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Evaluating ultrastructural preservation quality in banked brain tissue 

Macy Garrood1*, Alicia Keberle1*, Allison Sowa2, William Janssen2, Emma L. Thorn3,4, Claudia De Sanctis3,4, 
Kurt Farrell3,4, John F. Crary3,4, Andrew T. McKenzie1 

1 Apex Neuroscience, Salem, Oregon, USA 

2 Microscopy and Advanced Bioimaging Core, Icahn School of Medicine at Mount Sinai, New York, New York, USA 

3 Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, 
Icahn School of Medicine at Mount Sinai, New York, New York, USA 

4 Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School 
of Medicine at Mount Sinai, New York, New York, USA 

 The authors contributed equally to this work. 

Corresponding author: 
Andrew T. McKenzie · Apex Neuroscience · 3265 Marietta St SE · Salem · OR 97317 · USA 
amckenzie@apexneuro.org 

Submitted: 06 May 2025 · Accepted: 09 June 2025 · Copyedited by: Alessia Sciortino · Published: 25 June 2025 

Abstract 

The ultrastructural analysis of postmortem brain tissue can provide important insights into cellular architecture 
and disease-related changes. For example, connectomics studies offer a powerful emerging approach for  
understanding neural circuit organization. However, electron microscopy (EM) data is difficult to interpret when 
the preservation quality is imperfect, which is common in brain banking and may render it unsuitable for certain 
research applications. One common issue is that EM images of postmortem brain tissue can have an expansion 
of regions that appear to be made up of extracellular space and / or degraded cellular material, which we call 
ambiguous interstitial zones. In this study, we report a method to assess whether EM images have ambiguous 
interstitial zone artifacts in a cohort of 10 postmortem brains with samples from each of the cortex and thalamus. 
Next, in matched samples from the contralateral hemisphere of the same brains, we evaluate the structural 
preservation quality of light microscopy images, including immunostaining for cytoskeletal proteins. Through this 
analysis, we show that on light microscopy, cell membrane morphology can be largely maintained, and neurite 
trajectory visualized over micrometer distances, even in specimens for which there are ambiguous interstitial 
zone artifacts on EM. Additionally, we demonstrate that synaptic structures can be successfully traced across 
serial EM sections in some postmortem samples, indicating the potential for connectivity studies in banked  
human brain tissue when appropriate preservation and visualization protocols are employed. Taken together, 
our analysis may assist in maximizing the usefulness of donated brain tissue by informing tissue selection and 
preparation protocols for various research goals. 
 

Keywords: Brain banking, Postmortem changes, Perfusion fixation, Neurofilaments, Ultrastructural quality, Connectomics 

Original Paper 

https://doi.org/10.17879/freeneuropathology-2025-6763
https://creativecommons.org/licenses/by/4.0/
https://creativecommons.org/publicdomain/zero/1.0/
mailto:amckenzie@apexneuro.org


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Abbreviations 

AIZ - Ambiguous Interstitial Zones, EM -  
Electron Microscopy, GFAP - Glial Fibrillary Acidic 
Protein, h - Hour, H&E - Hematoxylin and Eosin, IRR 
- Inter-Rater Reliability, LM - Light Microscopy, NBF 
- Neutral Buffered Formalin, PMI - Postmortem  
Interval, WSI - Whole Slide Image. 

Introduction 

Since the 1950s, when the synapse was first  
visualized with an electron microscope, the ultra-
structural analysis of brain tissue has enabled many 
critical discoveries about the structure of the brain 
(Sotelo, 2020; Nahirney and Tremblay, 2021). In  
recent years, EM-based connectomics, in particular, 
has enabled key insights into larger-scale neural  
circuitry across diverse species (Lichtman et al., 
2014; Shiu et al., 2024). Expanding connectomics to 
a larger set of human brains may allow us to answer 
fundamental questions about our brains in health 
and disease. However, data collection for connec-
tomics relies on high-quality tissue preservation that 
enables the reliable tracing of neuronal processes 
and identification of synaptic connections. These  
requirements are challenging to achieve in human 
brain tissue samples, which generally have quality 
limitations due to agonal factors, the postmortem 
interval (PMI), and impediments in preservation 
methods (McKee, 1999; McFadden et al., 2019; 
McKenzie et al., 2022). To date, most volume  
electron microscopy studies have been performed 
on non-human brain tissue (Chiappini et al., 2025). 
The successful volume electron microscopy and  
connectomics studies on human brain tissue have 
been limited to tissue that is selected for having 
ideal preservation quality, such as surgical biopsy 
tissue or deceased donor tissue with very low PMI 
(Shapson-Coe et al., 2024; Plaza-Alonso et al., 2025). 

While mapping an entire human brain with 
electron microscopy far exceeds our current techno-
logical capabilities, the ability to image nanoscale 
neural connectivity in tissue from a wider set of 
banked brains would still be valuable for several  
reasons. First, brain banks serve diverse research 
communities, and investigators require access to  
tissue from different brain regions and with  

different donor characteristics, which may not  
always be possible to acquire from surgical biopsies. 
Second, larger sample sizes are critical for statisti-
cally robust inferences regarding the structural  
correlates of disease, as the history of genomics has 
shown (Uffelmann et al., 2021). Third, advances in 
imaging and computing technologies are rapidly  
improving our ability to analyze neural circuits at 
scale. As these tools continue to develop, having  
access to more banked brain tissue whose ultra-
structure can be profiled may enable increasingly 
larger-scale connectomics studies of the human 
brain. Given these considerations, there is a critical 
need to investigate whether current techniques 
used in brain banking are sufficient to maintain the 
structural integrity needed for future connectome 
analyses, despite the fact that our present connec-
tome imaging and reconstruction capabilities are 
still limited. 

There is a lack of standardized methods to  
assess brain preservation quality, which means  
that it may be useful to consider first principles  
(McFadden et al., 2019; Wahyudi et al., 2025).  
Structural changes can occur prior to fixation, during 
fixation, and during subsequent tissue processing, 
and may include membrane blebbing, vacuoles,  
cytoplasmic washout, and chromatin alterations 
(Garman, 2011; Krassner et al., 2023; McKenzie et 
al., 2024). Some of these artifacts, such as blebbing 
or vacuoles, may not prevent us from tracing the 
connectome, instead only leading to the expansion 
or compression of certain cellular structures, which 
can still be adequately visualized. A more significant 
challenge arises from the observed phenomenon in 
some samples of enlarged, electron-lucent, non-
membrane-bound regions between cells, which we 
call ambiguous interstitial zones (AIZs). Crucially, 
these AIZs are usually also associated with an  
apparent decrease in the density of visualized  
cellular structures, such as thin neurites. Instead, 
the AIZs often contain what appears to be poorly  
defined structures, possibly cellular debris. These 
poorly defined structures are not usually visible in 
tissue that has been preserved with a negligible  
duration of ischemia prior to preservation. These 
AIZs and associated poorly defined structures have 
been described in previous literature, for example, 
as causing a “lacey” appearance in postmortem 

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brain tissue (Palay et al., 1962; Liewald et al., 2014; 
Lewis et al., 2019). 

Mechanistically, very early in the PMI, the  
extracellular space is actually expected to shrink due 
to ischemic cell swelling (Nicholson and Syková, 
1998). As the PMI becomes prolonged, biomolecular 
structures break down and cell membrane integrity 
is eventually lost, leading to passive fluid redistribu-
tion and an expected expansion of the apparent  
extracellular space (Krassner et al., 2023). This  
excess fluid may affect fine neural structures in  
various ways, from complete dissolution in severe 
cases to preservation of some elements but with  
insufficient compactness for visualization in others. 
The difficulty in visualization may be in part because 
microscopy depends on biomolecules being densely 
aggregated enough to maintain their structural  
integrity during tissue processing and bind  
adequately with staining chemicals (Wang and  
Minassian, 1987). However, during prolonged PMI, 
these biomolecular networks progressively dissoci-
ate, reducing their density. 

Previous studies have found that fixation and 
sample preparation methods can influence the  
visualized ultrastructure of brain tissue (Schiff and 
Gennaro Jr., 1979; Small, 1981; Sele et al., 2019; 
Eberhardt et al., 2022; Shafiei et al., 2024). For  
example, one study reported that there can be  
significant extraction of proteins and lipids during 
EM preparation, creating large empty spaces, which 
is an issue that worsens with longer PMI (Lewis  
et al., 2019). They found that adding 0.1 %  
glutaraldehyde to their formalin fixative partially 
rescued this. Another study found that the use of 
embedding techniques for EM at room temperature, 
which is standard for the field, introduced ultra-
structural artifacts such as swollen mitochondria, 
disrupted membranes, and extraction of cellular 
components (Sosinsky et al., 2008). However, these 
artifacts were avoided when fixation was instead 
followed by a high-pressure freezing protocol,  
which led to images with smoother cell membranes 
and more dense cytoplasm. Finally, one study  
tested more than one hundred protocol variations 
on human brain tissue and found that even  
subtle differences in fixation, washing, dehydration,  
and embedding can affect the ultrastructural  

appearance, including the preservation of extra- 
cellular space (Karlupia et al., 2023). 

Our working hypothesis is that the observed  
artifacts on ultrastructural imaging may result solely 
from structural degradation due to decomposition 
prior to fixation, and / or may be partially accounted 
for by our current methods of sample preparation, 
staining, and imaging, which are not optimized for 
decomposed tissue. If true structural loss is the 
dominant factor, then strict constraints on PMI and 
preservation procedures may be necessary for  
selecting samples that are suitable for connectome 
imaging. On the other hand, if enough morpho- 
molecular markers are still theoretically present to 
reconstruct the cellular skeleton but are not visual-
ized with current methods due to insufficient  
optimization for this purpose, then improved  
postfixation, embedding, staining, imaging, and 
analysis methods could potentially recover them. 

In this study, we attempt to address the  
challenge of distinguishing true structural degrada-
tion from visualization artifacts in postmortem brain 
EM images. We develop a metric to assess the  
extent of AIZs in the EM images as an index for  
evaluating preservation quality. We also analyze 
matched samples from the contralateral hemi-
sphere stained with hematoxylin and eosin (H&E) 
and via immunohistochemistry, to attempt to  
identify cases where cellular structures remain  
intact on light microscopy. Our goal is to help  
improve our methods for assessing ultrastructural 
preservation quality and explore the differences  
between the measured preservation quality at the 
light and electron microscopy levels. 

Methods 

Brain banking procedures 

Anatomical whole-body donations were  
performed by a partner whole-body donation  
organization operating under Oregon Health  
Authority regulations. Additionally, through our  
canine brain bank program, we were donated the 
body of one deceased canine following euthanasia 
by a licensed veterinarian, with signed owner  
consent for research use (Sándor et al., 2021). The 
Apex Neuroscience Brain and Tissue Bank operates 

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under an exemption determination issued by the 
Pearl Institutional Review Board (IRB) after the  
submission of our protocols for review. 

The PMI was calculated as the time elapsed  
between death and the initiation of the preservation 
procedure. When the day of death but not the hour 
was known, the time of death was estimated at  
the middle of the day (12 pm) to provide a standard-
ized approach for PMI calculation in cases with  
incomplete time data. During the PMI, the donor 
bodies were generally stored in refrigeration, for  
example, in a hospital morgue. However, we do not 
have the exact durations of this refrigerated storage 
period for each donor, which is a potential  
confound, as higher temperatures during the PMI 
are associated with more structural breakdown. 

One of the brain specimens (donor #57) was 
fixed by immersion in 10 % neutral buffered  
formalin (NBF, Azer Scientific NBF55G) alone. Note 
that 10 % NBF contains 3.7 % formaldehyde (Snyder 
et al., 2022). The rest of the human brains were  
perfused in situ with the use of a peristaltic  
pump, following cannulation of the bilateral carotid  
arteries with 10 % NBF. For several of the donors 
(donors #7, 30, 34, and 37), the carotid arteries were 
accessed via dissection in the anterior cervical  
region. For the remaining human donors, the  
cephalon was isolated via dissection at the  
approximate spinal level of C4-C5 (Turkoglu et al., 
2014). This allowed for cannulation of the bilateral 
internal carotid arteries and clamping of the  
vertebral arteries to prevent outflow through them. 
The one canine brain was from a 2.3 kg Miniature 
Pinscher whose brain was perfused in situ with 10 % 
NBF via cannulation of the left ventricle and the use 
of a peristaltic pump. 

The brains were removed from the skull  
following standard procedures (Adams and Murray, 
1982). They were then immersed in 10 % NBF at 4 °C 
for at least one month prior to further processing 
(McKee, 1999). Small samples were taken from grey 
matter of the sensorimotor cortex and the grey  
matter of the thalamus, from one hemisphere for 
light microscopy and the contralateral for EM. 

Electron microscopy 

Tissue for EM was post-fixed in a solution of 
2 % paraformaldehyde and 2.5 % glutaraldehyde in 
0.1M sodium cacodylate buffer. A version of the  
National Center for Microscopy and Imaging  
Research (NCMIR) protocol was adapted to  
provide enhanced contrast (Deerinck et al., 2010).  
Specifically, after fixation, the tissue underwent a 
multi-step enhanced contrast protocol at room  
temperature including sequential treatments with 
tannic acid, reduced osmium, thiocarbohydrazide,  
osmium, and uranyl acetate. This was followed by 
lead aspartate staining at 60 °C. The brain sample 
was then dehydrated through a graded ethanol  
series, infiltrated with Embed 812 epoxy resin 
(EMS), and polymerized for 72 h at 60 °C. Semithin 
sections (0.5 μm) were cut using a Leica UC7 ultra-
microtome (Leica, Buffalo Grove, IL) and  
counterstained with 1 % toluidine blue to identify 
the regions of interest within layers. Images were 
taken on a HT7500 transmission electron micro-
scope (Hitachi High-Technologies, Tokyo, Japan)  
using an AMT NanoSprint12 12-megapixel CMOS 
TEM Camera System, software version 7.0.1.485 
(Advanced Microscopy Techniques, Danvers, MA). 
Images were only adjusted for contrast on the AMT 
software. For three of the samples, we performed 
serial section transmission electron microscopy 
(ssTEM), using ultra-thin sections of 80 nm  
thickness, collected onto nickel slot grids. There 
were 6 image series from the identified region of  
interest across 10 serial sections. 

We first performed fine-scale manual  
annotation of a subset of EM images, including one 
high-magnification image from all 20 unique brain 
samples (from different donors and brain regions). 
We annotated the boundaries of four mutually  
exclusive classes of structures across the image: (a) 
cell bodies, (b) membrane-bound structures with 
electron-dense interior, (c) membrane-bound  
structures with electron-lucent interior, and (d)  
myelinated axons. Category (c) is expected to  
include fluid-filled, swollen astrocyte processes, 
which is a common artifact seen in postmortem 
  

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brain tissue, but is not necessarily expected to make 
it more difficult to trace neural processes (Krassner 
et al., 2023). Notably, category (b) could include 
neurites as well as astrocyte, oligodendrocyte, or 
microglia processes. Because we only have 2D  
images for most of the EM data, we cannot more  
definitively annotate these on the basis of their 3D 
structure. The remainder of the image is designated 
as AIZs. These extracellular spaces may or may  
not contain partially degraded cellular membranes 
or other structural elements that cannot be  
reliably visualized due to postmortem changes or  
preparation artifacts. To assess inter-rater reliability 
for the fine-scale manual annotation, two independ-
ent raters annotated the same image. The  
spatial agreement between their annotations was  
quantified using the Dice similarity coefficient, with 
the median pairwise Dice score calculated across all 
polygons that were identified as having the most 
similar coordinates between the annotations. 

We next graded two-dimensional EM images 
on whether or not they had AIZ artifacts, rating  
each image as either having or not having both (a)  
extensive AIZs and (b) a low degree of cell  
membrane intactness. We added the additional  
criterion of (b) to ensure that the images did not 
merely have expanded extracellular space, which 
could theoretically occur in conjunction with clearly 
delineated, well-preserved lipid membranes, for  
example depending upon the osmolarity of the  
preservative solutions (Pallotto et al., 2015). Two 
raters worked together to determine the grade for 
each image and resolved any discrepancies via  
consensus review. We calculated the percentage of 
images graded as having AIZ artifacts across each of 

the 5 medium-magnification EM images available 
for all 20 samples. 

Light microscopy 

Brain tissue sampled for light microscopy was 
placed into cassettes for processing and embedded 
in paraffin. Paraffin-embedded brain sections 6 µm 
thick were baked, deparaffinized, and stained for 
H&E. Chromogenic immunohistochemistry was  
performed on Ventana Discovery Ultra according to 
the manufacturer’s directions (Neuropathology 
Brain Bank and Research CoRe, at Mount Sinai). The 
slides 6 µm thick were baked, deparaffinized, and 
pretreated using Cell Conditioning (CC1) antigen  
retrieval buffer (Tris / Borate/ EDTA buffer, pH  
8.0–8.5, 950-224, Roche Diagnostics). Primary anti-
bodies (Table 1) were diluted in antibody dilution 
buffer (ADB250, Ventana Medical System Inc., 
Roche Diagnostics). SMI-311 and SMI-312 are anti-
body cocktails that target neurofilament heavy  
(NF-H) and medium (NF-M) chain proteins (Ulfig et 
al., 1998). SMI-311 recognizes non-phosphorylated 
epitopes and therefore primarily stains dendrites 
and perikarya, while SMI-312 targets the highly 
phosphorylated epitopes predominantly found in 
axons. The detection was performed using the ultra-
View Universal DAB Detection Kit (760-500, Roche 
Diagnostics). Hematoxylin and Bluing reagent  
(760-2021, 760-2037, Roche Diagnostics) were used 
as a nuclear counterstain. Digital images of the 
stained sections were captured at 40X as whole slide 
images (WSIs) using the Aperio GT450 high-resolu-
tion scanner (Leica Biosystems). WSIs were viewed 
using the default display settings in QuPath (v. 
0.4.3). 

Table 1: List of antibodies used in this study. 

Antibody Company Catalog # Dilution 

Vimentin (V9) Roche, Cell Marque 05278139001 2.5 ug/ml 

GFAP (EP672Y) Roche, Cell Marque 5269784001 1 ug/ml 

SMI-311 BioLegend 837904 1/1000 

SMI-312 BioLegend 837801 1/1000 

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For the H&E- and immunohistochemically 
stained WSIs, we first performed a qualitative  
assessment of preservation quality, examining the 
images for whether cell membrane morphology  
appeared intact across samples and also for  
common postmortem artifacts. For semi-quantita-
tive grading of the samples, two raters collabora-
tively evaluated each sample and decided upon  
consensus grades. Perfusion quality on H&E staining 
was graded on a 0-3 scale by examining for the  
presence of intravascular material (including blood 
cells) across the WSI, with 0 indicating minimal intra-
vascular material and 3 indicating extensive intra-
vascular material. This analysis was done with the 
raters blinded to the preservation method used. We 
attempted to perform a grading scale for Glial  
Fibrillary Acidic Protein (GFAP), SMI-311, and  
SMI-312 immunostaining. However, for GFAP  
immunostaining, we determined that variability in 
staining could reflect multiple factors, including  
pre-mortem influence, the region sampled, and the 
fixation time, making it unsuitable as a reliable  
metric for preservation quality assessment. For  
SMI-311 and SMI-312, we were unable to identify 
enough variability between the samples, as  
they all appeared to have robust and consistent  

immunoreactivity, with the exception of SMI-311 for 
the two canine samples, which had negligible  
immunostaining. 

Results 

Preservation quality in electron microscopy images 

Our cohort consisted of nine human brains and 
one canine brain, which we selected following their 
preservation to have a wide range of PMIs, from 1.5 
hours to 4 days (Table 2). For each brain, small  
samples were obtained from the grey matter of the 
sensorimotor cortex and thalamus. 

Qualitatively, we observed varying degrees of 
ultrastructural preservation across the specimens. 
Across all samples, we detected several artifacts 
commonly found in postmortem brain tissue,  
including cellular swelling and shrinkage, vacuoliza-
tion, myelin disbanding, and partially disrupted cell 
membranes whose potential shapes could still be at 
least partially distinguished (Krassner et al., 2023). 
The canine brain, which had the shortest PMI of 1.5 
hours, was found to have the lowest burden of these 
postmortem artifacts. 

Table 2: Characteristics of brain donors included in this study. 

Donor ID Age Sex PMI Reported cause of death Preservation method Fixation time 

7 78 Male 4.25 hours Cancer* Perfusion fixation 5 months 

30 77 Male 17 hours Kidney failure, failure to thrive  Perfusion fixation 4 months 

34 88 Male 20 hours Cancer* Perfusion fixation 4 months 

37 70 Male 72 hours Myocardial infarction Perfusion fixation 4 months 

55 70 Male 36 hours Cardiac causes Perfusion fixation 3 months 

57 75 Male 96 hours Leukemia Immersion fixation 3 months 

59 41 Female 91 hours Leukemia  Perfusion fixation 2.5 months 

65 17** Female 1.5 hours Euthanasia (Donated canine) Perfusion fixation 2 months 

66 89 Female 61 hours Sepsis and acute renal failure Perfusion fixation 2 months 

78 89 Male 2.5 hours Failure to thrive Perfusion fixation 1 month 

Fixation time refers to the amount of time in 10 % neutral buffered formalin at 4 °C. *: This donor utilized medical aid in dying (MAID) for 
end-of-life care. **: Canine brain. PMI: Postmortem interval 

  

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We next performed fine-scale manual  
annotation of ultrastructural components in the  
images (Figure 1). To assess the reproducibility of 
our annotation approach, two independent raters 
annotated the same image, which was from the  
cortex sample of donor #66. Inter-rater reliability 

was quantified by calculating the Dice similarity  
coefficient for each pair of matching polygons,  
yielding a median Dice score of 0.79 (Figure 2). In 
one high-magnification image from each unique 
sample, we also quantified the percentage of area 
occupied by AIZs (Figure 3, Table 3).

 
Figure 1. Fine-scale annotation of ultrastructural components in one representative EM image from the cortex of donor #7. Color coding 
identifies distinct cellular structures: Green: membrane-bound structures with electron-dense interior (e.g., organelle-rich neurites);  
Purple: membrane-bound structures with electron-lucent interior (e.g., swollen astrocytic processes); Blue: myelinated axons; Yellow: cell 
bodies. Non-colored regions represent ambiguous interstitial zones (AIZs) that lack clearly defined membrane boundaries. Upper scale 
bar: 2 µm. Lower scale bar: 1 µm. 

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Figure 2. Overlap of annotations of a sample from the cortex of donor #66 by independent annotators. The top and middle image were 
done by two independent annotators. The bottom image is a combination of the overlays to compare how alike the two annotations are. 
Color coding identifies distinct cellular structures: Green: membrane-bound structures with electron-dense interior (e.g., organelle-rich 
neurites); Purple: membrane-bound structures with electron-lucent interior (e.g., swollen astrocytic processes); Blue: myelinated axons; 
Yellow: cell bodies. Non-colored regions represent ambiguous interstitial zones (AIZs) that lack clearly defined membrane boundaries. 
Scale bars: 1 µm. 

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Figure 3. Fine-scale manual annotation of ambiguous interstitial zones (AIZs) from one EM image across all samples. Samples are sorted 
by the percentage of ambiguous interstitial zones (AIZs), from the lowest to the highest: 7-C (a), 37-T (b), 34-C (c), 65-C (d), 59-C (e), 55-C 
(f), 37-C (g), 78-C (h), 57-C (i), 30-C (j), 65-T (k), 57-T (l), 55-T (m), 78-T (n), 30-T (o), 34-T (p), 66-C (q), 7-T (r), 66-T (s), 59-T (t), where the 
number is the donor ID number, and then “-T” indicates that it is from the thalamus and “-C” from the cortex. Color coding identifies 
distinct cellular structures: Green: membrane-bound structures with electron-dense interior (e.g., organelle-rich neurites); Purple:  
membrane-bound structures with electron-lucent interior (e.g., swollen astrocytic processes); Blue: myelinated axons; Yellow: cell bodies. 
Non-colored regions AIZs that lack clearly defined membrane boundaries. Scale bars: 500 nm. 
  

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Table 3: Summary of tissue preservation quality metrics by donor and brain region. 

Donor ID PMI Fixation time Region AIZ percentage (in 
one annotated image) 

Percentage of images with AIZ 
artifacts (count/total) 

7 4.25 hours 5 months 
Thalamus 37.18 % 100 % (5/5) 

Cortex 7.97 % 0 % (0/5) 

30 17 hours 4 months 
Thalamus 33.14 % 100 % (5/5) 

Cortex 17.76 % 100 % (5/5) 

34 20 hours 4 months 
Thalamus 34.79 % 80 % (4/5) 

Cortex 8.91 % 60 % (3/5) 

37 72 hours 4 months 
Thalamus 8.46 % 100 % (5/5) 

Cortex 10.61 % 0 % (0/5)  

55 36 hours 3 months 
Thalamus 24.51 % 100 % (5/5) 

Cortex 17.52 % 100 % (5/5) 

57 96 hours 3 months 
Thalamus 21.51 % 20 % (1/5) 

Cortex 17.52 % 40 % (2/5) 

59 91 hours 2.5 months 
Thalamus 40.44 % 100 % (5/5) 

Cortex 11.29 % 100 % (5/5) 

65 1.5 hours 2 months 
Thalamus 20.95 % 0 % (0/5) 

Cortex 9.57 % 0 % (0/5)  

66 61 hours 2 months 
Thalamus 39.37 % 100 % (5/5) 

Cortex 35.31 % 20 % (1/5) 

78 2.5 hours 1 month 
Thalamus 27.49 % 100 % (5/5) 

Cortex 15.65 % 40 % (2/5) 

The “AIZ percentage” column shows the proportion of area occupied by AIZs in one high magnification, annotated EM image, representing 
electron-lucent, non-membrane-bound regions that may contain degraded cellular structures. The “Percentage of images with AIZ  
artifacts” column indicates how many EM images were graded as having AIZ artifacts, with the raw number of affected images shown in 
parentheses (out of 5 total images evaluated per sample). PMI: Postmortem interval; AIZ: Ambiguous interstitial zone. 

We next developed a grading method to rate 
EM images for AIZs that could both be performed 
more rapidly by trained annotators and could also 
take into account the degree of cell membrane  
intactness. Specifically, the images were graded as 
having AIZ artifacts if they displayed both (a)  
extensive AIZs and (b) poor delineation of cellular 
membrane boundaries (Figure 4). This combined  
assessment is meant to distinguish artifactual AIZs 
from potential scenarios with non-artifactual extra-
cellular space expansion. The frequency of images 
meeting these criteria for having AIZ artifacts was 
calculated for each sample (Table 3). We found that 

samples from a donated canine preserved after a 
PMI of 1.5 hours yielded EM images with no AIZ  
artifacts in either brain region. The brains from two 
of the human donors, one with a PMI of 4.25 hours 
(donor #7) and one with a PMI of 72 hours (donor 
#37), also yielded EM images with no AIZ artifacts in 
the cortical samples, but both of these brains had 
AIZ artifacts detected in images from the thalamus 
samples. The cortex and thalamus samples from the 
other 7 brains produced EM images graded as  
having AIZ artifacts in at least one of the five  
available EM images. 

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Figure 4. Representative EM images graded as having or not having ambiguous interstitial zone (AIZ) artifacts. Five examples images are 
shown that were graded as having AIZ artifacts: 30-T (b), 39-C (d), 59-C (f), 59-T (h), 66-T (j), as well as five examples that were not: 7-C 
(a), 57-C (c), 65-C (e), 65-T (g), 66-C (i), where the number is the donor ID number, and then “-T” indicates that it is from the thalamus and 
“-C” from the cortex. Scale bars: 1 µm. 

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We found that there was no significant rank 
correlation between the PMI and the annotated AIZ 
percentage in the images from either the cortex  
(rho = 0.35, p = 0.327) or the thalamus (rho = 0.09,  
p = 0.811). Similarly, we found no significant rank 
correlation between the PMI and the percentage of 
images graded as having AIZ artifacts in the samples 
from either the cortex (rho = 0.27, p = 0.454) or the 
thalamus (rho = 0.10, p = 0.790). We also found that 
there was no significant rank correlation between 
the fixation time and either of these metrics related 
to the percentage of AIZs in either brain region (all 
p-values > 0.1). Next, we found that there was a  
significantly higher annotated AIZ percentage in  
images from the thalamus than the cortex (mean in 
thalamus = 28.8 %, mean in cortex = 15.2 %, t-test  

p-value = 0.004). This result may reflect differences 
in preservation quality, baseline differences  
between the regions, or other factors. There was 
also a non-significant regional trend in the  
percentage of images graded as having AIZ artifacts,  
which was higher in the thalamus than the cortex  
(mean in thalamus = 80 %, mean in cortex = 46 %,  
t-test p-value = 0.074). 

We next performed a qualitative analysis of  
the ssTEM data, which was derived from cortical  
samples. First, synapses were identified in the  
available image stacks, all of which could be traced 
through the image stack until synapse termination 
or the end of the image stack, without apparent loss 
of structure (Figure 5). Next, we attempted to trace 

 
Figure 5. Representative images in the serial section TEM data sets showing that synapses can be traced. Samples from the cortex of 
donor IDs #7 (a), #35 (b), #65 (c). Synapses are highlighted in color. Scale bars: 1 µm. 

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Figure 6. Representative serial section image stack with annotations for afferent neurites from one synapse. All images are from a serial 
section from the cortex sample of donor #65. Scale bars: 1 µm. 

the neural connections arising from synapses to 
their associated dendrites and axons across the  
image stacks. Qualitatively, we found that for the 
sample from donor #35, which had a more extensive 
burden of AIZ artifacts on the 2D EM images, it was 
more difficult to manually trace the neurite  
structures. For the other two samples imaged with 
ssTEM (donor IDs #7 and #65), we successfully  

identified traceable neurites across the image stack 
in at least some instances (for example, Figure 6). 
However, we were unable to rigorously quantify the 
traceability due to two key limitations: (a) an  
insufficient sample size to establish reliable  
metrics, and (b) technical constraints related  
to our section thickness. Specifically, the resolution 
between sequential images made it challenging to  

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differentiate between potential structural damage 
and normal morphological variations where  
processes might naturally terminate or significantly 
change direction. 

Preservation quality in light microscopy images 

We next set out to compare preservation  
quality between modalities. We started by perform-
ing an analysis of H&E-stained light microscopy  
sections. These samples were obtained from the 
contralateral hemisphere of the same brain  
regions that were examined by electron microscopy. 
We detected expected postmortem changes in  
all images, including pericellular rarefactions,  
perivascular rarefactions, and neuropil vacuolization 
(Krassner et al., 2023). Qualitatively, the extent of 
pericellular rarefaction and neuropil vacuolization 
appeared to potentially be more pronounced in 
some cases with longer PMIs. However, no obvious 
differences in the preservation quality of cell  
membrane morphology were observed that  
corresponded with the PMI on these H&E-stained 
images (Figure 7). Additionally, the postmortem  
artifacts visualized did not have obvious qualitative 
differences based on the fixation time. Taken  
together, these findings suggest that basic cellular 
morphology remains largely intact at the light  
microscopy level in the samples from these brains, 
despite the range of PMIs. 

Notably, in cases where perfusion fixation was 
performed, the extent to which perfusate was  
successfully delivered to the brain regions examined 
varied across cases, as evidenced by differences in 
brain stiffness and the extent of blood clearance 
from surface vessels. This variability is consistent 
with previous findings on postmortem brain  
perfusion (McFadden et al., 2019). As one additional 
way to measure this, we assessed H&E-stained  
images to measure the degree to which blood  
vessels were cleared of material such as red blood 
cells (Figure 8, Table 4). These data demonstrate 
that blood vessels were not fully cleared, and  
therefore, perfusion was not complete, in the  

majority of the brains. This is further supported by 
the observation that the immersion-fixed brain  
(donor #57) had a similar grade for intravascular  
material clearance as several of the perfusion-fixed 
samples. To address a possible confounding  
variable, we also found that there was no significant 
rank correlation between the fixation time and the 
intravascular material grade on the H&E images, in 
the data from either the cortex (rho = 0.04,  
p = 0.92) or the thalamus (rho = 0.24, p = 0.51). 
Taken together, these results suggest that in cases 
where a perfusion procedure was performed, the 
fixative may not have fully penetrated the  
vasculature throughout the brain, perhaps instead 
only traversing through a subset of blood vessels. 

We next performed immunohistochemical 
staining to evaluate the preservation of specific  
neural components across our samples.  
Staining for SMI-312, a pan-axonal stain targeting 
highly phosphorylated neurofilaments, revealed  
consistent preservation of axonal architecture 
across samples with varying PMIs (Figure 9) (Ulfig et 
al., 1998). Even in samples with PMIs exceeding 60 
hours, we observed well-defined axonal processes 
with clear continuity and distinct morphology. In the 
cortical samples, neurofilament-positive axons were 
readily identifiable traversing throughout the  
neuropil, with minimal disruption of their trajectory 
detected on qualitative analysis. 

Staining for SMI-311, an antibody targeting 
non-phosphorylated neurofilaments that are  
primarily located in the dendrites and perikarya, also 
revealed consistent staining quality across samples 
with varying PMIs (Figure 10) (Ulfig et al., 1998). 
Dendritic morphology appeared to be largely intact, 
without the diffuse staining that would be expected 
with widespread breakdown of the dendritic  
cytoskeleton. A key exception was the canine brain, 
which did not stain adequately for this antibody in 
either brain region, possibly reflecting molecular  
differences in neurofilaments between human and 
canine brains (Dimakopoulos and Mayer, 2002). 

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Figure 7. Representative H&E-stained images demonstrate that cell membrane morphology is generally intact across a wide range of 
PMIs. Samples from the thalamus of donor IDs #7 (a, b), #65 (c, d), #57 (e, f), and #59 (g, h) with PMIs of 4.25 h, 1.5 h, 96 h, and 91 h, 
respectively. Insets on the lower magnification images correspond to the regions shown in the higher magnification images. Scale bars: 
(a, c, and g) 1 mm; (e) 2 mm; (b, d, f, and h) 50 μm. 

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Figure 8. Representative H&E-stained images from the thalamus showing variable vascular clearance. a, b: Images from donor #30 show 
extensive intravascular material. c, d: Images from donor #59 show minimal intravascular material. Scale bars: (a, c) 2 mm; (b, d) 200 μm. 

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Figure 9. Representative SMI-312-stained images demonstrate that axonal morphology is generally intact across a wide range of PMIs. 
Samples from the thalamus of donor IDs #65 (a), #78 (b), #7 (c), #37 (d), #59 (e), and #57 (f) with PMIs of 1.5 h, 2.5 h, 4.25 h, 72 h, 91 h, 
and 96 h, respectively. Scale bars: 50 μm. 

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Figure 10. Representative SMI-311-stained images demonstrate that dendritosomatic morphology on light microscopy is generally intact 
across a wide range of PMIs in human brains. Samples from the thalamus of donor IDs #78 (a), #7 (b), #30 (c), #37 (d), #59 (e), and #57 (f) 
with PMIs of 2.5 h, 4.25 h, 17 h, 72 h, 91 h, and 96 h, respectively. Scale bars: 50 μm. 
  

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Table 4: Semi-quantitative grades to evaluate preservation quality on light microscopy. 

Donor ID PMI Fixation time Region Intravascular material grade on H&E images 

7 4.25 hours 5 months 
Thalamus 1 

Cortex 1 

30 17 hours 4 months 
Thalamus 3 

Cortex 1 

34 20 hours 4 months 
Thalamus 2 

Cortex 2 

37 72 hours 4 months 
Thalamus 2 

Cortex 2 

55 36 hours 3 months 
Thalamus 2 

Cortex 1 

57 96 hours 3 months 
Thalamus 2 

Cortex 2 

59 91 hours 2.5 months 
Thalamus 0 

Cortex 2 

65 1.5 hours 2 months 
Thalamus 2 

Cortex 1 

66 61 hours 2 months 
Thalamus 2 

Cortex 2 

78 2.5 hours 1 month 
Thalamus 1 

Cortex 1 

The presence of intravascular material was graded on a scale of 0–3, where 0 indicates minimal intravascular material and 3 indicates 
extensive intravascular material. PMI: Postmortem interval. 

 
We next assessed immunostaining for the  

astrocyte marker GFAP (Figure 11). In samples from 
the thalamus, we observed that GFAP staining was 
generally lower compared to the cortical samples, 
with the exception of the subependymal area, which 
consistently showed higher immunoreactivity. In the 
cortical samples, the subpial area consistently had 
the highest density of staining, which is expected 
given previous findings about GFAP staining  
patterns (Halliday et al., 1996). The density of GFAP 
staining in the cortex appeared to be lower in some 
cases with longer PMIs, which had very few  
astrocytes stained by anti-GFAP (for example, see 
Figure 11e). However, there was no robust trend for 
lower GFAP staining with longer PMIs, as evidenced 

by strong staining in some samples that had  
relatively longer PMIs, such as one brain with  
a PMI of 96 hours (Figure 11f). Moreover, when  
GFAP-positive astrocytes were visible in the longer 
PMI cases, the individual cells that were stained  
appeared to still have intact morphology without 
obvious signs of partial decomposition, arguing 
against cellular decomposition playing the major 
role in mediating staining differences. However, 
given our relatively small sample size, we cannot 
clearly distinguish the reasons for variability in GFAP 
staining across samples. 

In a subset (n = 6) of the samples, we also per-
formed immunostaining with vimentin (see data 

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availability for access to these WSIs). While this 
marker did stain around blood vessels, its staining 
for astrocytes appeared highly sensitive to the  
duration of fixation, more so than GFAP, showing 

only weak and inconsistent staining in samples fixed 
for longer than one month. Due to this limitation of 
vimentin staining, we did not extend the vimentin 
staining to the full cohort.

 

Figure 11. Representative GFAP-stained images of the cortex show intact subpial astrocyte morphology in images from samples with a 
wide range of PMIs. Samples from donor IDs #65 (a), #78 (b), #7 (c), #37 (d), #59 (e), and #57 (f) with PMIs of 1.5 h, 2.5 h, 4.25 h, 72 h, 91 
h, and 96 h, respectively. Scale bars: 50 μm. 

  

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Discussion 

In this study, we first present a framework for 
evaluating preservation quality in postmortem brain 
tissue through the assessment of ultrastructural  
integrity in EM images. We found that AIZ artifacts 
occurred in at least one of the available EM images 
from our tested samples, with the exception of a  
canine sample with a relatively shorter PMI of 1.5 
hours and two cortical samples from human donors. 
Notably, in the cortical sample from the canine and 
one of these two human cortical samples, we were 
able to trace the neurites arising from synapses 
across ssTEM image stacks in some instances, 
though technical limitations and insufficient sample 
volumes prevented rigorous quantification. Our  
observations suggest that samples without AIZ  
artifacts on 2D images may be a proxy for the degree 
of ultrastructural integrity that could potentially 
support connectomics studies, though this  
requires more imaging and larger sample sizes for  
corroboration. We also detected a trend towards a 
higher percentage of AIZs in thalamic samples  
compared to cortical ones. Given that our perfusion 
quality was far from perfect, these observed  
regional differences could be due to the deeper  
thalamic structures being preserved more slowly by 
the post-perfusion immersion fixation of the entire 
brain, potentially leading to a longer period of  
autolysis prior to preservation. Alternatively, the  
result may also be due to statistical noise, baseline 
differences between the regions, or other factors. 
Next, we performed light microscopy on samples 
from the same brains, using both non-specific  
morphological staining as well as immunostaining 
for neurofilaments and GFAP. The subjective quality 
of the morphological staining and neurofilament 
staining appeared similar across samples from all 10 
brains, despite the varying PMIs and differences  
observed on EM images. Our data suggests a  
complex relationship between the imaging findings 
and the underlying tissue preservation depending 
on the imaging modality used, which warrants  
further investigation. 

Although our study identified several  
challenges in this field, it is important to emphasize 
the significant potential value that EM-based  
connectomics could provide. While a complete  
human brain connectome remains technologically 

unfeasible, volume EM imaging of targeted brain  
regions or circuits could complement emerging 
whole-brain volumetric methods (Hillman et al., 
2019). Such focused volume EM studies could  
be particularly valuable for investigating disease-
specific alterations in synaptic connectivity patterns. 
For example, alterations in dendritic spine density 
and synaptic connectivity have been reported in 
schizophrenia, which has potentially significant  
implications for the development of treatments for 
this disorder (Glausier and Lewis, 2013). However, 
pharmaceutical companies may not be confident 
enough in existing ultrastructural biomarkers of  
disease to pursue them as therapeutic targets, as 
these findings have often been primarily reported in 
relatively small tissue samples and in studies with 
modest sample sizes. Studies with larger volumes 
and larger sample sizes may be useful to corroborate 
existing ultrastructural correlates of disease and  
discover new ones, which could potentially be 
achieved through the improved use of banked brain 
samples. 

An important variable in brain banking is the 
agonal state of the donor, which includes factors 
such as fever, hypoxia, acidosis, and alterations in 
metabolism. Variability in the agonal state is often 
found to have an even larger effect on brain tissue 
quality than the PMI, and can affect cellular  
morphology (Williams et al., 1978; Hardy et al., 
1985; Ohm and Diekmann, 1994; Paasila et al., 
2019). In addition to the direct effect on brain  
structure, a prolonged or severe agonal phase is 
likely to lead to the accumulation of thrombi and 
other factors promoting impairment of postmortem 
perfusion of the brain (McFadden et al., 2019). We 
note that the canine brain sample was donated after 
the canine was euthanized by a licensed  
veterinarian, which entails effectively a negligible 
agonal duration. This is likely another reason that 
this brain had the highest ultrastructural quality, in 
addition to the shorter PMI. Although the agonal 
state is more difficult to quantify than the PMI, a 
better understanding of how the agonal state  
affects the quality of the tissue for downstream  
research applications is a critical goal for brain  
banking, in order to make the field more rigorous. 

There is an extensive literature on the visuali-
zation of extracellular space in brain tissue, with 

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many aspects of the preservation procedure,  
including the delivery technique, fixative, buffer, 
and osmolarity, all significantly affecting it (Van 
Harreveld and Malhotra, 1967; Cragg, 1980; Fix and 
Garman, 2000; Korogod et al., 2015; Fulton and 
Briggman, 2021). Living brain tissue generally  
contains around 20 % extracellular space (Nicholson 
and Syková, 1998). Standard methods of perfusion 
fixation in laboratory animals, which involve a  
minimal duration of ischemia prior to preservation, 
can decrease the extracellular space (ECS) in an  
artifactual manner from its typical in vivo volume 
(Pallotto et al., 2015). Our findings suggest that  
although there may be an initial decrease in the ECS 
from in vivo levels with minimal PMI, which may  
involve ischemic cell swelling, as the PMI progresses, 
the ECS may once again grow to in vivo levels and 
beyond as fluid redistributes. Indeed, one would  
expect that given a sufficiently long PMI, the brain 
would be entirely “extracellular,” as all of the  
cellular structures would eventually break down and 
the brain liquefy. Although we expect that molecular 
decomposition and fluid redistribution are the most 
likely explanation for AIZs, there are several  
non-mutually exclusive explanations for the AIZs we 
observed in our samples with longer PMIs. Some  
degree of extracellular space is expected even in  
ideally preserved tissue, and may in fact be desirable 
as this better reflects in vivo conditions and can aid 
in neurite tracing (Korogod et al., 2015; Pallotto et 
al., 2015). However, the appearance of potential  
debris alongside the expansion of the extracellular 
space suggests a significant change from normal  
tissue architecture. This is why our grading method 
for AIZ artifacts takes into account both the  
presence of AIZs and a qualitative determination of 
poor cell membrane intactness. 

One notable pattern we observed in our data is 
that the occurrence of AIZ artifacts qualitatively  
appears to coincide with other postmortem changes 
involving fluid shifts. For example, images with AIZ 
artifacts also tend to exhibit increased astrocyte 
process swelling, vacuolization, and cytoplasmic 
washout. This pattern is evident in both our images 
and in other publicly available electron microscopy 
data sets of postmortem human brain tissue (Oost 
et al., 2023). These observations suggest that there 
may be a generalized “excess fluid” phenomenon in 
some postmortem brain tissue, with AIZ artifacts  

being just one manifestation of this. Theoretically, 
one possibility is that it may be possible to develop 
sample preparation, staining, or analysis methods 
that can partially adjust for the consequences of  
excessive fluid accumulation, including AIZ  
artifacts, potentially allowing for inference of neural  
morphology despite these artifacts. A previous  
approach to address extracellular space shrinkage in 
EM images classified the space into sheet-like and 
tunnel-like regions, then used computational  
models to redistribute volume between these  
compartments (Kinney et al., 2013). However, it is 
highly questionable that approaches designed for 
controlled shrinkage artifacts could be sufficient for 
adjustment of postmortem brain EM images, as the 
AIZ artifacts present are anisotropic, haphazard, and 
enigmatic. Instead, more complex computational 
approaches, developed in consideration of the  
physiology of agonal and postmortem degradation, 
would likely be required, to the extent that it is  
feasible at all. 

Our light microscopy findings provide  
complementary data to help interpret the EM  
results. H&E and immunohistochemical staining  
revealed relatively well-preserved cellular  
morphology in samples from the same brains that 
had substantial changes on EM images. Particularly 
notable was the integrity of neurofilament staining, 
which allowed for visualization of axonal and  
dendritic trajectories across substantial distances 
despite varying PMIs. This is consistent with  
previous data showing the robustness of  
neurofilament antigen staining to extended PMI 
(Ulfig et al., 1998; Blair et al., 2016; Bouvier et al., 
2016). As a result, our findings corroborate previous 
observations that electron microscopy is more  
sensitive to postmortem changes than light  
microscopy (Krassner et al., 2023). One obvious  
potential explanation for this difference is simply 
that EM has better resolution and is therefore better 
able to detect early, minute aspects of tissue  
decomposition. It is also possible that relative  
differences in the sensitivity of light microscopy and 
EM staining procedures to postmortem changes 
could help to explain the inconsistency between the 
modalities. For example, osmium tetroxide, a key 
staining agent for EM, has been found to bind  
primarily to unsaturated fatty acids arranged in lipid 
membranes (Wigglesworth, 1957, 1981; Belazi et al., 

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2009; Li et al., 2024). Autolysis causes a rapid  
release and redistribution of membrane lipids,  
including unsaturated fatty acids, via the activity of  
phospholipase A2 (van der Vusse et al., 1989; Pueyo 
et al., 2000). If unsaturated fatty acids in lipid  
membranes degrade relatively faster than proteins 
in the PMI, then this would disproportionately affect 
visualization following standard EM protocols,  
compared to other methods that target protein  
antigens. Notably, previous data has found that the 
more lipid-dense myelinated axons are more  
recognizable than unmyelinated axons via EM after 
postmortem disintegration prior to fixation (Liewald 
et al., 2014). As another possibility, cellular  
structures might remain partially present during  
the postmortem period, but their constituent  
biomolecules could become insufficiently compact 
for adequate visualization by non-specific morpho-
logical stains alone. Immunostaining, in particular, 
may be better able to amplify partially intact  
structures and therefore not be affected as rapidly 
by the postmortem breakdown of gel-like  
biomolecular networks as the typical non-specific 
EM staining methods (Krassner et al., 2023). This 
possibility would parallel light microscopy  
studies on postmortem brain tissue, showing that 
immunostaining can sometimes reveal cellular 
structures not visible with non-specific morphologi-
cal stains (Monroy-Gómez et al., 2020). Further  
research using complementary methods, such as  
immunoelectron microscopy, correlative light and 
electron microscopy, or expansion microscopy, may 
help to clarify the reasons for the differences in  
results between light and electron microscopy. 

Several limitations should be considered when 
interpreting our findings. First, our sample size of 
ten brains obviously does not capture the full  
spectrum of preservation quality variation seen in 
brain banking. Information about the donors, such 
as the PMI, may have inaccuracies, which becomes 
a bigger problem with smaller sample sizes. As a  
result, our findings will require larger subsequent 
studies for corroboration. Second, our analysis of 
the contralateral hemispheres for light and electron 
microscopy introduces obvious potential confound-
ing factors. Preservation quality, including the  
quality of perfusion, can clearly vary between the 
hemispheres, which might affect our results. Third, 

although formaldehyde alone has been used  
successfully for fixation in some studies, others  
recommend the addition of glutaraldehyde  
(Gonzalez Aguilar and De Robertis, 1963; Westrum 
and Lund, 1966; Lewis et al., 2019). On initial fixation 
we used formaldehyde alone without the addition 
of glutaraldehyde, which may have reduced the  
ultrastructural quality of our resulting EM images. A 
future study comparing post-perfusion immersion 
fixation of small samples from the same brain with 
either paraformaldehyde-glutaraldehyde or neutral 
buffered formalin could directly test the relative 
contribution of fixative composition to ultrastruc-
tural preservation quality. Fourth, our semi-quanti-
tative grading systems for the EM and immunohisto-
chemically stained images represent a simplified  
assessment of complex data. Further, our analysis of 
the light microscopy images was largely qualitative, 
which renders this more vulnerable to bias. We  
encourage any interested readers to analyze the raw 
image data, all of which we have made available, to 
come to their own conclusions. Lastly, our study  
focused primarily on 2D ultrastructural features. The 
implications for 3D connectivity reconstruction  
remain speculative without more direct volumetric 
data and analysis. These limitations highlight the 
need for future studies with larger sample sizes and 
more direct comparisons via multiple imaging  
techniques. 

Conclusions 

Our study provides insights into the  
relationship between preservation quality, PMI, and 
imaging modality in banked brain tissue. We found 
that the level of ultrastructural preservation  
required for performing connectomics studies  
appears to be achievable in some postmortem  
samples. These findings suggest that under close to 
optimal brain banking conditions, postmortem  
human brain tissue could potentially be suitable for 
connectomics studies using current EM methods. 
However, in at least a subset of EM images from the 
other samples, our analysis revealed the presence of 
AIZ artifacts, which may indicate significant  
challenges for the reliable tracing of neural  
processes. These AIZ artifacts may result from true 
structural degradation prior to fixation, inadequate 

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visualization of thin axons and other cellular  
components, or both. Notably, our light microscopy 
data from these same brains indicates that many 
cellular structures remain intact and potentially 
traceable at this level of resolution via  
neurofilament staining. This suggests a difference 
between preservation quality as observed via  
different imaging modalities. However, this is not 
necessarily surprising, because while both light and 
electron microscopy can provide windows into cell 
membrane morphology, they examine structures at 
different resolutions and thus can be considered 
complementary. To advance connectomics research 
using banked brain tissue, further methodological 
development may be valuable. Current approaches 
can only reliably visualize key ultrastructural  
features in a small subset of banked brain samples, 
constraining the possible sample sizes. It is not yet 
clear if these are the true biological limits to ultra-
structural visualization. Future research could  
focus on optimizing fixation protocols, staining  
techniques, and computational methods specifically 
for postmortem brain tissue. Such research may be  
critical for realizing the full potential of human brain 
connectomics as a tool for understanding neural  
circuit organization in both health and disease. 

Author contributions 

A.K., M.G., K.F., J.C., and A.T.M. conceptualized 
the article. A.S. and W.J. performed electron  
microscopy experiments. E.T. and C.D.S. performed 
light microscopy experiments. A.K., M.G., and 
A.T.M. performed data analysis. A.T.M. wrote the  
initial draft of the manuscript. All authors reviewed 
the manuscript. All authors approved the final  
manuscript. 

Acknowledgements 

We would like to acknowledge the technical  
assistance of Laura Paredes and Alexander Parra, 

and we would like to thank Kenneth Hayworth for 
helpful personal communications on this topic. We 
acknowledge the Neuropathology Brain Bank &  
Research CoRE at the Icahn School of Medicine at 
Mount Sinai for their histology and tissue processing 
services. Electron microscopy tissue preparation 
and imaging were performed at The Microscopy and 
Advanced Bioimaging CoRE at the Icahn School of 
Medicine at Mount Sinai. The Icahn School of  
Medicine at Mount Sinai provided access to library 
resources. 

Funding statement 

This work was supported by the Rainwater 
Charitable Foundation as well as NIH grants P30 
AG066514, K01 AG070326, RF1 AG062348, P30 
AG066514, RF1 NS095252, U54 NS115266, and RF1 
MH128969. The funders had no role in the design of 
the study or in the collection or interpretation of the 
data. 

Conflict of interest statement 

Alicia Keberle, Macy Garrood, and Andrew 
McKenzie are employees of Oregon Brain  
Preservation, a non-profit brain preservation  
organization. Andrew McKenzie is a director of Apex 
Neuroscience, a non-profit research organization. 

Data availability 

Code used for data analysis is available here: 
https://github.com/andymckenzie/Ultrastructure_ 
quality_manuscript. All raw image data can be  
accessed in a public repository on Zenodo, available 
here: https://zenodo.org/communities/evaluating 
ultrastructuralpreservationqualityinbankedbraintis-
sue/ 

  

https://doi.org/10.17879/freeneuropathology-2025-6763
https://github.com/andymckenzie/Ultrastructure_quality_manuscript
https://github.com/andymckenzie/Ultrastructure_quality_manuscript
https://zenodo.org/communities/evaluatingultrastructuralpreservationqualityinbankedbraintissue/
https://zenodo.org/communities/evaluatingultrastructuralpreservationqualityinbankedbraintissue/
https://zenodo.org/communities/evaluatingultrastructuralpreservationqualityinbankedbraintissue/


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DOI: https://doi.org/10.17879/freeneuropathology-2025-6763 page 25 of 27 
 
 

 

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https://doi.org/10.17879/freeneuropathology-2025-6763
https://doi.org/10.1016/s0046-8177(87)80243-5
https://doi.org/10.1242/jcs.1.2.229
https://doi.org/10.1016/0040-8166(81)90035-5
https://doi.org/10.1098/rspb.1957.0043
https://doi.org/10.1097/00005072-197801000-00002

	Original Paper
	Abbreviations
	Introduction
	Methods
	Brain banking procedures
	Electron microscopy
	Light microscopy

	Results
	Preservation quality in electron microscopy images
	Preservation quality in light microscopy images

	Discussion
	Conclusions
	Author contributions
	Acknowledgements
	Funding statement
	Conflict of interest statement
	Data availability
	References

