Yael Arbel

Parsing the componential structure of post-error ERPs: A principal component analysis of ERPs following errors

We report the results of two experiments designed to clarify the spatial and temporal characteristics of the positive deflection that follows the error related negativity (ERN) elicited to incorrect responses in speeded reaction time tasks. Principal components analysis (PCA) indicates that the positive deflection reported to follow the ERN is composed of two different components: (a) a fronto-central positive deflection that follows the ERN and shares its spatial distribution and (b) a P300. When accuracy was required of the participants, the ERN and the P300 were larger in amplitude than when speed and accuracy were equally weighted. On the other hand, the amplitude of the fronto-central positive component was not affected by the degree to which accuracy was stressed.

Control of a 9-DoF Wheelchair-mounted robotic arm system using a P300 Brain Computer Interface: Initial experiments

A wheelchair-mounted robotic arm (WMRA) system was designed and built to meet the needs of mobilityimpaired persons with limitations of upper extremities, and to exceed the capabilities of current devices of this type. The control of this 9-degree-of-freedom system expands upon conventional control methods and combines the 7-DoF robotic arm control with the 2-degree-of-freedom power wheelchair control. The 3- degrees of redundancy are optimized to effectively perform activities of daily living and overcome singularities, joint limits and some workspace limitations. The control system is designed for teleoperated or autonomous coordinated Cartesian control, which offers expandability for future research. A P300 Brain Computer Interface (BCI), the BCI2000, was implemented to control the WMRA system. The control is done by recording and analysing the brain activity through an electrode cap while providing visual stimulation to the user via a visual matrix. The visual matrix contains a symbolic or an alphabetic array corresponding to the motion of the WMRA. By recognizing online and in real-time, which element in the matrix elicited a P300, the BCI system can identify which element the user chose to communicate. The chosen element is then communicated to the controller of the WMRA system. The speed and accuracy of the BCI system was tested. This paper gives details of the WMRAs integration with the BCI2000 and documents the experimental results of the BCI and the WMRA in simulation.

Single trial independent component analysis for P300 BCI system

A Brain Computer Interface (BCI) is a device that allows the user to communicate with the world without utilizing voluntary muscle activity (i.e., using only the electrical activity of the brain). It makes use of the well-studied observation that the brain reacts differently to different stimuli, as a function of the level of attention allotted to the stimulus stream and the specific processing triggered by the stimulus. In this article we present a single trial independent component analysis (ICA) method that is working with a BCI system proposed by Farwell and Donchin. It can dramatically reduce the signal processing time and improve the data communicating rate. This ICA method achieved 76.67% accuracy on single trial P300 response identification.

The good, the bad, or the useful? the examination of the relationship between the feedback-related negativity frn and long-term learning outcomes

According to the reinforcement learning account of the error-related negativity (ERN), the ERN is a manifestation of a signal generated in ACC as a consequence of a phasic decrease in the activity of the mesencephalic dopamine system occurring when the monitoring system evaluates events as worse than expected. This signal is also hypothesized to be used to modify behavior to ascertain that future events will have better outcomes. It is therefore expected that this signal be correlated with learning outcomes. We report a study designed to examine the extent to which the ERN is related to learning outcomes within a paired-associates learning task. The feedback-related negativity (FRN) elicited by stimuli that indicated to the participants whether their response was correct or not was examined both according the degree to which the associates were learned in the session and according to whether participants recalled the associations on the next day. The results of the spatio-temporal PCA indicate that, whereas the process giving rise to the negative feedback elicited a FRN whose amplitude was not correlated with long-term learning outcomes, positive feedback was associated with a FRN-like activity, which was correlated with the learning outcomes. Another ERP component that follows the FRN temporally and shares its spatial distribution was found associated with long-term learning outcomes. Our findings shed light on the functional significance of the feedback-related ERP components and are discussed within the framework of the reinforcement learning ERN hypothesis.

When a child errs: The ERN and the Pe complex in children

We report an analysis of the componential structure of the event-related potentials (ERPs) elicited when 8-10-year-old children err. We demonstrated previously that the positive deflection that follows the error-related negativity (ERN) in young adults is a combination of two ERP components, a fronto-central positive component and a P300. As these findings affect the interpretation of error-related ERP data, it is essential to determine if the componential structure of the ERPs elicited by childrens errors is similar to that found in young adults. The results of the current study confirm that, as is the case in adults, both an ERN and a fronto-central positivity are elicited by errors committed by children. In contrast to what has been previously found in adults, errors committed by children elicited a central positivity in addition to a parietal negativity that was elicited by correct responses.

On the utility of positive and negative feedback in a paired-associate learning task

This study offers a neurophysiological examination of the relationship between feedback processing and learning. A two-choice paired-associate learning task borrowed and modified from Tricomi and Fiez [Tricomi, E., & Fiez, J. A. Feedback signals in the caudate reflect goal achievement on a declarative memory task. Neuroimage, 41, 1154–1167, 2008] was employed to examine the mediofrontal electrophysiological brain activity associated with the processing of performance feedback in a learning task and to elucidate the extent to which the processing of the initial informative feedback is related to learning outcomes. Twenty participants were tasked with learning to correctly pair 60 novel objects with their names by choosing on a trial-by-trial basis between two possible names and receiving feedback about the accuracy of their selection. The novel objects were presented in three blocks of trials (rounds), each of which presented the same set of 60 objects once. The rounds allowed the separation of the initial informative feedback in Round 1 from the other feedback stimuli in Rounds 2 and 3. The results indicated differences in the processing of initial informative and proceeding feedback stimuli. More specifically, the difference appeared to be driven by the change in the processing of positive feedback. Moreover, very first positive feedback provided in association with a particular new object was found associated with learning outcomes. The results imply that signs of successful and unsuccessful learning may be detected as early as the initial positive feedback provided in a learning task. The results suggest that the process giving rise to the feedback-related negativity is sensitive to the utility of the feedback and that the processing of the first informative positive feedback is associated with learning outcomes.

The N400 and the P300 are not all that independent

This study assessed whether two ERP components that are elicited by unexpected events interact. The conditions that are known to elicit the N400 and the P300 ERP components were applied separately and in combination to terminal-words in sentences. Each sentence ended with a terminal-word that was highly expected, semantically unexpected, physically deviant, or both semantically unexpected and physically deviant. In addition, we varied the level of semantic relatedness between the unexpected terminal-words and the expected exemplars. Physically deviant words elicited a P300, whereas semantically unexpected words elicited an N400, whose amplitude was sensitive to the level of semantic relatedness. Words that were both semantically unexpected and physically deviant elicited both an N400 with enhanced amplitude, and a P300 with reduced amplitude. These results suggest an interaction between the processes manifested by the two components.

Efficiency of responding to unexpected information varies with sex, age, and pubertal development in early adolescence

Entry into adolescence is marked by dramatic changes resulting from a dynamic interplay among biological and psychosocial processes. Despite the complexity, development is often indexed only by age in event-related potential (ERP) studies. To broaden this approach, we address the effects of gender and pubertal development, along with age, in adolescents using a psychophysiological probe of decision making, the P300 component. Overall, girls exhibited shorter P300 latencies and smaller P300 amplitudes compared to boys, suggesting more efficient information processing. In both genders, P300 latency and amplitude also diminished as age and pubertal status increased, again suggesting increasing efficiency of information processing with development. Our findings highlight the necessity of considering more than age when examining cognitive functioning in adolescents and, in particular, the necessity of considering gender whenever developmental issues are addressed.

P300 Based Single Trial Independent Component Analysis on EEG Signal

A Brain Computer Interface (BCI) is a device that allows the user to communicate with the world without utilizing voluntary muscle activity (i.e., using only the electrical activity of the brain). It makes use of the well-studied observation that the brain reacts differently to different stimuli, as a function of the level of attention allotted to the stimulus stream and the specific processing triggered by the stimulus. In this article we present a single trial independent component analysis (ICA) method that is working with a BCI system proposed by Farwell and Donchin. It can dramatically reduce the signal processing time and improve the data communicating rate. This ICA method achieved 76.67% accuracy on single trial P300 response identification.

P300 Based Brain Computer Interfaces: A Progress Report

Brain-Computer Interfaces (BCI) are the only means of communication available to patients who are locked-in, that is for patients who are completely paralyzed yet are fully conscious. We focus on the status of the P300-BCI first described by Farwell and Donchin (1988). This system has now been tested with several dozen ALS patients and some have been using this approach for communication at a very extensive level. More recently, we have adapted this BCI (in collaboration with the laboratory of Dr. Rajiv Dubey) to the control of a robotic arm. In this presentation we will discuss the special problems of human computer interaction that occur within the context of such a BCI. The special needs of the users forced the development of variants of this system, each with advantages and disadvantages. The general principles that can be derived from the experience we have had with this BCI will be reviewed.