No Evidence for Entrainment: Endogenous Gamma Oscillations and Rhythmic Flicker Responses Coexist in Visual Cortex.

Over the past decades, numerous studies have linked cortical gamma oscillations (∼30-100 Hz) to neurocomputational mechanisms. Their functional relevance, however, is still passionately debated. Here, we asked whether endogenous gamma oscillations in the human brain can be entrained by a rhythmic photic drive >50 Hz. Such a noninvasive modulation of endogenous brain rhythms would allow conclusions about their causal involvement in neurocognition. To this end, we systematically investigated oscillatory responses to a rapid sinusoidal flicker in the absence and presence of endogenous gamma oscillations using magnetoencephalography (MEG) in combination with a high-frequency projector. The photic drive produced a robust response over visual cortex to stimulation frequencies of up to 80 Hz. Strong, endogenous gamma oscillations were induced using moving grating stimuli as repeatedly done in previous research. When superimposing the flicker and the gratings, there was no evidence for phase or frequency entrainment of the endogenous gamma oscillations by the photic drive. Unexpectedly, we did not observe an amplification of the flicker response around participants' individual gamma frequencies (IGFs); rather, the magnitude of the response decreased monotonically with increasing frequency. Source reconstruction suggests that the flicker response and the gamma oscillations were produced by separate, coexistent generators in visual cortex. The presented findings challenge the notion that cortical gamma oscillations can be entrained by rhythmic visual stimulation. Instead, the mechanism generating endogenous gamma oscillations seems to be resilient to external perturbation.SIGNIFICANCE STATEMENT We aimed to investigate to what extent ongoing, high-frequency oscillations in the gamma-band (30-100 Hz) in the human brain can be entrained by a visual flicker. Gamma oscillations have long been suggested to coordinate neuronal firing and enable interregional communication. Our results demonstrate that rhythmic visual stimulation cannot hijack the dynamics of ongoing gamma oscillations; rather, the flicker response and the endogenous gamma oscillations coexist in different visual areas. Therefore, while a visual flicker evokes a strong neuronal response even at high frequencies in the gamma-band, it does not entrain endogenous gamma oscillations in visual cortex. This has important implications for interpreting studies investigating the causal and neuroprotective effects of rhythmic sensory stimulation in the gamma-band.

The visual cortex produces gamma band echo in response to broadband visual flicker.

The aim of this study is to uncover the network dynamics of the human visual cortex by driving it with a broadband random visual flicker. We here applied a broadband flicker (1-720 Hz) while measuring the MEG and then estimated the temporal response function (TRF) between the visual input and the MEG response. This TRF revealed an early response in the 40-60 Hz gamma range as well as in the 8-12 Hz alpha band. While the gamma band response is novel, the latter has been termed the alpha band perceptual echo. The gamma echo preceded the alpha perceptual echo. The dominant frequency of the gamma echo was subject-specific thereby reflecting the individual dynamical properties of the early visual cortex. To understand the neuronal mechanisms generating the gamma echo, we implemented a pyramidal-interneuron gamma (PING) model that produces gamma oscillations in the presence of constant input currents. Applying a broadband input current mimicking the visual stimulation allowed us to estimate TRF between the input current and the population response (akin to the local field potentials). The TRF revealed a gamma echo that was similar to the one we observed in the MEG data. Our results suggest that the visual gamma echo can be explained by the dynamics of the PING model even in the absence of sustained gamma oscillations.

Neural correlates of cue-induced changes in decision-making distinguish subjects with gambling disorder from healthy controls.

In addiction, there are few human studies on the neural basis of cue-induced changes in value-based decision making (Pavlovian-to-instrumental transfer, PIT). It is especially unclear whether neural alterations related to PIT are due to the physiological effects of substance abuse or rather related to learning processes and/or other etiological factors related to addiction. We have thus investigated whether neural activation patterns during a PIT task help to distinguish subjects with gambling disorder (GD), a nonsubstance-based addiction, from healthy controls (HCs). Thirty GD and 30 HC subjects completed an affective decision-making task in a functional magnetic resonance imaging (fMRI) scanner. Gambling-associated and other emotional cues were shown in the background during the task. Data collection and feature modeling focused on a network of nucleus accumbens (NAcc), amygdala, and orbitofrontal cortex (OFC) (derived from PIT and substance use disorder [SUD] studies). We built and tested a linear classifier based on these multivariate neural PIT signatures. GD subjects showed stronger PIT than HC subjects. Classification based on neural PIT signatures yielded a significant area under the receiver operating curve (AUC-ROC) (0.70, p = 0.013). GD subjects showed stronger PIT-related functional connectivity between NAcc and amygdala elicited by gambling cues, as well as between amygdala and OFC elicited by negative and positive cues. HC and GD subjects were thus distinguishable by PIT-related neural signatures including amygdala-NAcc-OFC functional connectivity. Neural PIT alterations in addictive disorders might not depend on the physiological effect of a substance of abuse but on related learning processes or even innate neural traits.

Integrating electric field modeling and neuroimaging to explain inter-individual variability of tACS effects.

Transcranial electrical stimulation (tES) of the brain can have variable effects, plausibly driven by individual differences in neuroanatomy and resulting differences of the electric fields inside the brain. Here, we integrated individual simulations of electric fields during tES with source localization to predict variability of transcranial alternating current stimulation (tACS) aftereffects on α-oscillations. In two experiments, participants received 20-min of either α-tACS (1 mA) or sham stimulation. Magnetoencephalogram (MEG) was recorded for 10-min before and after stimulation. tACS caused a larger power increase in the α-band compared to sham. The variability of this effect was significantly predicted by measures derived from individual electric field modeling. Our results directly link electric field variability to variability of tACS outcomes, underline the importance of individualizing stimulation protocols, and provide a novel approach to analyze tACS effects in terms of dose-response relationships.