1. Temporal dynamics of spatial phase congruency sensitivity in human visual cortex Linda Henriksson 1,2, Aapo Hyvärinen 3 and Simo Vanni 1 1 Brain Research Unit and AMI Centre, O.V. Lounasmaa Laboratory, Aalto University, FINLAND 2 MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge UK 3 Dept of Mathematics & Statistics, Dept of Computer Science, University of Helsinki, FINLAND Introduction Edges are perceived at locations of local phase alignment across a range of spatial frequencies, i.e., at locations of high phase congruency (Morrone and Burr 1988, Kovesi 1999). In primary visual cortex (V1), a typical neuron responds to a narrow range of spatial frequencies. Detection of phase congruency requires pooling of frequency information across multiple spatial scales. Where are spatial frequency components combined in the human visual system? Henriksson et al. 2009: fMRI study Stronger response for congruent than random phase stimuli in several visual areas Phase congruency selectivity increased along ventral stream areas, that is from V1 to pFus (an object-selective area around posterior fusiform gyrus) Previous studies (Perna et al. 2008, Henriksson et al. 2009) used fMRI to show the phase congruency sensitivity in human visual cortex, and thus were unable to separate feedforward and feedback effects in V1. In the present study, our main aim was to find out whether the phase congruency sensitivity starts early at the level of V1 or has its origin in a higher-level visual area (e.g., in pFus). To address this question, we used magnetoencephalography (MEG) and cortically-constrained source analysis. Methods Stimuli Compound grating stimuli with 5 spatial frequency components: f, 3f, 5f, 7f, 9f, where f = 0.4 cyc/deg 10 congruent phase stimuli 10 random phase stimuli Stimulus on-time 300 ms, inter-trial-interval 3.4 s Grating orientation changed between trials Left lower visual field quadrant, mean eccentricity 7.5 ⁰ Subjects and data acquisition 10 healthy subjects with normal or corrected-to-normal vision 306-channel whole-head MEG device (Elekta Neuromag) at Aalto Univ. MEG data sampled at 600 Hz, band-pass filtered between 0.03- 200 Hz (f)MRI data with 3T scanner (General Electric) at Aalto Univ. Data analysis Preprocessing with MaxFilter (Elekta Neuromag) to suppress magnetic interference of external sources, to compensate for head movement, and to transform each individual's data into a common head position Evoked responses averaged time-locked to the stimulus onset, baseline corrected from -200 ms to 0 ms and low-pass filtered at 45 Hz using MNE Suite (http://www.martinos.org/mne/) Sources estimated using cortically constrained minimum-norm estimate (MNE) using the MNE Suite (http://www.martinos.org/mne/) MNE current estimates extracted from pre-defined ROIs (V1 and pFus) Cortical surface-based group-averaging of source estimates using Freesurfer (http://surfer.nmr.mgh.harvard.edu/) Results First difference in the evoked responses 60 ms after stimulus onset First responses were observed around 50 ms after the stimulus onset in the posterior sensors close to the midline. The first difference between the responses to the two stimulus categories was observed in the same sensors starting around 60 ms after the stimulus onset. At longer latencies, a larger response for the congruent phase stimuli was observed in multiple occipito- temporal sensors. Early sensitivity to phase congruency in V1, later in pFUS Source currents extracted from two a priori defined ROIs showed significant differences between the two stimulus categories. Stronger response for the phase congruent stimuli were first observed in V1, starting already around 60 ms after the stimulus onset, and only later (~180 ms) in pFus. Activity distributions Group averages of the noise-normalized estimates (dSPM) confirmed that the activity started in the medial surface of the occipital cortex, approximately where V1 is located, and later spread to lateral and ventral occipito-temporal cortex with a wide-spread enhancement of the activity for the congruent phase stimuli. Conclusion s We found an early modulation of the neuromagnetic responses to spatial phase congruency, and localized this effect to V1. This finding is in agreement with the few electrophysiological animal studies on the sensitivity of V1 neurons to features emerging from phase regularities in natural images (Mechler et al. 2002, Felsen et al. 2005), and is also consistent with the Local Energy Model of feature detection (Morrone and Burr 1988). Taken together, this suggests that the early extraction of phase congruency in V1 could form the basis of efficient detection of natural broadband edges in the human visual system. References: Felsen G, Touryan J, Han F, Dan Y (2005) Cortical sensitivity to visual features in natural scenes. PLoS Biol 3:e342. Henriksson L, Hyvärinen A, Vanni S (2009) Representation of cross-frequency spatial phase relationships in human visual cortex. J Neurosci 29:14342- 14351. Kovesi P (1999) Image Features From Phase Congruency. Videre: A Journal of Computer Vision Research 1. Mechler F, Reich DS, Victor JD (2002) Detection and discrimination of relative spatial phase by V1 neurons. J Neurosci 22:6129-6157. Morrone MC, Burr DC (1988) Feature detection in human vision: a phase-dependent energy model. Proc R Soc Lond B Biol Sci 235:221-245. Perna A, Tosetti M, Montanaro D, Morrone MC (2008) BOLD response to spatial phase congruency in human brain. Journal of Vision 8(10):15:1-15.