Data and results

Data used to generate figures in the publication. For details please refer to the README.txt file

Split2: N=5

Raw data in BIDS forma

EEG-T1

EEG data acquired during CueCue experiment (linguistic Posner paradigm

CueCueT2

Data associated with CueCue experiment (linguistic Posner paradigm) conducted at second measurement time (T2

MR-BIDS-T1

MRI data acquired during CueCue paradigm (linguistic Posner paradigm) in measurement time T

Large-scale network dynamics of beta-band oscillations underlie auditory perceptual decision-making

Perceptual decisions vary in the speed at which we make them. Evidence suggests that translating sensory information into perceptual decisions relies on distributed interacting neural populations, with decision speed hinging on power modulations of the neural oscillations. Yet the dependence of perceptual decisions on the large-scale network organization of coupled neural oscillations has remained elusive. We measured magnetoencephalographic signals in human listeners who judged acoustic stimuli composed of carefully titrated clouds of tone sweeps. These stimuli were used in two task contexts, in which the participants judged the overall pitch or direction of the tone sweeps. We traced the large-scale network dynamics of the source-projected neural oscillations on a trial-by-trial basis using power-envelope correlations and graph-theoretical network discovery. In both tasks, faster decisions were predicted by higher segregation and lower integration of coupled beta-band (∼16–28 Hz) oscillations. We also uncovered the brain network states that promoted faster decisions in either lower-order auditory or higher-order control brain areas. Specifically, decision speed in judging the tone sweep direction critically relied on the nodal network configurations of anterior temporal, cingulate, and middle frontal cortices. Our findings suggest that global network communication during perceptual decision-making is implemented in the human brain by large-scale couplings between beta-band neural oscillations. The speed at which we make perceptual decisions varies. This translation of sensory information into perceptual decisions hinges on dynamic changes in neural oscillatory activity. However, the large-scale neural-network embodiment supporting perceptual decision-making is unclear. We addressed this question by experimenting two auditory perceptual decision-making situations. Using graph-theoretical network discovery, we traced the large-scale network dynamics of coupled neural oscillations to uncover the brain network states that support the speed of auditory perceptual decisions. We found that higher network segregation of coupled beta-band oscillations supports faster auditory perceptual decisions over trials. Moreover, when auditory perceptual decisions are relatively difficult, the decision speed benefits from higher segregation of frontal cortical areas, but lower segregation and greater integration of auditory cortical areas

The effect of 10 Hz repetitive transcranial magnetic stimulation of posterior parietal cortex on visual attention.

Repetitive transcranial magnetic stimulation (rTMS) of the posterior parietal cortex (PPC) at frequencies lower than 5 Hz transiently inhibits the stimulated area. In healthy participants, such a protocol can induce a transient attentional bias to the visual hemifield ipsilateral to the stimulated hemisphere. This bias might be due to a relatively less active stimulated hemisphere and a relatively more active unstimulated hemisphere. In a previous study, Jin and Hilgetag (2008) tried to switch the attention bias from the hemifield ipsilateral to the hemifield contralateral to the stimulated hemisphere by applying high frequency rTMS. High frequency rTMS has been shown to excite, rather than inhibit, the stimulated brain area. However, the bias to the ipsilateral hemifield was still present. The participants' performance decreased when stimuli were presented in the hemifield contralateral to the stimulation site. In the present study we tested if this unexpected result was related to the fact that participants were passively resting during stimulation rather than performing a task. Using a fully crossed factorial design, we compared the effects of high frequency rTMS applied during a visual detection task and high frequency rTMS during passive rest on the subsequent offline performance in the same detection task. Our results were mixed. After sham stimulation, performance was better after rest than after task. After active 10 Hz rTMS, participants' performance was overall better after task than after rest. However, this effect did not reach statistical significance. The comparison of performance after rTMS with task and performance after sham stimulation with task showed that 10 Hz stimulation significantly improved performance in the whole visual field. Thus, although we found a trend to better performance after rTMS with task than after rTMS during rest, we could not reject the hypothesis that high frequency rTMS with task and high frequency rTMS during rest equally affect performance

Corrected conditional response accuracies (CORR) after 10 Hz rTMS.

<p>Stars indicate significant differences after correcting for time on task as indicated by one-tailed paired t-tests with <i>p</i> < 0.05 after correcting for multiple comparisons.</p