Auditory Oddball Task Research Articles

Unveiling Functional Biomarkers in Schizophrenia: Insights from Region of Interest Analysis Using Machine Learning.

Schizophrenia is a complex and disabling mental disorder that represents one of the most important challenges for neuroimaging research. There were many attempts to understand these basic mechanisms behind the disorder, yet we know very little. By employing machine learning techniques with age-matched samples from the auditory oddball task using multi-site functional magnetic resonance imaging (fMRI) data, this study aims to address these challenges. The study employed a three-stage model to gain a better understanding of the neurobiology underlying schizophrenia and techniques that could be applied for diagnosis. At first, we constructed four-level hierarchical sets from each fMRI volume of 34 schizophrenia patients (SZ) and healthy controls (HC) individually in terms of hemisphere, gyrus, lobes, and Brodmann areas. Second, we employed statistical methods, namely, t-tests and Pearson's correlation, to assess the group differences in cortical activation. Finally, we assessed the predictive power of the brain regions for machine learning algorithms using K-nearest Neighbor (KNN), Naive Bayes, Decision Tree (DT), Random Forest (RF), Support Vector Machines (SVMs), and Extreme Learning Machine (ELM). Our investigation depicts promising results, obtaining an accuracy of up to 84% when applying Pearson's correlation-selected features at lobes and Brodmann region level (81% for Gyrus), as well as Hemispheres involving different stages. Thus, the results of our study were consistent with previous studies that have revealed some functional abnormalities in several brain regions. We also discovered the involvement of other brain regions which were never sufficiently studied in previous literature, such as the posterior lobe (posterior cerebellum), Pyramis, and Brodmann Area 34. We present a unique and comprehensive approach to investigating the neurological basis of schizophrenia in this study. By bridging the gap between neuroimaging and computable analysis, we aim to improve diagnostic accuracy in patients with schizophrenia and identify potential prognostic markers for disease progression.

Abnormal inter-hemispheric effective connectivity from left to right auditory regions during Mismatch Negativity (MMN) tasks in psychosis

Anomalous Mismatch Negativity (MMN) in psychosis could be a consequence of disturbed neural oscillatory activity at sensory/perceptual stages of stimulus processing. This study investigated effective connectivity within and between the auditory regions during auditory odd-ball deviance tasks. The analyses were performed on two magnetoencephalography (MEG) datasets: one on duration MMN in a cohort with various diagnoses within the psychosis spectrum and neurotypical controls, and one on duration and pitch MMN in first-episode psychosis patients and matched neurotypical controls. We applied spectral Granger causality to MEG source-reconstructed signals to compute effective connectivity within and between the left and right auditory regions. Both experiments showed that duration-deviance detection was associated with early increases of effective connectivity in the beta band followed by increases in the alpha and theta bands, with the connectivity strength linked to the laterality of the MMN amplitude. Compared to controls, people with psychosis had overall smaller effective connectivity, particularly from left to right auditory regions, in the pathway where bilateral information converges toward lateralized processing, often rightward. Blunted MMN in psychosis might reflect a deficit in inter-hemispheric communication between auditory regions, highlighting a “dysconnection” already at preattentive stages of stimulus processing as a model system of widespread pathophysiology.

Skin Carotenoids Are Related to Cognitive Abilities among Toddlers

BackgroundCarotenoids are antioxidant pigments that deposit in human tissues (e.g., skin, macula, and brain) upon dietary consumption. The health implications of skin carotenoids, which reflect overall dietary carotenoid consumption, have not been adequately studied in younger populations. ObjectivesThis work aimed to examine links between skin carotenoids and cognitive, language, and motor skills among toddlers. A secondary aim explored relationships between skin carotenoids and neurophysiologic outcomes of sensory memory [i.e., mismatch negativity (MMN)] and the functional integrity of the visual pathway [i.e., visual evoked potentials (VEPs)]. MethodsToddlers aged 12–18 mo (n = 45) were included in a cross-sectional study. Skin carotenoids were measured with reflection spectroscopy via the Veggie Meter®. Cognitive, language, and motor skills were measured using the Bayley Scale of Infant and Toddler Development IV Screening Test (BSID-IV). MMN and VEPs were collected with an auditory oddball task and a pattern reversal task, respectively, using electroencephalography. Analyses adjusted for age, household income, highest level of parental education, and total carotenoid intake (mg/1000 kcal). ResultsRegression modeling revealed that skin carotenoids significantly related to cognition (β = 0.24; P = 0.04) and not to any other BSID-IV subsets. Neither MMN nor VEP outcomes significantly related to skin carotenoids. ConclusionsGreater skin carotenoids were selectively related to cognition, indicating that carotenoids may play a role in cognition in toddlers. Additional research is needed to understand links between skin carotenoids and specific domains of cognitive function and brain health in early life.

Low-Cost Classroom and Laboratory Exercises for Investigating Both Wave and Event-Related Electroencephalogram Potentials.

Electroencephalography (EEG) has given rise to a myriad of new discoveries over the last 90 years. EEG is a noninvasive technique that has revealed insights into the spatial and temporal processing of brain activity over many neuroscience disciplines, including sensory, motor, sleep, and memory formation. Most undergraduate students, however, lack laboratory access to EEG recording equipment or the skills to perform an experiment independently. Here, we provide easy-to-follow instructions to measure both wave and event-related EEG potentials using a portable, low-cost amplifier (Backyard Brains, Ann Arbor, MI) that connects to smartphones and PCs, independent of their operating system. Using open-source software (SpikeRecorder) and analysis tools (Python, Google Colaboratory), we demonstrate tractable and robust laboratory exercises for students to gain insights into the scientific method and discover multidisciplinary neuroscience research. We developed 2 laboratory exercises and ran them on participants within our research lab (N = 17, development group). In our first protocol, we analyzed power differences in the alpha band (8-13 Hz) when participants alternated between eyes open and eyes closed states (n = 137 transitions). We could robustly see an increase of over 50% in 59 (43%) of our sessions, suggesting this would make a reliable introductory experiment. Next, we describe an exercise that uses a SpikerBox to evoke an event-related potential (ERP) during an auditory oddball task. This experiment measures the average EEG potential elicited during an auditory presentation of either a highly predictable ("standard") or low-probability ("oddball") tone. Across all sessions in the development group (n=81), we found that 64% (n=52) showed a significant peak in the standard response window for P300 with an average peak latency of 442ms. Finally, we tested the auditory oddball task in a university classroom setting. In 66% of the sessions (n=30), a clear P300 was shown, and these signals were significantly above chance when compared to a Monte Carlo simulation. These laboratory exercises cover the two methods of analysis (frequency power and ERP), which are routinely used in neurology diagnostics, brain-machine interfaces, and neurofeedback therapy. Arming students with these methods and analysis techniques will enable them to investigate this laboratory exercise's variants or test their own hypotheses.

Mismatch negativity between discriminating and undiscriminating participants on the front-back sound localization

Sound localization in the front-back dimension is reported to be challenging, with individual differences. We investigated whether auditory discrimination processing in the brain differs based on front-back sound localization ability. This study conducted an auditory oddball task using speakers in front of and behind the participants. We used event-related brain potentials to examine the deviance detection process between groups that could and could not discriminate front-back sound localization. The results indicated that mismatch negativity (MMN) occurred during the deviance detection process, and P2 amplitude differed between standard and deviant locations in both groups. However, the latency of MMN was shorter in the group that could discriminate front-back sounds than in the group that could not. Additionally, N1 amplitude increased for deviant locations compared to standard ones only in the discriminating group. In conclusion, the sensory memories matching process based on traces of previously presented stimuli (MMN, P2) occurred regardless of discrimination ability. However, the response to changes in the physical properties of sounds (MMN latency, N1 amplitude) differed depending on the ability to discriminate front-back sounds. Our findings suggest that the brain may have different processing strategies for the two directions even without subjective recognition of the front-back direction of incoming sounds.

Inter-individual variability in neural response to low doses of LSD

The repeated use of small doses of psychedelics (also referred to as “microdosing”) to facilitate benefits in mental health, cognition, and mood is a trending practice. Placebo-controlled studies however have largely failed to demonstrate strong benefits, possibly because of large inter-individual response variability. The current study tested the hypothesis that effects of low doses of LSD on arousal, attention and memory depend on an individual’s cognitive state at baseline. Healthy participants (N = 53) were randomly assigned to receive repeated doses of LSD (15 mcg) or placebo on 4 occasions divided over 2 weeks. Each treatment condition also consisted of a baseline and a 1-week follow-up visit. Neurophysiological measures of arousal (resting state EEG), pre-attentive processing (auditory oddball task), and perceptual learning and memory (visual long-term potentiation (LTP) paradigm) were assessed at baseline, dosing session 1 and 4, and follow-up. LSD produced stimulatory effects as reflected by a reduction in resting state EEG delta, theta, and alpha power, and enhanced pre-attentive processing during the acute dosing sessions. LSD also blunted the induction of LTP on dosing session 4. Stimulatory effects of LSD were strongest in individuals with low arousal and attention at baseline, while inhibitory effects were strongest in high memory performers at baseline. Decrements in delta EEG power and enhanced pre-attentive processing in the LSD treatment condition were still present during the 1-week follow-up. The current study demonstrates across three cognitive domains, that acute responses to low doses of LSD depend on the baseline state and provides some support for LSD induced neuroadaptations that sustain beyond treatment.

Investigating cognitive-motor effects during slacklining using mobile EEG.

Balancing is a very important skill, supporting many daily life activities. Cognitive-motor interference (CMI) dual-tasking paradigms have been established to identify the cognitive load of complex natural motor tasks, such as running and cycling. Here we used wireless, smartphone-recorded electroencephalography (EEG) and motion sensors while participants were either standing on firm ground or on a slackline, either performing an auditory oddball task (dual-task condition) or no task simultaneously (single-task condition). We expected a reduced amplitude and increased latency of the P3 event-related potential (ERP) component to target sounds for the complex balancing compared to the standing on ground condition, and a further decrease in the dual-task compared to the single-task balancing condition. Further, we expected greater postural sway during slacklining while performing the concurrent auditory attention task. Twenty young, experienced slackliners performed an auditory oddball task, silently counting rare target tones presented in a series of frequently occurring standard tones. Results revealed similar P3 topographies and morphologies during both movement conditions. Contrary to our predictions we observed neither significantly reduced P3 amplitudes, nor significantly increased latencies during slacklining. Unexpectedly, we found greater postural sway during slacklining with no additional task compared to dual-tasking. Further, we found a significant correlation between the participant's skill level and P3 latency, but not between skill level and P3 amplitude or postural sway. This pattern of results indicates an interference effect for less skilled individuals, whereas individuals with a high skill level may have shown a facilitation effect. Our study adds to the growing field of research demonstrating that ERPs obtained in uncontrolled, daily-life situations can provide meaningful results. We argue that the individual CMI effects on the P3 ERP reflects how demanding the balancing task is for untrained individuals, which draws on limited resources that are otherwise available for auditory attention processing. In future work, the analysis of concurrently recorded motion-sensor signals will help to identify the cognitive demands of motor tasks executed in natural, uncontrolled environments.

Distributed representations of prediction error signals across the cortical hierarchy are synergistic

A relevant question concerning inter-areal communication in the cortex is whether these interactions are synergistic. Synergy refers to the complementary effect of multiple brain signals conveying more information than the sum of each isolated signal. Redundancy, on the other hand, refers to the common information shared between brain signals. Here, we dissociated cortical interactions encoding complementary information (synergy) from those sharing common information (redundancy) during prediction error (PE) processing. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded synergistic and redundant information about PE processing. The information conveyed by ERPs and BB signals was synergistic even at lower stages of the hierarchy in the auditory cortex and between auditory and frontal regions. Using a brain-constrained neural network, we simulated the synergy and redundancy observed in the experimental results and demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback, and feedforward connections. These results indicate that distributed representations of PE signals across the cortical hierarchy can be highly synergistic.

Correlated P300b and phasic pupil-dilation responses to motivationally significant stimuli.

Motivationally significant events like oddball stimuli elicit both a characteristic event-related potential (ERPs) known as P300 and a set of autonomic responses including a phasic pupil dilation. Although co-occurring, P300 and pupil-dilation responses to oddball events have been repeatedly found to be uncorrelated, suggesting separate origins. We re-examined their relationship in the context of a three-stimulus version of the auditory oddball task, independently manipulating the frequency (rare vs. repeated) and motivational significance (relevance for the participant's task) of the stimuli. We used independent component analysis to derive a P300b component from EEG traces and linear modeling to separate a stimulus-related pupil-dilation response from a potentially confounding action-related response. These steps revealed that, once the complexity of ERP and pupil-dilation responses to oddball targets is accounted for, the amplitude of phasic pupil dilations and P300b are tightly and positively correlated (across participants: r = .69 p = .002), supporting their coordinated generation.

Decoding of auditory surprise in adult magnetoencephalography data using Bayesian models

BackgroundThe Bayesian brain framework has been proposed to explain how the brain processes and interprets sensory information. Magnetoencephalography (MEG) and electroencephalography (EEG) are two neuroimaging techniques commonly used with decoding models to study neural responses to auditory, visual and somatosensory stimuli. Our study aims to investigate neural responses to auditory stimuli using MEG data and to determine which temporal components in MEG data are sufficient for decoding surprise based on Bayesian models. MethodMEG data acquired from 18 subjects during an auditory binary oddball task was used. The data were pre-processed, and features were selected from different time windows. Five Bayesian learning models were applied to the experimental task stimuli, and each single trial's surprise value was calculated. The relationship between the extracted features in MEG data and the surprise regressors was investigated using linear regression and 5-fold cross-validation. ResultsThe results showed that the middle and late components of the MEG evoked potentials were significantly more informative than the early components. The results indicated that the Dirichlet-Categorical model outperformed the other model's decoding performance as demonstrated by higher R-squared values and lower MSE and BIC values. ConclusionsThe findings of this study provide evidence for the existence of a neural network that generates surprise in the human brain and highlight the importance of the middle and late components of the MEG evoked potentials for decoding the surprise value of auditory stimuli.

Locus coeruleus features are linked to vagus nerve stimulation response in drug-resistant epilepsy.

The locus coeruleus-norepinephrine system is thought to be involved in the clinical effects of vagus nerve stimulation. This system is known to prevent seizure development and induce long-term plastic changes, particularly with the release of norepinephrine in the hippocampus. However, the requisites to become responder to the therapy and the mechanisms of action are still under investigation. Using MRI, we assessed the structural and functional characteristics of the locus coeruleus and microstructural properties of locus coeruleus-hippocampus white matter tracts in patients with drug-resistant epilepsy responding or not to the therapy. Twenty-three drug-resistant epileptic patients with cervical vagus nerve stimulation were recruited for this pilot study, including 13 responders or partial responders and 10 non-responders. A dedicated structural MRI acquisition allowed in vivo localization of the locus coeruleus and computation of its contrast (an accepted marker of LC integrity). Locus coeruleus activity was estimated using functional MRI during an auditory oddball task. Finally, multi-shell diffusion MRI was used to estimate the structural properties of locus coeruleus-hippocampus tracts. These characteristics were compared between responders/partial responders and non-responders and their association with therapy duration was also explored. In patients with a better response to the therapy, trends toward a lower activity and a higher contrast were found in the left medial and right caudal portions of the locus coeruleus, respectively. An increased locus coeruleus contrast, bilaterally over its medial portions, correlated with duration of the treatment. Finally, a higher integrity of locus coeruleus-hippocampus connections was found in patients with a better response to the treatment. These new insights into the neurobiology of vagus nerve stimulation may provide novel markers of the response to the treatment and may reflect neuroplasticity effects occurring in the brain following the implantation.

Influence of Perceptual Load on Attentional Orienting in Post-Stroke Fatigue: A Study of Auditory Evoked Potentials

Objective Increasing perceptual load alters behavioral outcomes in post-stroke fatigue (PSF). While the effect of perceptual load on top-down attentional processing is known, here we investigate if increasing perceptual load modulates bottom-up attentional processing in a fatigue dependent manner. Methods In this cross-sectional observational study, in 29 first-time stroke survivors with no clinical depression, an auditory oddball task consisting of target, standard, and novel tones was performed in conditions of low and high perceptual load. Electroencephalography was used to measure auditory evoked potentials. Perceived effort was rated using the visual analog scale at regular intervals during the experiment. Fatigue was measured using the fatigue severity scale. The effect of fatigue and perceptual load on behavior (response time, accuracy, and effort rating) and auditory evoked potentials (amplitude and latency) was examined using mixed model ananlysis of variances (ANOVA). Results Response time was prolonged with greater perceptual load and fatigue. There was no effect of load or fatigue on accuracy. Greater effort was reported with higher perceptual load both in high and low fatigue. p300a amplitude of auditory evoked potentials (AEP) for novel stimuli was attenuated in high fatigue with increasing load when compared to low fatigue. Latency of p300a was longer in low fatigue with increasing load when compared to high fatigue. There were no effects on p300b components, with smaller N100 in high load conditions. Interpretation High fatigue specific modulation of p300a component of AEP with increasing load is indicative of distractor driven alteration in orienting response, suggestive of compromise in bottom-up selective attention in PSF.

Relation between task-related activity modulation and cortical inhibitory function in schizophrenia and healthy controls: a TMS–EEG study

Schizophrenia has been associated with a reduced task-related modulation of cortical activity assessed through electroencephalography (EEG). However, to the best of our knowledge, no study so far has assessed the underpinnings of this decreased EEG modulation in schizophrenia. A possible substrate of these findings could be a decreased inhibitory function, a replicated finding in the field. In this pilot study, our aim was to explore the association between EEG modulation during a cognitive task and the inhibitory system function in vivo in a sample including healthy controls and patients with schizophrenia. We hypothesized that the replicated decreased task-related activity modulation during a cognitive task in schizophrenia would be related to a hypofunction of the inhibitory system. For this purpose, 27 healthy controls and 22 patients with schizophrenia (including 13 first episodes) performed a 3-condition auditory oddball task from which the spectral entropy modulation was calculated. In addition, cortical reactivity—as an index of the inhibitory function—was assessed by the administration of 75 monophasic transcranial magnetic stimulation single pulses over the left dorsolateral prefrontal cortex. Our results replicated the task-related cortical activity modulation deficit in schizophrenia patients. Moreover, schizophrenia patients showed higher cortical reactivity following transcranial magnetic stimulation single pulses over the left dorsolateral prefrontal cortex compared to healthy controls. Cortical reactivity was inversely associated with EEG modulation, supporting the idea that a hypofunction of the inhibitory system could hamper the task-related modulation of EEG activity.

Connectivity changes in two-channel prefrontal ERP associated with early cognitive decline in the elderly population: beta band responses to the auditory oddball stimuli.

This study utilized recent advancements in electroencephalography (EEG) technology that enable the measurement of prefrontal event-related potentials (ERPs) to facilitate the early detection of mild cognitive impairment (MCI). We investigated two-channel prefrontal ERP signals obtained from a large cohort of elderly participants and compare among cognitively normal (CN), subjective cognitive decline (SCD), amnestic MCI (aMCI), and nonamnestic MCI (naMCI) groups. Signal processing and ERP component analyses, specifically adapted for two-channel prefrontal ERP signals evoked by the auditory oddball task, were performed on a total of 1,754 elderly participants. Connectivity analyses were conducted to assess brain synchronization, especially in the beta band involving the phase locking value (PLV) and coherence (COH). Time-frequency, time-trial, grand average, and further statistical analyses of the standard and target epochs were also conducted to explore differences among the cognition groups. The MCI group's response to target stimuli was characterized by greater response time variability (p < 0.001) and greater variability in the P300 latency (p < 0.05), leading to less consistent responses than those of the healthy control (HC) group (CN+SCD subgroups). In the connectivity analyses of PLV and COH waveforms, significant differences were observed, indicating a loss of synchronization in the beta band in response to standard stimuli in the MCI group. In addition, the absence of event-related desynchronization (ERD) indicated that information processing related to readiness and task performance in the beta band was not efficient in the MCI group. Furthermore, the observed decline in the P200 amplitude as the standard trials progressed suggests the impaired attention and inhibitory processes in the MCI group compared to the HC group. The aMCI subgroup showed high variability in COH values, while the naMCI subgroup showed impairments in their overall behavioral performance. These findings highlight the variability and connectivity measures can be used as markers of early cognitive decline; such measures can be assessed with simple and fast two-channel prefrontal ERP signals evoked by both standard and target stimuli. Our study provides deeper insight of cognitive impairment and the potential use of the prefrontal ERP connectivity measures to assess early cognitive decline.

Mobile EEG for the study of cognitive-motor interference during swimming?

Research on brain function in natural environments has become a new interest in cognitive science. In this study, we aim to advance mobile electroencephalography (EEG) participant and device mobility. We investigated the feasibility of measuring human brain activity using mobile EEG during a full-body motion task as swimming, by the example of cognitive-motor interference (CMI). Eleven participants were given an auditory oddball task while sitting and swimming, with mobile EEG recording ongoing brain activity. Measures of interest were event-related potentials (ERPs) elicited by experimental stimuli. While the auditory N100 was measured to verify signal quality, the P300 to task-relevant stimuli served as a marker of CMI effects. Analyzes were first performed within subjects, while binomial tests assessed the proportion of significant effects. Event-related changes in the time-frequency domain around turns during swimming were analyzed in an exploratory fashion. The successful recording of the N100 in all conditions shows that the setup was functional throughout the experiment. Regarding CMI, we did not find reliable changes in P300 amplitude in different motor settings in all subjects. However, we found plausible modulations in the alpha/mu and beta bands before and after turns. This study shows that it is generally feasible to measure mobile EEG in the time and time-frequency domain in an aquatic environment while subjects are freely moving. We see promising potential in the use of mobile EEG in extreme settings, advancing toward the application of mobile EEG in more real-life situations.

Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response.

Despite attempts to unify the different theoretical accounts of the mismatch negativity (MMN), there is still an ongoing debate on the neurophysiological mechanisms underlying this complex brain response. On one hand, neuronal adaptation to recurrent stimuli is able to explain many of the observed properties of the MMN, such as its sensitivity to controlled experimental parameters. On the other hand, several modeling studies reported evidence in favor of Bayesian learning models for explaining the trial-to-trial dynamics of the human MMN. However, direct comparisons of these two main hypotheses are scarce, and previous modeling studies suffered from methodological limitations. Based on reports indicating spatial and temporal dissociation of physiological mechanisms within the timecourse of mismatch responses in animals, we hypothesized that different computational models would best fit different temporal phases of the human MMN. Using electroencephalographic data from two independent studies of a simple auditory oddball task (n = 82), we compared adaptation and Bayesian learning models' ability to explain the sequential dynamics of auditory deviance detection in a time-resolved fashion. We first ran simulations to evaluate the capacity of our design to dissociate the tested models and found that they were sufficiently distinguishable above a certain level of signal-to-noise ratio (SNR). In subjects with a sufficient SNR, our time-resolved approach revealed a temporal dissociation between the two model families, with high evidence for adaptation during the early MMN window (from 90 to 150-190 ms post-stimulus depending on the dataset) and for Bayesian learning later in time (170-180 ms or 200-220ms). In addition, Bayesian model averaging of fixed-parameter models within the adaptation family revealed a gradient of adaptation rates, resembling the anatomical gradient in the auditory cortical hierarchy reported in animal studies.

The mismatch negativity as an index of cognitive impairment in adults with Down syndrome

AbstractBackgroundPeople with Down syndrome (DS) have a high risk of developing Alzheimer’s disease (AD; Zis and Strydom 2018). The mismatch negativity (MMN) is an event‐related potential that can be used to index cognitive decline (Näätänen et al., 2011). Given its relative independence from attentional processes (Naatanen and Näätänen 1992), the MMN may be particularly useful when studying populations with intellectual disability, who may find sustained attention tasks challenging. We therefore investigated the MMN in people with DS and its association with cognitive abilities.MethodsMMN responses to a passive auditory oddball task were recorded from 27 adults with DS (aged 18 to 59) without any hearing impairments. Associations between MMN and age, as well as memory, language, IQ, and attention scores were examined.ResultsThe MMN was present only in young adults up to the age of 40 and the latency was prolonged. Attenuation of MMN amplitude was associated with poorer memory scores. Finally, longer MMN latencies were associated with increased inter‐individual performance variability and worse performance on memory, verbal, and general IQ tasks.ConclusionOverall, our results indicate that MMN amplitude may be associated with AD‐related memory loss, while increased MMN latency seems to reflect verbal abilities in people with DS. Furthermore, the association between MMN latency and inter‐individual performance variability may suggest the presence of AD‐driven white matter degenerations affecting the brian’s frontal lobe. Therefore, the MMN may represent a valuable tool for studying cognitive abilities and AD pathology in DS.

The relationship between Event‐Related Potentials and MRI cortical atrophy in a memory disorders clinic

AbstractBackgroundThere is a need for accessible and affordable ways to assess biomarkers of Alzheimer’s disease (AD). Event‐related potentials (ERPs) are associated with disease severity of AD (Fruehwirt et al., 2019) and are a candidate biomarker for AD (Olichney et al., 2022). There is, however, little understanding of how ERP components relate to neurodegeneration of specific brain structures in AD.MethodWe investigated the correlation between electrophysiology, as measured by ERPs and brain structure using quantitative structural MRI measurements using FreeSurfer. A dataset containing older veteran memory disorders patients (N = 25) from VA Boston Healthcare System was analyzed. Participants completed an MRI and an auditory oddball task ERP paradigm.ResultAn exploratory analysis was performed using a Pearson correlation coefficient to evaluate the relationship between ERPs and the thickness and volume of different cortical areas. There was a negative relationship between P300 target amplitude and inferior temporal volume (p &lt; .05), as well as P300 target latency and thickness of the superior temporal (p &lt; .05) and transverse temporal regions (p &lt; .01). P200 standard amplitude had a positive correlation with thickness in the middle temporal (p &lt; .01), and superior temporal regions (p ≤ .05), and P200 target latency had a negative correlation with thickness of the superior temporal region (p &lt; .05). N200 target amplitude had a negative correlation with the superior parietal volume (right hemisphere = p ≤ .05, left hemisphere = p ≤ .01), left inferior temporal volume (p ≤ .05), and the middle temporal volume (left = p ≤ .05, right = p ≤ .01). N200 target latency was negatively correlated with right superior parietal volume (p ≤ .05).ConclusionA correlation was found between ERP measures P200, N200 and P300 with cortical thickness and volume of areas that are commonly impacted by AD pathology, further substantiating use of ERPs as possible AD biomarkers. We conclude that ERPs provide insights as to structural changes of brain structures affected by AD pathology. ERPs could help inform areas of brain atrophy and related patterns of cognitive impairment.

Event Related Brain Responses Reveal the Impact of Spatial Augmented Reality Predictive Cues on Mental Effort.

This article presents the results from a Spatial Augmented Reality (SAR) study which evaluated the cognitive cost of several predictive cues. Participants performed a validated procedural button pressing task, where the predictive cue annotations guided them to the upcoming task. While existing research has evaluated predictive cues based on their performance and self-rated mental effort, actual cognitive cost has yet to be investigated. To measure the user's brain activity, this study utilized electroencephalogram (EEG) recordings. Cognitive load was evaluated by measuring brain responses for a secondary auditory oddball task, with reduced brain responses to oddball tones expected when cognitive load in the primary task is highest. A simple monitor n-back task and procedural task comparing monitor versus SAR were conducted, followed by a version of the procedural task comparing the SAR predictive cues. Results from the brain responses were able to distinguish between performance enhancing cues with a high and low cognitive load. Electrical brain responses also revealed that having an arc or arrow guide towards the upcoming task required the least amount of mental effort.

A study on neural changes induced by sauna bathing: Neural basis of the "totonou" state.

Saunas are becoming increasingly popular worldwide, being an activity that promotes relaxation and health. Intense feelings of happiness have been reported shortly after enjoying a hot sauna and cold water, what is known in Japan as the "totonou" state. However, no research has investigated what occurs in the brain during the "totonou" state. In the present study, participants underwent a sauna phase, consisting of three sets of alternating hot sauna, cold water, and rest. We elucidated changes in brain activity and mood in the "totonou" state by measuring and comparing brain activity and emotional scales before and after the sauna phase and during the rest phase in each set. We found significant increases in theta and alpha power during rest and after the sauna phase compared to before the sauna phase. Moreover, in an auditory oddball task, the p300 amplitude decreased significantly and MMN amplitude increased significantly after the sauna phase. The increase in MMN indicates higher activation of the pre-attentional auditory process, leading to a decrease in attention-related brain activity P300. Hence, the brain reaches in a more efficient state. Further, the response time in behavioral tasks decreased significantly. In addition, the participants' subjective responses to the questionnaire showed significant changes in physical relaxation and other indicators after being in the sauna. Finally, we developed an artificial intelligence classifier, obtaining an average accuracy of brain state classification of 88.34%. The results have potential for future application.