An Electrophysiological Investigation into the Role of Cognitive Control in the Attentional Blink

Accuracy at reporting a second-target (T2) is reduced if it is presented within approximately 500 ms of the first target (T1) – an attentional blink (AB). Early models explained the AB in terms of attentional limitations creating a processing bottleneck such that T2 processing would be impaired while T1 processing was ongoing. Theoretical models of the AB have more recently been expanded to include the role of cognitive control. In this dissertation I propose that cognitive control, defined as the optimization of information processing in order to achieve goals, is maladapted to the dual-task conditions of the AB task in that cognitive control optimizes the T1 goal, due to its temporal proximity, at the cost of T2. I start with the concept that the role of cognitive control is to serve goals, and that how goals are conceived of and the degree of motivation associated with those goals will determine whether cognitive control will create the condition that cause the AB. This leads to the hypothesis that electrophysiological measures of cognitive control and the degree of attentional investment resulting from cognitive control modulate the AB and explain individual differences in the AB. In a series of four studies feedback-related N2 amplitude, (reflecting individual differences in the strength of cognitive control), and event-related and resting alpha frequency oscillatory activity (reflecting degree of attentional investment), are used to explain both intra- and inter-individual variability in performance on the AB task. Results supported the hypothesis that stronger cognitive control and greater attentional investment are associated with larger AB magnitudes. Attentional investment, as measured by alpha frequency oscillations, and cognitive control, as measured by the feedback-related N2, did not relate to each other as hypothesized. It is proposed that instead of a measure of attentional investment alone, alpha frequency oscillatory activity actually reflects control over information processing over time, in other words the timing of attention. With this conceptualization, various aspects of cognitive control, either related to the management of goals (feedback-related N2) or the management of attention over time to meet goals, explain variability in the AB.

Task-Dependent Oscillatory Brain Activity During Oculomotor Delayed Response Task

This study used three Oculomotor Delayed Response (ODR) tasks to investigate the unique cognitive demands during the delay period. Changes in alpha power were used to index cognitive efforts during the delay period. Continuous EEGs from 25 healthy young adults (18-34 years) were recorded using dense electrode array. The data was analyzed by 6-cycle Morlet wavelet decompositions in the frequency range of 2-30 Hz to create time- frequency decompositions for four midline electrode sites. The 99% confidence intervals using the bootstrapped 20% trimmed mean of the 10 Hz frequency were used to examine the differences among conditions. Compared to two Memory conditions (Match and Non-Match), Control condition yielded significant differences in all frequencies over the entire trial period, suggesting a cognitive state difference. Compared to Match condition, the Non–Match condition had lower alpha activity during the delay period at each midline electrode site reflecting the higher cognitive effort required.

Top-down and Bottom-up influences on ACC activation: Evaluation of a proposed model of the feedback-related negativity

The Feedback-Related Negativity (FRN) is thought to reflect the dopaminergic prediction error signal from the subcortical areas to the ACC (i.e., a bottom-up signal). Two studies were conducted in order to test a new model of FRN generation, which includes direct modulating influences of medial PFC (i.e., top-down signals) on the ACC at the time of the FRN. Study 1 examined the effects of one’s sense of control (top-down) and of informative cues (bottom-up) on the FRN measures. In Study 2, sense of control and instruction-based (top-down) and probability-based expectations (bottom-up) were manipulated to test the proposed model. The results suggest that any influences of medial PFC on the activity of the ACC that occur in the context of incentive tasks are not direct. The FRN was shown to be sensitive to salient stimulus characteristics. The results of this dissertation partially support the reinforcement learning theory, in that the FRN is a marker for prediction error signal from subcortical areas. However, the pattern of results outlined here suggests that prediction errors are based on salient stimulus characteristics and are not reward specific. A second goal of this dissertation was to examine whether ACC activity, measured through the FRN, is altered in individuals at-risk for problem-gambling behaviour (PG). Individuals in this group were more sensitive to the valence of the outcome in a gambling task compared to not at-risk individuals, suggesting that gambling contexts increase the sensitivity of the reward system to valence of the outcome in individuals at risk for PG. Furthermore, at-risk participants showed an increased sensitivity to reward characteristics and a decreased response to loss outcomes. This contrasts with those not at risk whose FRNs were sensitive to losses. As the results did not replicate previous research showing attenuated FRNs in pathological gamblers, it is likely that the size and time of the FRN does not change gradually with increasing risk of maladaptive behaviour. Instead, changes in ACC activity reflected by the FRN in general can be observed only after behaviour becomes clinically maladaptive or through comparison between different types of gain/loss outcomes.

Examining peer-controlled KR schedules during the learning of a movement-timing task as a function of task experience.

Learners can be provided with feedback in the form of knowledge of results (KR), under self-controlled and peer-controlled schedules. Recently, McRae, Hansen, and Patterson (2015), identified that inexperienced peers can provide KR that can facilitate motor skill acquisition. However, it is currently unknown whether previous task experience differentially impacts how peers present learners with KR and whether this KR impacts motor skill acquisition. In the present study, participants were randomly assigned to become inexperienced peer facilitators, learners with an inexperienced peer, learners with self-control who later became experienced peers, learners with an experienced peer, or learners in a control group. During acquisition learners completed a serial-timing task with a goal of 2500ms and returned approximately twenty four hours later for a delayed retention, time transfer, and pattern transfer test. We predicted that during the delayed tests, learners with self-control would outperform all other groups. Furthermore, we predicted that learners who received KR from experienced peers would outperform learners who received KR from inexperienced peers. However, our results indicated that participants who received peer-controlled and self-controlled KR schedules learned the task in an equivalent manner. Thus, our results are novel as they identify that inexperienced peers can provide KR that is as effective as KR provided by experienced peers and KR requested under self-controlled conditions.