On the interpretation of synchronization in EEG hyperscanning studies:a cautionary note

EEG Hyperscanning is a method for studying two or more individuals simultaneously with the objective of elucidating how co-variations in their neural activity (i.e., hyperconnectivity) are influenced by their behavioral and social interactions. The aim of this study was to compare the performance of different hyper-connectivity measures using (i) simulated data, where the degree of coupling could be systematically manipulated, and (ii) individually recorded human EEG combined into pseudo-pairs of participants where no hyper-connections could exist. With simulated data we found that each of the most widely used measures of hyperconnectivity were biased and detected hyper-connections where none existed. With pseudo-pairs of human data we found spurious hyper-connections that arose because there were genuine similarities between the EEG recorded from different people independently but under the same experimental conditions. Specifically, there were systematic differences between experimental conditions in terms of the rhythmicity of the EEG that were common across participants. As any imbalance between experimental conditions in terms of stimulus presentation or movement may affect the rhythmicity of the EEG, this problem could apply in many hyperscanning contexts. Furthermore, as these spurious hyper-connections reflected real similarities between the EEGs, they were not Type-1 errors that could be overcome by some appropriate statistical control. However, some measures that have not previously been used in hyperconnectivity studies, notably the circular correlation co-efficient (CCorr), were less susceptible to detecting spurious hyper-connections of this type. The reason for this advantage in performance is discussed and the use of the CCorr as an alternative measure of hyperconnectivity is advocated. © 2013 Burgess

How conventional visual representations of time-frequency analyses bias our perception of EEG/MEG signals and what to do about it

Time-frequency decompositions of the EEG/MEG have become such a familiar part of the cognitive neuroscience landscape over the past two decades that their appearance no longer seems remarkable. But to those of us who laboured in the days when the signal analysis toolbox contained Fourier analysis, event-related potentials and not much else, the arrival of time-frequency decompositions was little short of revolutionary. With their introduction, complex information about both the timing and frequency of changes in the EEG/MEG could be presented in the visually attractive format of time-frequency plots (TFPs). Like maps, with time on the abscissa, frequency on the ordinate and a colour or grey scale to indicate the amplitude or power at each time-frequency location, TFPs provide a convenient and efficient way to represent a large amount of detailed information in an easily digestible format and, for that, they are to be commended. Yet, despite all these benefits, it is my contention that TFPs, in the format most commonly seen in journal articles and at conferences, systematically distort and bias our perception of the EEG/MEG signals that they are supposed to help us understand. Specifically, my contention is that TFPs are biased by the use of linear frequency scales. Linear frequency scales distort our perception of the EEG/MEG signal by placing far too much emphasis on the high frequency components of the signal, where there is very little energy, and far too little emphasis on the lower frequencies where the biggest changes are seen. This disproportionate focus on high frequencies confers a degree of significance to the gamma band that is not justified by the evidence

Towards a unified understanding of event-related changes in the EEG:the Firefly model of synchronization through cross-frequency phase modulation

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not. Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing

Hypnotic induction is followed by state-like changes in the organization of EEG functional connectivity in the theta and beta frequency bands in high-hypnotically susceptible individuals

Altered state theories of hypnosis posit that a qualitatively distinct state of mental processing, which emerges in those with high hypnotic susceptibility following a hypnotic induction, enables the generation of anomalous experiences in response to specific hypnotic suggestions. If so then such a state should be observable as a discrete pattern of changes to functional connectivity (shared information) between brain regions following a hypnotic induction in high but not low hypnotically susceptible participants. Twenty-eight channel EEG was recorded from 12 high susceptible (highs) and 11 low susceptible (lows) participants with their eyes closed prior to and following a standard hypnotic induction. The EEG was used to provide a measure of functional connectivity using both coherence (COH) and the imaginary component of coherence (iCOH), which is insensitive to the effects of volume conduction. COH and iCOH were calculated between all electrode pairs for the frequency bands: delta (0.1-3.9 Hz), theta (4-7.9 Hz) alpha (8-12.9 Hz), beta1 (13-19.9 Hz), beta2 (20-29.9 Hz) and gamma (30-45 Hz). The results showed that there was an increase in theta iCOH from the pre-hypnosis to hypnosis condition in highs but not lows with a large proportion of significant links being focused on a central-parietal hub. There was also a decrease in beta1 iCOH from the pre-hypnosis to hypnosis condition with a focus on a fronto-central and an occipital hub that was greater in high compared to low susceptibles. There were no significant differences for COH or for spectral band amplitude in any frequency band. The results are interpreted as indicating that the hypnotic induction elicited a qualitative change in the organization of specific control systems within the brain for high as compared to low susceptible participants. This change in the functional organization of neural networks is a plausible indicator of the much theorized "hypnotic-state". © 2014 Jamieson and Burgess

A facial expression for anxiety.

Anxiety and fear are often confounded in discussions of human emotions. However, studies of rodent defensive reactions under naturalistic conditions suggest anxiety is functionally distinct from fear. Unambiguous threats, such as predators, elicit flight from rodents (if an escape-route is available), whereas ambiguous threats (e.g., the odor of a predator) elicit risk assessment behavior, which is associated with anxiety as it is preferentially modulated by anti-anxiety drugs. However, without human evidence, it would be premature to assume that rodent-based psychological models are valid for humans. We tested the human validity of the risk assessment explanation for anxiety by presenting 8 volunteers with emotive scenarios and asking them to pose facial expressions. Photographs and videos of these expressions were shown to 40 participants who matched them to the scenarios and labeled each expression. Scenarios describing ambiguous threats were preferentially matched to the facial expression posed in response to the same scenario type. This expression consisted of two plausible environmental-scanning behaviors (eye darts and head swivels) and was labeled as anxiety, not fear. The facial expression elicited by unambiguous threat scenarios was labeled as fear. The emotion labels generated were then presented to another 18 participants who matched them back to photographs of the facial expressions. This back-matching of labels to faces also linked anxiety to the environmental-scanning face rather than fear face. Results therefore suggest that anxiety produces a distinct facial expression and that it has adaptive value in situations that are ambiguously threatening, supporting a functional, risk-assessing explanation for human anxiet

TETRA mobile radios interfere with electroencephalography recording equipment

We observed an anomaly in the human electroencephalogram (EEG) associated with exposure to terrestrial trunked radio (TETRA) Radiofrequency Fields (RF). Here, we characterize the time and frequency components of the anomaly and demonstrate that it is an artefact caused by TETRA RF interfering with the EEG recording equipment and not by any direct or indirect effect on the brain

From Bibliophile to Sesquipedalian: Modeling the Role of Reading Experience in Vocabulary and Reading Comprehension

Purpose We investigated the roles of leisure reading and word reading ability in vocabulary and reading comprehension development in 598 adolescents at ages 10, 11, and 12 (285 girls, 313 boys). Method Structural equation modeling was used to test whether word reading was associated with vocabulary and reading comprehension: a) directly; b) indirectly via leisure reading; or c) both. Results We found both direct and indirect effects of word reading on vocabulary: word reading ability directly predicted outcomes, and also predicted the amount of leisure reading, which in turn predicted vocabulary. For reading comprehension we observed direct but not indirect effects of word reading. As expected, vocabulary and reading comprehension outcomes were strongly correlated. Conclusion Our findings demonstrate the direct effect of word reading ability in predicting vocabulary and reading comprehension, and reveal a crucial mediating role of leisure reading in the development of vocabulary

Tracking vocabulary and reading growth in children from lower and higher socioeconomic backgrounds during the transition from primary to secondary education

We examined the relation between socioeconomic status (SES), vocabulary, and reading in middle childhood, during the transition from primary (elementary) to secondary (high) school. Children (N = 279, 163 girls) completed assessments of everyday and curriculum‐related vocabulary, (non)word reading, and reading comprehension at five timepoints from age 10 to 13. Piecewise linear mixed‐effects models showed significant growth in everyday vocabulary and word reading between every time point. Curriculum vocabulary and reading comprehension showed significant growth during the school year, but not during the summer holidays. There were significant effects of SES on all measures except word reading; yet, SES differences did not widen over time. Our findings motivate targeted reading and vocabulary support for secondary school students from lower SES backgrounds

Deep machine learning provides state-of-the art performance in image-based plant phenotyping

Deep learning is an emerging field that promises unparalleled results on many data analysis problems. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping, and demonstrate state-of-the-art results for root and shoot feature identification and localisation. We predict a paradigm shift in image-based phenotyping thanks to deep learning approaches

Palaeogeographical evolution of the Rattray Volcanic Province, Central North Sea

Funded by Carnegie Trust for the Universities of Scotland PHD060365Peer reviewedPostprin