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The decade that has passed since the original position paper offers a useful vantage point for assessing not only what neuroscience has achieved, but also what kinds of questions it has learned to ask. The authors of the anniversary review emphasize that technical progress and conceptual progress are not the same thing, and their distinction deserves careful unpacking. Instruments can improve by orders of magnitude while the explanatory frameworks applied to the resulting data remain essentially unchanged. This is precisely the situation they describe: recording techniques, manipulative methods, and data infrastructures have advanced dramatically, yet many research programs continue to operate within reductionist assumptions that treat mental phenomena as straightforwardly derivable from molecular or cellular events. The gap between data volume and conceptual sophistication is not a minor inconvenience; it shapes which hypotheses are formulated, which findings are considered explanatory, and which clinical applications are promised to funders and patients.

One way to understand this gap is through the notion of system levels. A neuron, a neural circuit, a whole brain, an embodied organism, and a socially embedded person are not simply larger and larger versions of the same kind of thing. Each level has its own characteristic entities, regularities, and descriptive vocabulary. What counts as an explanation at the molecular level—say, the kinetics of a receptor protein—does not automatically translate into an explanation at the level of attention, memory, mood, or decision-making. The authors argue that failure to acknowledge these differences, and the complex interactions between levels, is a persistent weakness in the field. Domain-specific languages compound the problem: terms such as “representation,” “computation,” “regulation,” or “information” carry different meanings in molecular biology, systems neuroscience, psychology, and philosophy, and uncritical translation between them can create the illusion of integration where only juxtaposition exists.

The institutional analysis in the review adds an important dimension that is often absent from purely methodological discussions. Large-scale projects in neuroscience, sometimes described as “big science,” share features with big science in physics: major broadly accepted aims, promises of application, multiple participating institutions, standardized data formats, industrial-style workflows, and a focus on overarching goals rather than individual contributions. These features enable unprecedented scale and coordination, but they also concentrate decisions about research direction in the hands of funding bodies whose criteria include political and commercial considerations. The authors note that initiatives such as the “decade of the brain” and the “human brain project” raised expectations, particularly regarding clinical applications, that the results did not fully meet. This is not an argument against large-scale science; rather, it is a reminder that resource allocation decisions embed assumptions about what neuroscience is and what it can deliver, and those assumptions themselves merit critical scrutiny before commitments are made.

The emergence of large-scale digital infrastructures and curated data collections represents a genuinely novel development in this landscape. Well-organized corpora of neuroscientific data allow researchers to test hypotheses across datasets that no single laboratory could have produced, and they open possibilities for meta-analyses and computational modeling at scales previously unimaginable. Yet the authors point out that such resources, while powerful, do not by themselves resolve conceptual questions. A dataset assembled from many laboratories reflects the measurement choices, paradigms, and population characteristics of those laboratories, and aggregating it does not automatically yield multi-level understanding. Big data can reveal correlations and regularities, but the interpretation of those regularities—what they mean, at which level, and for whom—remains a theoretical task that no amount of data volume can perform on its own.

This is where the authors’ call for an interdisciplinary neurophilosophy becomes concrete rather than abstract. They are careful to specify that the task is not merely collaboration between philosophers and neuroscientists, in which philosophers comment on finished work from the outside. Instead, they advocate the development of a critical philosophical stance within the neurosciences themselves. This means that practicing neuroscientists should be equipped and encouraged to reflect on the nature of their explanations, the assumptions embedded in their models, and the interfaces between their level of analysis and others. Philosophy of mind and philosophy of science, on this view, are not ornamental additions but constitutive parts of a mature neuroscience. The demand for institutionalization is significant: without dedicated positions, curricula, journals, and funding lines, such reflection remains dependent on the incidental interests of individuals and cannot accumulate into a stable tradition.

The review’s turn to complex systems science provides the positive methodological program that complements this critical stance. Complex systems research studies how many interacting components give rise to collective phenomena that cannot be predicted from the properties of the components in isolation. Concepts such as self-organization, emergence, nonlinearity, feedback, and multi-scale dynamics offer a vocabulary for describing how molecular, cellular, network, organismic, and social processes can each contribute to mental phenomena without any single level being privileged as the “real” cause. The authors suggest that systemic approaches are particularly helpful for integrating interdisciplinary knowledge and for developing new strategies for modeling multi-level relations. In the mind sciences, this implies moving beyond linear causal chains toward models in which circular causality, reciprocal determination, and context-dependence are built in from the start rather than treated as complications to be controlled away.

A systems perspective also changes what counts as a disorder. In psychiatry, conditions such as depression, schizophrenia, or addiction involve disturbances that manifest simultaneously at biological, psychological, and social levels. A purely neurobiological account may identify correlates of symptom dimensions, but the lived experience of illness, the meaning of symptoms to the person, and the interpersonal and social conditions that trigger or maintain them are not captured by brain measures alone. The authors’ proposal of a systems psycho(patho)logy is an attempt to provide a theoretical framework in which these levels are related systematically rather than merely listed side by side. Such a framework would allow clinicians and researchers to ask how perturbations at one level propagate to others, how stabilizing processes maintain functioning, and why interventions at different levels—pharmacological, psychotherapeutic, or social—can each be effective without being reducible to one another.

The ecological perspective presented in the review extends this reasoning to the conception of the human being itself. The authors criticize what they call the cephalocentric paradigm, the tendency to locate all psychologically relevant activity in the brain. On their account, the brain should be understood as a regulative organ in a situated organism: it does not act alone but regulates the interactions of the whole body with its environment. In humans, moreover, the acting person is “extended” to tools, technologies, and social structures. This resonates with lines of research in cognitive science that treat cognition as distributed across brain, body, and environment, and with phenomenological traditions that emphasize the lived body as the medium of experience and action. The practical implication is considerable: understanding a mental disorder requires attention not only to neural dysregulation but also to the person’s bodily condition, material surroundings, technologies of daily life, and social relationships, because these are constitutive parts of the system whose functioning is disturbed.

The discussion of free will in the final section illustrates how these conceptual commitments play out in a concrete debate. Experimental studies that purport to show that conscious decisions are determined by unconscious brain processes ahead of awareness have often been interpreted through a deterministic lens. The authors argue that any position respecting the complexity and irreducibility of mental phenomena will escape inappropriate reductionist and deterministic assumptions while fully acknowledging the scientific evidence. This is not a retreat into dualism or an appeal to gaps in scientific knowledge. Rather, it reflects the systems-theoretic insight that a decision made by a situated, embodied person involves processes at multiple levels, including the person’s reasons, values, and social context, and that the relation between these levels is not one of simple one-way determination. Experimental findings about the timing of neural correlates of choice remain fully compatible with a conception of agency in which mental phenomena, as phenomena of persons, are not eliminated by their neural correlates.

Read as a whole, the anniversary review is best understood as a diagnosis of the relationship between neuroscience’s institutional dynamics and its conceptual development. Technical success attracts resources, resources enable big science, big science standardizes data and workflows, and standardization favors questions that fit existing measurement paradigms. Conceptual innovation, by contrast, requires reflective distance, interdisciplinary dialogue, and theoretical training—activities that are harder to fund and harder to standardize. The authors’ demand for an institutionalized, interdisciplinary, systems-oriented neurophilosophy is therefore not a complaint about neuroscience’s achievements but a proposal about the conditions under which the next decade of those achievements can become genuinely integrative. The measure of progress, on their account, will not be the volume of data accumulated but the field’s capacity to relate levels of description coherently, to respect the situated and extended character of human persons, and to hold its own explanatory claims to critical account.

Subject of Research: …

Article Title: Progress and ongoing conceptual challenges “on the way to integrative human neuroscience”–ten years after

Article References: Tretter, F., Löffler-Stastka, H., Braun, H. A., Schleim, S., Falkenburg, B., Hastedt, H., Northoff, G., Fuchs, T., Kotchoubey, B., Maderthaner, R., & Draguhn, A. (2026). Progress and ongoing conceptual challenges “on the way to integrative human neuroscience”–ten years after. Frontiers in Integrative Neuroscience, 20, Article 1792478. https://doi.org/10.3389/fnint.2026.1792478

Image Credits: AI Generated

DOI: 10.3389/fnint.2026.1792478

Keywords: neuroscience, neurophilosophy, free will, systems science, 4E cognition, consciousness, psychiatry, Progress, ongoing, conceptual, challenges, integrative