0000000000138169
AUTHOR
Lauri Parkkonen
Time-resolved classification of dog brain signals reveals early processing of faces, species and emotion
Dogs process faces and emotional expressions much like humans, but the time windows important for face processing in dogs are largely unknown. By combining our non-invasive electroencephalography (EEG) protocol on dogs with machine-learning algorithms, we show category-specific dog brain responses to pictures of human and dog facial expressions, objects, and phase-scrambled faces. We trained a support vector machine classifier with spatiotemporal EEG data to discriminate between responses to pairs of images. The classification accuracy was highest for humans or dogs vs. scrambled images, with most informative time intervals of 100–140 ms and 240–280 ms. We also detected a response sensitive…
Child specific activation in left auditory cortex predicts behavioral performance in inhibition tasks
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 to show that child-unique 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 not present in adults, our results suggest divergent brai…
Activity level in left auditory cortex predicts behavioral performance in inhibition tasks in children
Funding Information: We are grateful to Hanna-Maija Lapinkero, Suvi Karjalainen, Maria Vesterinen & Janne Rajaniemi for help with data collection and to Amit Jaiswal, Erkka Heinilä and Jukka Nenonen for their help with preprocessing and scripting. This work was supported by EU project ChildBrain (Horizon2020 Marie Skłodowska-Curie Action (MSCA) Innovative Training Network (ITN) – European Training Network (ETN), grant agreement no. 641652) and the Academy of Finland grant number 311877. Publisher Copyright: © 2022 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…
Decoding attentional states for neurofeedback Mindfulness vs. wandering thoughts
Abstract Neurofeedback requires a direct translation of neuronal brain activity to sensory input given to the user or subject. However, decoding certain states, e.g., mindfulness or wandering thoughts, from ongoing brain activity remains an unresolved problem. In this study, we used magnetoencephalography (MEG) to acquire brain activity during mindfulness meditation and thought-inducing tasks mimicking wandering thoughts. We used a novel real-time feature extraction to decode the mindfulness, i.e., to discriminate it from the thought-inducing tasks. The key methodological novelty of our approach is usage of MEG power spectra and functional connectivity of independent components as features …
Musicianship can be decoded from magnetic resonance images
AbstractLearning induces structural changes in the brain. Especially repeated, long-term behaviors, such as extensive training of playing a musical instrument, are likely to produce characteristic features to brain structure. However, it is not clear to what extent such structural features can be extracted from magnetic resonance images of the brain. Here we show that it is possible to predict whether a person is a musician or a non-musician based on the thickness of the cerebral cortex measured at 148 brain regions en-compassing the whole cortex. Using a supervised machine-learning technique, we achieved a significant (κ = 0.321, p < 0.001) agreement between the actual and predicted par…
Unsupervised representation learning of spontaneous MEG data with nonlinear ICA
Funding Information: We wish to thank the reviewers and editors for the useful comments to improve the paper a lot. We thank Dr. Hiroshi Morioka for the useful discussion at the beginning of the project. L.P. was funded in part by the European Research Council (No. 678578 ). A.H. was supported by a Fellowship from CIFAR, and the Academy of Finland. The authors acknowledge the computational resources provided by the Aalto Science-IT project, and also wish to thank the Finnish Grid and Cloud Infrastructure (FGCI) for supporting this project with computational and data storage resources. | openaire: EC/H2020/678578/EU//HRMEG Resting-state magnetoencephalography (MEG) data show complex but stru…
Spectral signatures of cross-modal attentional control in the adolescent brain and their link with physical activity and aerobic fitness levels
AbstractTop–down attentional control seems to increase and suppress the activity of sensory cortices for relevant stimuli and to suppress activity for irrelevant ones. Higher physical activity (PA) and aerobic fitness (AF) levels have been associated with improved attention, but most studies have focused on unimodal tasks (e.g., visual stimuli only). The impact of higher PA or AF levels on the ability of developing brains to focus on certain stimuli while ignoring distractions remains unknown. The aim of this study was to examine the neural processes in visual and auditory sensory cortices during a cross-modal attention–allocation task using magnetoencephalography in 13–16-year-old adolesce…
PCA-based source-space contrast maps reveal psychologically meaningful individual differences in continuous MEG activity
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 mindful…