ERP Markers of Auditory Go/NoGo Processing

The Sequential Processing Schema is a data-driven model that uses event-related potential (ERP) components to chart the important psychophysiological processes activated when completing auditory equiprobable Go/NoGo tasks. This model is useful for measuring experimental effects on basic cognitive processes and provides a valuable framework to synthesise and test ERP component theories. Determining the cognitive and behavioural correlates of ERP components is critical for understanding their functional significance and utility in psychology. Additional research is also needed to refine the conceptualisation of the ERP components and cognitive processing requirements in equiprobable Go/NoGo tasks, which are commonly used in psychophysiological research. To do that, robust data-driven methods such as temporal Principal Components Analysis (PCA) are needed for effective ERP component quantification and analyses of the Go/NoGo ERP component ‘processing’ series. This doctoral thesis aimed to clarify ERP component functionality and refine our understanding of equiprobable Go/NoGo tasks by developing the Sequential Processing Schema and exploring how ERP/PCA components relate to cognitive and behavioural processing under different Go/NoGo task conditions. Study 1 compared the ERP component processing series associated with auditory equiprobable and oddball variants of the Go/NoGo task. The manipulation of probability and the relevant modulation of the ERP component series reflected a shift in particular cognitive demands or task requirements, which promoted the conceptual development of component functionality and the generalisability of the Schema. The results of Study 1 questioned the identity of a core ERP component (i.e., Processing Negativity) previously linked to auditory Go/NoGo processing; this was pursued in detail in Study 2, which aimed to clarify the ERP components associated with early information processing in auditory equiprobable and ‘frequent Go’ variants of the Go/NoGo task. Stimulus probability differences (this time the inverse of Study 1) were again used to elucidate component functionality and provide insight into the cognitive task demands. Study 3 and 4 explored ERP component functionality by examining Go stimulus- and response-locked ERP averaging effects, and the link between the equiprobable NoGo P3a and motor response inhibition. Studies 1–4 provided insight into the sequential processing requirements in auditory equiprobable Go/NoGo tasks, and the associated ERP/PCA components, promoting the development of common ERP components as indices of cognitive processes. These outcomes clarified the utility of the equiprobable Go/NoGo task, and highlight important similarities and differences between Go/NoGo and oddball processing, encouraging ERP theory development and integration between those common research paradigms. An update to the Schema was proposed to accommodate the ERP findings and reflect the refined interpretation of equiprobable Go/NoGo processing developed in this thesis, including a shift in the conceptualisation of the sensory processing and inhibitory requirements in the equiprobable task. This was considered to improve the conceptual framework of the Schema and its utility for charting the cognitive and behavioural processing in different task conditions. The outcomes also provide novel insight into how healthy young adults process information and encourage further studies of sequential processing to help delineate abnormalities in cognitive processing related to different psychopathologie

The Spatial-Numerical Association of Response Codes (SNARC) effect in highly math-anxious individuals: An ERP study

The Spatial-Numerical Association of Response Codes (SNARC) effect was examined in highly (HMA) and low math-anxious (LMA) individuals performing a number comparison in an ERP study. The SNARC effect consists of faster latencies when the response side is congruent with number location in the mental number line (MNL). Despite the stronger SNARC effect in the HMA group, their responses in incongruent trials were slower than in congruent trials only for the largest numerical magnitudes. Moreover, HMAs showed a less positive centroparietal P3b component in incongruent trials than in congruent ones, but only for the largest magnitudes. Since the SNARC effect arises during response selection and P3b positivity decreases with the difficulty of decision, this result suggests that HMA individuals might find it more difficult than LMAs to control the conflict between the automatically activated location of numbers in the MNL and the response side, especially in more cognitively demanding trials

Tracking the implicit acquisition of nonadjacent transitional probabilities by ERPs

The implicit acquisition of complex probabilistic regularities has been found to be crucial in numerous automatized cognitive abilities, including language processing and associative learning. However, the neurocognitive processes supporting the implicit extraction of 2nd order non-adjacent transitional probabilities have not been completely elucidated. Therefore, this study investigated the sensitivity of event-related brain potentials (ERPs) to these probabilistic regularities embedded in a sequence of visual stimuli without providing explicit information on the structure of the stimulus stream. Healthy young adults (N = 32) performed a perceptual-motor RT task that included an alternating sequential regularity between non-adjacent trials while RTs and ERPs were measured time-locked to the onset of the stimulus. RT effects indicated the rapid acquisition of transitional probabilities. The acquisition process was also tracked by the P3 component. Modulations of the P3 amplitude indicated that the more probable short-range relations could be integrated in the internal representations formed on the experienced stimulus environment. Meanwhile, the less probable short-range relations delivered possibly surprising information over the course of the task, by which the internal representations could have been updated. These results suggest that representations on the probabilistic regularities of the ongoing stimulus context are implicitly formed and constantly revised. Overall, this study (1) highlights the role of predictive processes during implicit memory formation, and (2) delineates a potential to gain further insight into the dynamics of implicit acquisition processes

On the Neurophysiological Mechanisms Underlying the Adaptability to Varying Cognitive Control Demands

Cognitive control processes are advantageous when routines would not lead to the desired outcome, but this can be ill-advised when automated behavior is advantageous. The aim of this study was to identify neural dynamics related to the ability to adapt to different cognitive control demands – a process that has been referred to as ‘metacontrol.’ A sample of N = 227 healthy subjects that was split in a ‘high’ and ‘low adaptability’ group based on the behavioral performance in a task with varying control demands. To examine the neurophysiological mechanisms, we combined event-related potential (ERP) recordings with source localization and machine learning approaches. The results show that individuals who are better at strategically adapting to different cognitive control demands benefit from automatizing their response processes in situations where little cognitive control is needed. On a neurophysiological level, neither perceptual/attentional selection processes nor conflict monitoring processes paralleled the behavioral data, although the latter showed a descriptive trend. Behavioral differences in metacontrol abilities were only significantly mirrored by the modulation of response-locked P3 amplitudes, which were accompanied by activation differences in insula (BA13) and middle frontal gyrus (BA9). The machine learning result corroborated this by identifying a predictive/classification feature near the peak of the response-locked P3, which arose from the anterior cingulate cortex (BA24; BA33). In short, we found that metacontrol is associated to the ability to manage response selection processes, especially the ability to effectively downregulate cognitive control under low cognitive control requirements, rather than the ability to upregulate cognitive control

Evoked Potentials during Language Processing as Neurophysiological Phenomena

The evoked, event-related potential of the EEG has been extensively employed to study language processing. But what is the ERP? An extensive discussion of contemporary theories about the neurophysiology underlying late ERPs is given. Then, in a series of experiments, domain-general perspectives on ERP components are tested regarding their applicability for language-related brain activity. A range of analysis methods (some of which have not been previously applied to the study of auditory sentence processing) such as single-trial analyses and independent component decomposition, demonstrate the degree to which domain general mechanisms explain the language-related EEG

Neurofeedback of Theta and Beta Frequencies: Effects on Selective Attention and Response Inhibition

Despite the widespread employment of electroencephalographic (EEG) neurofeedback (NF) in clinical and cognitive enhancement contexts, its impact on selective attention and response inhibition remains poorly understood. The present research investigated the influence of theta frequency suppression and low-beta frequencies enhancement on these cognitive functions. A first study investigated the differential impact of the sensorimotor rhythm (SMR) and beta1 amplitude enhancement NF on event-related potentials (ERP) and behavioral measures indexing selective attention and response inhibition in the three-stimuli oddball and in the cued-Go/Nogo tasks. The learning curves evinced training-specific amplitude increments in the beta1 but not in the SMR frequency. However, SMR NF was associated with increased Go-P3 amplitude, decreased mean RT and RT SD, while control and beta1 NF were associated with increased false alarm rates in the cued-Go/Nogo. A second study attempted to understand whether performance increments in selective attention and response inhibition could be explained by theta suppression NF when compared to beta1 NF in the same task conditions. Within-session theta amplitude was decreased in theta relative to beta1 NF in passive resting state but not during feedback trials. However, for both theta and beta1 NF there was no evidence of training-specific amplitude changes relative to controls. Regarding selective attention, the mean RT was increased following beta1 NF and decreased after theta NF but not in the same task conditions. This study also failed to provide evidence of increased or decreased performance in response inhibition. In conclusion, the present research was not conclusive regarding the NF conditions that might have contributed to improvements in target processing efficiency and cancellation of a previously prepared response in previous studies. Specific proposals to address several methodological limitations that might have hindered the possibility of detecting frequency-specific amplitude changes and cognitive improvements were advanced

Bayesian modeling of temporal expectations in the human brain

The ability to predict when a relevant event might occur is critical to survive in our dynamic and uncertain environment. This cognitive ability, usually referred to as temporal preparation, allows us to prepare temporally optimized responses to forthcoming stimuli by anticipating their timing: from safely crossing a busy road during rush hours, to timing turn taking in a conversation, to catching something in mid-air, are all examples of how important and ubiquitous temporal preparation is in our everyday life (e.g., Correa, 2010; Coull & Nobre, 2008; Nobre, Correa, & Coull, 2007). In laboratory settings, temporal preparation has been traditionally investigated, in its implicit form, through the “variable foreperiod paradigm” (see Coull, 2009; Niemi & Näätänen, 1981, for a review). In such a paradigm, the foreperiod is a time interval of variable duration that separates a warning stimulus and a target stimulus requiring a response. What is usually observed with this paradigm is that response times (RTs) reflect the temporal probability of stimulus onset: RTs decrease with increasing probability. This implies that participants learn to use the information implicitly afforded by the passage of time and that related to the temporal probability of the onset of the target stimulus (i.e., hazard rate; Janssen & Shadlen, 2005). In other words, it seems that they are able to use predictive internal models of event timing in order to optimize behaviour. Despite previous studies have started to investigate which brain areas encode temporal probabilities (i.e., predictive models) to anticipate event onset (e.g., Bueti, Bahrami, Walsh, & Rees, 2010; Cui, Stetson, Montague, & Eagleman, 2009; also see Vallesi et al., 2007), to our knowledge, there is no evidence on how the brain does form and update such predictive models. Based on such premises, the overarching goal of the present PhD project was to pinpoint the neural mechanisms by which predictive models of event timing are dynamically updated. Moreover, given that in real life updating usually occurs in the presence of surprising events (i.e. low probable events under a predictive model), it is challenging to disentangle between updating and surprise (O’Reilly et al, 2013). Therefore, our second and interrelated research goal was to understand whether, and to which extent, it is possible to dissociate between the neural mechanisms specifically involved in updating and those dealing with surprising events that do not require an update of internal models. To accomplish our research goals, we capitalized on both state-of-the-art methodologies [i.e., functional magnetic resonance imaging (fMRI) and electrophysiology (EEG)] and computational modelling. Specifically, we considered the brain like a Bayesian observer. Indeed, Bayesian frameworks are gaining increasing popularity to explain cognitive brain functions (Friston, 2012). In a nutshell, the construction of computational Bayesian models allows us to quantitatively describe temporal expectations in terms of probability distributions and to capture updating using Bayes’ rule. In order to accomplish our goals, the present PhD project is composed of three studies. In the first two studies we implemented a version of the foreperiod paradigm in which participants could predict target onsets by estimating their underlying temporal probability distributions. During the task, these distributions changed, hence requiring participants to update their temporal expectations. Furthermore, a simple manipulation of the colors in which the target were presented (cf., O’Reilly et al., 2013) allowed us to independently vary updating and surprise across trials. Then, we constructed a normative Bayesian learner (a computational model adapted from O’Reilly et al., 2013) in order to obtain an estimate of a participant’s temporal expectations on a trial-by-trial basis. In Study 1, trial-by-trial fMRI data acquired during our foreperiod paradigm were correlated with two information theoretical parameters calculated with reference to our Bayesian model: the Kullbach-Leibler divergence (DKL) and the Shannon’s information (IS). These two measures have been previously used to formally describe belief updating and surprise associated with events under a predictive model, respectively (e.g., Baldi & Itti, 2010; Kolossa, Kopp, & Fingscheidt, 2015; O'Reilly et al., 2013; Strange et al., 2005). Our results showed that the fronto-parietal network and the cingulo-opercular network were differentially involved in the updating of temporal expectations and in dealing with surprising events, respectively. Having successfully validated the use of Bayesian models in our first fMRI study and dissociated between updating and surprise, the next step was to investigate the temporal dynamics of these two processes. Do updating and surprise act on similar or distinct processing stage(s)? What is the time course associated with the two? To address these questions, in Study 2 participants performed our adapted foreperiod task (same task as in Study 1) while their EEG activity was recorded. In this study, we relied on the literature on the P3 (a specific ERP component related to information processing) and the Bayesian brain (e.g., Kopp, 2008; Kopp et al., 2016; Mars et al., 2008; Seer, Lange, Boos, Dengler, & Kopp, 2016). Importantly, however, we also took advantage from the combination of a mass-univariate approach with novel deconvolution methods to explore the entire spatio-temporal pattern of EEG data. This enabled us to extend our analyses beyond the P3 component. Results from study 2 confirmed that surprise and updating can be differentiated also at the electrophysiological level and that updating elicited a more complex pattern than surprise. As regards the P3 in relation to the literature on the Bayesian brain (Kolossa, Fingscheidt, Wessel, & Kopp, 2013; Kolossa et al., 2015; Mars et al., 2008), our findings corroborated the idea that such a component is selectively modulated by surprise and updating. While in Studies 1 and 2, participants were explicitly encouraged to form and update temporal expectations using the target color, in Study 3 we wanted to make a step further by asking whether the use of a more implicit task structure might influence the construction of the predictive internal model. To that aim, during the foreperiod task designed for the third study, participants were not explicitly informed about the presence of the underlying temporal probability distributions from which target onsets were drawn. In this way, we aimed to investigate behavioural and EEG differences in the way participants learnt to form and updated temporal expectations when changes in the underlying distributions were not explicitly signalled. Critically, we again found that surprise and updating could be differentiated. Moreover, coupled with the results from study 2, we isolated two EEG signatures of the inferential process underlying updating of prior temporal expectations, which responded to both explicit and implicit contextual changes. Overall, we believe that the results of the present PhD project will further our understanding of the cognitive processes and neural mechanisms that allow us to optimize our temporal preparation abilities

Investigating the relationship between cognitive control and speech-in-noise recognition in tinnitus from perceptual, neuroanatomical, and electrophysiological aspects

Purpose: Individuals with tinnitus commonly report difficulties understanding speech in adverse listening environments. Although such speech-in-noise (SiN) difficulties are believed to relate to deficits in cognitive control, there is as yet no evidence to underpin this assumption. The aim of this dissertation was to investigate the relationship between cognitive control and SiN recognition in individuals with tinnitus and normal hearing sensitivity. Method: Three studies linking behavioral to brain imaging measures were conducted. In the first study, the effect of tinnitus pitch on the recognition of consonants in noise at various frequency ranges was examined to better understand if the tinnitus percept impacts SiN recognition. Using voxel-based morphometry, the second study investigated the relationship between SiN performance and gray matter volume in auditory and cognitive processing regions in individuals with tinnitus. Lastly, using electroencephalogram to record brain activity during Go/Nogo tasks, the third study examined whether event-related potentials related to cognitive control are associated with SiN performance in individuals with tinnitus. Results and Discussion: Overall, the findings of the three studies suggest that 1) perceiving tinnitus at a given frequency does not interfere with speech recognition at the same frequency, suggesting that the effect of tinnitus on SiN recognition may involve higher-level cognitive processes rather than being solely mediated by perceptual abilities; 2) individuals with tinnitus and normal hearing showed comparable SiN recognition and neuropsychological performance relative to hearing-matched controls, however, they still demonstrated neuroanatomical changes and neural alterations pertaining to cognitive control; and 3) individuals with tinnitus may use different cognitive control strategies relative to hearing-matched controls to maintain their performance of daily tasks. Conclusions: The findings confirmed that incorporating multimodal approaches to examine the relationship between cognitive control and SiN recognition can be beneficial to detect neuroanatomical or neural alterations before any overt changes in behavioral performance. Further, the results will serve as the baseline for future endeavors to explicitly investigate the effect of tinnitus and hearing loss on cognitive control abilities and SiN recognition, which can be invaluable in advancing tinnitus consultation and intervention

A Behavioural and Cognitive Neuroscience Investigation of Deceptive Communication

There is a rich literature on how people tell lies and detect them in others, but the underlying mechanisms are still poorly understood. The first aim of this thesis was to elucidate key cognitive and neural processes underlying cued (i.e., instructed) and uncued lies. The second aim, based on recent research suggesting a link between dishonesty and creativity, was to determine whether creative cognition contributes to deceptive communication. In a first behavioural study, performance on generating and detecting lies was measured in a socially interactive setting involving cued and uncued lies. Results of a multiple regression analysis showed that creativity predicted lying generation ability: more creative individuals were better liars than less creative people. In contrast, the ability to detect lies showed no association with creativity measures, suggesting that generating and detecting lies are distinct abilities. A second event-related potential (ERP) study investigated the neural mechanisms underlying the generation of uncued lies using a novel bluffing paradigm where participants lied at will. Results showed no stimulus-locked differences between uncued lies and truths, suggesting that decision processes leading to both required comparable cognitive resources. Once the uncued decision has been made, it requires strategic monitoring to keep track of the responses in order to maximize the gains regardless of whether the outcome is a lie or the truth as indexed by no response-locked differences between uncued lies and truths. Finally, parallel functional magnetic resonance imaging (fMRI) and ERP studies were conducted to determine the role of creativity in countermeasure use in a concealed information paradigm requiring cued lying. Results showed that countermeasures degraded the neural signatures of deception and more so for more creative individuals. This work advances understanding of the cognitive and neural mechanisms underlying deception as well as their dependence on individual differences in creative cognition