scholarly journals PCA-based source-space contrast maps reveal psychologically meaningful individual differences in continuous MEG activity

2019 ◽  
Author(s):  
Erkka Heinilä ◽  
Aapo Hyvärinen ◽  
Tapani Ristaniemi ◽  
Lauri Parkkonen ◽  
Tiina Parviainen
Keyword(s):  
Individual Differences ◽  
Brain Activity ◽  
Principal Component ◽  
Mind Wandering ◽  
Oscillatory Activity ◽  
Behavioral Characteristics ◽  
Focused Attention ◽  
Specific Method ◽  
List Type ◽  
The Brain

AbstractWithin the field of neuroimaging, there has been an increasing trend towards studying brain activity in naturalistic conditions, and it is possible to robustly estimate networks of on-going oscillatory activity in the brain. However, not many studies have focused on differences between individuals in on-going brain activity that would be associable to psychological or behavioral characteristics. Existing standard methods can perform well at single-participant level, but generalizing the methodology across many participants is challenging due to individual differences of brains. As an example of a clinically relevant, naturalistic condition we consider here mindfulness. Trait mindfulness, as well as a mindfulness-based intervention cultivating focused attention, is often associated with benefits for psychological health. Therefore, the manner in which the brain engages in focused attention vs. mind wandering is likely to associate with individual differences in psycho–behavioral tendencies.We recorded MEG from 29 participants both in a state of focused attention and in a state of simulated mind wandering. We used Principal Component Analysis to decompose spatial average activation maps of focused attention contrasted with two different mind wandering states. The first principal component, which reflected differential engagement of bilateral parietal areas during focused attention vs. mind wandering, was associated with behavioral characteristics of inhibition, anxiousness and depression, as measured by standard questionnaires. We demonstrated that such decomposition of time-averaged contrast maps can overcome some of the challenges in methods based on concatenated data, especially from the perspective of behaviorally and clinically relevant characteristics in the ongoing brain oscillatory activity.HighlightsWe present a specific method to analyse/establish associations between brain oscillations and behavioral characteristics.We found that activity levels in parietal areas during mind wandering compared to focused attention were associated with the behavioral trait of inhibition and anxiety.

scholarly journals The Noise-Resilient Brain: Resting-State Oscillatory Activity Predicts Words-In-Noise Recognition

2019 ◽  
Author(s):  
Thomas Houweling ◽  
Robert Becker ◽  
Alexis Hervais-Adelman
Keyword(s):  
Individual Differences ◽  
Phonological Processing ◽  
Resting State ◽  
Recognition Performance ◽  
Brain Activity ◽  
Superior Temporal Gyrus ◽  
Oscillatory Activity ◽  
List Type ◽  
Gamma Frequency ◽  
Human Connectome Project

AbstractThe role of neuronal oscillations in the processing of speech has recently come to prominence. Since resting-state (RS) brain activity has been shown to predict both task-related brain activation and behavioural performance, we set out to establish whether inter-individual differences in spectrally-resolved RS-MEG power are associated with variations in words-in-noise recognition in a sample of 88 participants made available by the Human Connectome Project. Positive associations with resilience to noise were observed with power in the range 21 and 29Hz in a number of areas along the left temporal gyrus and temporo-parietal association areas peaking in left posterior superior temporal gyrus (pSTG). Significant associations were also found in the right posterior superior temporal gyrus in the frequency range 30 to 40Hz. We propose that individual differences in words-in-noise performance are related to baseline excitability levels of the neural substrates of phonological processing.HighlightsPower of resting MEG activity predicts Words-In-Noise recognition performanceSignificant associations in higher beta and lower gamma frequency bandStrongest in left-lateralised perisylvian cluster peaking in posterior STGEffects are spectrally and spatially consistent with phoneme-level processing

scholarly journals Dissecting individual differences in responses to naturalistic stimuli in functional MRI: effects of development and gender

2020 ◽  
Author(s):  
Xin Di ◽  
Bharat B. Biswal
Keyword(s):  
Principal Component Analysis ◽  
Individual Differences ◽  
Functional Mri ◽  
Principal Component ◽  
Component Analysis ◽  
Gender Effects ◽  
Delayed Response ◽  
List Type ◽  
And Gender ◽  
The Individual

AbstractFunctional MRI (fMRI) study of naturalistic conditions, e.g. movie watching, usually focuses on shared responses across subjects. However, individual differences in the responses have been attracting increasing attention in search of group differences or associations with behavioral outcomes. The individual differences have been studied by directly modeling the cross-subject correlation matrix or projecting the relations into a 1-D space. We contend that it is critical to examine whether there are single or multiple consistent components of responses underlying the whole population, because multiple components may undermine the individual relations using the previous methods. We use principal component analysis (PCA) to examine the heterogeneity of brain responses across subjects in terms of the eigenvalues of the covariance matrix, and utilize this approach to study developmental trajectories and gender effects in a movie watching dataset. We identified several brain networks in the parietal cortex that showed a significant second principal component (PC) of regional responses, which were mainly represented the younger children. The second PCs in some networks, i.e. the supramarginal network, resembled a delayed version of the first PCs for 4 seconds (2 TR), indicating delayed responses in the younger children than the older children and adults. However, no apparent gender effects were found in the first and second PCs. The analyses highlight the importance of identifying multiple consistent responses underlying individual differences in responses to naturalistic stimuli. And the PCA-based approach could be complementary to the commonly used intersubject correlation analysis.HighlightsThere may be multiple consistent responses among subjects during movie watchingPrincipal component analysis can be used to identify the multiple consistent responsesMany brain regions showed two principal components that were separated by ageYounger children showed delayed response in the supramarginal gyrus and precuneus

scholarly journals Effector-independent brain network for auditory-motor integration: fMRI evidence from singing and cello playing

2020 ◽  
Author(s):  
Melanie Segado ◽  
Robert J. Zatorre ◽  
Virginia B. Penhune
Keyword(s):  
Motor Control ◽  
Auditory Feedback ◽  
Brain Activity ◽  
Brain Networks ◽  
Anterior Cingulate ◽  
List Type ◽  
Control Mechanisms ◽  
Monitoring And Control ◽  
Pitch Regulation ◽  
The Brain

AbstractMany everyday tasks share high-level sensory goals but differ in the movements used to accomplish them. One example of this is musical pitch regulation, where the same notes can be produced using the vocal system or a musical instrument controlled by the hands. Cello playing has previously been shown to rely on brain structures within the singing network for performance of single notes, except in areas related to primary motor control, suggesting that the brain networks for auditory feedback processing and sensorimotor integration may be shared (Segado et al. 2018). However, research has shown that singers and cellists alike can continue singing/playing in tune even in the absence of auditory feedback (Chen et al. 2013, Kleber et al. 2013), so different paradigms are required to test feedback monitoring and control mechanisms. In singing, auditory pitch feedback perturbation paradigms have been used to show that singers engage a network of brain regions including anterior cingulate cortex (ACC), anterior insula (aINS), and intraparietal sulcus (IPS) when compensating for incorrect pitch feedback, and posterior superior temporal gyrus (pSTG) and supramarginal gyrus (SMG) when ignoring it (Zarate et al. 2005, 2008). To determine whether the brain networks for cello playing and singing directly overlap in these sensory-motor integration areas, in the present study expert cellists were asked to compensate for or ignore introduced pitch perturbations when singing/playing during fMRI scanning. We found that cellists were able to sing/play target tones, and compensate for and ignore introduced feedback perturbations equally well. Brain activity overlapped for singing and playing in IPS and SMG when compensating, and pSTG and dPMC when ignoring; differences between singing/playing across all three conditions were most prominent in M1, centered on the relevant motor effectors (hand, larynx). These findings support the hypothesis that pitch regulation during cello playing relies on structures within the singing network and suggests that differences arise primarily at the level of forward motor control.HighlightsExpert cellists were asked to compensate for or ignore introduced pitch perturbations when singing/playing during fMRI scanning.Cellists were able to sing/play target tones, and compensate for and ignore introduced feedback perturbations equally well.Brain activity overlapped for singing and playing in IPS and SMG when compensating, and pSTG and dPMC when ignoring.Differences between singing/playing across were most prominent in M1, centered around the relevant motor effectors (hand, larynx)Findings support the hypothesis that pitch regulation during cello playing relies on structures within the singing network with differences arising primarily at the level of forward motor control

MONOTONOUS TASKS AND ALCOHOL CONSUMPTION EFFECTS ON THE BRAIN BY EEG ANALYSIS USING NEURAL NETWORKS

2012 ◽  
Vol 11 (03) ◽  
pp. 1250015 ◽  
Author(s):  
STEPHEN KARUNGARU ◽  
TOSHIHIRO YOSHIDA ◽  
TORU SEO ◽  
MINORU FUKUMI ◽  
KENJI TERADA
Keyword(s):  
Neural Networks ◽  
Mental Stress ◽  
Brain Activity ◽  
Principal Component ◽  
Eeg Signals ◽  
Linear Discriminant ◽  
The Relationship ◽  
Electroencephalogram Eeg ◽  
The Brain ◽  
Eeg Signal Analysis

An analysis of the Electroencephalogram (EEG) signals while performing a monotonous task and drinking alcohol using principal component analysis (PCA), linear discriminant analysis (LDA) for feature extraction and Neural Networks (NNs) for classification is proposed. The EEG is captured while performing a monotonous task that can adversely affect the brain and possibly cause stress. Moreover, we investigate the effects of alcohol on the brain by capturing the data continuously after consumption of equal amounts of alcohol. We hope that our work will shed more light on the relationship between such actions and EEG, and investigate if there is any relation between the tasks and mental stress. EEG signals offers a rare look at brain activity, while, monotonous activities are well known to cause irritation which may contribute to mental stress. We apply PCA and LDA to characterize the change in each component, extract it and discriminate using a NN. After experiments, it was found that PCA and LDA are effective analysis methods in EEG signal analysis.

scholarly journals Neocortical activity tracks syllable and phrasal structure of self-produced speech during reading aloud

2019 ◽  
Author(s):  
Mathieu Bourguignon ◽  
Nicola Molinaro ◽  
Mikel Lizarazu ◽  
Samu Taulu ◽  
Veikko Jousmäki ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Reading Aloud ◽  
Auditory Information ◽  
List Type ◽  
Feedback Processing ◽  
Speech Monitoring ◽  
Directional Coupling ◽  
Auditory Cortices ◽  
The Brain

AbstractTo gain novel insights into how the human brain processes self-produced auditory information during reading aloud, we investigated the coupling between neuromagnetic activity and the temporal envelope of the heard speech sounds (i.e., speech brain tracking) in a group of adults who 1) read a text aloud, 2) listened to a recording of their own speech (i.e., playback), and 3) listened to another speech recording. Coherence analyses revealed that, during reading aloud, the reader’s brain tracked the slow temporal fluctuations of the speech output. Specifically, auditory cortices tracked phrasal structure (<1 Hz) but to a lesser extent than during the two speech listening conditions. Also, the tracking of syllable structure (4–8 Hz) occurred at parietal opercula during reading aloud and at auditory cortices during listening. Directionality analyses based on renormalized partial directed coherence revealed that speech brain tracking at <1 Hz and 4–8 Hz is dominated by speech-to-brain directional coupling during both reading aloud and listening, meaning that speech brain tracking mainly entails auditory feedback processing. Nevertheless, brain-to-speech directional coupling at 4– 8 Hz was enhanced during reading aloud compared with listening, likely reflecting speech monitoring before production. Altogether, these data bring novel insights into how auditory verbal information is tracked by the human brain during perception and self-generation of connected speech.HighlightsThe brain tracks phrasal and syllabic rhythmicity of self-produced (read) speech.Tracking of phrasal structures is attenuated during reading compared with listening.Speech rhythmicity mainly drives brain activity during reading and listening.Brain activity drives syllabic rhythmicity more during reading than listening.

scholarly journals EEG correlates of working memory performance in females

2017 ◽  
Author(s):  
Yuri G. Pavlov ◽  
Boris Kotchoubey
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
High Performance ◽  
Brain Activity ◽  
Memory Performance ◽  
Two Dimensions ◽  
Oscillatory Activity ◽  
Theta Power ◽  
Low Performance ◽  
Oscillatory Brain Activity

AbstractBackgroundThe study investigates oscillatory brain activity during working memory (WM) tasks. The tasks employed varied in two dimensions. First, they differed in complexity from average to highly demanding. Second, we used two types of tasks, which required either only retention of stimulus set or retention and manipulation of the content. We expected to reveal EEG correlates of temporary storage and central executive components of WM and to assess their contribution to individual differences.ResultsGenerally, as compared with the retention condition, manipulation of stimuli in WM was associated with distributed suppression of alpha1 activity and with the increase of the midline theta activity. Load and task dependent decrement of beta1 power was found during task performance. Beta2 power increased with the increasing WM load and did not significantly depend on the type of the task.At the level of individual differences, we found that the high performance (HP) group was characterized by higher alpha rhythm power. The HP group demonstrated task-related increment of theta power in the left anterior area and a gradual increase of theta power at midline area. In contrast, the low performance (LP) group exhibited a drop of theta power in the most challenging condition. HP group was also characterized by stronger desynchronization of beta1 rhythm over the left posterior area in the manipulation condition. In this condition, beta2 power increased in the HP group over anterior areas, but in the LP group over posterior areas.ConclusionsWM performance is accompanied by changes in EEG in a broad frequency range from theta to higher beta bands. The most pronounced differences in oscillatory activity between individuals with high and low WM performance can be observed in the most challenging WM task.

scholarly journals Decoding individual differences in STEM learning from functional MRI data

2018 ◽  
Author(s):  
Joshua S. Cetron ◽  
Andrew C. Connolly ◽  
Solomon G. Diamond ◽  
Vicki V. May ◽  
James V. Haxby ◽  
...  
Keyword(s):  
Individual Differences ◽  
Conceptual Understanding ◽  
Brain Activity ◽  
Data Driven ◽  
Stem Learning ◽  
Concept Knowledge ◽  
Wide Range ◽  
Concept Inventories ◽  
Using Data ◽  
The Brain

Traditional tests of concept knowledge generate scores to assess how well a learner understands a concept. Here, we investigated whether patterns of brain activity collected during a concept knowledge task could be used to compute a neural 'score' to complement traditional scores of an individual’s conceptual understanding. Using a novel data-driven multivariate neuroimaging approach—informational network analysis—we successfully derived a neural score from patterns of activity across the brain that predicted individual differences in multiple concept knowledge tasks in the physics and engineering domain. These tasks include an fMRI paradigm, as well as two other previously validated concept inventories. The informational network score outperformed alternative neural scores computed using data-driven neuroimaging methods, including multivariate representational similarity analysis. This technique could be applied to quantify concept knowledge in a wide range of domains, including classroom-based education research, machine learning, and other areas of cognitive science.

How Does the Brain Discriminate Familiar and Unfamiliar Faces?: A PET Study of Face Categorical Perception

2001 ◽  
Vol 13 (7) ◽  
pp. 1019-1034 ◽  
Author(s):  
Bruno Rossion ◽  
Christine Schiltz ◽  
Laurence Robaye ◽  
David Pirenne ◽  
Marc Crommelinck
Keyword(s):  
Categorical Perception ◽  
Brain Activity ◽  
Principal Component ◽  
Neural Responses ◽  
Lexical Information ◽  
Ventral Pathway ◽  
Middle Occipital Gyrus ◽  
The Right ◽  
The Brain ◽  
Unfamiliar Faces

Where and how does the brain discriminate familiar and unfamiliar faces? This question has not been answered yet by neuroimaging studies partly because different tasks were performed on familiar and unfamiliar faces, or because familiar faces were associated with semantic and lexical information. Here eight subjects were trained during 3 days with a set of 30 faces. The familiarized faces were morphed with unfamiliar faces. Presented with continua of unfamiliar and familiar faces in a pilot experiment, a group of eight subjects presented a categorical perception of face familiarity: there was a sharp boundary in percentage of familiarity decisions between 40% and 60% faces. In the main experiment, subjects were scanned (PET) on the fourth day (after 3 days of training) in six conditions, all requiring a sex classification task. Completely novel faces (0%) were presented in Condition 1 and familiar faces (100%) in Condition 6, while faces of steps of 20% in the continuum of familiarity were presented in Conditions 2 to 5 (20% to 80%). A principal component analysis (PCA) indicated that most variations in neural responses were related to the dissociation between faces perceived as familiar (60% to 100%) and faces perceived as unfamiliar (0 to 40%). Subtraction analyses did not disclose any increase of activation for faces perceived as familiar while there were large relative increases for faces perceived as unfamiliar in several regions of the right occipito-temporal visual pathway. These changes were all categorical and were observed mainly in the right middle occipital gyrus, the right posterior fusiform gyrus, and the right inferotemporal cortex. These results show that (1) the discrimination between familiar and unfamiliar faces is related to relative increases in the right ventral pathway to unfamiliar/novel faces; (2) familiar and unfamiliar faces are discriminated in an all-or-none fashion rather than proportionally to their resemblance to stored representations; and (3) categorical perception of faces is associated with abrupt changes of brain activity in the regions that discriminate the two extremes of the multidimensional continuum.

scholarly journals Individual Differences in Brain Responses: New Opportunities for Tailoring Health Communication Campaigns

2020 ◽  
Vol 14 ◽  
Author(s):  
Richard Huskey ◽  
Benjamin O. Turner ◽  
René Weber
Keyword(s):  
Individual Differences ◽  
Brain Activity ◽  
Brain Regions ◽  
Future Research ◽  
Message Processing ◽  
Response Patterns ◽  
Message Tailoring ◽  
Brain Responses ◽  
And Behavior ◽  
The Brain

Prevention neuroscience investigates the brain basis of attitude and behavior change. Over the years, an increasingly structurally and functionally resolved “persuasion network” has emerged. However, current studies have only identified a small handful of neural structures that are commonly recruited during persuasive message processing, and the extent to which these (and other) structures are sensitive to numerous individual difference factors remains largely unknown. In this project we apply a multi-dimensional similarity-based individual differences analysis to explore which individual factors—including characteristics of messages and target audiences—drive patterns of brain activity to be more or less similar across individuals encountering the same anti-drug public service announcements (PSAs). We demonstrate that several ensembles of brain regions show response patterns that are driven by a variety of unique factors. These results are discussed in terms of their implications for neural models of persuasion, prevention neuroscience and message tailoring, and methodological implications for future research.

The melody of the immature brain

e-Neuroforum ◽  
2013 ◽  
Vol 19 (1) ◽  
Author(s):  
K. Sieben ◽  
H. Hartung ◽  
A. Wolff ◽  
I. Hanganu-Opatz
Keyword(s):  
Energy Efficient ◽  
Brain Activity ◽  
Sensory Perception ◽  
Brain Regions ◽  
Adult Brain ◽  
Oscillatory Activity ◽  
Recent Experimental Data ◽  
Immature Brain ◽  
Rodent Brain ◽  
The Brain

AbstractThe periodicity of brain activity became ob­vious even after the first attempt to capture it, with Hans Berger noting in 1929 that the “electroencephalogram represents a con­tinuous curve with continuous oscillations”. This rhythmicity of neural activity, the ‘melo­dy’ of the brain, has since gained interest as an energy-efficient strategy for the organisa­tion and communication both within and be­tween brain regions. While it is now known that these oscillations actively contribute to sensory perception and cognition in the adult brain, their function during development is still largely unknown. Recent experimental data revealed the ability of immature human and rodent brain to generate various patterns of electrical activity. Their properties and un­derlying mechanisms may vary among dif­ferent brain areas. However, these early pat­terns of activity seem to facilitate the refine­ment of cortical maps involved in sensory perception as well as mnemonic and execu­tive processing. Here we review recent stud­ies, which characterize the early oscillatory activity and demonstrate its impact on brain development.

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