Results & Discussion Conclusions Introduction Methods The phase of pre-stimulus theta oscillations gates cortical information flow and predicts behavioural performance Volberg G, Hanslmayr S, Wimber M, Dalal SS, Greenlee MW Institut für Psychologie, Universität Regensburg gregor.volberg@ur.de The results of recent behavioural studies suggest that input into the visual system is sampled rhythmically, at a frequency of 5-10 Hz [1, 2]. Similarly, the results of EEG studies demonstrate that the probability for detecting near-threshold visual stimuli varies with the phase of on-going brain oscillations in the same frequency range [3, 4]. Ongoing brain oscillations might underlie the rhythmic nature of perception, by providing transient time windows for information exchange [5]. To test this hypothesis, we investigated pre-stimulus phase differences between hits and misses in a detection task, using combined EEG-fMRI recordings. Subjects 6 male, 7 female, mean age 24.2 years Stimuli & Procedure The subjects performed a visual detection task with 150 target (contour) stimuli and 150 non-target (non- contour) stimuli, presented in a random order. EEG and fMRI were recorded simultaneously using a 64-channel EEG and a 3 Tesla head scanner running a standard echo-planar imaging sequence. Differences in the pre-stimulus phase between hit and miss trials were investigated by means of the phase bifurcation index [6]. The data showed a significant pre-stimulus phase bifurcation, with a maximum at 7 Hz, - 250 ms relative to stimulus onset (p < .05 by randomization test). The present results suggest that a low frequency oscillatory signal at 7 Hz dynamically opens and closes time windows for sensory information transfer between lower and higher level visual brain regions, thereby modulating the likelihood that a visual stimulus is consciously perceived and reported by the participant. This oscillatory gating of information transfer between cortical regions might underlie the rhythmic nature of our visual system. [1] Landau AN, Fries P (2012). Attention samples stimuli rhythmically. Curr Biol 22, 1000 - 1004. [2] VanRullen R, Carlson T, Cavanagh P (2007). The blinking spotlight of attention. Proc Natl Acad Sci USA, 104, 19204 - 19209. [3] VanRullen R, Busch NA, Drewes J, Dubois J (2011). Ongoing EEG Phase as a Trial-by-Trial Predictor of Perceptual and Attentional Varia- bility. Front Psychol, 2, 60. [4] Jensen O, Bonnefond M, VanRullen R (2012). An oscillatory mechanism for prioritizing salient unattended stimuli. Trends Cogn Sci, 16, 200 - 206. [5] Fries P (2005). A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn Sci, 9, 474 - 480. [6] Busch NA, Dubois J, VanRullen R (2009). The phase of ongoing EEG oscillations predicts visual perception. J Neurosci, 29, 7869 - 7876. References contour non-contour A C + + + Fixation 1 - 3 s Stimulus 0.194 s Fixation (until response) Θ 1 Θ 2 s Θ 3 α A B C Example stimuli. Target stimuli contained a path of ten Gabor patches whose orientation was aligned to an invisible contour. The path angle was individually adjusted to the detection threshold (75 % correct responses, 21 - 34°). The distance between adjacent Gabor patches was 2 ± 0.55°. Trial sequence. Θ α S B The hit rate was 72.34 ± % (mean sd), the false-alarm rate was 23.96 %. The sensitivity measure was 1.37 0.53. 8.59 ± ± 10.87 d-prime ± -π - /2 π π/2 π 0 Phase (rad) % Correct 60 70 75 80 85 65 A B The pre-stimulus phase distribution, investigated across participants at centro-frontal electrodes, clustered around pi/-pi for hits and around 0 phase for misses (7 Hz, -250 ms; Kuiper-Test, K = 117, p < .05). The performance, sorted according to the pre- stimulus phase (blue), followed an inverted cosine function (red; circular-to-linear correlation Ro = 0.97, p < .001). rIPS lOcc rIPS lOcc rIPS lOcc A B The phase difference between hits and misses was also observable in the ERP amplitudes ~250 ms prior to stimulus onset, at right centro-frontal and left parieto- occipital electrodes (data shown for frontal cluster). A similar difference occurred 145 ms later, suggesting that the difference was driven by a 7 Hz oscillation. A beamformer analysis on the ERP difference between hits and misses (shaded area) revealed sources in the right intra-parietal sulcus (IPS) and left occipital cortex. Behavioral EEG: Phase bifurcation EEG: Phase distribution EEG: ERPs EEG-fMRI: Pre-stimulus EEG phase and BOLD -0.4 -0.2 0 0.2 -0.4 Time (s) 4 6 8 10 12 14 Frequency (Hz) 3 2 1 0 -1 -2 -3 t-values 2.5 5 pi/2 0 pi -pi -pi/2 -pi/2 pi/2 0 pi -pi 2 4 Hits Misses Hits Misses ~145 ms 0 1 2 Amplitude ( V) μ -0.4 -0.2 0 0.2 0.4 Time (s) 3 0 -3 t-values 3 2 t-values B A A B -π - /2 π π π/2 0 Phase (rad) Beta estimates -0.2 0 0.2 0.4 0.6 0.8 1.0 1.2 We next calculated correlations between EEG phase (7 Hz, -250 ms, averaged over significant fronto-central electrodes) and the BOLD signal on a single trial level. A specific effect of phase on the BOLD amplitude emerged in the right IPS (~BA 7; p < 0.001; k > 10 voxels), where the BOLD signal followed an inverted cosine function. Accordingly, pre-stimulus phase at 7 Hz appears to gate activity in the intra-parietal sulcus. uncorr EEG-fMRI: EEG phase and BOLD connectivity LO1 (~BA 19) A rIPS (~BA 7) LO1 (~BA 19) A rIPS (~BA 7) LO1 (~BA 19) LO1 (~BA 19) A rIPS (~BA 7) 0 π -π B Connectivity - / > 0 ππ 0 π -π LO1 (Beta est.) rIPS (Beta est.) 0 1 -1 0 1 -1 0 1 -1 0 1 -1 rIPS (Beta est.) LO1 (Beta est.) Using a psychophysical interaction (PPI) analysis, we investigated whether the functional connectivity between rIPS as a seed region and any other brain site within the occipital cortex was modulated by the pre-stimulus theta phase. The pre- stimulus phase modulated the connectivity between rIPS and the posterior part of the left lateral occipital complex, LO1 (~BA 19). The beta estimates for LO1 and rIPS were correlated when the stimulus was , but not when it was presented at phase 0. A B shown during the optimal phase at -pi or pi Gregor Volberg Institut für Psychologie Universität Regensburg 93040 Regensburg http://www.uni-regensburg.de/psychologie-paedagogik-sport/psychologie-greenlee/team/volberg/index.html Authors GV and HS contributed equally to this work.