Frequency-selective alteration in the resting-state corticostriatal-thalamo-cortical circuit correlates with symptoms severity in first-episode drug-naive patients with schizophrenia
Introduction
Patients with schizophrenia show a lack of integration between thought, emotion, and behavior, cognitive and affective deficits, positive symptoms such as delusions, hallucinations and thought disorder, and negative symptoms such as a flattened affect and volitional disturbances (Camchong et al., 2011, Fornito et al., 2012). The fundamental mechanism of schizophrenia is unclear. In patients with schizophrenia, altered resting-state brain activity has been found extending in regions throughout the brain (Lencz et al., 2003, Shenton et al., 2001). For example, the dopamine (DA) hypothesis of schizophrenia has received the most attention and is thought to be central to the fundamental mechanism (Abi-Dargham and Rodenhiser, 2000, Carlsson and Lindqvist, 1962, Carter and Pycock, 1980, Heinz et al., 1999, Saunders et al., 1998, Weinberger, 1987). Schizophrenia, as a prototypical disorder of brain connectivity, may be the result of hyperactive subcortical and hypoactive cortical DA metabolism (Catani and Mesulam, 2008, Friston and Frith, 1995, Howes and Kapur, 2009, Howes et al., 2009, Volkow et al., 1988).
The physiopathological mechanism of schizophrenia may be frequency-specific. The frequency-specific physiological functions of the human brain occur in the low-frequency range (Buzsaki and Draguhn, 2004, Buzsaki et al., 2013). Distinct oscillations with specific properties and physiological functions generate independent frequency bands (Buzsaki and Draguhn, 2004, Buzsaki et al., 2013). Electroencephalogram (EEG), studies suggest that altered oscillatory neuronal synchronization in the gamma band reflect core neural circuit abnormalities and cognitive deficits in schizophrenia (Cunningham et al., 2006, Spencer et al., 2008, Symond et al., 2005). In addition, review of electrophysiological studies of schizophrenia noted the importance of investigating frequency band abnormalities and interactions in schizophrenia (Moran and Hong, 2011). In this regard, resting-state functional magnetic resonance imaging (fMRI) may be useful, as frequency-specific characteristics in resting-state BOLD signals show an anatomically constrained spatial distribution (Baria et al., 2011). For example, subcortical regions such as the basal ganglia and thalamus show prominent slow-4 (0.027–0.073 Hz) frequencies, while other cortical regions show mainly slow-5 (0.013–0.027 Hz) frequencies (Zuo et al., 2010a). Notable, the basal ganglia and prefrontal cortex have critical roles in the physiopathology of schizophrenia (Howes and Kapur, 2009).
Studies have shown that alteration can vary for different frequency bands. For example, a wavelet transform to decompose fMRI time series into many frequency intervals revealed significantly altered global functional connectivity only in the frequency interval of 0.06–0.125 Hz (Lynall et al., 2010). Moreover, regional homogeneity (ReHo) changes in schizophrenia are widespread and frequency dependent (Yu et al., 2013). Furthermore, alterations of the amplitude of low-frequency fluctuations (ALFF) in schizophrenia vary with different frequency bands (Yu et al., 2014). These studies suggest that the physiological mechanism of schizophrenia may be frequency-specific. Exploring frequency-specific abnormality may provide novel insight in the study of schizophrenia.
Here, we used empirical mode decomposition (EMD) to explore frequency-specific dysfunction of functional connectivity in first-episode drugs-naive patients with schizophrenia. EMD is a pure data-driven method that can divide nonlinear and nonstationary brain signals into different intrinsic frequency bands (Huang et al., 1998). The advantage of EMD is that it avoids the arbitrary selection of a frequency band, as such as an approach may present two limitations, namely the loss of other frequency realms and physiological fluctuations confounding potentially specific frequencies (Wang et al., 2014b). Previous studies have used EMD to analyze fMRI data (Al-Subari et al., 2015, Song et al., 2014, Wang et al., 2014a). In our study, EMD was used to decompose BOLD signals into different intrinsic frequency bands. We hypothesized that frequency-specific altered functional connectivity is a fundamental mechanism of schizophrenia.
Section snippets
Participants
The Ethics Committee of the Second Affiliated Hospital of Xinxiang Medical University approved the study and all patients provided written informed consent for their participation in this study. In the present study, 42 antipsychotic-naive patients with first-episode schizophrenia were recruited during consecutive admission at the Second Affiliated Hospital of Xinxiang Medical University. Participants were right-handed and of Han Chinese ethnicity (patient details are summarized in Table 1).
Altered connections in schizophrenia are frequency specific
Significantly altered connections only survived for the highest frequency band. Within the first frequency band, Connections within the basal ganglia, and between the basal ganglia and SMA, were reduced in patients with schizophrenia. Connections between the right SMA and bilateral cuneus were increased in schizophrenia (Fig. 2; Table 3).
Relationship between altered connections
The altered connections in patients with schizophrenia, but not controls, were significantly correlated (Table 4). For example, a connection linking the left
Discussion
In present study, significantly altered functional connectivity in schizophrenia occurred only in the first frequency band (with a peak spectrum power of 0.06 Hz) using EMD in first-episode drug-naive patients with schizophrenia. In this frequency band, corticostriatal-thalamo-cortical circuits were altered in patients with schizophrenia. In addition, striatal dysfunction had a close relationship with prefrontal dysfunction. Moreover, these altered functional connections in the first frequency
Limitations
The original BOLD signal was band-pass (0.01–0.08 Hz) filtered, removing any respiratory- and cardiac-related oxygenation fluctuations (Lowe et al., 1998), and reducing low-frequency drift and high-frequency physiological noises (Tao et al., 2013). Cardiac and respiratory sources are considered to contribute to oscillations in the frequency interval (0.06–0.125 Hz) (Lynall et al., 2010). However, studies have found that neuronal fluctuations at high and low frequencies are closely associated,
Conclusion
In the present study, we used the EMD method to identify frequency-selective altered corticostriatal-thalamo-cortical circuits in first-episode drug-naive patients with schizophrenia. The patients with schizophrenia showed significantly altered functional connectivity only at a higher frequency band (~ 0.06 Hz). For this frequency, the dysfunction of frontal regions correlated with the dysfunction of striatal and limbic regions. This dysfunctional functional connectivity was associated with the
Funding disclosure
All authors declared no conflicts of interest.
Acknowledgments
The work was supported by the 863 project (2015AA020505 the Natural Science Foundation of China (61125304).
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