Increased local connectivity of brain functional networks during facial processing in schizophrenia: evidence from EEG data - PubMed (original) (raw)

Increased local connectivity of brain functional networks during facial processing in schizophrenia: evidence from EEG data

Tianyi Yan et al. Oncotarget. 2017.

Abstract

Schizophrenia is often considered to be a disconnection syndrome. The abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. The present study investigated event-related functional connectivity networks to compare facial processing in individuals with and without schizophrenia. Faces and tables were presented to participants, and event-related phase synchrony, represented by the phase lag index (PLI), was calculated. In addition, cortical oscillatory dynamics may be useful for understanding the neural mechanisms underlying the disparate cognitive and functional impairments in schizophrenic patients. Therefore, the dynamic graph theoretical networks related to facial processing were compared between individuals with and without schizophrenia. Our results showed that event-related phase synchrony was significantly reduced in distributed networks, and normalized clustering coefficients were significantly increased in schizophrenic patients relative to those of the controls. The present data suggest that schizophrenic patients have specific alterations, indicated by increased local connectivity in gamma oscillations during facial processing.

Keywords: dynamic brain network; facial processing; graph theory; phase synchrony; schizophrenia.

PubMed Disclaimer

Conflict of interest statement

CONFLICTS OF INTEREST The authors declare there are no conflicts of interest regarding the publication of this paper.

Figures

Figure 1

Figure 1. Time courses of connectivity strength

Time courses of the gamma-band connectivity strength calculated by the PLI between the Fz and Pz electrode sites averaged across subjects. Values are standard deviations from the 150 ms baseline.

Figure 2

Figure 2. Topography

Topography of phase synchrony for all conditions, baseline and time window, respectively, in the 150–300 ms gamma band. Top row, healthy controls. Middle row, patients with schizophrenia. Bottom row, difference map. In the map of the healthy controls and the map of the schizophrenia patients, synchrony between electrodes is indicated by lines, which were drawn only if the synchrony value was beyond the distribution of shuffled data sets (p < 0.05). In the difference maps, functional connectivity differences between the patients and the controls involve a decreased distributed network of connections (black edges) for the frontal, central parietal, temporal and occipital areas.

Figure 3

Figure 3. Normalized clustering coefficient differences

Bar graphs display the mean (standard error) Event -related normalized clustering coefficients in healthy controls and schizophrenia patients in the –150∼0 ms baseline time window and the 150∼300 ms active time window.

Figure 4

Figure 4. Stimuli

Examples of faces and objects, as well as the target flowers used as stimuli.

Figure 5

Figure 5. Schematic of the network-based statistics analysis

(A) Schematic of the comparison of functional connectivity networks in healthy participants and schizophrenia patients, as calculated by the PLI, in the upright face condition. (B) A _t_-test statistic was computed at each network edge, resulting in a matrix of statistical values. (C) This matrix was then thresholded using a primary, component-forming threshold (T = 1.7, corresponding to p < 0.01) to yield a thresholded and binarized statistical matrix. (D) The connected components of this thresholded statistical matrix were identified, and the size of each was computed; this component comprises 22 edges. (E) The control and patient subjects of were shuffled randomly 5000 times, and steps (b-d) were repeated. (F) At each iteration, the size of the largest component was stored to generate an empirical null distribution of maximal component sizes. (G) The observed size of the component illustrated in (d) corresponded to P = 0.0150. The functional connectivity differences between the patients and the controls involve a distributed network of connections (d) for the frontal, central parietal, temporal and occipital areas.

References

    1. Marwick K, Hall J. Social cognition in schizophrenia: a review of face processing. British Medical Bulletin. 2008;88:43–58. -PubMed
    1. Walther S, Federspiel A, Horn H, Bianchi P, Wiest R, Wirth M. Encoding deficit during face processing within the fusiform face area in schizophrenia. Psychiatry Research. 2009;172:184. -PubMed
    1. Onitsuka T, Niznikiewicz MA, Spencer KM, Frumin M, Kuroki N, Lucia LC, Shenton ME, Mccarley RW. Functional and structural deficits in brain regions subserving face perception in schizophrenia. American Journal of Psychiatry. 2006;163:455. -PMC -PubMed
    1. Habel U, Chechko N, Pauly K, Koch K, Backes V, Seiferth N, Shah NJ, Stöcker T, Schneider F, Kellermann T. Neural correlates of emotion recognition in schizophrenia. Schizophrenia Research. 2010;122:113–23. -PubMed
    1. Li H, Chan RC, Mcalonan GM, Gong QY. Facial emotion processing in schizophrenia: a meta-analysis of functional neuroimaging data. Schizophrenia Bulletin. 2010;36:1029. -PMC -PubMed

LinkOut - more resources