Cerebrovascular accidents and depression contribute significantly to the global economic burden. Depression is one of the causes of disability worldwide [1], and stroke is marked third in the burden of disease [2]. Mood disorders, including post-stroke depression (PSD) and post-stroke anxiety (PSA), are mental complications of stroke [3], affecting approximately 30% of stroke survivors. Symptoms of post-stroke depression and anxiety arise from damage to the endocrine, nervous, and cardiovascular systems of stroke patients, negatively impacting their rehabilitation and quality of life. Post-stroke patients often experience aphasia and cognitive impairment, making it challenging for healthcare professionals and family members to comprehend their emotions and interests. Therefore, it brings great challenges to the diagnosis, evaluation, and treatment of mood disorder symptoms in stroke patients, and currently, limited literature is available to address this aspect [4]. Scholars have different opinions on the pathogenesis of PSD, which may be related to the general factors, lesion location, and disease-related factors [4]. Previous research had indicated that the prefrontal cortex, a crucial nerve center in the brain regulating thinking and behavior, was often damaged in patients with depression [5]. Wei et al. reported a significant association between right hemisphere stroke and the incidence of depression within 1–6 months of stroke [6]. Robinson's research showed a correlation between PSD and frontal lobe lesions [7]. In addition, the occurrence of PSD might be related to changes in the neurotransmitter system related to the frontal lobe/temporal lobe-basal ganglia-ventral brainstem. The basal ganglia has been shown to play an important role in the cortex and cortical circuits, including the frontal cortex, the frontal lobe motor network, and frontal-parietal-occipital nerve dysfunction in stroke which may be caused by basal ganglia disorders [8]. When the prefrontal cortex and basal ganglia experience infarction, the disruption in neurotransmitters related to emotional circuits and pathways can lead to depressive disorders.
The brain forms a highly complex network with interconnected regions, each governing specific tasks. This network ensures precise coordination across multiple spatiotemporal scales [9]. Connectomics provides a powerful analytical framework for localizing pathology, tracking disease transmission patterns, and predicting regions to be subsequently affected. Therefore, connectivity is at the core of understanding the pathology of neurological diseases. Clinical symptoms in patients may arise from disruptions in neural connectivity. Current research suggested that the destruction of brain functional connectivity was more important than the location of the lesion for PSD [10, 11]. Depressive symptoms do not arise from dysfunction in a single brain area; rather, they result from alterations in the "depression network," comprising connections among the neocortex, cingulate, limbic system, striatum, and thalamus [12]. Studies have suggested that symptoms of depressive disorders in stroke patients might be attributed to overactivation of the right parietal lobe, the posterior region of the temporal lobe, and central areas. It is well known that the frontal lobe can regulate emotion and cognition. Studies have shown that the activation of the frontoparietal cortex is reduced in the performance of working memory in elderly patients with depression, associated with symptoms such as anhedonia or blunted affect [13]. Changes in Alpha power observed in patients with major depressive disorder may reflect the activation decline in disease-associated regions such as the prefrontal cortex [14]. Some studies have employed functional magnetic resonance imaging (fMRI) to investigate the relationship between negative emotions, such as, anxiety and depression, and the resting state brain network in patients with subacute stroke. These investigations have shown associations between patients with PSA and PSD and alterations in the resting state brain network. Additionally, the prefrontal cortex and cingulate cortex are related to the degree of depressive symptoms [15, 16]. Disturbances in functional brain networks provide a comprehensive model to elucidate the biological mechanisms underlying depression. In post-stroke patients, aberrant connectivity and pronounced neural plasticity associated with negative emotional symptoms might drive the pathogenesis of the disease. This may be particularly evident in brain regions where symptoms of "disconnect" manifest.
Due to continuous technological advancements, electroencephalography (EEG), a non-invasive brain stimulation technique, has become pivotal in brain research [17]. EEG signals come from post-synaptic excitatory or inhibitory potentials, which are generated by action potentials moving through the dendrites of pyramidal neurons in the outer layer of the cortex [18]. Compared with other neurophysiological techniques, EEG offers high temporal resolution and is characterized by its ease of operation, accessibility, and cost-effectiveness [18, 19]. EEG is increasingly utilized to assess human cognition, and serve as an objective biomarker for the early diagnosis and ongoing evaluation of cognitive impairments. EEG can detect changes in the power spectrum and network in patients with brain injuries. Resting-state EEG, recorded during quiet wakefulness, is valuable in clinical studies. It facilitates the extraction of biological markers that elucidate the mechanisms of cortical neuronal synchronization [20]. Additionally, two primary methods have been proposed for studying brain networks: measuring “effective connectivity” and “functional connectivity.” Functional connectivity is a potent tool for characterizing various brain functional states, such as those in healthy individuals or those with neurological or mental disorders, each exhibiting distinct features [21]. As a measure of neural synchrony, functional connectivity refers to the statistical interdependence between time-series data recorded from different brain regions and can be identified as two parameters: correlation and coherence. Connectivity analysis allows us to understand the functional systemic state and neural plasticity of complex brain networks. Doruk et al. found that the Delta, Theta, Alpha, and Beta interhemispheric coherence decreased in patients with depression, possibly because pathological conditions that affected the integrity of neural tissue could cause changes in the structure and function of the damaged area. Doruk et al. posited that observed the reduction in cerebral interhemispheric connectivity is indicative of post-stroke anatomical, adaptive and maladaptive changes in neural connections between damaged and undamaged cerebral hemispheres [22]. Studies have investigated the functional connectivity of amygdala subregions in patients with major depression, showing that the functional connectivity between the right central medial, lateral basal, and right middle frontal gyrus may be responsible for the neurobiological mechanism of anxiety-induced depression [23].
Transcranial magnetic stimulation (TMS) is widely used in evidence-based treatments for depression and post-stroke depression symptoms. Therefore, transcranial magnetic stimulation therapy has been studied extensively. TMS is a non-invasive brain stimulation technique that specifically modulates the human nervous system regarding to cognitive and behavioral functions. Repetitive transcranial magnetic stimulation (rTMS) and intermittent theta burst stimulation (iTBS) targeting specific cortical regions can modulate neural circuits and improve symptoms and outcomes in patients with psychiatric disorders and abnormal behaviors, especially guided by resting-state and task-related neuroimaging measures [24]. iTBS induces plasticity of specific brain regions in patients with depression through accelerated, high-dose, functional connectivity-oriented targeted stimulation. iTBS has shown a measurable therapeutic impact on depression in certain cases. An animal model study has demonstrated effectiveness in inducing neural synaptic plasticity using high-frequency theta bursts stimulation protocols [25]. iTBS regulates a balance between the GABAergic and glutamatergic systems. However, the dysregulation of this system is a key feature of depression. Compared to sham stimulations in healthy individuals, the GABAergic to glutamatergic neurons ratio decreased, and effective connectivity of the right anterior insula, as well as the dorsolateral prefrontal lobe (DLPFC), increased after iTBS, which may reveal a possible mechanism of iTBS in the pathophysiology of depression [26, 27]. In patients with major depressive disorder, iTBS primarily modulates the anterior cingulate circuit, including the anterior cingulate cortex (ACC) and medial prefrontal cortex (PFC) (i.e., two theta-prominent brain regions). It has been demonstrated that frontal theta activity, recorded from the scalp, increases during cognitive tasks and is associated with enhanced ACC glucose uptake. This evidence can be used to predict better antidepressant efficacy [28, 29].
The combination of TMS with EEG (TMS-EEG) has garnered interest as a tool to record immediate and downstream cortical responses following magnetically targeted stimulation [30]. Studies using TMS-EEG have demonstrated that fronto-midline Theta power and Theta connectivity show good potential for predicting responses to rTMS treatment for depression [31]. A study of enhanced resting state EEG Gamma power and Theta-Gamma coupling (TGC) after high-frequency rTMS in the left dorsolateral prefrontal lobe of patients with depression suggested that resting state Gamma power and TGC may represent potential biomarkers of depression improvement associated with rTMS therapeutic efficacy [32]. TMS-EEG can reveal physiological activity in specific brain regions, and provides insights into the cross-sectional structure and functional connectivity of electrodes, and employ brief magnetic pulses to momentarily activate targeted cortical areas. At the same time, it captures neuronal responses through electrodes on the scalp [33], which allows us to gain a unique insight into cortical responses in stimulated regions and the wider cortical network. TMS-EEG offers a direct, objective, and non-invasive means to characterize various properties of the cerebral cortex, including excitatory and inhibitory responses, oscillatory patterns, and functional connections [24]. Therefore, TMS-EEG analysis provides a better understanding of neural network alterations and introduces a novel diagnostic and therapeutic approach for post-stroke negative emotional symptoms.
The cerebellum is small in size, but it contains more than 70% of the neurons in the brain and plays a key role in many brain functions and injuries, including sensory, motor, cognitive, and emotional processes. The cerebellum’s repetitive modular cortical structure suggests it plays a fundamental role in many aspects of brain function. It has been suggested that the cerebellum may play a fundamental role by regulating the timing necessary for temporal dynamics in information processing. Simple and complex spikes in the Purkinje cells of the cerebellar cortex regulate the temporal patterns related to the function of the inferior olivary nucleus [34]. However, few studies have explored the relationship between post-stroke negative emotional symptoms and brain networks following iTBS over the cerebellum. Therefore, our group conducted research using TMS-EEG to investigate the temporal dynamics between negative emotional symptoms and brain networks in stroke patients who underwent iTBS over the cerebellum. Our research objectives are: (1) to examine the temporal dynamics in the power spectrum and functional connectivity of post-stroke patients following iTBS over the cerebellum and (2) to determine if iTBS over the cerebellum alters the negative emotional symptoms in these patients.