Smartphone usage is now integral to human behavior. Recent studies associate extensive usage with a range of debilitating effects. We sought to determine whether excessive usage is accompanied by measurable neural, cognitive and behavioral changes. Subjects lacking previous experience with smartphones (n = 35) were compared to a matched group of heavy smartphone users (n = 16) on numerous behavioral and electrophysiological measures recorded using electroencephalogram (EEG) combined with transcranial magnetic stimulation (TMS) over the right prefrontal cortex (rPFC). In a second longitudinal intervention, a randomly selected sample of the original non-users received smartphones for 3 months while the others served as controls. All measurements were repeated following this intervention. Heavy users showed increased impulsivity, hyperactivity and negative social concern. We also found reduced early TMS evoked potentials in the rPFC of this group, which correlated with severity of self-reported inattention problems. Heavy users also obtained lower accuracy rates than nonusers in a numerical processing. Critically, the second part of the experiment revealed that both the numerical processing and social cognition domains are causally linked to smartphone usage. Heavy usage was found to be associated with impaired attention, reduced numerical processing capacity, changes in social cognition, and reduced right prefrontal cortex (rPFC) excitability. Memory impairments were not detected. Novel usage over short period induced a significant reduction in numerical processing capacity and changes in social cognition.

Major depressive disorder (MDD) is a debilitating psychiatric condition with a 16% lifelong prevalence.¹ Antidepressant medication is widely used and has been researched for more than 4 decades. However, the mechanism of antidepressant action remains unclear, and nearly 40% of patients with MDD experience persistent depression even after 2 antidepressant treatments.² To improve outcomes, the neurophysiology of MDD and underlying therapeutic mechanisms of treatments need to be better understood.

Using concurrent transcranial magnetic stimulation (TMS) and electroencephalography (TMS-EEG), this study aims to compare the effect of three intermittent theta-burst stimulation (iTBS) doses on cortical activity in the left dorsolateral prefrontal (DLPFC) cortex. Fourteen neurotypical participants took part in the following three experimental conditions: 600, 1200 and 1800 pulses. TMS-EEG recordings were conducted on the left DLPFC pre/post iTBS, including single-pulse TMS and short- and long-interval intracortical inhibition (SICI, LICI). TMS-evoked potentials (TEP) and event-related spectral perturbation (ERSP) were quantified. Linear mixed models were used to assess the effect of iTBS on brain activity. The effects of iTBS on DLPFC activity did not significantly differ between the three doses. Specifically, regardless of dose, iTBS modulated the amplitude of most TEP components (P30, N45, P60, P200), reduced SICI and LICI ratios of P30 and P200, and decreased ERSP power of theta oscillations. In neurotypical individuals, doubling or tripling the number of iTBS pulses does not result in stronger potentiation of prefrontal activity. However, all iTBS conditions induced significant modulations of DLPFC activity. Replicating the study in clinical populations could help define optimal parameters for clinical applications.

Electroconvulsive therapy (ECT) is a highly effective neuromodulatory intervention for treatment-resistant major depressive disorder (MDD). Presently, however, understanding of its neurophysiological effects remains incomplete. In the present study, we utilised resting-state electroencephalography (RS-EEG) to explore changes in functional connectivity, network topology, and spectral power elicited by an acute open-label course of ECT in a cohort of 23 patients with treatment-resistant MDD. RS-EEG was recorded prior to commencement of ECT and again within 48 h following each patient’s final treatment session. Our results show that ECT was able to enhance connectivity within lower (delta and theta) frequency bands across subnetworks largely confined to fronto-central channels, while, conversely, more widespread subnetworks of reduced connectivity emerged within faster (alpha and beta) bands following treatment. Graph-based topological analyses revealed changes in measures of functional segregation (clustering coefficient), integration (characteristic path length), and small-world architecture following ECT. Finally, post-treatment enhancement of delta and theta spectral power was observed, which showed a positive association with the number of ECT sessions received. Overall, our findings indicate that RS-EEG can provide a sensitive measure of dynamic neural activity following ECT and highlight network-based analyses as a promising avenue for furthering mechanistic understanding of the effects of convulsive therapies.