TRANSLATED FROM TURKISH:
NEUROIMAGING BIOPHYSICAL LIMITS IN BRAIN SCIENCE TECHNOLOGIES, LEGAL-JUDICIAL ABUSE
by GEMINI, ChatGPT and SWE-1.6 AI
ABSTRACT
This blog examines the abuse and exploitation of neuroimaging technologies in legal settings, guardianship cases, and global medical practice, while acknowledging the tremendous developments in molecular biology, radiology, quantum mechanics, and biophysics that have reached their peak in neuroimaging. The clinical and theoretical competence limits of 24 advanced scientific methods examining living brain tissue are delineated; the legal and ethical crises created by the use of this data by charlatan psychologists, charlatan clinicians, and incompetent legal panels as a "biological caste system" or "normality test" are examined from a radical perspective.
Current neuroimaging methods measure indirect structural, hemodynamic, metabolic, or electrophysiological correlates of brain activity. However, many fundamental biological processes remain incompletely understood, including the multilevel organization and dynamics of proteins, synaptic plasticity, neurotransmitter turnover, neuromodulation, glia–neuron interactions, and complex cellular and molecular networks. Consequently, statistical deviations identified through neuroimaging cannot, by themselves, establish pathology, cognitive superiority, legal incapacity, or other complex psychological and legal constructs.
The history of neuroscience is a history of remarkable discoveries, but also of humility. Despite decades of progress, no current neuroimaging technology can directly measure consciousness, judgment, personality, free will, moral reasoning, or legal capacity. Claims that exceed these scientific limits risk transforming neuroscience from an evidence-based discipline into an instrument of speculation.
Blood glucose is a direct biochemical measurement with validated diagnostic thresholds. By contrast, EEG, neuroimaging does not provide comparably validated quantitative measures macaque or human intelligence, legal competence, or decision-making capacity.
Current neuroimaging techniques cannot distinguish, on the basis of imaging alone, between the cognitive achievements of a highly educated, highly accomplished scientist and those of a non-human primate (macaque). Such complex capacities arise from lifelong learning, experience, and higher cognitive functions that cannot be inferred directly from neuroimaging findings.
If current neuroimaging techniques cannot reliably determine which of two non-human primates possesses greater cognitive capacity or overall intelligence based solely on brain imaging, then claiming that these same techniques can determine an individual human's legal capacity, competence, or suitability for guardianship is scientifically unjustified.
Using neuroimaging beyond its scientifically validated scope in guardianship law cases risks transforming legitimate neuroscience into scientific charlatanism.
No individual should be deprived of legal capacity, liberty, or property on the basis of speculative interpretations of neuroimaging findings. Where objective evidence—including educational attainment, licensure, university degrees, scientific publications and scientific quality, biography performance—demonstrates long-term competence, such evidence should carry substantial weight. Scientific tools that remain inherently probabilistic and indirect must never be elevated real life biography, factual evidence in legal decision-making.
The power of science lies not in being able to answer every question; but in honestly admitting which questions it cannot yet answer. The use of scientific data as a tool for legal manipulation destroys not only individual rights but also trust in science itself.
1. INTRODUCTION: SUCCESSFUL PROGRESS OF SCIENCE AND REAL DISCOVERIES
Over the past thirty years, neuroimaging technologies have shown extraordinary development. Through functional magnetic resonance imaging, diffusion imaging techniques, high-resolution electroencephalography, magnetoencephalography, molecular imaging systems, and artificial intelligence-supported radiomic analyses, the structural, functional, and metabolic characteristics of the human brain can now be examined at a level of detail not previously possible (Logothetis, 2008; Le Bihan, 2014; Poldrack et al., 2020).
These developments have contributed not only to more accurate diagnosis of neurological and psychiatric diseases, but also to more effective management of epilepsy surgery, brain tumors, dementia, Parkinson's disease, and neurodegenerative processes (Raichle, 2015; Filippi et al., 2012; Barkhof et al., 2019).
Therefore, these methods developed in contemporary neuroscience and radiology are extremely valuable technological gains from a scientific perspective. Honest scientific studies aimed at understanding the complex biology of the human brain are among the fundamental research areas that should be supported for the advancement of medicine (National Academies of Sciences, Engineering, and Medicine, 2021).
However, the fact that a scientific measurement instrument has high technical accuracy does not mean that the data it produces can be interpreted without limits. All neuroimaging methods currently in use measure certain biophysical processes indirectly. Biological indicators such as blood flow, oxygen consumption, water molecule diffusion, electrical activity, or metabolic receptor densities do not directly represent all cognitive, ethical, and legal characteristics of the human mind (Logothetis, 2008; Poldrack, 2006; Varoquaux & Poldrack, 2019).
Therefore, reaching deterministic conclusions about an individual's intelligence, personality, moral competence, or legal capacity based on correlations exceeds the limits of scientific methodology. The current literature draws attention to risks of overinterpretation, reverse inference, and statistical false positives, particularly in predictions made at the individual level (Poldrack, 2006; Eklund et al., 2016; Poldrack et al., 2020).
The primary purpose of this review is to discuss the legal and scientific problems that may arise when the methodological limits of advanced neuroimaging technologies are exceeded, while acknowledging their scientific value. In particular, presenting these methods as absolute measurement tools that determine an individual's "normality," "legal capacity," or "personality characteristics" can pave the way for misinterpretation of science and charlatan practices. This criticism is directed not at neuroimaging technologies themselves, but at interpretations that exceed scientific limits (Farah, 2012; Morse, 2006; OECD, 2019; UNESCO, 2021).
The common purpose of these human health technologies is not to "judge" the human brain, but to understand the biological mechanisms of diseases, facilitate diagnosis, and increase treatment success (National Academies of Sciences, Engineering, and Medicine, 2021).
A. Electrophysiological Imaging
1. High-Density EEG (HD-EEG)
High-density electroencephalography enables monitoring of cortical electrical activity with high temporal resolution by using many more electrodes than classical EEG. It makes important contributions particularly in the localization of epileptogenic foci prior to refractory epilepsy surgery (Michel & Murray, 2012; Seeck et al., 2017).
2. Magnetoencephalography (MEG)
MEG can evaluate the functional organization of the brain at the millisecond level by measuring the extremely weak magnetic fields created by postsynaptic currents. It is one of the most powerful tools of neuroimaging in showing the timing of electrophysiological events (Hämäläinen et al., 1993; Baillet, 2017).
3. OPM-MEG
Optically Pumped Magnetometers technology has made portable MEG applications possible by eliminating the need for cryogenic systems. It is considered an important technological advancement in terms of measuring brain magnetic fields in moving children, speaking individuals, and real-life conditions (Boto et al., 2018; Hill et al., 2020).
B. Molecular Imaging
4. PET Ligand Imaging
Positron Emission Tomography (PET) is one of the few clinical imaging methods that can examine dopamine, serotonin, acetylcholine, and other neurotransmitter systems at the receptor level. It plays an important role in evaluating molecular mechanisms in Parkinson's disease, Alzheimer's disease, and various psychiatric disorders (Cherry et al., 2018; Brooks, 2010).
5. Magnetic Resonance Spectroscopy (MRS)
MRS can measure N-acetylaspartate, choline, creatine, lactate, and various metabolites in a non-invasive manner. It provides important information particularly in the metabolic characterization of tumors and the investigation of neurodegenerative diseases (Öz et al., 2014).
6. GABA and Glutamate Spectroscopy
GABA and glutamate spectroscopy performed in high-field MR systems enables evaluation of inhibitory and excitatory neurotransmission. It is widely used in epilepsy, depression, and schizophrenia research (Mullins et al., 2014).
7. PET/MR Hybrid Imaging
Combining PET and magnetic resonance imaging in the same device enables simultaneous acquisition of structural and metabolic information. It offers significant advantages particularly in the evaluation of oncology, epilepsy, and neurodegenerative diseases (Quick et al., 2013).
C. Structural Brain Analysis
8. Voxel-Based Morphometry (VBM)
VBM is a powerful method that statistically evaluates regional changes in gray and white matter volumes. It is widely used in the investigation of structural changes related to learning, experience, and neuroplasticity (Ashburner & Friston, 2000).
9. Cortical Thickness Analysis
Cortical thickness measurements have high sensitivity in developmental neuroscience, aging, and the investigation of neurodegenerative diseases. It is one of the important biomarkers in early detection of cortical atrophy in Alzheimer's disease (Fischl & Dale, 2000).
10. Diffusion Tensor Imaging (DTI)
DTI maps white matter tracts by analyzing the oriented movement of water molecules along axons. Today, tractography in neurosurgery has become one of the fundamental components of surgical planning (Le Bihan, 2014; Mori & van Zijl, 2002).
11. Diffusion Kurtosis Imaging (DKI)
DKI can model the complex microstructure of biological tissues in more detail by going beyond classical DTI. It shows promising results in the investigation of multiple sclerosis, traumatic brain injury, and early neurodegenerative processes (Jensen et al., 2005).
12. Perfusion MRI (PWI)
Perfusion imaging evaluates regional perfusion of brain tissue. It has important clinical value in determining salvageable penumbra tissue in acute ischemic stroke (Wintermark et al., 2005).
D. FUNCTIONAL NETWORKS, METABOLISM AND CEREBRAL HEMODYNAMICS
13. Resting-State Functional MRI (rs-fMRI)
Resting-state functional magnetic resonance imaging (rs-fMRI) evaluates functional connectivity by analyzing the brain's spontaneous low-frequency BOLD signal fluctuations without applying any task. This method has made important contributions to understanding the organization of large-scale neural networks such as the Default Mode Network (DMN), salience network, and executive control networks (Biswal et al., 1995; Raichle et al., 2001; Raichle, 2015).
rs-fMRI is widely used in the investigation of Alzheimer's disease, epilepsy, traumatic brain injury, depression, and consciousness disorders. However, the connectivity maps obtained do not allow deterministic inferences about intelligence, personality, or legal capacity at the individual level (Poldrack, 2006; Smith et al., 2013; Varoquaux & Poldrack, 2019).
14. FDG-PET and Glucose Metabolism
18F-fluorodeoxyglucose positron emission tomography (FDG-PET) provides an indirect indicator of neuronal activity by evaluating cerebral glucose metabolism. It provides important clinical benefits in the differential diagnosis of neurodegenerative diseases such as Alzheimer's disease, Lewy body dementia, and frontotemporal dementia (Mosconi, 2013; Cherry et al., 2018).
However, FDG-PET shows metabolic activity and does not alone provide definitive conclusions about an individual's cognitive capacity, character, or legal responsibility (National Academies of Sciences, Engineering, and Medicine, 2021).
15. Regional Cerebral Blood Flow (rCBF)
Regional cerebral blood flow measurements evaluate perfusion changes in different regions of the brain. It is used as an auxiliary biomarker particularly in stroke, epilepsy, and various neurodegenerative diseases (Detre et al., 2009).
However, differences in cerebral blood flow are influenced by many physiological, age-related, pharmacological, and environmental variables. Therefore, it cannot be evaluated as an objective criterion determining an individual's mental competence or legal capacity alone (Logothetis, 2008; Poldrack et al., 2020).
16. BOLD fMRI
Blood Oxygen Level Dependent (BOLD) functional magnetic resonance imaging measures hemodynamic changes accompanying neural activity. It carries important clinical value particularly in preoperative mapping of speech, motor cortex, and sensory areas (Ogawa et al., 1990; Logothetis, 2008).
However, the BOLD signal shows not neural activity directly but the vascular response accompanying neural activity. Therefore, converting biological correlations into definitive interpretations about an individual's cognitive characteristics requires methodological caution (Logothetis, 2008; Poldrack, 2006).
17. Arterial Spin Labeling (ASL)
Arterial Spin Labeling is a non-invasive MR method that evaluates cerebral perfusion by magnetically labeling water protons in arterial blood without using external contrast agents. Its safe application in patients with renal failure is one of its important advantages (Detre et al., 2012).
ASL provides reliable physiological information in cerebrovascular diseases, tumors, and dementia research (Alsop et al., 2015).
E. THERAPEUTIC NEUROMODULATION
18. Low-Intensity and High-Intensity Focused Ultrasound (LIFU/HIFU)
Focused ultrasound technologies are among important biophysical developments that combine imaging with treatment. High-Intensity Focused Ultrasound (HIFU) shows successful results in non-invasive ablation of specific thalamic nuclei, particularly in essential tremor and Parkinson's disease (Elias et al., 2016).
Low-Intensity Focused Ultrasound (LIFU) shows promising results in experimental applications such as neuromodulation and temporary opening of the blood-brain barrier (Lipsman et al., 2018).
19. Adaptive Deep Brain Stimulation (Adaptive DBS)
Adaptive Deep Brain Stimulation systems provide stimulation only when pathological activity occurs by using real-time electrophysiological feedback instead of classical continuous stimulation. This approach can increase clinical effectiveness while reducing energy consumption (Little et al., 2013; Rosa et al., 2017).
F. MICROSTRUCTURE, GLYMPHATIC SYSTEM AND GENOMICS
20. Glymphatic Imaging (DTI-ALPS)
The DTI-ALPS method is one of the new imaging techniques developed to indirectly evaluate the function of the glymphatic system. It contributes to the investigation of brain waste removal mechanisms particularly in Alzheimer's disease and various neurodegenerative processes (Taoka et al., 2017; Taoka & Naganawa, 2020).
21. Functional Near Infrared Spectroscopy (fNIRS)
Functional near-infrared spectroscopy is a portable neuroimaging technique that evaluates cortical oxygenation changes with optical methods. It offers important advantages in children and rehabilitation research because it can collect data during movement (Ferrari & Quaresima, 2012).
22. Functional Ultrasound (fUS)
Functional ultrasound can evaluate high-resolution cerebral microvascular blood flow in real time. In recent years, it has shown remarkable developments particularly in experimental neuroscience and intraoperative brain surgery (Mace et al., 2011; Tanter & Fink, 2014).
23. Polygenic Scoring and Transcriptomics
Polygenic risk scores produce statistical risk predictions for certain diseases by evaluating thousands of genetic variants together. However, the current scientific literature does not support the use of polygenic scores for deterministic evaluation of individual intelligence, character, or legal responsibility (Lewis & Vassos, 2020; National Academies of Sciences, Engineering, and Medicine, 2021).
G. AI-SUPPORTED RADIOMIC AND PROTEIN MODELING
24. Radiomic Analysis and AlphaFold
Radiomic analyses are artificial intelligence-supported methods that enable extraction of high-dimensional quantitative features from medical images that the human eye cannot distinguish. They show promising results particularly in tumor classification, prognosis prediction, and prediction of treatment response (Lambin et al., 2017).
AlphaFold can predict the three-dimensional structure of proteins with high accuracy using deep learning methods and constitutes an important turning point in structural biology (Jumper et al., 2021).
However, both radiomic algorithms and artificial intelligence-based biological prediction systems should be evaluated as tools supporting clinical decision-making. Current scientific evidence does not support the use of these methods as absolute and deterministic decision-making tools regarding an individual's mental capacity, moral competence, or legal capacity (Topol, 2019; UNESCO, 2021; OECD, 2019; World Health Organization, 2021).
2. METHODOLOGICAL LIMITS: COMPUTER ANALOGY AND BLINDNESS PROBLEM
We must draw a definite biophysical limit for what this massive medical literature listed above can and cannot measure. To summarize with the computer analogy; measuring a computer's processor clock speed (GHz), RAM data bus width, motherboard path smoothness, or air flow passing through the fan (blood flow) is not equivalent to measuring the quality of the software running on that computer, the depth of a philosophical text written, or the intellectual and aesthetic value of a produced artwork.
Moreover, these macroscopic and indirect methods are too blind to even see the core silicon structure in the transistors of that processor (molecular protein skeletons and delicate synaptic plasticity dynamics). Taking the scientifically high-value methods listed below and similar ones, taking biological and statistical indirect correlations and turning them into absolute "intelligence, morality, or normality meters" is nothing but modern charlatanism that abuses science by hiding behind current positivist hard-science claims.
Important Warning: Current scientific evidence shows that neuroimaging technologies do not allow deterministic determination of the following multidimensional concepts:
- intelligence,
- personality,
- honesty,
- moral character,
- future behaviors,
- decision-making competence
There is no scientific method showing that such multidimensional concepts can be determined based on coercive guardianship case memorandum conspiracy committee report imaging findings (Morse, 2006; Farah, 2012; National Academies of Sciences, Engineering, and Medicine, 2021).
Deterministic interpretation of such imaging results is contrary to the scientific uncertainty principle.
Biological Coercion and Global Crisis: This biological coercion is not just a local inadequacy problem; unfortunately, it is a global "medical abuse" crisis carried out by clinicians worldwide, led by the United States. Today, even in America and developed health systems, some clinicians and neurologists, under the pressure of pharmaceutical companies, insurance giants, or legal structures, or entirely through professional charlatanism, force individuals into these medical imaging processes without a clinical symptom or acute neurological loss (stroke, paralysis, tumor, etc.).
Directing individuals to advanced neuroimaging processes solely for administrative, legal, or social purposes without clinical necessity is considered among applications that may raise important discussions in terms of ethics, law, and human rights (WHO, 2021; UNESCO, 2021).
Imposing these methods as a necessity solely to manipulate a legal process, create a basis for guardianship cases, or corner an individual is a betrayal of science. This is not honest health practice; it is modern coercion that turns the patient into a client and justice into biological laboratory subjects.
6. CONCLUSION AND MANIFESTO
The more than twenty advanced neuroimaging and neuromodulation technologies examined in this review are among the most important scientific achievements of contemporary medicine. These methods carry great scientific value in the diagnosis of neurological diseases, brain tumors, epilepsy surgery, neurodegenerative diseases, and personalized treatment approaches (Filippi et al., 2012; Barkhof et al., 2019).
However, the current level of scientific knowledge does not show that these technologies can directly and definitively measure an individual's intelligence, moral capacity, personality, or legal capacity (Poldrack, 2006; Logothetis, 2008; Varoquaux & Poldrack, 2019).
Scientific Fact: Neuroimaging data consist of indirect biological correlations, and converting these correlations into definitive, deterministic interpretations about an individual's complex cognitive, ethical, and legal characteristics is incompatible with the level of information reached by current neuroscience literature.
A brain measurement that is smaller, larger, or otherwise different from a reference population—even if it falls outside the typical human range or overlaps with values observed in non-human primates—does not, by itself, determine cognitive ability, functional capacity, or legal competence. Brain function emerges from highly complex, multiscale interactions rather than from any single anatomical or imaging-derived metric. To preserve the scientific integrity of these technologies and prevent abuses that violate human rights; strict adherence to the clinical necessity principle must be maintained, exceeding scientific limits must not be allowed, and legal mechanisms against the abuse of these methods as tools for legal manipulation must be strengthened.
The purpose of science is not to "judge" the human brain; but to understand the biological mechanisms of diseases, facilitate diagnosis, and increase treatment success. A scientific approach faithful to this principle will contribute to the advancement of medicine while protecting human rights and trust in science itself (National Academies of Sciences, Engineering, and Medicine, 2021).
Consequently, statistical deviations observed in neuroimaging cannot, by themselves, establish pathology, cognitive superiority, inferiority, personality traits, legal capacity, or legal incapacity.
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