A neurophysiologically plausible population code model for feature integration explains visual crowding.

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

Vector-Based Integration of Local and Long-Range Information in Visual Cortex

Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we propose a new analytic framework for understanding integration within cortical neuronal receptive fields. Based on the synaptic organization of cortex, we argue that neuronal integration is a systems--level process better studied in terms of local cortical circuitry than at the level of single neurons, and we present a method for constructing self-contained modules which capture (nonlinear) local circuit interactions. In this framework, receptive field elements naturally have dual (rather than the traditional unitary influence since they drive both excitatory and inhibitory cortical neurons. This vector-based analysis, in contrast to scalarsapproaches, greatly simplifies integration by permitting linear summation of inputs from both "classical" and "extraclassical" receptive field regions. We illustrate this by explaining two complex visual cortical phenomena, which are incompatible with scalar notions of neuronal integration.

Coding of visual space during motor preparation: approaching objects rapidly modulate corticospinal excitability in hand-centered coordinates

Defensive behaviors, such as withdrawing your hand to avoid potentially harmful approaching objects, rely on rapid sensorimotor transformations between visual and motor coordinates. We examined the reference frame for coding visual information about objects approaching the hand during motor preparation. Subjects performed a simple visuomanual task while a task-irrelevant distractor ball rapidly approached a location either near to or far from their hand. After the distractor ball appearance, single pulses of transcranial magnetic stimulation were delivered over the subject's primary motor cortex, eliciting motor evoked potentials (MEPs) in their responding hand. MEP amplitude was reduced when the ball approached near the responding hand, both when the hand was on the left and the right of the midline. Strikingly, this suppression occurred very early, at 70-80ms after ball appearance, and was not modified by visual fixation location. Furthermore, it was selective for approaching balls, since static visual distractors did not modulate MEP amplitude. Together with additional behavioral measurements, we provide converging evidence for automatic hand-centered coding of visual space in the human brain.

Effect of instructive visual stimuli on neurofeedback training for motor imagery-based braincomputer interface

Event-related desynchronization (ERD) of the electroencephalogram (EEG) from the motor cortex is associated with execution, observation, and mental imagery of motor tasks. Generation of ERD by motor imagery (MI) has been widely used for brain-computer interfaces (BCIs) linked to neuroprosthetics and other motor assistance devices. Control of MI-based BCIs can be acquired by neurofeedback training to reliably induce MI-associated ERD. To develop more effective training conditions, we investigated the effect of static and dynamic visual representations of target movements (a picture of forearms or a video clip of hand grasping movements) during the BCI training. After 4 consecutive training days, the group that performed MI while viewing the video showed significant improvement in generating MI-associated ERD compared with the group that viewed the static image. This result suggests that passively observing the target movement during MI would improve the associated mental imagery and enhance MI-based BCIs skills.

Analysis of functional networks involved in motor execution and motor imagery using combined hierarchical clustering analysis and independent component analysis

Cognitive experiments involving motor execution (ME) and motor imagery (MI) have been intensively studied using functional magnetic resonance imaging (fMRI). However, the functional networks of a multitask paradigm which include ME and MI were not widely explored. In this article, we aimed to investigate the functional networks involved in MI and ME using a method combining the hierarchical clustering analysis (HCA) and the independent component analysis (ICA). Ten right-handed subjects were recruited to participate a multitask experiment with conditions such as visual cue, MI, ME and rest. The results showed that four activation clusters were found including parts of the visual network, ME network, the MI network and parts of the resting state network. Furthermore, the integration among these functional networks was also revealed. The findings further demonstrated that the combined HCA with ICA approach was an effective method to analyze the fMRI data of multitasks.

Anticipatory engineering: anticipation in sensory-motor systems of human

In visual tracking experiments, distributions of the relative phase be-tween target and tracer showed positive relative phase indicating that the tracer precedes the target position. We found a mode transition from the reactive to anticipatory mode. The proposed integrated model provides a framework to understand the antici-patory behaviour of human, focusing on the integration of visual and soma-tosensory information. The time delays in visual processing and somatosensory feedback are explicitly treated in the simultaneous differential equations. The anticipatory behaviour observed in the visual tracking experiments can be ex-plained by the feedforward term of target velocity, internal dynamics, and time delay in somatosensory feedback.

Multi-sensory treatment for children with developmental motor speech disorders

What this paper adds? What is already known on the subject? Multi-sensory treatment approaches have been shown to impact outcome measures positively, such as accuracy of speech movement patterns and speech intelligibility in adults with motor speech disorders, as well as in children with apraxia of speech, autism and cerebral palsy. However, there has been no empirical study using multi-sensory treatment for children with speech sound disorders (SSDs) who demonstrate motor control issues in the jaw and orofacial structures (e.g. jaw sliding, jaw over extension, inadequate lip rounding/retraction and decreased integration of speech movements). What this paper adds? Findings from this study indicate that, for speech production disorders where both the planning and production of spatiotemporal parameters of movement sequences for speech are disrupted, multi-sensory treatment programmes that integrate auditory, visual and tactile–kinesthetic information improve auditory and visual accuracy of speech production. The training (practised in treatment) and test words (not practised in treatment) both demonstrated positive change in most participants, indicating generalization of target features to untrained words. It is inferred that treatment that focuses on integrating multi-sensory information and normalizing parameters of speech movements is an effective method for treating children with SSDs who demonstrate speech motor control issues.

Online motor control in children with developmental coordination disorder: chronometric analysis of double-step reaching performance

Background
Although there are a number of plausible accounts to explain movement clumsiness in children [or developmental coordination disorder (DCD)], the cause(s) of the disorder remain(s) an issue of debate. One aspect of motor control that is particularly important to the fluid expression of skill is rapid online control (ROC). Data on DCD have been conflicting. While some recent work using double-step reaching suggests no difficulty in online control, others suggest deficits (e.g. based on sequential pointing). To help resolve this debate, we suggest two things: use of recent neuro-computational models as a framework for investigating motor control in DCD, and more rigorous investigation of double-step reaching. Our working assumption here is that ROC is only viable through the seamless integration of predictive (or forward) models of movement and feedback-based mechanisms.

Aim
The aim of this chronometric study was to explore ROC in children with DCD using a double-step reaching paradigm. We predicted slower online adjustments in DCD based on the argument that these children manifest a core difficulty in predictive control.

Methods
Participants were a group of 17 children with DCD and 27 typically developing children aged between 7 and 12 years. Visual targets were presented on a 17-inch LCD touch screen, inclined to an angle of 15° from horizontal. The children were instructed to press each target as it appeared as quickly and accurately as possible. For 80% of the trials, the central target location remained unchanged for the duration of the movement (non-jump trials), while for the remaining 20% of trials, the target jumped at movement onset to one of the two peripheral locations (jump trials). Reaction time (RT), movement time (MT) and reaching errors were recorded.

Results
For both groups, RT did not vary according to trial condition, while children with DCD were slower to initiate movement. Further, the MT of children with DCD was prolonged to a far greater extent on jump trials relative to controls, with a large effect size. As well, children with DCD committed significantly more errors, notably a reduced ability to inhibit central responses on jump trials.

Conclusion
Our findings help reconcile some disparate findings in the literature using similar tasks. The pattern of performance in children with DCD suggests impairment in the ability to make rapid online adjustments that are based on a predictive (or internal) model of the action. These results pave the way for future kinematic investigation.