Parametric study of EEG sensitivity to phase noise during face processing

<b>Background: </b> The present paper examines the visual processing speed of complex objects, here faces, by mapping the relationship between object physical properties and single-trial brain responses. Measuring visual processing speed is challenging because uncontrolled physical differences that co-vary with object categories might affect brain measurements, thus biasing our speed estimates. Recently, we demonstrated that early event-related potential (ERP) differences between faces and objects are preserved even when images differ only in phase information, and amplitude spectra are equated across image categories. Here, we use a parametric design to study how early ERP to faces are shaped by phase information. Subjects performed a two-alternative force choice discrimination between two faces (Experiment 1) or textures (two control experiments). All stimuli had the same amplitude spectrum and were presented at 11 phase noise levels, varying from 0% to 100% in 10% increments, using a linear phase interpolation technique. Single-trial ERP data from each subject were analysed using a multiple linear regression model. <b>Results: </b> Our results show that sensitivity to phase noise in faces emerges progressively in a short time window between the P1 and the N170 ERP visual components. The sensitivity to phase noise starts at about 120–130 ms after stimulus onset and continues for another 25–40 ms. This result was robust both within and across subjects. A control experiment using pink noise textures, which had the same second-order statistics as the faces used in Experiment 1, demonstrated that the sensitivity to phase noise observed for faces cannot be explained by the presence of global image structure alone. A second control experiment used wavelet textures that were matched to the face stimuli in terms of second- and higher-order image statistics. Results from this experiment suggest that higher-order statistics of faces are necessary but not sufficient to obtain the sensitivity to phase noise function observed in response to faces. <b>Conclusion: </b> Our results constitute the first quantitative assessment of the time course of phase information processing by the human visual brain. We interpret our results in a framework that focuses on image statistics and single-trial analyses

Attentional modulations of the early and later stages of the neural processing of visual completion

The brain effortlessly recognizes objects even when the visual information belonging to an object is widely separated, as well demonstrated by the Kanizsa-type illusory contours (ICs), in which a contour is perceived despite the fragments of the contour being separated by gaps. Such large-range visual completion has long been thought to be preattentive, whereas its dependence on top-down influences remains unclear. Here, we report separate modulations by spatial attention and task relevance on the neural activities in response to the ICs. IC-sensitive event-related potentials that were localized to the lateral occipital cortex were modulated by spatial attention at an early processing stage (130–166 ms after stimulus onset) and modulated by task relevance at a later processing stage (234–290 ms). These results not only demonstrate top-down attentional influences on the neural processing of ICs but also elucidate the characteristics of the attentional modulations that occur in different phases of IC processing

Neuroanatomical Circuitry Associated with Exploratory Eye Movement in Schizophrenia: A Voxel-Based Morphometric Study

Schizophrenic patients present abnormalities in a variety of eye movement tasks. Exploratory eye movement (EEM) dysfunction appears to be particularly specific to schizophrenia. However, the underlying mechanisms of EEM dysfunction in schizophrenia are not clearly understood. To assess the potential neuroanatomical substrates of EEM, we recorded EEM performance and conducted a voxel-based morphometric analysis of gray matter in 33 schizophrenic patients and 29 well matched healthy controls. In schizophrenic patients, decreased responsive search score (RSS) and widespread gray matter density (GMD) reductions were observed. Moreover, the RSS was positively correlated with GMD in distributed brain regions in schizophrenic patients. Furthermore, in schizophrenic patients, some brain regions with neuroanatomical deficits overlapped with some ones associated with RSS. These brain regions constituted an occipito-tempro-frontal circuitry involved in visual information processing and eye movement control, including the left calcarine cortex [Brodmann area (BA) 17], the left cuneus (BA 18), the left superior occipital cortex (BA 18/19), the left superior frontal gyrus (BA 6), the left cerebellum, the right lingual cortex (BA 17/18), the right middle occipital cortex (BA19), the right inferior temporal cortex (BA 37), the right dorsolateral prefrontal cortex (BA 46) and bilateral precentral gyri (BA 6) extending to the frontal eye fields (FEF, BA 8). To our knowledge, we firstly reported empirical evidence that gray matter loss in the occipito-tempro-frontal neuroanatomical circuitry of visual processing system was associated with EEM performance in schizophrenia, which may be helpful for the future effort to reveal the underlying neural mechanisms for EEM disturbances in schizophrenia

Complementary fMRI and EEG evidence for more efficient neural processing of rhythmic vs. unpredictably timed sounds

The brain's fascinating ability to adapt its internal neural dynamics to the temporal structure of the sensory environment is becoming increasingly clear. It is thought to be metabolically beneficial to align ongoing oscillatory activity to the relevant inputs in a predictable stream, so that they will enter at optimal processing phases of the spontaneously occurring rhythmic excitability fluctuations. However, some contexts have a more predictable temporal structure than others. Here, we tested the hypothesis that the processing of rhythmic sounds is more efficient than the processing of irregularly timed sounds. To do this, we simultaneously measured functional magnetic resonance imaging (fMRI) and electro-encephalograms (EEG) while participants detected oddball target sounds in alternating blocks of rhythmic (e.g., with equal inter-stimulus intervals) or random (e.g., with randomly varied inter-stimulus intervals) tone sequences. Behaviorally, participants detected target sounds faster and more accurately when embedded in rhythmic streams. The fMRI response in the auditory cortex was stronger during random compared to random tone sequence processing. Simultaneously recorded N1 responses showed larger peak amplitudes and longer latencies for tones in the random (vs. the rhythmic) streams. These results reveal complementary evidence for more efficient neural and perceptual processing during temporally predictable sensory contexts

A human intracranial study of long-range oscillatory coherence across a frontal–occipital–hippocampal brain network during visual object processing

Visual object-recognition is thought to involve activation of a distributed network of cortical regions, nodes of which include the lateral prefrontal cortex, the so-called lateral occipital complex (LOC), and the hippocampal formation. It has been proposed that long-range oscillatory synchronization is a major mode of coordinating such a distributed network. Here, intracranial recordings were made from three humans as they performed a challenging visual object-recognition task that required them to identify barely recognizable fragmented line-drawings of common objects. Subdural electrodes were placed over the prefrontal cortex and LOC, and depth electrodes were placed within the hippocampal formation. Robust beta-band coherence was evident in all subjects during processing of recognizable fragmented images. Significantly lower coherence was evident during processing of unrecognizable scrambled versions of the same. The results indicate that transient beta-band oscillatory coupling between these three distributed cortical regions may reflect a mechanism for effective communication during visual object processing