Neurofeedback (NF) techniques have gained increasing attention as noninvasive means to regulate brain function for scientific and therapeutic purposes.^1,2 The corresponding methods employ a biofeedback approach that uses real-time information of brain activity to enable self-regulation of a particular neural signal.^1,3 Compared with the traditionally used electroencephalography NF, the use of hemodynamic imaging signals as near-real-time neural feedback is relatively new. The majority of hemodynamic NF studies employ functional magnetic resonance imaging (fMRI) techniques^1,3 and a growing number of studies have demonstrated that fMRI NF-guided regulation of regional brain activity can produce changes in cognitive and emotional processes specifically associated with the target brain region.^1,2,4 Based on accumulating evidence for the behavioral relevance of the NF-induced modulation of brain function, initial studies evaluated the potential of fMRI NF as a promising innovative intervention for psychiatric disorders.⁵

Problematic use of short video (PUSV) refers to a psychological dependency on short‐video applications, characterized by an intense attachment and inability to control usage, resulting in typical addiction symptoms. Although PUSV shares similarities with substance addiction, its clinical presentation exhibits significant differences. Notably, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM‐5), and the International Classification of Diseases, 11th Revision (ICD‐11), have not yet officially classified PUSV as an addiction disorder. However, the profound impact of short‐video platforms on individuals' physical, mental and daily lives necessitates attention to PUSV. To enable more in‐depth and standardized research on this issue, synthesizing and organizing existing studies on its theoretical foundations and mechanisms is crucial. This paper aims to integrate and evaluate existing research on PUSV from four perspectives: qualitative analysis, underlying mechanisms, negative effects and measurement tools, providing a more systematic understanding and approach to this emerging issue.

The mirror neuron system (MNS), including the inferior frontal gyrus (IFG), inferior parietal lobule (IPL) and superior temporal sulcus (STS) plays an important role in action representation and imitation and may be dysfunctional in autism spectrum disorder (ASD). However, it's not clear how these three regions respond and interact during the imitation of different basic facial expressions and whether the pattern of responses is influenced by autistic traits. Thus, we conducted a natural facial expression (happiness, angry, sadness and fear) imitation task in 100 healthy male subjects where expression intensity was measured using facial emotion recognition software (FaceReader) and MNS responses were recorded using functional near-infrared spectroscopy (fNIRS). Autistic traits were measured using the Autism Spectrum Quotient questionnaire. Results showed that imitation of happy expressions produced the highest expression intensity but a small deactivation in MNS responses, suggesting a lower processing requirement compared to other expressions. A cosine similarity analysis indicated a distinct pattern of MNS responses during imitation of each facial expression with functional intra-hemispheric connectivity between the left IPL and left STS being significantly higher during happy compared to other expressions, while inter-hemispheric connectivity between the left and right IPL differed between imitation of fearful and sad expressions. Furthermore, functional connectivity changes during imitation of each different expression could reliably predict autistic trait scores. Overall, the results provide evidence for distinct patterns of functional connectivity changes between MNS regions during imitation of different emotions which are also associated with autistic traits.

Smartphone Addiction is a social issue caused by excessive smartphone use, affecting decision-making processes. Current research on the risky decision-making abilities of smartphone addicts is limited. This study used the functional Near-Infrared Spectroscopy (fNIRS) brain imaging technique and a Sequential Risk-Taking Task experimental paradigm to investigate the decision-making behavior and brain activity of smartphone addicts under varying risk levels. Using a mixed experimental design, the research assessed decision-making ability and brain activation levels as dependent variables across two groups (addiction and control), two risk amounts (high and low), and two outcomes (gain and loss). The study included 42 participants, with 25 in the addiction group and 17 in the control group. Results indicated that risk level significantly impacted the decision-making ability of smartphone addicts, with high-risk levels leading to weaker decision-making ability and increased risk-taking. However, at low-risk levels, decision-making abilities between addicts and healthy individuals showed no significant difference. Furthermore, brain imaging results using fNIRS revealed stronger brain activation in the dorsolateral Prefrontal Cortex (dlPFC) region for smartphone addicts under loss outcome conditions, with no significant differences between the two groups in terms of brain activation at varying risk volumes. These findings are critical in promoting healthy smartphone use, guiding clinical treatment, and advancing brain mechanism research.

Smartphone addiction, emerging from excessive use of smartphones, poses a challenge to inhibitory control functions within society. This research employed transcranial direct current stimulation (tDCS) as an intervention alongside the stop signal task (SST) to explore behavioral distinctions between individuals with smartphone addiction and a non-addicted control group, focusing on the efficacy of tDCS intervention. The participant cohort comprised 80 individuals, divided into an addiction group (39 participants, with 19 receiving active tDCS and 20 receiving sham tDCS) and a control group (41 participants, with 20 receiving active tDCS and 21 receiving sham tDCS), with anodal stimulation applied over the right dorsolateral prefrontal cortex (dlPFC) and cathodal placement over the left arm. The findings indicate that university students struggling with smartphone addiction exhibit reduced inhibitory control compared to their non-addicted peers, while maintaining similar levels of general cognitive control. Remarkably, tDCS interventions were observed to enhance inhibitory control in both groups. Although the improvement in the addiction group appeared more pronounced numerically than in the control group, no significant interaction with group was noted. However, a higher percentage of participants in the smartphone addiction (SA) group exhibited enhanced response inhibition under active tDCS. This study demonstrates the inhibitory control deficits in individuals addicted to smartphones and underscores the potential of tDCS in enhancing response inhibition. It provides a valuable reference for future tDCS research targeting smartphone addiction and highlights the importance of developing healthier smartphone usage habits.

The pervasive use of smartphones, while enhancing accessibility to information and communication, has raised concerns about its potential negative effects on physical and mental health, including the impairment of decision-making abilities. This study investigates the influence of smartphone addiction on decision-making in college students. A sample of 80 individuals aged 17 to 26 was selected and divided into two groups based on their Smartphone Addiction Scale-Short Version (SAS-SV) scores. Participants underwent the Iowa Gambling Task (IGT) to evaluate their decision-making in risky and uncertain conditions, while fNIRS recorded their prefrontal cortex activity. The study found that individuals prone to smartphone addiction tend to make riskier choices in risky situations. However, when faced with decisions based on ambiguity, the smartphone addiction group showed increased brain activity in the dlPFC (specifically in channels 4, 9, and 11) compared to when making risky decisions. Despite this increased brain activation, there was no observable difference in behavior between the addiction-prone and control groups in ambiguous scenarios. Notably, the left dlPFC (e.g., channel 4) exhibited significantly higher activation in the addiction group compared to the control group. Findings suggest that smartphone addiction can detrimentally influence decision-making, behaviorally and neurologically, particularly in uncertain contexts. This study supports the classification of smartphone addiction as a genuine addiction and underscores its significance in psychiatric research. In essence, our research underscores the adverse effects of excessive smartphone use on decision-making processes, reinforcing the necessity to treat smartphone addiction as a pressing public health issue.