A Quantitative Evaluation of the AVITEWRITE Model of Handwriting Learning

Much sensory-motor behavior develops through imitation, as during the learning of handwriting by children. Such complex sequential acts are broken down into distinct motor control synergies, or muscle groups, whose activities overlap in time to generate continuous, curved movements that obey an intense relation between curvature and speed. The Adaptive Vector Integration to Endpoint (AVITEWRITE) model of Grossberg and Paine (2000) proposed how such complex movements may be learned through attentive imitation. The model suggest how frontal, parietal, and motor cortical mechanisms, such as difference vector encoding, under volitional control from the basal ganglia, interact with adaptively-timed, predictive cerebellar learning during movement imitation and predictive performance. Key psycophysical and neural data about learning to make curved movements were simulated, including a decrease in writing time as learning progresses; generation of unimodal, bell-shaped velocity profiles for each movement synergy; size scaling with isochrony, and speed scaling with preservation of the letter shape and the shapes of the velocity profiles; an inverse relation between curvature and tangential velocity; and a Two-Thirds Power Law relation between angular velocity and curvature. However, the model learned from letter trajectories of only one subject, and only qualitative kinematic comparisons were made with previously published human data. The present work describes a quantitative test of AVITEWRITE through direct comparison of a corpus of human handwriting data with the model's performance when it learns by tracing human trajectories. The results show that model performance was variable across subjects, with an average correlation between the model and human data of 89+/-10%. The present data from simulations using the AVITEWRITE model highlight some of its strengths while focusing attention on areas, such as novel shape learning in children, where all models of handwriting and learning of other complex sensory-motor skills would benefit from further research.

Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives

A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model-the N-STREAMS neural network model-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.

SOVEREIGN: A Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-Oriented Navigation System

Both animals and mobile robots, or animats, need adaptive control systems to guide their movements through a novel environment. Such control systems need reactive mechanisms for exploration, and learned plans to efficiently reach goal objects once the environment is familiar. How reactive and planned behaviors interact together in real time, and arc released at the appropriate times, during autonomous navigation remains a major unsolved problern. This work presents an end-to-end model to address this problem, named SOVEREIGN: A Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation system. The model comprises several interacting subsystems, governed by systems of nonlinear differential equations. As the animat explores the environment, a vision module processes visual inputs using networks that arc sensitive to visual form and motion. Targets processed within the visual form system arc categorized by real-time incremental learning. Simultaneously, visual target position is computed with respect to the animat's body. Estimates of target position activate a motor system to initiate approach movements toward the target. Motion cues from animat locomotion can elicit orienting head or camera movements to bring a never target into view. Approach and orienting movements arc alternately performed during animat navigation. Cumulative estimates of each movement, based on both visual and proprioceptive cues, arc stored within a motor working memory. Sensory cues are stored in a parallel sensory working memory. These working memories trigger learning of sensory and motor sequence chunks, which together control planned movements. Effective chunk combinations arc selectively enhanced via reinforcement learning when the animat is rewarded. The planning chunks effect a gradual transition from reactive to planned behavior. The model can read-out different motor sequences under different motivational states and learns more efficient paths to rewarded goals as exploration proceeds. Several volitional signals automatically gate the interactions between model subsystems at appropriate times. A 3-D visual simulation environment reproduces the animat's sensory experiences as it moves through a simplified spatial environment. The SOVEREIGN model exhibits robust goal-oriented learning of sequential motor behaviors. Its biomimctic structure explicates a number of brain processes which are involved in spatial navigation.

SOVEREIGN: An Autonomous Neural System for Incrementally Learning Planned Action Sequence to Navigate Towards a Rewarded Goal

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goaloriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and sizeinvariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory movements to efficient goal-oriented planned movement sequences. Volitional signals gate interactions between model subsystems and the release of overt behaviors. The model can control different motor sequences under different motivational states and learns more efficient sequences to rewarded goals as exploration proceeds.

Fast Learning VIEWNET Architectures for Recognizing 3-D Objects from Multiple 2-D Views

The recognition of 3-D objects from sequences of their 2-D views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With NETworks. VIEWNET incorporates a preprocessor that generates a compressed but 2-D invariant representation of an image, a supervised incremental learning system that classifies the preprocessed representations into 2-D view categories whose outputs arc combined into 3-D invariant object categories, and a working memory that makes a 3-D object prediction by accumulating evidence from 3-D object category nodes as multiple 2-D views are experienced. The simplest VIEWNET achieves high recognition scores without the need to explicitly code the temporal order of 2-D views in working memory. Working memories are also discussed that save memory resources by implicitly coding temporal order in terms of the relative activity of 2-D view category nodes, rather than as explicit 2-D view transitions. Variants of the VIEWNET architecture may also be used for scene understanding by using a preprocessor and classifier that can determine both What objects are in a scene and Where they are located. The present VIEWNET preprocessor includes the CORT-X 2 filter, which discounts the illuminant, regularizes and completes figural boundaries, and suppresses image noise. This boundary segmentation is rendered invariant under 2-D translation, rotation, and dilation by use of a log-polar transform. The invariant spectra undergo Gaussian coarse coding to further reduce noise and 3-D foreshortening effects, and to increase generalization. These compressed codes are input into the classifier, a supervised learning system based on the fuzzy ARTMAP algorithm. Fuzzy ARTMAP learns 2-D view categories that are invariant under 2-D image translation, rotation, and dilation as well as 3-D image transformations that do not cause a predictive error. Evidence from sequence of 2-D view categories converges at 3-D object nodes that generate a response invariant under changes of 2-D view. These 3-D object nodes input to a working memory that accumulates evidence over time to improve object recognition. ln the simplest working memory, each occurrence (nonoccurrence) of a 2-D view category increases (decreases) the corresponding node's activity in working memory. The maximally active node is used to predict the 3-D object. Recognition is studied with noisy and clean image using slow and fast learning. Slow learning at the fuzzy ARTMAP map field is adapted to learn the conditional probability of the 3-D object given the selected 2-D view category. VIEWNET is demonstrated on an MIT Lincoln Laboratory database of l28x128 2-D views of aircraft with and without additive noise. A recognition rate of up to 90% is achieved with one 2-D view and of up to 98.5% correct with three 2-D views. The properties of 2-D view and 3-D object category nodes are compared with those of cells in monkey inferotemporal cortex.

Towards a Unified Theory of Neocortex: Laminar Cortical Circuits for Vision and Cognition

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of pre-attentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.

An Integrated Neural Network-Event-Related Potentials Model of Temporal and Probability Context Effects on Event Categorization

We present a neural network that adapts and integrates several preexisting or new modules to categorize events in short term memory (STM), encode temporal order in working memory, evaluate timing and probability context in medium and long term memory. The model shows how processed contextual information modulates event recognition and categorization, focal attention and incentive motivation. The model is based on a compendium of Event Related Potentials (ERPs) and behavioral results either collected by the authors or compiled from the classical ERP literature. Its hallmark is, at the functional level, the interplay of memory registers endowed with widely different dynamical ranges, and at the structural level, the attempt to relate the different modules to known anatomical structures.

The impact of anxiety-inducing distraction on cognitive performance: a combined brain imaging and personality investigation.

BACKGROUND: Previous investigations revealed that the impact of task-irrelevant emotional distraction on ongoing goal-oriented cognitive processing is linked to opposite patterns of activation in emotional and perceptual vs. cognitive control/executive brain regions. However, little is known about the role of individual variations in these responses. The present study investigated the effect of trait anxiety on the neural responses mediating the impact of transient anxiety-inducing task-irrelevant distraction on cognitive performance, and on the neural correlates of coping with such distraction. We investigated whether activity in the brain regions sensitive to emotional distraction would show dissociable patterns of co-variation with measures indexing individual variations in trait anxiety and cognitive performance. METHODOLOGY/PRINCIPAL FINDINGS: Event-related fMRI data, recorded while healthy female participants performed a delayed-response working memory (WM) task with distraction, were investigated in conjunction with behavioural measures that assessed individual variations in both trait anxiety and WM performance. Consistent with increased sensitivity to emotional cues in high anxiety, specific perceptual areas (fusiform gyrus--FG) exhibited increased activity that was positively correlated with trait anxiety and negatively correlated with WM performance, whereas specific executive regions (right lateral prefrontal cortex--PFC) exhibited decreased activity that was negatively correlated with trait anxiety. The study also identified a role of the medial and left lateral PFC in coping with distraction, as opposed to reflecting a detrimental impact of emotional distraction. CONCLUSIONS: These findings provide initial evidence concerning the neural mechanisms sensitive to individual variations in trait anxiety and WM performance, which dissociate the detrimental impact of emotion distraction and the engagement of mechanisms to cope with distracting emotions. Our study sheds light on the neural correlates of emotion-cognition interactions in normal behaviour, which has implications for understanding factors that may influence susceptibility to affective disorders, in general, and to anxiety disorders, in particular.

Quality of Life and Neurocognitive Functioning in Children with Sickle Cell Disease: Investigating the Feasibility of a Computerized Cognitive Training Program

Children with sickle cell disease (SCD) have a high risk of neurocognitive impairment. No known research, however, has examined the impact of neurocognitive functioning on quality of life in this pediatric population. In addition, limited research has examined neurocognitive interventions for these children. In light of these gaps, two studies were undertaken to (a) examine the relationship between cognitive functioning and quality of life in a sample of children with SCD and (b) investigate the feasibility and preliminary efficacy of a computerized working memory training program in this population. Forty-five youth (ages 8-16) with SCD and a caregiver were recruited for the first study. Participants completed measures of cognitive ability, quality of life, and psychosocial functioning. Results indicated that cognitive ability significantly predicted child- and parent-reported quality of life among youth with SCD. In turn, a randomized-controlled trial of a computerized working memory program was undertaken. Eighteen youth with SCD and a caregiver enrolled in this study, and were randomized to a waitlist control or the working memory training condition. Data pertaining to cognitive functioning, psychosocial functioning, and disease characteristics were obtained from participants. The results of this study indicated a high degree of acceptance for this intervention but poor feasibility in practice. Factors related to feasibility were identified. Implications and future directions are discussed.

Imagery and retrieval of auditory and visual information: neural correlates of successful and unsuccessful performance.

Remembering past events - or episodic retrieval - consists of several components. There is evidence that mental imagery plays an important role in retrieval and that the brain regions supporting imagery overlap with those supporting retrieval. An open issue is to what extent these regions support successful vs. unsuccessful imagery and retrieval processes. Previous studies that examined regional overlap between imagery and retrieval used uncontrolled memory conditions, such as autobiographical memory tasks, that cannot distinguish between successful and unsuccessful retrieval. A second issue is that fMRI studies that compared imagery and retrieval have used modality-aspecific cues that are likely to activate auditory and visual processing regions simultaneously. Thus, it is not clear to what extent identified brain regions support modality-specific or modality-independent imagery and retrieval processes. In the current fMRI study, we addressed this issue by comparing imagery to retrieval under controlled memory conditions in both auditory and visual modalities. We also obtained subjective measures of imagery quality allowing us to dissociate regions contributing to successful vs. unsuccessful imagery. Results indicated that auditory and visual regions contribute both to imagery and retrieval in a modality-specific fashion. In addition, we identified four sets of brain regions with distinct patterns of activity that contributed to imagery and retrieval in a modality-independent fashion. The first set of regions, including hippocampus, posterior cingulate cortex, medial prefrontal cortex and angular gyrus, showed a pattern common to imagery/retrieval and consistent with successful performance regardless of task. The second set of regions, including dorsal precuneus, anterior cingulate and dorsolateral prefrontal cortex, also showed a pattern common to imagery and retrieval, but consistent with unsuccessful performance during both tasks. Third, left ventrolateral prefrontal cortex showed an interaction between task and performance and was associated with successful imagery but unsuccessful retrieval. Finally, the fourth set of regions, including ventral precuneus, midcingulate cortex and supramarginal gyrus, showed the opposite interaction, supporting unsuccessful imagery, but successful retrieval performance. Results are discussed in relation to reconstructive, attentional, semantic memory, and working memory processes. This is the first study to separate the neural correlates of successful and unsuccessful performance for both imagery and retrieval and for both auditory and visual modalities.

We want to touch IT. Are hybrid laptops just new fancy gadgets or a new revolution?

While the number of traditional laptops and computers sold has dipped slightly year over year, manufacturers have developed new hybrid laptops with touch screens to build on the tactile trend. This market is moving quickly to make touch the rule rather than the exception and the sales of these devices have tripled since the launch of Windows 8 in 2012, to reach more than sixty million units sold in 2015. Unlike tablets, that benefit from easy-to-use applications specially designed for tactile interactions, hybrid laptops are intended to be used with regular user-interfaces. Hence, one could ask whether tactile interactions are suited for every task and activity performed with such interfaces. Since hybrid laptops are increasingly used in educational situations, this study focuses on information search tasks which are commonly performed for learning purposes. It is hypothesized that tasks that require complex and/or less common gestures will increase user's cognitive load and impair task performance in terms of efficacy and efficiency. A study was carried out in a usability laboratory with 30 participants for whom prior experience with tactile devices has been controlled. They were asked to perform information search tasks on an online encyclopaedia by using only the touch screen of and hybrid laptop. Tasks were selected with respect to their level of cognitive demand (amount of information that had to be maintained in working memory) and the complexity of gestures needed (left and/or right clicks, zoom, text selection and/or input.), and grouped into 4 sets accordingly. Task performance was measured by the number of tasks succeeded (efficacy) and time spent on each task (efficiency). Perceived cognitive load was assessed thanks to a questionnaire given after each set of tasks. An eye tracking device was used to monitor users' attention allocation and to provide objective cognitive load measures based on pupil dilation and the Index of Cognitive Activity. Each experimental run took approximately one hour. The results of this within-subjects design indicate that tasks involving complex gestures led to a lower efficacy, especially when the tasks were cognitively demanding. Regarding efficacy, there is no significant differences between sets of tasks excepted for tasks with low cognitive demand and complex gestures that required more time to be achieved. Surprisingly, users that declared the biggest experience with tactile devices spent more time than less frequent users. Cognitive load measures indicate that participants reported having devoted more mental effort in the interaction when they had to use complex gestures.

Changes in fos expression in the rat brain after unilateral lesions of the anterior thalamic nuclei

Activity of the immediate early gene c-fos was compared across hemispheres in rats with unilateral anterior thalamic lesions. Fos protein was quantified after rats performed a spatial working memory test in the radial-arm maze, a task that is sensitive to bilateral lesions of the anterior thalamic nuclei. Unilateral anterior thalamic lesions produced evidence of a widespread hippocampal hypoactivity, as there were significant reductions in Fos counts in a range of regions within the ipsilateral hippocampal formation (rostral CA1, rostral dentate gyrus, 'dorsal' hippocampus, presubiculum and postsubiculum). A decrease in Fos levels was also found in the rostral and caudal retrosplenial cortex but not in the parahippocampal cortices or anterior cingulate cortices. The Fos changes seem most closely linked to sites that are also required for successful task performance, supporting the notion that the anterior thalamus, retrosplenial cortex and hippocampus form key components of an interdependent neuronal network involved in spatial mnemonic processing.

The differential effects of chlorpromazine and haloperidol on latent inhibition in healthy volunteers.

Latent inhibition (LI) is a measure of reduced learning about a stimulus to which there has been prior exposure without any consequence. It therefore requires a comparison between a pre-exposed (PE) and a non-pre-exposed (NPE) condition. Since, in animals, LI is disrupted by amphetamines and enhanced by antipsychotics, LI disruption has been proposed as a measure of the characteristic attentional deficit in schizophrenia: the inability to ignore irrelevant stimuli. The findings in humans are, however, inconsistent. In particular, a recent investigation suggested that since haloperidol disrupted LI in healthy volunteers, and LI was normal in non-medicated patients with schizophrenia, the previous findings in schizophrenic patients were entirely due to the negative effects of their medication on LI (Williams et al., 1998). We conducted two studies of antipsychotic drug effects on auditory LI using a within-subject, parallel group design in healthy volunteers. In the first of these, single doses of haloperidol (1 mg. i.v.) were compared with paroxetine (20 mg p.o.) and placebo, and in the second, chlorpromazine (100 mg p.o.) was compared with lorazepam (2 mg. p.o.) and placebo. Eye movements, neuropsychological test performance (spatial working memory (SWM), Tower of London and intra/extra dimensional shift, from the CANTAB test battery) and visual analogue rating scales, were also included as other measures of attention and frontal lobe function. Haloperidol was associated with a non-significant reduction in LI scores, and dysphoria/akathisia (Barnes Akathisia Rating Scale) in three-quarters of the subjects. The LI finding may be explained by increased distractibility which was indicated by an increase in antisaccade directional errors in this group. In contrast, LI was significantly increased by chlorpromazine but not by an equally sedative dose of lorazepam (both drugs causing marked decreases in peak saccadic velocity). Paroxetine had no effect on LI, eye movements or CANTAB neuropsychological test performance. Haloperidol was associated with impaired SWM, which correlated with the degree of dysphoria/akathisia, but no other drug effects on CANTAB measures were detected. We conclude that the effect of antipsychotics on LI is both modality and pharmacologically dependent and that further research using a wider range of antipsychotic compounds is necessary to clarify the cognitive effects of these drugs, and to determine whether there are important differences between them.

Imaging the genetics of executive function

Recent advances in neuroimaging technologies have allowed ever more detailed studies of the human brain. The combination of neuroimaging techniques with genetics may provide a more sensitive measure of the influence of genetic variants on cognitive function than behavioural measures alone. Here we present a review of functional magnetic resonance imaging (fMRI) studies of genetic links to executive functions, focusing on sustained attention, working memory and response inhibition. In addition to studies in the normal population, we also address findings from three clinical populations: schizophrenia, ADHD and autism spectrum disorders. While the findings in the populations studied do not always converge, they all point to the usefulness of neuroimaging techniques such as fMRI as potential endophenotypes for parsing the genetic aetiology of executive function. (C) 2007 Elsevier B.V. All rights reserved.

The story of some: Everyday pragmatic inference by children and adults

The statement, some elephants have trunks, is logically true but pragmatically infelicitous. Whilst some is logically consistent with all, it is often pragmatically interpreted as precluding all. In Experiments 1 and 2, we show that with pragmatically impoverished materials, sensitivity to the pragmatic implicature associated with some is apparent earlier in development than has previously been found. Amongst 8-year-old children, we observed much greater sensitivity to the implicature in pragmatically enriched contexts. Finally, in Experiment 3, we found that amongst adults, logical responses to infelicitous some statements take longer to produce than do logical responses to felicitous some statements, and that working memory capacity predicts the tendency to give logical responses to the former kind of statement. These results suggest that some adults develop the ability to inhibit a pragmatic response in favour of a logical answer. We discuss the implications of these findings for theories of pragmatic inference.