Contemporary Single and Multi-Tablet HIV Treatment Regimens Are Associated With Similar Levels of Viral Suppression.

Major depressive disorder (MDD) is highly prevalent and burdensome, resulting in increased efforts to understand mechanisms contributing to the development and maintenance of MDD. Electroencephalography (EEG) methods have made considerable contributions to our understanding of the neural mechanisms of MDD. Historically, this literature has used event-related potentials (ERPs) and frequency oscillations as the primary outcome variables; however, recent studies have highlighted the important role of aperiodic parameters (i.e., aperiodic exponent and offset) in relation to aging, cognition, and a growing number of psychopathologies, including schizophrenia, attention-deficit/hyperactivity disorder (ADHD), and depression. Of the aperiodic parameters, the exponent describes the 1/f-shape of the power spectrum and has been theorized to represent the balance of excitatory and inhibitory neurotransmitter systems (E-I balance) with flatter (i.e., lower absolute value) exponents indicating higher relative excitation and steeper exponents indicating higher relative inhibition. In turn, the aperiodic offset reflects the vertical displacement of the 1/f curve from the x-axis and has been theorized to represent neuronal cell spiking. Deficits in both inhibitory and excitatory systems have been implicated in MDD, suggesting that the aperiodic exponent, in particular, may be important for understanding neural mechanisms of depression. Despite this compelling evidence, existing studies of aperiodic activity within the context of MDD have been mostly limited to within-person changes following treatment with neuromodulation. Accordingly, it remains unclear whether aperiodic activity parameters differ based on an individual’s current depressive status or if this is driven by treatment effects. Thus, the current study sought to compare aperiodic activity in individuals with and without depression. EEG metrics from the frequency domain (e.g., alpha asymmetry, delta-beta coupling, functional connectivity, frequency band power) have yielded important findings relevant to etiology, maintenance, and treatment of MDD (see Newson and Thiagarajan, de Aguiar Neto and Rosa, Miljevic and colleagues, and Thibodeau and colleauges for reviews). Such research typically uses Fourier analysis to convert time-series EEG traces into a set of sinusoids with a given frequency and power that together describe the observed EEG trace. These sinusoids are plotted in spectrograms, allowing for extraction of power in frequency bands (e.g., delta, theta, alpha, and beta) for subsequent analyses. Historically, the characteristic 1/f-shape of the spectrogram (i.e., aperiodic exponent) and the vertical offset from the x-axis of this curve have been treated as neural noise. However, recent findings in biophysical modeling (i.e., neural simulations, non-human primate models, human anesthesiology, and human magnetic resonance spectroscopy (MRS) studies) have shown that aperiodic parameters have important relations to arousal states and may not just be noise. For example, following anesthetization, a state characterized by high levels of inhibition, both monkeys and humans showed steeper exponents (i.e., higher relative inhibition) than in their awake state. Additionally, MRS findings in humans have demonstrated significant linear relationships between gamma-aminobutyric acid (GABA; the main inhibitory neurotransmitter in the brain) and glutamate (the main excitatory neurotransmitter in the brain) ratios and aperiodic exponent. Together, such studies support the relevance of aperiodic exponent to neural excitatory-inhibitory (E-I) balance. As a result, pipelines have been developed to extract the exponent and offset values from the spectrogram curve (e.g., “fitting oscillations one-over f” (FOOOF)), promoting further study to understand aperiodic neural activity. Of the aperiodic parameters, little research has investigated the offset; however, it has been theorized as a proxy of neuronal cell spiking and found to decrease throughout development and adulthood. The inverse relationship between offset and age has been tied to the neural noise hypothesis, which posits that the aging brain exhibits more asynchronous activity that flattens the aperiodic exponent and decreases aperiodic offset. Given associations between elevated brain age and depression, it may be the case that a decreased aperiodic offset may be associated with depression. The aperiodic exponent has garnered more attention given its theorized representation as E-I balance and the importance of inhibitory and excitatory mechanisms in aging and psychopathology. For example, studies examining cohorts across the lifespan have reported a decrease in exponent (i.e., a flattening of the slope) as age increases, which aligns with MRS findings indicating reduced inhibition with increasing age. Moreover, individuals with MDD characteristically show lower levels of GABA and glutamatergic metabolites compared t