Penalized canonical correlation analysis reveals a relationship between temperament traits and brain oscillations during mind wandering.

INTRODUCTION: There has been a growing interest in studying brain activity under naturalistic conditions. However, the relationship between individual differences in ongoing brain activity and psychological characteristics is not well understood. We investigated this connection, focusing on the association between oscillatory activity in the brain and individually characteristic dispositional traits. Given the variability of unconstrained resting states among individuals, we devised a paradigm that could harmonize the state of mind across all participants. METHODS: We constructed task contrasts that included focused attention (FA), self-centered future planning, and rumination on anxious thoughts triggered by visual imagery. Magnetoencephalography was recorded from 28 participants under these 3 conditions for a duration of 16 min. The oscillatory power in the alpha and beta bands was converted into spatial contrast maps, representing the difference in brain oscillation power between the two conditions. We performed permutation cluster tests on these spatial contrast maps. Additionally, we applied penalized canonical correlation analysis (CCA) to study the relationship between brain oscillation patterns and behavioral traits. RESULTS: The data revealed that the FA condition, as compared to the other conditions, was associated with higher alpha and beta power in the temporal areas of the left hemisphere and lower alpha and beta power in the parietal areas of the right hemisphere. Interestingly, the penalized CCA indicated that behavioral inhibition was positively correlated, whereas anxiety was negatively correlated, with a pattern of high oscillatory power in the bilateral precuneus and low power in the bilateral temporal regions. This unique association was found in the anxious-thoughts condition when contrasted with the focused-attention condition. CONCLUSION: Our findings suggest individual temperament traits significantly affect brain engagement in naturalistic conditions. This research underscores the importance of considering individual traits in neuroscience and offers an effective method for analyzing brain activity and psychological differences.

Divergent auditory activation in relation to inhibition task performance in children and adults.

Adults and children show remarkable differences in cortical auditory activation which, in children, have shown relevance for cognitive performance, specifically inhibitory control. However, it has not been tested whether these differences translate to functional differences in response inhibition between adults and children. We recorded auditory responses of adults and school-aged children (6-14 years) using combined magneto- and electroencephalography (M/EEG) during passive listening conditions and an auditory Go/No-go task. The associations between auditory cortical responses and inhibition performance measures diverge between adults and children; while in children the brain-behavior associations are not significant, or stronger responses are beneficial, adults show negative associations between auditory cortical responses and inhibitory performance. Furthermore, we found differences in brain responses between adults and children; the late (~200 ms post stimulation) adult peak activation shifts from auditory to frontomedial areas. In contrast, children show prolonged obligatory responses in the auditory cortex. Together this likely translates to a functional difference between adults and children in the cortical resources for performance consistency in auditory-based cognitive tasks.

Unsupervised representation learning of spontaneous MEG data with nonlinear ICA.

Resting-state magnetoencephalography (MEG) data show complex but structured spatiotemporal patterns. However, the neurophysiological basis of these signal patterns is not fully known and the underlying signal sources are mixed in MEG measurements. Here, we developed a method based on the nonlinear independent component analysis (ICA), a generative model trainable with unsupervised learning, to learn representations from resting-state MEG data. After being trained with a large dataset from the Cam-CAN repository, the model has learned to represent and generate patterns of spontaneous cortical activity using latent nonlinear components, which reflects principal cortical patterns with specific spectral modes. When applied to the downstream classification task of audio-visual MEG, the nonlinear ICA model achieves competitive performance with deep neural networks despite limited access to labels. We further validate the generalizability of the model across different datasets by applying it to an independent neurofeedback dataset for decoding the subject's attentional states, providing a real-time feature extraction and decoding mindfulness and thought-inducing tasks with an accuracy of around 70% at the individual level, which is much higher than obtained by linear ICA or other baseline methods. Our results demonstrate that nonlinear ICA is a valuable addition to existing tools, particularly suited for unsupervised representation learning of spontaneous MEG activity which can then be applied to specific goals or tasks when labelled data are scarce.

Activity level in left auditory cortex predicts behavioral performance in inhibition tasks in children.

Sensory processing during development is important for the emerging cognitive skills underlying goal-directed behavior. Yet, it is not known how auditory processing in children is related to their cognitive functions. Here, we utilized combined magneto- and electroencephalographic (M/EEG) measurements in school-aged children (6-14y) to show that child auditory cortical activity at ∼250 ms after auditory stimulation predicts the performance in inhibition tasks. While unaffected by task demands, the amplitude of the left-hemisphere activation pattern was significantly correlated with the variability of behavioral response time. Since this activation pattern is typically not present in adults, our results suggest divergent brain mechanisms in adults and children for consistent performance in auditory-based cognitive tasks. This difference can be explained as a shift in cortical resources for cognitive control from sensorimotor associations in the auditory cortex of children to top-down regulated control processes involving (pre)frontal and cingulate areas in adults.

Neural Mechanisms Underlying Human Auditory Evoked Responses Revealed By Human Neocortical Neurosolver.

Auditory evoked fields (AEFs) are commonly studied, yet their underlying neural mechanisms remain poorly understood. Here, we used the biophysical modelling software Human Neocortical Neurosolver (HNN) whose foundation is a canonical neocortical circuit model to interpret the cell and network mechanisms contributing to macroscale AEFs elicited by a simple tone, measured with magnetoencephalography. We found that AEFs can be reproduced by activating the neocortical circuit through a layer specific sequence of feedforward and feedback excitatory synaptic drives, similar to prior simulation of somatosensory evoked responses, supporting the notion that basic structures and activation patterns are preserved across sensory regions. We also applied the modeling framework to develop and test predictions on neural mechanisms underlying AEF differences in the left and right hemispheres, as well as in hemispheres contralateral and ipsilateral to the presentation of the auditory stimulus. We found that increasing the strength of the excitatory synaptic cortical feedback inputs to supragranular layers simulates the commonly observed right hemisphere dominance, while decreasing the input latencies and simultaneously increasing the number of cells contributing to the signal accounted for the contralateral dominance. These results provide a direct link between human data and prior animal studies and lay the foundation for future translational research examining the mechanisms underlying alteration in this fundamental biomarker of auditory processing in healthy cognition and neuropathology.

Parametric merging of MEG and fMRI reveals spatiotemporal differences in cortical processing of spoken words and environmental sounds in background noise.

There is an increasing interest to integrate electrophysiological and hemodynamic measures for characterizing spatial and temporal aspects of cortical processing. However, an informative combination of responses that have markedly different sensitivities to the underlying neural activity is not straightforward, especially in complex cognitive tasks. Here, we used parametric stimulus manipulation in magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) recordings on the same subjects, to study effects of noise on processing of spoken words and environmental sounds. The added noise influenced MEG response strengths in the bilateral supratemporal auditory cortex, at different times for the different stimulus types. Specifically for spoken words, the effect of noise on the electrophysiological response was remarkably nonlinear. Therefore, we used the single-subject MEG responses to construct parametrization for fMRI data analysis and obtained notably higher sensitivity than with conventional stimulus-based parametrization. fMRI results showed that partly different temporal areas were involved in noise-sensitive processing of words and environmental sounds. These results indicate that cortical processing of sounds in background noise is stimulus specific in both timing and location and provide a new functionally meaningful platform for combining information obtained with electrophysiological and hemodynamic measures of brain function.

Neural processing of spoken words in specific language impairment and dyslexia.

Young adults with a history of specific language impairment (SLI) differ from reading-impaired (dyslexic) individuals in terms of limited vocabulary and poor verbal short-term memory. Phonological short-term memory has been shown to play a significant role in learning new words. We investigated the neural signatures of auditory word recognition and word repetition in young adults with SLI, dyslexia and normal language development using magnetoencephalography. The stimuli were 7-8 letter spoken real words and pseudo-words. They evoked a transient peak at 100 ms (N100m) followed by longer-lasting activation peaking around 400 ms (N400m) in the left and right superior temporal cortex. Both word repetition (first vs. immediately following second presentation) and lexicality (words vs. pseudowords) modulated the N400m response. An effect of lexicality was detected about 400 ms onwards as activation culminated for words but continued for pseudo-words. This effect was more pronounced in the left than right hemisphere in the control subjects. The left hemisphere lexicality effect was also present in the dyslexic adults, but it was non-significant in the subjects with SLI, possibly reflecting their limited vocabulary. The N400m activation between 200 and 700 ms was attenuated by the immediate repetition of words and pseudo-words in both hemispheres. In SLI adults the repetition effect evaluated at 200-400 ms was abnormally weak. This finding suggests impaired short-term maintenance of linguistic activation that underlies word recognition. Furthermore, the size of the repetition effect decreased from control subjects through dyslexics to SLIs, i.e. when advancing from milder to more severe language impairment. The unusually rapid decay of speech-evoked activation could have a detrimental role on vocabulary growth in children with SLI.

Cortical differentiation of speech and nonspeech sounds at 100 ms: implications for dyslexia.

Neurophysiological measures indicate cortical sensitivity to speech sounds by 150 ms after stimulus onset. In this time window dyslexic subjects start to show abnormal cortical processing. We investigated whether phonetic analysis is reflected in the robust auditory cortical activation at approximately 100 ms (N100m), and whether dyslexic subjects show abnormal N100m responses to speech or nonspeech sounds. We used magnetoencephalography to record auditory responses of 10 normally reading and 10 dyslexic adults. The speech stimuli were synthetic Finnish speech sounds (/a/, /u/, /pa/, /ka/). The nonspeech stimuli were complex nonspeech sounds and simple sine wave tones, composed of the F1+F2+F3 and F2 formant frequencies of the speech sounds, respectively. All sounds evoked a prominent N100m response in the bilateral auditory cortices. The N100m activation was stronger to speech than nonspeech sounds in the left but not in the right auditory cortex, in both subject groups. The leftward shift of hemispheric balance for speech sounds is likely to reflect analysis at the phonetic level. In dyslexic subjects the overall interhemispheric amplitude balance and timing were altered for all sound types alike. Dyslexic individuals thus seem to have an unusual cortical organization of general auditory processing in the time window of speech-sensitive analysis.