Multi-modal neuroimaging technique: Innovations and applications

In the last two decades, neuroimaging techniques have made quite a splash in not only our general understanding of healthy brain working mechanisms but also in gaining a better understanding of cognitive system alterations in brain disorders, such as Alzheimer’s disease (AD), Parkinson’s disease (PD) and schizophrenia (SZ), bipolar disorder (BD), etc. Multi-modal neuroimaging techniques usually includes electroencephalography (EEG), magnetic resonance imaging (MRI), magnetoencephalography (MEG), positron emission tomography (PET), near-infrared spectroscopy (NIRS). Compared with single-modal neuroimaging technique, multi-modal neuroimaging techniques should significantly contribute to the brain working mechanisms, and promote to identify more valuable information of potential neurobiological markers, and improve the diagnosis accuracy of neurological diseases.

The special session includes five papers contributed by experts who have been studying the conceptual and methodological innovations as well as practical applications of the multi-modal neuroimaging techniques.

Niu and his colleague [1] focused on how the network complexity changes driving spontaneous functional MRI (fMRI) activity in SZ and BD patients. Functional entropy (FE) is a novel way of measuring the dispersion (or spread) of functional connectivities inside the brain. The FE of SZ and BD patients was considerably lower than that of normal control (NC). At the intra-module level, the FE of SZ was substantially higher than that of BD in the cingulo-opercular network. Moreover, a strong negative association between FE and clinical measures was discovered in patient groups. This paper proposed that network connectivity’s complexity analyses using FE can provide important insights for the diagnosis of mental illness.

Top-down attention mechanisms require the selection of specific objects or locations; however, the brain mechanism involved when attention is allocated across different modalities is not well understood. Guan and his colleague [2] define the neural mechanisms underlying divided and selective spatial attention by fMRI and Posner paradigm with concurrent audiovisual. They explored the audiovisual top-down allocation of attention and observed the differences in neural mechanisms under endogenous attention modes, which revealed the differences in cross-modal expression in visual and auditory attention under attentional modulation. Specially, the differences in the activation level of the frontoparietal network, visual/auditory cortex, the putamen and the salience network under different attention conditions. In addition, the differences in Granger causality (GC) connectivity between visual and auditory selective tasks reflected the visual dominance effect under spatial attention.

Parkinson’s disease is a common neurodegenerative disorder, typically characterized by motor dysfunctional symptoms, due to the cortico–subcortical circuit dysfunction. Transcranial electrical stimulation is a common form of noninvasive brain stimulation technique, including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), which can improve the motor symptomsin in PD. Dr. Liu and his group [3] investigated changes in ortico–subcortical spatiotemporal dynamics to explore the treatment mechanisms of tACS in PD patients. The pattern haracterized by the de-activation of the visual network and the activation of the thalamus showed a significantly low amplitude in the patients with PD than in NCs, and this amplitude increased after tACS treatment. Furthermore, the co-occurrence of cortico–subcortical CAPs was significantly higher in patients with PD than in NCs and decreased after tACS treatment.

Brain asymmetry, involving structural and functional differences between the two hemispheres, is a major organizational principle of the human brain. Elucidating left-right differences of the hemispheric network provides opportunities for brain asymmetry exploration. Wang et al. [4] review examines the asymmetry in the hemispheric white matter and functional network to assess health and brain disorders. This review suggests that the hemispheric network is highly conserved for measuring human brain asymmetries and has potential in the study of the cognitive system and brain disorders.

Biofeedback improves motor and nonmotor functions of patients by regulating abnormal EEG, electrocardiogram (ECG), photoplethysmography (PPG), electromyography (EMG), respiration (RSP), or other physiological signals. Given that multimodal signals are closely related to PD states, Shi et al. [5] explored the clinical effect of multimodal biofeedback on PD patients. The EEG group significantly improved motor symptoms and increased Berg balance scale scores by regulating β band activity; the multimodal group significantly improved nonmotor symptoms and reduced Hamilton rating scale for depression scores by improving θ band activity. Their results demonstrated that multimodal biofeedback can improve the clinical symptoms of PD.

In summary, this special issue covers a collection of studies by of EEG, fMRI, and also innovated multimodal biofeedback and brain stimulation technique. These studies would significantly contribute to the fundamental mechanisms of brain, such as attention, integration of multisensory, brain asymmetry; and deep understand the diagnosis and treatment of neurological diseases, such as PD, schizophrenia and bipolar disorder patients. We hope our readers will learn something from this special issue, and we would also like to thank all the authors for their valuable contributions to this special issue.