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Dive into the research topics where Jack S. Fogarty is active.

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Featured researches published by Jack S. Fogarty.


International Journal of Psychophysiology | 2016

ERP Go/NoGo condition effects are better detected with separate PCAs.

Robert J. Barry; Frances M. De Blasio; Jack S. Fogarty; Diana Karamacoska

We explored the separation of Go and NoGo effects in the ERP components elicited in an equiprobable Go/NoGo task, using different forms of temporal Principal Components Analysis (PCA). Following exploratory simulation studies assessing the PCA impact of latency jitter and between-condition latency differences in the P3 latency range, an empirical study compared results of a Combined PCA carried out using both Go and NoGo ERPs together as input, with those from two Separate PCAs carried out on the Go and NoGo ERPs separately. The simulation studies indicated that Separate PCAs provide adequate component recovery in the presence of P3 latency jitter, and that Combined PCAs provide good separation of components only when systematic condition-related latency differences are sufficiently large (here ~110ms). In the empirical data, broadly-similar components were obtained from the Combined and Separate PCAs, supporting previous findings from Combined PCA investigations, and the consequent interpretations of the sequential processing involved. However, the Separate PCAs generated latency differences for components in the Go and NoGo processing chains that better matched the late Go/NoGo ERP peaks, and produced better-defined and larger components that fitted the stages in a hypothetical processing schema developed for this paradigm. Overall, the Separate PCAs yielded a better partitioning of the ERP variance associated with the Go and NoGo conditions, and should be considered as the first choice in future investigations if systematic component or subcomponent latency differences are present or suspected.


Frontiers in Psychology | 2016

Identifying objective EEG based markers of linear vection in depth

Stephen Palmisano; Robert J. Barry; Frances M. De Blasio; Jack S. Fogarty

This proof-of-concept study investigated whether a time-frequency EEG approach could be used to examine vection (i.e., illusions of self-motion). In the main experiment, we compared the event-related spectral perturbation (ERSP) data of 10 observers during and directly after repeated exposures to two different types of optic flow display (each was 35° wide by 29° high and provided 20 s of motion stimulation). Displays consisted of either a vection display (which simulated constant velocity forward self-motion in depth) or a control display (a spatially scrambled version of the vection display). ERSP data were decomposed using time-frequency Principal Components Analysis (t–f PCA). We found an increase in 10 Hz alpha activity, peaking some 14 s after display motion commenced, which was positively associated with stronger vection ratings. This followed decreases in beta activity, and was also followed by a decrease in delta activity; these decreases in EEG amplitudes were negatively related to the intensity of the vection experience. After display motion ceased, a series of increases in the alpha band also correlated with vection intensity, and appear to reflect vection- and/or motion-aftereffects, as well as later cognitive preparation for reporting the strength of the vection experience. Overall, these findings provide support for the notion that EEG can be used to provide objective markers of changes in both vection status (i.e., “vection/no vection”) and vection strength.


Psychophysiology | 2018

ERP components and behavior in the auditory equiprobable go/no-go task: Inhibition in young adults

Jack S. Fogarty; Robert J. Barry; Frances M. De Blasio; Genevieve Z. Steiner

Previous research suggests that young adults do not need active and effortful inhibition to successfully complete the auditory equiprobable go/no-go task, a view that was incorporated into Barry and De Blasios sequential processing schema for this task. However, recent evidence in children suggests that view could be incorrect. The present research aims to clarify the functionality of the N2 and P3 subcomponents within the proposed schema, assessing the role of inhibition in this task. To optimize the quantification of the N2 and P3 subcomponents, separate temporal PCAs were applied to the go/no-go ERP data from 40 young adults. Correlations were then used to link subcomponent amplitudes with performance outcomes, informing a functional interpretation of each subcomponent. Larger N2b and P3a amplitudes were each linked to fewer commission errors. N2c amplitude also increased with intraindividual reaction time variability, but no performance outcomes were associated with P3b. These findings link the young adult N2b and P3a with inhibition in the auditory equiprobable task, confirming the importance of control for successful nontarget processing in that paradigm. The functionality of N2c and P3b remain unclear from our results. However, these outcomes improve our understanding of cognitive processing in equiprobable tasks, and contribute to an improved conceptualization of the sequential processing schema.


International Journal of Psychophysiology | 2018

A processing schema for children in the auditory equiprobable Go/NoGo task: ERP components and behaviour

Robert J. Barry; Frances M. De Blasio; Jack S. Fogarty

A sequential processing model for adults in the auditory equiprobable Go/NoGo task has been developed in recent years. This used temporal principal components analysis (PCA) to decompose Go/NoGo event related potential (ERP) data into components that mark stages of perceptual and cognitive processing. The model has been found useful in frameworking several studies in young and older adults, and in children. Recently, it has been demonstrated that the common PCA approach of decomposing Go and NoGo ERP data together results in misallocation of variance between the conditions, distorting the timing, topography, and amplitudes of the resultant components in each condition. The present study thus reanalyses data from a child study, conducting separate PCAs on the data from each condition. Multiple regression was then used to seek links with behavioural measures from the task. In addition to confirming the previous NoGo N2b/inhibitory processing link, novel NoGo Negative Slow Wave/error evaluation and Go N1-1/RT variability links were obtained. Based on these outcomes, the recommended separate application of PCAs to Go and NoGo data was confirmed. The present data were used to develop a child-specific sequential processing schema for this paradigm, suggesting earlier separation of the Go and NoGo processing chains, and the need to include an additional inhibition and evaluation stage. The child schema should be useful in future studies involving this and other two-choice reaction tasks.


Biological Psychology | 2018

EEG phase states at stimulus onset in a variable-ISI Go/NoGo task: Effects on ERP components

Robert J. Barry; Jack S. Fogarty; Frances M. De Blasio; Diana Karamacoska


International Journal of Psychophysiology | 2018

EEG theta/beta ratio during mind wandering episodes

D. Van Son; F.M. De Blasio; Jack S. Fogarty; W. Van der Does; Robert J. Barry; Peter Putman


International Journal of Psychophysiology | 2018

Subcomponents of the Late Positive Complex (P300)

Robert J. Barry; Genevieve Z. Steiner; F.M. De Blasio; Jack S. Fogarty; Diana Karamacoska; Brett MacDonald


International Journal of Psychophysiology | 2016

Linking Behaviour into the Go/NoGo Processing Schema

Jack S. Fogarty; Robert J. Barry; Frances M. De Blasio; Diana Karamacoska; Genevieve Z. Steiner


International Journal of Psychophysiology | 2016

Applying the Go/NoGo processing schema to a visual oddball task in older adults

Genevieve Z. Steiner; Robert J. Barry; Jack S. Fogarty


International Journal of Psychophysiology | 2016

Optimising PCA methodology to better assess stimulus-specific processes

Frances M. De Blasio; Robert J. Barry; Jack S. Fogarty; Diana Karamacoska

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F.M. De Blasio

University of Wollongong

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