cells.     

Primary motor cortex neuronal discharge during reach-to-grasp: controlling the hand as a unit

This study has begun to test the hypothesis that aspects of hand/object shape are represented in the discharge of primary motor cortex (M1) neurons. Two monkeys were trained in a visually cued reach-to-grasp task, in which object properties and grasp forces were systematically varied. Behavioral analyses show that the reach and grasp force production were constant across the objects. The discharge of M1 neurons was highly modulated during the reach and grasp. Multiple linear regressions models revealed that the M1 discharge was highly dependent on the object grasped, with object class, volume, orientation and grasp force as significant predictors. These findings are interpreted as evidence that the CNS controls the hand as a unit.     

When the Sun Prickles Your Nose: An EEG Study Identifying Neural Bases of Photic Sneezing

Background

Exposure to bright light such as sunlight elicits a sneeze or prickling sensation in about one of every four individuals. This study presents the first scientific examination of this phenomenon, called ‘the photic sneeze reflex’.

Methodology and Principal Findings

In the present experiment, ‘photic sneezers’ and controls were exposed to a standard checkerboard stimulus (block 1) and bright flashing lights (block 2) while their EEG (electro-encephalogram) was recorded. Remarkably, we found a generally enhanced excitability of the visual cortex (mainly in the cuneus) to visual stimuli in ‘photic sneezers’ compared with control subjects. In addition, a stronger prickling sensation in the nose of photic sneezers was found to be associated with activation in the insula and stronger activation in the secondary somatosensory cortex.

Conclusion

We propose that the photic sneeze phenomenon might be the consequence of higher sensitivity to visual stimuli in the visual cortex and of co-activation of somatosensory areas. The ‘photic sneeze reflex’ is therefore not a classical reflex that occurs only at a brainstem or spinal cord level but, in stark contrast to many theories, involves also specific cortical areas.     

What to do, or how to do it?

In this issue of Neuron, Ajemian et al. present a computational model of the activity of neurons in primary motor cortex (M1) during isometric movements in different postures. By modeling the output of M1 neurons in terms of their influence on muscles, they find each M1 neuron maps its output into a particular pattern of muscle actions.