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Structural diverseness of neurons between brain areas and between cases
Published 1 Jul 2020 in q-bio.NC and physics.bio-ph | (2007.00212v1)
Abstract: The cerebral cortex is composed of multiple cortical areas that exert a wide variety of brain functions. Although human brain neurons are genetically and areally mosaic, the three-dimensional structural differences between neurons in different brain areas or between the neurons of different individuals have not been delineated. Here, we report a nanometer-scale geometric analysis of brain tissues of the superior temporal gyrus of 4 schizophrenia and 4 control cases by using synchrotron radiation nanotomography. The results of the analysis and a comparison with results for the anterior cingulate cortex indicated that 1) neuron structures are dissimilar between brain areas and that 2) the dissimilarity varies from case to case. The structural diverseness was mainly observed in terms of the neurite curvature that inversely correlates with the diameters of the neurites and spines. The analysis also revealed the geometric differences between the neurons of the schizophrenia and control cases, suggesting that neuron structure is associated with brain function. The area dependency of the neuron structure and its diverseness between individuals should represent the individuality of brain functions.
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Overview: What this paper is about
This study looks at the tiny 3D shapes of brain cells and how they differ:
- between two brain areas that do different jobs, and
- between different people, including people with and without schizophrenia.
The big idea is that the brain’s “wiring” (the shape and thickness of the branches of neurons) can vary by location and person, and these differences may relate to how each brain works.
Key questions the researchers asked
The study set out to find simple, clear answers to a few questions:
- Do neuron shapes differ between two brain areas: one involved in hearing/language (BA22, temporal lobe) and one involved in thinking/feelings (BA24, anterior cingulate cortex)?
- Do these shapes vary from person to person?
- Are there differences in these shapes in people with schizophrenia compared to people without it?
- Is there a basic rule that links how “bendy” a neuron branch is to how thick it is, and how that relates to the little “spines” where neurons connect?
How they studied it (in everyday language)
To see extremely tiny details, the team used a special kind of super-strong X-ray microscope called a synchrotron. Think of it like taking a super-detailed 3D X-ray of brain tissue, but at the nanometer scale (a nanometer is a billionth of a meter).
What they did:
- They examined thin pieces of brain tissue taken after death from 8 people: 4 with schizophrenia and 4 without (matched by age and gender).
- They looked in two places in the brain:
- BA22 (superior temporal gyrus): supports hearing and language.
- BA24 (anterior cingulate cortex): supports thinking and emotions.
- They “stained” the tissue so some neurons show up clearly (a classic method called Golgi staining that only colors a subset of neurons).
- Using the synchrotron, they built 3D images and then traced the neurons’ “branches” (called neurites—these include dendrites and axons) and the tiny bumps on them (dendritic spines), which are where connections (synapses) form.
Key measurements, explained with analogies:
- Curvature: how bendy a branch is. Imagine a road—curvy mountain roads have high curvature; straight highways have low curvature.
- Torsion: how much a curve twists out of a flat plane. Think of twisting a ribbon so it doesn’t stay flat.
- Thickness (radius): like comparing a thin string to a thick rope.
- Spine size and length: spines are tiny bumps on dendrites that help neurons talk to each other; their size can affect how strong that “talk” is.
They also “blinded” the analysis (removed case labels during tracing) to reduce bias.
What they found and why it matters
Here are the main takeaways.
- Neuron shapes differ by brain area, and the amount of difference depends on the person.
- In the same person, BA22 and BA24 showed different patterns of curvature (how bendy the branches are) and spine sizes. But the direction and size of these differences weren’t the same for everyone.
- This suggests each brain area has its own “style” of wiring, and each person’s brain is uniquely wired.
- Schizophrenia was linked with more bendy and thinner neuron branches.
- On average, the people with schizophrenia had neurites that were more tortuous (higher curvature) and thinner, and their spines were thinner too.
- Thinner, more bendy branches could change how electrical signals move through the brain’s wiring. This might help explain why some brain volume changes are seen in schizophrenia in MRI studies and why symptoms differ from person to person.
- A simple rule connected bendiness and thickness.
- Thinner branches and spines tend to bend more; thicker ones bend less. This is like how a thin wire is easier to bend than a thick metal rod.
- This rule held for both neurites and spines, in both brain areas, and in both groups.
- Neurite and spine sizes go together.
- Where neurites were thicker, the spines tended to be thicker too. This suggests that different parts of a neuron are built in a coordinated way.
- Some features were stable across people and areas.
- While curvature (bendiness) changed a lot across areas and people, torsion (the amount of twisting out of a plane) looked more similar overall.
Why this matters:
- Curvature and thickness affect how signals travel and how strong synapses can be. So, differences in these features could change how brain circuits work.
- Differences between areas and between people may help explain why people have different strengths (for example, someone might be especially strong in language or in complex thinking).
- The extra bendiness and thinning linked with schizophrenia suggest that microscopic wiring differences may contribute to the disorder, and that these differences can vary a lot from one person to another with schizophrenia.
What this could mean going forward
- Understanding individuality: The brain seems to have “modular” areas that are wired differently across people. These small-scale differences might add up to the unique ways we think, feel, and learn.
- Better insight into disorders: The wide variety of neuron shapes in schizophrenia might explain why the disorder looks different from person to person and why past studies sometimes disagree. It points to the need for personalized views of brain structure and function.
- Methods matter: 3D nanoscale imaging gives a more accurate picture than traditional 2D slices, which can miss features hidden behind others. This approach can reduce measurement bias and reveal rules that shape neurons.
- Limits and next steps: The study looked at a small number of cases (4 with schizophrenia, 4 without), and the staining method only shows some neurons. Medicine effects could also play a role. More studies with more people and brain areas are needed to confirm and expand these findings.
In short, the study shows that the brain’s wiring—how straight or curvy, thick or thin neuron branches and spines are—changes across brain areas and across people. These tiny differences likely shape how our brains function and may relate to mental health conditions like schizophrenia.
Knowledge Gaps
Knowledge gaps, limitations, and open questions
Below is a concise list of unresolved issues that future studies could address to strengthen, generalize, and mechanistically interpret the findings.
- Limited cohort size and power: Only 4 schizophrenia and 4 control cases were analyzed; findings require replication in larger, independent cohorts with adequate power to detect case, area, and interaction effects.
- Sampling restricted to one hemisphere and one layer: All samples were from the left hemisphere and cortical layer V; cross-hemisphere symmetry/asymmetry and layer-specificity (layers II–VI) remain untested.
- Regional scope is narrow: Only BA22 and BA24 were examined; it is unknown whether curvature/thickness/spine differences generalize across other cortical and subcortical regions.
- Potential pseudo-replication and nesting: Statistical models did not clearly account for the hierarchical structure (neurites/spines nested within neurons, fields-of-view, and cases); mixed-effects models and case-level inference are needed.
- Cell-type ambiguity: “Neurites” were not separated into dendrites vs axons, and neuron classes (e.g., pyramidal vs interneuron, IT vs PT) were not identified; type-specific structural differences remain unresolved.
- Incomplete neuronal reconstructions: Field-of-view limitations likely captured neurite fragments rather than full arbors; full-cell morphometrics (e.g., total dendritic length, branch order, Sholl profiles) are missing.
- Spine taxonomy unresolved: Spine subtypes (mushroom, thin, stubby), density per dendritic length, and distance-from-soma dependencies were not analyzed; functional inferences from average spine length/radius remain coarse.
- Torsion analysis underexplored: Torsion distributions were reported as “zero-centered,” but potential subtle case/area effects, scale-dependence, and measurement sensitivity were not examined.
- Golgi staining bias: Golgi impregnation labels only a subset of neurons with unknown selection biases (cell-type, size, state); the representativeness of stained cells across areas and cases remains unquantified.
- Tissue processing artifacts: Potential fixation-, impregnation-, embedding-, and radiation-induced shrinkage or deformation were not measured or corrected; absolute diameter and curvature estimates may be biased.
- Medication confounding: Schizophrenia cases likely had antipsychotic exposure; dose, duration, and drug class were not modeled, and unmedicated cases were not included to disentangle disease vs treatment effects.
- Postmortem and clinical covariates: Effects of postmortem interval, brain pH, age, sex, illness duration, smoking, and comorbidities on geometric measures were not controlled; residual confounding is possible.
- Batch and site effects: Data were acquired at two beamlines with differing optics; cross-site calibration and batch-effect assessment on geometric parameters were not reported.
- Measurement reliability and reproducibility: Manual editing and tracing were involved; inter- and intra-rater reliability, test–retest reproducibility, and algorithmic accuracy (precision/recall vs ground truth) were not quantified.
- Parameter space is limited: Beyond curvature, torsion, radius, and spine length, other morphometrics (branching angles, segment tapering, fractal dimension, betti numbers/topology) were not evaluated.
- Axial anisotropy and orientation: Relations of neurite geometry to cortical depth, columnar orientation, and local cytoarchitectonic boundaries were not analyzed.
- Mechanistic basis of curvature–thickness reciprocity: The proposed “common physical/geometric principle” is not mechanistically explained; roles of cytoskeletal composition, membrane tension, and extracellular matrix are untested.
- Functional linkage is indirect: No electrophysiology, biophysical modeling, or synaptic current simulations were performed to quantify how observed geometry affects EPSP/EPSC propagation and firing.
- Synaptic ultrastructure and density: Postsynaptic density size, synapse number per length, bouton density, and astrocytic coverage were not measured; structure–synapse–function links are inferred but not demonstrated.
- Genetic mosaicism untested within cases: No single-cell sequencing or in situ genotyping was performed to connect somatic variants to local neuronal geometry within individuals.
- Heterogeneity and “compensation” hypothesis: The suggestion of inter-area compensation in schizophrenia is speculative; within-subject multimodal evidence (behavior, fMRI/MEG connectivity, microstructure) is needed to test it.
- Developmental and lifespan context: It is unknown how curvature/thickness evolve across development, aging, and disease stages (prodrome, first-episode, chronic).
- Generalizability across species: Whether the curvature–thickness relationship and area/case differences are conserved in nonhuman primates or rodents is untested.
- Clinical relevance: No correlations with cognitive/auditory performance, symptom dimensions, treatment response, or polygenic risk were conducted; translational value remains to be established.
- Data and model completeness: The number of neurons per case, fraction of cells stained, and sampling scheme within BA22/BA24 (spatial coverage) were not quantified; risk of local sampling bias persists.
- Spatial autocorrelation: Potential clustering of geometric features within microdomains was not modeled; independence assumptions may be violated.
- Validation across modalities: Cross-validation with intracellular fills, expansion microscopy, or volume EM was not performed to confirm dimensions and spine classifications.
- Absolute scaling and calibration: External standards to calibrate voxel size and correct for potential magnification/nonlinearity across instruments were not detailed for final morphometric comparability.
- Causality vs correlation: It remains unresolved whether observed geometric differences are causal contributors to schizophrenia pathophysiology or epiphenomena secondary to disease or treatment.
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