Hebbian Learning of Artificial Grammars

A connectionist model is presented that used a hebbian learning rule to acquire knowledge about an artificial grammar (AG). The validity of the model was evaluated by the simulation of two classic experiments from the A G learning literature. The first experiment showed that human subjects were significantly better at learning to recall a set of strings generated by an A G , than by a random, process. The model shows the same pattern of performance. The second experiment showed that human subjects were able to generalize the knowledge they acquired during A G learning to novel strings generated by the same grammar. The model is also capable of generalization, and the percentage of errors made by human subjects and by the model are qualitatively and quantitatively very similar. Overall, the model suggests that hebbian learning is a viable candidate for the mechanism by which human subjects become sensitive to the regularities present in AG's. From the perspective of computational neuroscience, the implications of the model for implicit learning theory . as well as what the model may suggest about the relationship between implicit and explicit memory, are discussed

Attention, Memory, and Concepts in Autism

peer-reviewed publicatio

Mental simulation for grounding object cognition

Grounded (embodied) theories of cognition propose that memory, including knowledge and meaning, is grounded in sensorimotor and mental state processes. The main proposed mechanism for how memory is grounded is mental simulation. Simulation occurs when neural activity in modal association cortex triggers time-locked, recurrent and feedback activity across multiple lower-level modal processing areas from which the memory was initially constructed. Through this distributed multi-regional activity, seeing an object or reading its name (e.g., “dog”) re-enacts associated features that were stored during earlier learning experiences (e.g. its shape, color, motion, actions with it), thereby constructing cognition, memory, and meaning. This paper reviews convergent evidence from cognitive neuroscience of mental imagery, object cognition, and memory that supports a multi-state interactive (MUSI) account of automatic and strategic mental simulation mechanisms that can ground memory, including the meaning, of objects in modal processing of visual features

The sensitive, open creator

Identifying a creative personality has been challenging. Sensitivity was implicated in creativity in early studies but more recently defined as a biologically-based personality dimension (i.e., temperament). In this paper we aim to establish relationships between temperament, personality and creative potential and achievement. This laboratory study with a large diverse sample used multiple recently established sensitivity and creativity measures while controlling negative-affect and Big-Five personality traits. Only sensitivity and openness correlate positively with three creativity measures and independently predict two (achievement, ideation). Openness predicts creative products and achievement more strongly as sensitivity rises above average, and conversely. Sensitivity and openness primarily determine diverse creative abilities and demonstrate vantage-sensitivity. Developmental environment interacting with neurosensitivity mechanisms (especially lower inhibition), and automatic attention may explain why sensitive, open people are more creative

Labels direct infants’ attention to commonalities during novel category learning

Recent studies have provided evidence that labeling can influence the outcome of infants’ visual categorization. However, what exactly happens during learning remains unclear. Using eye-tracking, we examined infants’ attention to object parts during learning. Our analysis of looking behaviors during learning provide insights going beyond merely observing the learning outcome. Both labeling and non-labeling phrases facilitated category formation in 12-month-olds but not 8-month-olds (Experiment 1). Non-linguistic sounds did not produce this effect (Experiment 2). Detailed analyses of infants’ looking patterns during learning revealed that only infants who heard labels exhibited a rapid focus on the object part successive exemplars had in common. Although other linguistic stimuli may also be beneficial for learning, it is therefore concluded that labels have a unique impact on categorization

Sensory Processing Sensitivity in the context of Environmental Sensitivity: A critical review and development of research agenda

Sensory Processing Sensitivity (SPS) is a common, heritable and evolutionarily conserved trait describing inter-individual differences in sensitivity to both negative and positive environments. Despite societal interest in SPS, scientific knowledge is lagging behind. Here we critically discuss how SPS relates to other theories, how to measure SPS, whether SPS is a continuous vs categorical trait, its relation to other temperament and personality traits, the underlying aetiology and neurobiological mechanisms, and relations to both typical and atypical development, including mental and sensory disorders. Drawing on the diverse expertise of the authors, we set an agenda for future research to stimulate the field. We conclude that SPS increases risk for stress-related problems in response to negative environments, but also provides greater benefit from positive and supportive experiences. The field requires more reliable and objective assessment of SPS, deeper understanding of its mechanisms to differentiate it from other traits. Future research needs to target prevention of adverse effects associated with SPS, and exploitation of its positive potential to improve well-being and mental health

Task and spatial frequency modulations of object processing: an EEG study.

Visual object processing may follow a coarse-to-fine sequence imposed by fast processing of low spatial frequencies (LSF) and slow processing of high spatial frequencies (HSF). Objects can be categorized at varying levels of specificity: the superordinate (e.g. animal), the basic (e.g. dog), or the subordinate (e.g. Border Collie). We tested whether superordinate and more specific categorization depend on different spatial frequency ranges, and whether any such dependencies might be revealed by or influence signals recorded using EEG. We used event-related potentials (ERPs) and time-frequency (TF) analysis to examine the time course of object processing while participants performed either a grammatical gender-classification task (which generally forces basic-level categorization) or a living/non-living judgement (superordinate categorization) on everyday, real-life objects. Objects were filtered to contain only HSF or LSF. We found a greater positivity and greater negativity for HSF than for LSF pictures in the P1 and N1 respectively, but no effects of task on either component. A later, fronto-central negativity (N350) was more negative in the gender-classification task than the superordinate categorization task, which may indicate that this component relates to semantic or syntactic processing. We found no significant effects of task or spatial frequency on evoked or total gamma band responses. Our results demonstrate early differences in processing of HSF and LSF content that were not modulated by categorization task, with later responses reflecting such higher-level cognitive factors

The Timing of the Cognitive Cycle

We propose that human cognition consists of cascading cycles of recurring brain events. Each cognitive cycle senses the current situation, interprets it with reference to ongoing goals, and then selects an internal or external action in response. While most aspects of the cognitive cycle are unconscious, each cycle also yields a momentary “ignition” of conscious broadcasting. Neuroscientists have independently proposed ideas similar to the cognitive cycle, the fundamental hypothesis of the LIDA model of cognition. High-level cognition, such as deliberation, planning, etc., is typically enabled by multiple cognitive cycles. In this paper we describe a timing model LIDA's cognitive cycle. Based on empirical and simulation data we propose that an initial phase of perception (stimulus recognition) occurs 80–100 ms from stimulus onset under optimal conditions. It is followed by a conscious episode (broadcast) 200–280 ms after stimulus onset, and an action selection phase 60–110 ms from the start of the conscious phase. One cognitive cycle would therefore take 260–390 ms. The LIDA timing model is consistent with brain evidence indicating a fundamental role for a theta-gamma wave, spreading forward from sensory cortices to rostral corticothalamic regions. This posteriofrontal theta-gamma wave may be experienced as a conscious perceptual event starting at 200–280 ms post stimulus. The action selection component of the cycle is proposed to involve frontal, striatal and cerebellar regions. Thus the cycle is inherently recurrent, as the anatomy of the thalamocortical system suggests. The LIDA model fits a large body of cognitive and neuroscientific evidence. Finally, we describe two LIDA-based software agents: the LIDA Reaction Time agent that simulates human performance in a simple reaction time task, and the LIDA Allport agent which models phenomenal simultaneity within timeframes comparable to human subjects. While there are many models of reaction time performance, these results fall naturally out of a biologically and computationally plausible cognitive architecture