An implantable wireless brain-computer interface system developed by a Chinese company being exhibited at the Shanghai Expo Pavilion in 2024 Photo: IC PHOTO

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The mind-body problem has long been a central issue in Western philosophy, particularly within the domains of philosophy of mind and metaphysics. With the rise of intelligent technologies, fields such as computer science, neuroscience, and modern physics have increasingly recognized the cognitive significance of the mind and brain. These disciplines engage in discussions on the ontological nature, fundamental essence, and the relationship between mind and body or brain in psychological processes, turning the mind-body problem into a multidisciplinary research area with philosophy at its core. Among these fields, brain-computer interfaces (BCIs)—a frontier field that integrates insights from computer science, neuroscience, and bioengineering—offer a unique opportunity to revisit the mind-body problem.

Unlike traditional approaches that rely on either a first-person or third-person perspective, BCIs facilitate direct interaction between the psychological and physical realms in a human-computer integrated environment. Practically speaking, BCIs function by detecting and interpreting brain signals, enabling the transmission of cognitive states and intentions to external systems. Conversely, external stimuli can influence neural activity, leading to corresponding behavioral or psychological responses. This interactive mechanism offers strong empirical support for theories of mind-body interaction, while also reigniting debates on the mind-brain identity theory.

Bridging the epistemic gap

To date, no scientific theory has provided a definitive explanation of psychological phenomena like consciousness. This challenge stems from a fundamental distinction between consciousness research and other scientific inquiries: unlike observable natural phenomena, consciousness cannot be studied directly through empirical observation alone. As an integral part of our cognitive experience, consciousness inevitably influences researchers, making it difficult to maintain the detachment of an objective observer. Colin McGinn famously described this epistemic limitation as the “mysterian” nature of consciousness, arguing that the difficulty lies not in external reality but in the inherent constraints of human understanding.

McGinn contends that the intractability of the mind-body problem arises from the cognitive closure of human understanding—consciousness exceeds the structural and conceptual limits of human cognition. Building on this idea, David Chalmers framed the issue as a problem of perspective in consciousness research, distinguishing between “easy problems” (such as explaining the neural correlates, functions, and dynamics of consciousness) and the “hard problem” of consciousness.

Empirical science traditionally adopts a third-person perspective, emphasizing objectivity through behavioral and physiological observations of conscious activity. In contrast, introspection-based methods used by some philosophers and psychologists rely on a first-person perspective. While both approaches provide valuable insights, each has inherent limitations. A purely third-person approach risks overlooking the qualitative aspects of consciousness, which are only accessible through first-person experience. Conversely, first-person methodologies introduce subjective bias, making it difficult to ensure objectivity in research findings. The challenge in consciousness studies is to reconcile these perspectives by developing a scientifically rigorous framework that can systematically process subjective data and establish a unified theory of consciousness.

With its principles and achievements, BCI technology offers a promising avenue for addressing this epistemic gap. BCIs function as communication systems that bypass conventional neuromuscular pathways, directly linking the human brain with external devices through bioelectronic channels. Human brains continuously generate neuroelectric activity, which BCIs can detect, classify, and translate into commands for external systems such as computers. These external devices, in turn, generate feedback signals that are processed by the brain. By analyzing and refining these neural signals, BCIs can create predictive models of human behavior and cognitive states. As a cutting-edge interdisciplinary field, BCI technology aspires to create intelligent cognitive enhancements that seamlessly integrate with the human body, potentially propelling human evolution toward the era of “super-cyborgs.” This represents a bold attempt to break through the enclosed system of the “mysterian” nature and challenge the law of entropy increase. 

Advancing consciousness research

BCI technology originated in medicine and bioengineering, primarily serving as a tool for treatment and motor rehabilitation. Its applications include assisting individuals with motor impairments, replacing damaged biological structures with technologies such as brain-controlled robotic arms and wheelchairs. A notable case occurred in 2019 when a 72-year-old patient with high-level paraplegia in China successfully used BCI technology to control a robotic arm and play mahjong. This marked the beginning of a technologically enhanced lifestyle where intelligent devices operate under the direct control of human consciousness. 

To refine human-machine interactions, BCI systems must continuously monitor psychological states and neural activity, allowing for the identification of internal mechanisms governing external behavior. By analyzing the functional coordination of tens of billions of neurons, researchers assess activity patterns to infer human intentions. As BCI technology advances, its cognitive implications have attracted growing interest from philosophers and scientists. Many believe that the practical progress of BCI technology contributes to mind-brain cognition theories in philosophy and psychology, while these theoretical insights, in turn, provide the foundation for further technological advancements.

Traditional BCI systems, known as non-invasive BCIs, operate outside the human brain. However, tissues surrounding the cerebral cortex add an additional layer that obfuscates signals, leading to inevitable data errors. In contrast, implantable BCIs largely avoid signal degradation by establishing direct neural interfaces. These systems use implanted electrode arrays to record neural activity with high precision. When the brain generates electrical signals, these electrodes capture and transmit data in real time, enabling rapid and detailed decoding of neuroelectric patterns.

By leveraging implantable BCI technology, researchers can integrate first-person and third-person methodologies in consciousness studies, balancing subjective experience with objective measurement and bridging epistemological divides. An ideal implantable BCI system would capture cognitive states such as emotions, feelings, consciousness, and intentions from neural activity and represent them digitally, effectively transforming abstract mental states into tangible entities for observation and analysis. In this integrated human-machine environment, psychological and physical domains would be seamlessly connected, eliminating subjective variability while addressing the limitations of third-person methodologies in studying the mind.

In practice, BCI technology facilitates the externalization of cognitive processes, allowing for the quantitative analysis and real-time decoding of mental activity. By objectifying subjective data, BCI systems provide a methodological foundation for integrating first-person and third-person approaches, ensuring both objectivity and comprehensiveness in consciousness research. Ultimately, BCI technology is expected to evolve into a highly integrated neuro-technological system, enabling precise and comprehensive control over neural interactions. In this state, the biological brain and external devices like computers would collaborate and adapt to one another, allowing individuals to communicate thoughts directly, without reliance on speech or physical movement. This profound shift in cognitive interaction may lead to a future where human thought becomes increasingly transparent.

Ontological and ethical challenges

It is important to recognize that scientific research on BCI technology struggles to fully capture the depth and complexity of the mind. Contemporary natural sciences tend to conceptualize the mind strictly within the physical world, focusing on empirical inquiries into its nature and mechanisms while overlooking its intrinsic values and the influence of social and cultural factors. As a product of nature, human beings are an integral part of the natural world. The biological body must adhere to the laws of biological development, and the mind possesses natural attributes. Therefore, any study of the mind must necessarily engage with the methodologies of the natural sciences.

It is undeniable that BCIs enhance the transparency of the mind, offering a promising avenue for exploring the nature of consciousness. However, the deep integration of human cognition with machine systems also introduces challenges. Some studies suggest that the rapid advancement and widespread application of BCI technology could lead to a fundamental reconfiguration of human identity at the ontological level. Traditionally, clear distinctions have existed between humans and machines. Yet, as BCIs progress toward full brain-machine integration, both human cognition and artificial systems risk being reduced to mere encoded information, blurring or even erasing their defining characteristics. This transformation may give rise to a hybrid human-machine entity that demands a new conceptual framework for understanding identity. 

In other words, the traditional model of data-signal-information could evolve into a complex human-machine-environment intelligence network. Once individuals, either through self-modification or external intervention, merge with machine systems via brain-machine fusion, mental states that were once private and inaccessible may become externalized, objectified, and encoded into computable digital data. Furthermore, machines—traditionally devoid of subjectivity—could acquire human-like qualities when fused with biological cognition, exhibiting attributes such as intentionality and agency, as well as generating emotions, intentions, and purposes like humans. At this stage, the widespread application of BCI technology may necessitate a systematic and unified decoding of human consciousness, potentially requiring a necessary and comprehensive reconstruction of the brain. This could lead to depersonalization, potentially resulting in the dissolution of the intrinsic value of individual consciousness.

From a Marxist perspective, human beings are not merely biological organisms but products of social conditions. Human production and daily life are inherently social, with natural and social attributes integrated within the human experience. As a product of social practice, the human mind is inevitably shaped by cultural and societal values, distinguishing it from animal cognition by embodying individualized characteristics such as emotions, values, and cultural identity. Therefore, the study of human consciousness should be approached with a deep sense of respect and caution, recognizing the dynamic and historically situated interplay between nature and society, universality and individuality. It is essential to avoid reducing the complexities of human freedom and well-being to mere digital codes and abstract symbols.

Wang Feifan is from the School of Marxism at Central China Normal University.

Edited by REN GUANHONG