From mind reading to mind modulation: Applications and mechanisms of neural modulation in brain-computer interfaces from a psychological perspective

doi:10.3724/SP.J.1042.2025.1745

Abstract

Abstract:

Brain-Computer Interface (BCI) technology is rapidly evolving from a rehabilitative tool to a powerful medium for cognitive enhancement and psychotherapeutic intervention. This paper provides a comprehensive psychological analysis of this technological paradigm shift, conceptualized as a progression from “mind reading” to “mind modulation.” It moves beyond a general review of applications to construct a novel theoretical and ethical framework for understanding and guiding the future of BCI in psychology. The central thesis is that to responsibly harness BCI's potential, its development must be deeply integrated with psychological principles governing cognition, emotion, and human autonomy.

A primary contribution of this paper is the synthesis of established psychological theories with the technical mechanisms of BCI. We argue that the efficacy of BCI in cognitive enhancement is grounded in foundational models such as Posner's Attention Network Theory and Baddeley's Working Memory model, which provide neurological targets for intervention. Critically, the long-term benefits of BCI-driven training are explained through the lens of neuroplasticity, where closed-loop neurofeedback acts as a driver for activity-dependent synaptic reinforcement, a process analogous to reward-driven learning. This theoretical integration provides a robust scientific rationale for how BCI systems can precisely target and durably improve core cognitive functions, including attention, memory, and executive control.

While acknowledging the significant clinical potential of BCI in treating disorders like depression, anxiety, and PTSD, this paper foregrounds the associated ethical challenges, particularly the risk of technological dependence. To address this, we introduce a novel quantitative framework: the Technological Dependence Risk Index (TDRI). This multi-dimensional model is designed to systematically assess the potential adverse effects of long-term BCI use on psychological well-being. The TDRI integrates four key dimensions:

(1) Psychological Adaptability (PA): Measures changes in emotional stability and cognitive function after discontinuing BCI use, grounded in emotion regulation and cognitive load theories.

(2) Usage Frequency and Duration (UFD): Quantifies behavioral reliance on the BCI, drawing from technology addiction models to identify patterns of overuse.

(3) Autonomy and Control Perception (ACP): Assesses shifts in an individual’s sense of self-agency and control, based on Self-Determination Theory and theories of locus of control.

(4) Post-BCI Recovery Ability (PRA): Evaluates the capacity to return to baseline cognitive and emotional functioning post-intervention, accounting for individual differences. The composite index (TDRI = w₁·PA + w₂·UFD + w₃·ACP + w₄·PRA) offers a structured, empirically testable tool for researchers, clinicians, and ethicists to monitor and mitigate the risks of psychological dependence, ensuring that BCI serves as an empowering rather than a debilitating tool.

Furthermore, this paper outlines a forward-looking vision for the synergy between BCI and other frontier technologies, specifically Artificial Intelligence (AI) and Virtual Reality (VR), from a psychological standpoint. The integration with AI, particularly deep learning, is presented not merely as a technical enhancement but as a pathway to creating truly adaptive and personalized interventions. AI-driven algorithms can decode complex neural signatures in real time, allowing a BCI system to dynamically adjust therapeutic or training paradigms to an individual's fluctuating cognitive load and emotional state, thereby optimizing efficacy and user engagement. Similarly, the fusion of BCI with VR can create ecologically valid, immersive environments for therapy and cognitive training. For instance, in PTSD treatment, a VR-BCI system can modulate the intensity of an exposure scenario based on real-time neural markers of anxiety, creating a therapeutic window that is both safe and effective.

In conclusion, this paper contributes a unique psychological perspective on the advancement of BCI technologies. By proposing the “mind reading to mind modulation” framework, introducing the quantitative TDRI model, and systematically linking BCI design to cognitive and emotional theories, it offers a blueprint for future research and development. The ultimate goal is to foster a new generation of BCI systems that are not only technologically powerful but also human-centered, ethically sound, and psychologically empowering, ensuring a sustainable and beneficial integration of mind and machine.

Key words: brain-computer interface, cognitive enhancement, psychotherapy, neural plasticity, neural decoding, technological dependence risk index

CLC Number:

B841

CHEN Zhaojie, WANG Guofang. From mind reading to mind modulation: Applications and mechanisms of neural modulation in brain-computer interfaces from a psychological perspective[J]. Advances in Psychological Science, 2025, 33(10): 1745-1765.

Figures/Tables 2

References 141

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