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Neurofeedback (NF) is a promising intervention for improvements in motor performance in Parkinson's disease. This NF pilot study in healthy participants aimed to achieve the following: (1) determine participants' ability to bi-directionally modulate sensorimotor beta power and (2) determine the effect of NF on movement performance. A real-time EEG-NF protocol was used to train participants to increase and decrease their individual motor cortex beta power amplitude, using a within-subject double-blind sham-controlled approach. Movement was assessed using a Go/No-go task. Participants completed the NASA Task Load Index and provided verbal feedback of the NF task difficulty. All 17 participants (median age = 38 (19–65); 10 females) reliably reduced sensorimotor beta power. No participant could reliably increase their beta activity. Participants reported that the NF task was challenging, particularly increasing beta. A modest but significant increase in reaction time correlated with a reduction in beta power only in the real condition. Findings suggest that beta power control difficulty varies by modulation direction, affecting participant perceptions. A correlation between beta power reduction and reaction times only in the real condition suggests that intentional beta power reduction may shorten reaction times. Future research should examine the minimum beta threshold for meaningful motor improvements, and the relationship between EEG mechanisms and NF learning to optimise NF outcomes. [ABSTRACT FROM AUTHOR]

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.

Data from Neuropsychology have been widely used in order both to lest pre-existing cognitive theories and to develop new accounts. Indeed, several theorists have used dissociations, and in particular double dissociations, both in theory testing and in developing new theoretical accounts Double dissociations are indeed believed to be a key tool in revealing the gross structure or "modularity" of cognitive processes. In this paper, in the light of a case study in which a simple electrical system is systematically lesioned, we argue that double dissociation in an arbitrary modular system need not, and typically will not, reveal that modularity. These results suggest that the observation of a double dissociation implies little about the structure of the underlying system. W e finish arguing that the weakness of the methods described involves that neurobiological data have to be seriously taken into account in order to uncover the real structure of the cognitive system.

Neuropsychological evidence has proved influential both in testing pre-existing cognitive theories and in developing new accounts. It has been argued that dissociations, and, in particular, double dissociation are particularly valuable in developing new theoretical accounts, since they may reveal the gross structure or "modularity" of cognitive processes. In this paper, we show that even fully distributed systems -i.e. systems with no modularity can give rise to double dissociations. W e give the example of a recurrent neural network which draws loops and spirals which shows a double dissociation between the two tasks when lesioned. This result suggests that the observation of a double dissociation implies little about the modularity of the underlying system. In the final section we argue that a dual task technique can give additional hints about the structure of the underlying system because the class of distributed systems we describe are not able, in general, to perform two tasks at the same time. Finally, we argue that neurobiology has to be taken into account in order to interpret purely behavioral data.

An experiment was conducted in which subjects repeatedly constructed Origami boxes, following example models displayed by the experimenters. A microgenetic analysis was performed on videotapes of the experiment. Results show an increase in speed generally following the power law of practice, and the rearrangement and combination of operations into larger units. They give evidence for the importance of external information in the tasks people perform, and contain a possible example an occasion of insight prompted by earlier breakdowns. Most importantly, the experiment shows how an apparently straightforward improvement in performance can be dissected to uncover the myriad factors and effects that underlie it.

Visual perspective taking may rely on the ability to mentally rotate one's own body into that of another. Here, we test whether participants' ability to make active body movements plays a causal role in visual perspective taking. We utilised our recent task that measures whether participants spontaneously represent another's visual perspective in a (quasi-)perceptual format that can drive own perceptual decision making. Participants reported whether alphanumeric characters, presented in different orientations, are shown in their normal or mirror-inverted form (e.g., "R" vs. "Я"). Between trials, we manipulated whether another person was sitting either left or right of the character and whether participants' movement was restricted with a chinrest or whether they could move freely. As in our previous research, participants spontaneously took the visual perspective of the other person, recognising rotated letters more rapidly when they appeared upright to the other person in the scene, compared with when they faced away from that person, and these effects increased with age but were (weakly) negatively related to schizotypy and not to autistic traits or social skills. Restricting participants' ability to make active body movements did not influence these effects. The results, therefore, rule out that active physical movement plays a causal role in computing another's visual perspective, either to create alignment between own and other's perspective or to trigger perspective taking processes. The postural adjustments people sometimes make when making judgements from another's perspective may instead be a bodily consequence of mentally transforming one's actual to an imagined position in space. [ABSTRACT FROM AUTHOR]