Comparison of EEG propagation speeds under emotional stimuli on smartphone between the different anxiety states

The Texting Rhythm: A Novel EEG Waveform Using Smartphones

INTRODUCTION

We report a unique EEG phenomenon in patients with paroxysmal neurological events undergoing video EEG monitoring.

METHODS

Two epilepsy centers analyzed the interictal scalp EEG in patients using personal electronic devices during epilepsy monitoring. The texting rhythm (TR) was defined as a reproducible, stimulus-evoked, generalized frontocentral monomorphic burst of 5-6 Hz theta consistently induced by active text messaging. An independent prospective and retrospective cohort was analyzed and compared from two sites in Florida and Illinois. We assessed age, gender, diagnosis, epilepsy classification, MRI, and EEG to compare patients with a TR. Analysis was performed with statistical significance set at P < 0.05.

RESULTS

We identified 24 of 98 evaluable patients with a TR in a prospective arm at one center and 7 of 31 patients in a retrospective arm at another totaling 31/129 (24.0%). The waveform prevalence was similar at both centers independent of location. TR was highly specific to active texting. A similar waveform during independent cognitive, speech or language, motor activation and audio cellular telephone use was absent (P < 0.0001). It appeared to be increased in patients with epilepsy in one cohort (P = 0.03) and generalized seizures in the other (P = 0.025). Age, gender, epilepsy type, MRI results, and EEG lateralization in patients with focal epileptic seizures did not bear a relationship to the presence of a TR in either arm of the study (P = NS).

CONCLUSIONS

The TR is a novel waveform time-locked to text messaging and associated with active use of smartphones. Electroencephalographers should be aware of the TR to separate it from an abnormality in patients undergoing video EEG monitoring. Larger sample sizes and additional research may help define the significance of this unique cognitive-visual-cognitive-motor network that is technology-related and task-specific with implications in communication research and transportation safety.

Physiological Informatics: Collection and Analyses of Data from Wearable Sensors and Smartphone for Healthcare

Physiological data from wearable sensors and smartphone are accumulating rapidly, and this provides us the chance to collect dynamic and personalized information as phenotype to be integrated to genotype for the holistic understanding of complex diseases. This integration can be applied to early prediction and prevention of disease, therefore promoting the shifting of disease care tradition to the healthcare paradigm. In this chapter, we summarize the physiological signals which can be detected by wearable sensors, the sharing of the physiological big data, and the mining methods for the discovery of disease-associated patterns for personalized diagnosis and treatment. We discuss the challenges of physiological informatics about the storage, the standardization, the analyses, and the applications of the physiological data from the wearable sensors and smartphone. At last, we present our perspectives on the models for disentangling the complex relationship between early disease prediction and the mining of physiological phenotype data.

Cortical processing during smartphone text messaging

OBJECTIVE

The objective of this study was to report the EEG features of text messaging using smartphones.

METHODS

One hundred twenty-nine patients were prospectively evaluated during video-EEG monitoring (VEM) over 16months. A reproducible texting rhythm (TR) present during active text messaging with a smartphone was compared with passive and forced audio telephone use, thumb/finger movements, cognitive testing/calculation, scanning eye movements, and speech/language tasks in patients with and without epilepsy. Statistical significance was set at p<0.05.

RESULTS

Twenty-seven patients with a TR were identified from a cohort of 129 (93 female, mean age: 36; range: 18-71) unselected VEM patients. Fifty-three out of 129 patients had epileptic seizures (ES), 74/129 had nonepileptic seizures (NES), and 2/129 were dual-diagnosed. A reproducible TR was present in 27/129 (20.9%) specific to text messaging (p<0.0001) and present in 28% of patients with ES and 16% of patients with NES (p=NS). The TR was absent during independent tasks and audio cellular telephone use (p<0.0001). Age, gender, epilepsy type, MRI results, and EEG lateralization in patients with focal seizures were unrelated (p=NS).

CONCLUSIONS

Our results suggest that the TR on scalp EEG represents a novel technology-specific neurophysiological alteration of brain networks. We propose that cortical processing in the contemporary brain is uniquely activated by the use of PEDs.

SIGNIFICANCE

These findings have practical implications that could impact industry and research in nonverbal communication.

Brief learning induces a memory bias for arousing-negative words: an fMRI study in high and low trait anxious persons

Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety) participated in a criterion-based associative word-learning paradigm, in which neutral pseudowords were paired with aversive or neutral pictures, which should lead to a valence change for the negatively paired pseudowords. After learning, pseudowords were tested with fMRI to investigate differential brain activation of the amygdala evoked by the newly acquired valence. Explicit and implicit memory was assessed directly after training and in three follow-ups at 4-day intervals. The behavioral results demonstrate that associative word-learning leads to an explicit (but no implicit) memory bias for negatively linked pseudowords, relative to neutral ones, which confirms earlier studies. Bilateral amygdala activation underlines the behavioral effect: Higher trait anxiety is correlated with stronger amygdala activation for negatively linked pseudowords than for neutrally linked ones. Most interestingly, this effect is also present for negatively paired pseudowords that participants could not remember well. Moreover, neutrally paired pseudowords evoked higher amygdala reactivity than completely novel ones in highly anxious persons, which can be taken as evidence for generalization. These findings demonstrate that few word-learning trials generate a memory bias for emotional stimuli, indexed both behaviorally and neurophysiologically. Importantly, the typical memory bias for emotional stimuli and the generalization to neutral ones is larger in high anxious persons.