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Robert Barry
School of Psychology, University of Wollongong, Wollongong, Australia
Our brain dynamics studies have focused on the auditory equiprobable Go/NoGo task. This is an easy cognitive/behavioural task that can be used readily with a wide range of participants. Using ERP components, we have developed a processing schema that maps some of the cognitive stages involved, and have used this as a tool to explore developmental and sex differences, as well as some of the EEG/ERP brain-dynamics involved. Today I explore some of the correlates of inhibitory processing in this task, using a data-driven approach to the electrophysiology of cognitive processing.
We begin our data collection with an eye-calibration task to establish EEG-EOG regression coefficients for subsequent removal of EOG from the continuous task-related EEG data. We then filter, interpolate bad channels, extract 1 s epochs (-500 to +500 ms relative to stimulus onset) for correctly-responded trials, baseline these across the 100 ms period immediately-prestimulus, and reject trials with artefacts. For the ERP quantification, we form average Go and NoGo ERPs for each participant, then submit the -100 to 500 ms data to separate Go and NoGo temporal PCAs to extract the underlying ERP components. For EEG, we take the immediately-prestimulus 500 ms epochs (-500 to 0 ms), DC-correct these, zero-pad each to 1 s, decompose these with a Discrete Fourier Transform, then the Pink and White noise is computed and removed from each participant’s mean Go and NoGo spectra, after which the Go and NoGo noise-free spectra are submitted to separate frequency PCAs. We then relate the prestimulus EEG frequency components, and Pink and White noise amplitudes, to the ERP components and behavioural outcomes.
Krzysztof Bielski1,2, Szymon Wichary1, Magdalena Senderecka3
1Institute of Psychology, Faculty of Philosophy, Jagiellonian University, Cracow, Poland
2Doctoral School of Social Sciences, Jagiellonian University, Cracow, Poland
3Institute of Philosophy, Faculty of Philosophy, Jagiellonian University, Cracow, Poland
Errors can vary in their inevitability, rendering them more or less significant. Typically, more significant errors trigger more noticeable adjustments in behavior. However, this prompts the question: which specific brain system is accountable for recognizing the inevitability of errors? To address this issue we analyzed functional magnetic resonance imaging scans from 33 adults acquired during the stop signal task performance. Firstly, we observed heightened activity in the left medial frontal cortex (lMFC) during trials with failed inhibition compared to go trials with correct responses. Secondly, we investigated whether the activity within lMFC correlates with error inevitability. Employing mixed linear modelling on the time series of erroneous trials, we discovered a significant relationship between the magnitude of blood oxygenation level-dependent response within 4-8 seconds post-stop signal and the measure of error inevitability (value of the stop-response interval). We observed that the longer stop-response interval, the more pronounced the activity of lMFC was. Moreover, we also noticed that the more avoidable error was, the greater the slowing of response in the subsequent trial. These findings highlight the sensitivity of lMFC to error inevitability and their role in adaptive mechanisms during error processing. Thus, lMFC could be likened to the guiding role of a guardian angel, striving to make our actions better-suited.
Funding: This research was supported by the John Templeton Foundation grant “The Limits of Scientific Explanation” and by two grants from the National Science Centre of Poland: 2019/35/B/HS6/01173 (Opus) and 2020/38/E/HS6/00490 (Sonata Bis).
Patrycja Kałamała1,2, Máté Gyurkovics1,3, Daniel Bowie1, Grace Clements1, Kathy Low1, Florin Dolcos1, Monica Fabiani1, Gabriele Gratton1
1Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana-Champaign, United States
2Department of Philosophy, Jagiellonian University, Krakow, Poland
3School of Psychology & Neuroscience, University of Glasgow, Glasgow, United Kingdom
The broadband shape of the EEG spectrum, summarized using a 1/f^x function, is thought to reflect the Excitation:Inhibition (E:I) balance in cortical regions. This balance is an important feature of neural circuits and could inform aging studies, as older adults show a relative inhibitory deficit. Thus far, no studies have leveraged the event-related temporal dynamics of 1/f^x activity to understand the phases of information processing, especially in the context of aging. Here, for the first time, we examined variations of this activity during the foreperiod of a cued flanker task in younger (YA) and older adults (OA). We report a biphasic change in the spectral exponent (negative slopes in log-log space) after cue presentation, independent of ERPs, with an initial period of increased negativity (indicating cortical inhibition) followed by decreased negativity (indicating cortical excitation, especially in OA). The decrease in the exponent negativity was associated with lower performance and greater congruency costs in the flanker task. Finally, more novel cues reduced the shift towards excitation in OA, partly restoring their E:I balance and diminishing congruency costs. These findings demonstrate that the aperiodic EEG varies dynamically in a manner that is predictive of subsequent behavior. They also expand our understanding of how neural communication shapes cognition and have implications for neuroscientific models of cognitive processing and age-related cognitive decline.
Funding: NIA grant RF1AG062666 to G. Gratton and M. Fabiani.
Christina Thunberg1,2
1Multimodal Imaging and Cognitive Control Lab, Department of Psychology, University of Oslo, Oslo, Norway
2Cognitive and Translational Neuroscience Cluster, Department of Psychology, University of Oslo, Oslo, Norway
Response inhibition is crucial for flexible behavior. Significant efforts are made to characterize its biological underpinnings and identify neural markers of an inhibition process. The stop signal task is argued to be the purest inhibition task, and the associated model-based estimate of response inhibition latency (stop signal reaction time or SSRT) is central to much of this work. However, testing hypotheses about biological signatures require additional assumptions to those strictly derived from theory. For instance, when contrasting successful and failed inhibition to identify neural markers, it is implicitly assumed that this allows for isolating inhibitory differences. Similarly, when using the SSRT to validate neural markers, it is implicitly assumed that its variation is caused solely by inhibition variation. Or when using the SSRT as an endophenotype, one must assume that it measures a stable trait. Through a series of studies using stop signal task performance measures together with measures of central and peripheral nervous system activity, we have investigated these assumptions and found that several of them do not hold. Such flawed assumptions can leave findings uninterpretable and inferences invalid, ultimately limiting our understanding of biological substrates of response inhibition.
Funding: University of Oslo Life Sciences.
