Movement Planning Determines Sensory Suppression: An Event-related Potential Study

Sensory suppression refers to the phenomenon that sensory input generated by our own actions, such as moving a finger to press a button to hear a tone, elicits smaller neural responses than sensory input generated by external agents. This observation is usually explained via the internal forward model in which an efference copy of the motor command is used to compute a corollary discharge, which acts to suppress sensory input. However, because moving a finger to press a button is accompanied by neural processes involved in preparing and performing the action, it is unclear whether sensory suppression is the result of movement planning, movement execution, or both. To investigate this, in two experiments, we compared event-related potentials to self-generated tones that were produced by voluntary, semivoluntary, or involuntary button-presses, with externally generated tones that were produced by a computer. In Experiment 1, the semivoluntary and involuntary button-presses were initiated by the participant or experimenter, respectively, by electrically stimulating the median nerve in the participant's forearm, and in Experiment 2, by applying manual force to the participant's finger. We found that tones produced by voluntary button-presses elicited a smaller N1 component of the event-related potential than externally generated tones. This is known as N1-suppression. However, tones produced by semivoluntary and involuntary button-presses did not yield significant N1-suppression. We also found that the magnitude of N1-suppression linearly decreased across the voluntary, semivoluntary, and involuntary conditions. These results suggest that movement planning is a necessary condition for producing sensory suppression. We conclude that the most parsimonious account of sensory suppression is the internal forward model.

Motor and non-motor sequence prediction is equally affected in children with developmental coordination disorder

Children with Developmental Coordination Disorder (DCD) are diagnosed based on motor difficulties. However, they also exhibit difficulties in several other cognitive domains, including visuospatial processing, executive functioning and attention. One account of the difficulties seen in DCD proposes an impairment in internal forward modelling, i.e., the ability to (i) detect regularities of a repetitive perceptual or motor pattern, (ii) predict future outcomes of motor actions, and (iii) adapt behaviour accordingly. Using electroencephalographic recordings, the present study aimed to delineate these different aspects of internal forward modelling across several domains. To this end, 24 children with DCD and 23 typically-developing children (aged 7–10 years) completed a serial prediction task in the visual, temporal, spatial and motor domains. This task required them to learn short sequences and to indicate whether a sequence was disrupted towards its end. Analyses revealed that, across all domains, children with DCD showed poorer discrimination between intact and disrupted sequences, accompanied by a delayed late parietal positivity elicited by disrupted sequences. These results indicate an impairment in explicit sequence discrimination in DCD across motor and cognitive domains. However, there is no evidence for an impairment in implicit performance on the visuomotor task in DCD. These results suggest an impairment of the updating of an internal forward model in DCD resulting in a blurred representation of that model and, consequently, in a reduced ability to detect regularities in the environment (e.g., sequences). Such a detailed understanding of internal forward modelling in DCD could help to explain the wide range of co-occurring difficulties experienced by those with a diagnosis of DCD.

Dysmetria and Errors in Predictions: The Role of Internal Forward Model

The terminology of cerebellar dysmetria embraces a ubiquitous symptom in motor deficits, oculomotor symptoms, and cognitive/emotional symptoms occurring in cerebellar ataxias. Patients with episodic ataxia exhibit recurrent episodes of ataxia, including motor dysmetria. Despite the consensus that cerebellar dysmetria is a cardinal symptom, there is still no agreement on its pathophysiological mechanisms to date since its first clinical description by Babinski. We argue that impairment in the predictive computation for voluntary movements explains a range of characteristics accompanied by dysmetria. Within this framework, the cerebellum acquires and maintains an internal forward model, which predicts current and future states of the body by integrating an estimate of the previous state and a given efference copy of motor commands. Two of our recent studies experimentally support the internal-forward-model hypothesis of the cerebellar circuitry. First, the cerebellar outputs (firing rates of dentate nucleus cells) contain predictive information for the future cerebellar inputs (firing rates of mossy fibers). Second, a component of movement kinematics is predictive for target motions in control subjects. In cerebellar patients, the predictive component lags behind a target motion and is compensated with a feedback component. Furthermore, a clinical analysis has examined kinematic and electromyography (EMG) features using a task of elbow flexion goal-directed movements, which mimics the finger-to-nose test. Consistent with the hypothesis of the internal forward model, the predictive activations in the triceps muscles are impaired, and the impaired predictive activations result in hypermetria (overshoot). Dysmetria stems from deficits in the predictive computation of the internal forward model in the cerebellum. Errors in this fundamental mechanism result in undershoot (hypometria) and overshoot during voluntary motor actions. The predictive computation of the forward model affords error-based motor learning, coordination of multiple degrees of freedom, and adequate timing of muscle activities. Both the timing and synergy theory fit with the internal forward model, microzones being the elemental computational unit, and the anatomical organization of converging inputs to the Purkinje neurons providing them the unique property of a perceptron in the brain. We propose that motor dysmetria observed in attacks of ataxia occurs as a result of impaired predictive computation of the internal forward model in the cerebellum.

Motor and non-motor sequence prediction is equally affected in children with Developmental Coordination Disorder

Children with Developmental Coordination Disorder (DCD) are diagnosed based on motor difficulties. However, they also exhibit difficulties in several other cognitive domains, including visuospatial processing, executive functioning and attention. One account of the difficulties seen in DCD proposes an impairment in internal forward modelling, i.e., the ability to (i) detect regularities of a repetitive perceptual or motor pattern, (ii) predict future outcomes of motor actions, and (iii) adapt behaviour accordingly. Using electroencephalographic recordings, the present study aimed to delineate these different aspects of internal forward modelling across several domains. To this end, 24 children with DCD and 23 typically-developing children (aged 7-10 years) completed a serial prediction task in the visual, temporal, spatial and motor domains. This task required them to learn short sequences and to indicate whether a sequence was disrupted towards its end. Analyses revealed that, across all domains, children with DCD showed poorer discrimination between intact and disrupted sequences, accompanied by a delayed late parietal positivity elicited by disrupted sequences. These results indicate an impairment in explicit sequence discrimination in DCD across motor and cognitive domains. However, there is no evidence for an impairment in implicit performance on the motor task in DCD. These results suggest an impairment of the updating of an internal forward model in DCD resulting in a blurred representation of that model and consequently in a reduced ability to detect regularities in the environment (e.g., sequences). Such a detailed understanding of internal forward modelling in DCD could help to explain the wide range of co-occurring difficulties experienced by those with a diagnosis of DCD.

Did we get sensorimotor adaptation wrong? Implicit adaptation as direct policy updating rather than forward-model-based learning

The human motor system can rapidly adapt its motor output in response to errors. The prevailing theory of this process posits that the motor system adapts an internal forward model that predicts the consequences of outgoing motor commands, and that this forward model is then used to guide selection of motor output. However, although there is clear evidence for the existence of adaptive forward models to help track the state of the body, there is no real evidence that such models influence the selection of motor output. A possible alternative to the forward-model-based theory of adaptation is that motor output could be directly adjusted by movement errors (“direct policy learning”), in parallel with but independent of any updates to a predictive forward model. Here, we show evidence for this latter theory based on the properties of implicit adaptation under mirror-reversed visual feedback. We show that implicit adaptation still occurs under this extreme perturbation but acts in an inappropriate direction, following a pattern consistent with direct policy learning but not forward-model-based learning. We suggest that the forward-model-based theory of adaptation needs to be re-examined and that direct policy learning is a more plausible mechanism of implicit adaptation.

Auditory predictions and prediction errors in response to self-initiated vowels

It has been suggested that speech production is accomplished by an internal forward model, reducing processing activity directed to self-produced speech in the auditory cortex. The current study uses an established N1-suppression paradigm comparing self- and externally-initiated natural speech sounds to answer two questions:Are forward predictions generated to process complex speech sounds, such as vowels, initiated via a button press?Are prediction errors regarding self-initiated deviant vowels reflected in the corresponding ERP components?Results confirm an N1-suppression in response to self-initiated speech sounds. Furthermore, our results suggest that predictions leading to the N1-suppression effect are specific, as self-initiated deviant vowels do not elicit an N1-suppression effect. Rather, self-initiated deviant vowels elicit an enhanced N2b and P3a compared to externally-generated deviants, externally-generated standard, or self-initiated standards, again confirming prediction specificity.Results show that prediction errors are salient in self-initiated auditory speech sounds, which may lead to more efficient error correction in speech production.

The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1) or gradually ( experiment 2). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory prediction errors to update an internal model. Here we show that these individuals also have difficulty in discovering an aiming solution to overcome their adaptation deficit, suggesting a new role for the cerebellum in sensorimotor adaptation tasks.

The cerebellum does more than sensory-prediction-error-based learning in sensorimotor adaptation tasks

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory-prediction-error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why don’t individuals with cerebellar damage come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, prior to executing a movement on each trial, the participants verbally reported their intended aiming location. Compared to healthy controls, participants with spinocerebellar ataxia (SCA) displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly (Exp. 1) or gradually (Exp. 2). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability (Exp. 3). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory-prediction-error-based learning, but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials.New and noteworthyIndividuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory prediction errors to update an internal model. Here, we show that these individuals also have difficulty in discovering an aiming solution to overcome their adaptation deficit, suggesting a new role for the cerebellum in sensorimotor adaptation tasks.

Embodiment and American Sign Language

Little is known about how individual signs that occur in naturally produced signed languages are recognized. Here we examine whether sign understanding may be grounded in sensorimotor properties by evaluating a signer’s ability to make lexical decisions to American Sign Language (ASL) signs that are articulated either congruent with or incongruent with the observer’s own handedness. Our results show little evidence for handedness congruency effects for native signers’ perception of ASL, however handedness congruency effects were seen in non-native late learners of ASL and hearing ASL-English bilinguals. The data are compatible with a theory of sign recognition that makes reference to internally simulated articulatory control signals — a forward model based upon sensory-motor properties of one’s owns body. The data suggest that sign recognition may rely upon an internal body schema when processing is non-optimal as a result of having learned ASL later in life. Native signers however may have developed representations of signs which are less bound to the hand with which it is performed, suggesting a different engagement of an internal forward model for rapid lexical decisions.