Human Brain Research Articles

The sequence of acrania–exencephaly–anencephaly (AEAS)- An infrequent case report

Acrania–exencephaly–anencephaly sequence has an incidence of 3.6–5.4 for 10,000 live births and has been reported in literature. Exencephaly, described here is a defect of the neural tube which occurs due to the absence of closure of the neural fold. The main diagnostic ultrasound features include that are characterized by acrania, decreased size of cranial pole in comparison with the chest, irregular cranial surface, with increased amniotic fluid echogenicity due to the damaged brain tissue. Associated with amniotic band syndrome, Pentalogy of Cantrell, limb anomalies and ventral body wall defects. It is incompatible with life. Conducting programs training the budding neuro-sonographers about the knowledge in detection, diagnosis of NTD according to the Carnegie Classification is crucial to look forward in pathogenesis and application in the clinical scenario.

M1-type polarized macrophage contributes to brain damage through CXCR3.2/CXCL11 pathways after RGNNV infection in grouper.

The vertebrate central nervous system (CNS) is the most complex system of the body. The CNS, especially the brain, is generally regarded as immune-privileged. However, the specialized immune strategies in the brain and how immune cells, specifically macrophages in the brain, respond to virus invasion remain poorly understood. Therefore, this study aimed to examine the potential immune response of macrophages in the brain of orange-spotted groupers (Epinephelus coioides) following red-spotted grouper nervous necrosis virus (RGNNV) infection. We observed that RGNNV induced macrophages to produce an inflammatory response in the brain of orange-spotted grouper, and the macrophages exhibited M1-type polarization after RGNNV infection. In addition, we found RGNNV-induced macrophage M1 polarization via the CXCR3.2- CXCL11 pathway. Furthermore, we observed that RGNNV triggered M1 polarization in macrophages, resulting in substantial proinflammatory cytokine production and subsequent damage to brain tissue. These findings reveal a unique mechanism for brain macrophage polarization, emphasizing their role in contributing to nervous tissue damage following viral infection in the CNS.

Unveiling the Hidden Impact: Hematoma Volumes Unravel Circuit Disruptions in Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) imposes a significant burden on patients, and the volume of hematoma plays a crucial role in determining the severity and prognosis of ICH. Although significant recent progress has been made in understanding the cellular and molecular mechanisms of surrounding brain tissue in ICH, our current knowledge regarding the precise impact of hematoma volumes on neural circuit damage remains limited. Here, using a viral tracing technique in a mouse model of striatum ICH, two distinct patterns of injury response were observed in upstream connectivity, characterized by both linear and nonlinear trends in specific brain areas. Notably, even low-volume hematomas had a substantial impact on downstream connectivity. Neurons in the striatum-ICH region exhibited heightened excitability, evidenced by electrophysiological measurements and changes in metabolic markers. Furthermore, a strong linear relationship (R2 = 0.91) was observed between hematoma volumes and NFL damage, suggesting a novel biochemical index for evaluating changes in neural injury. RNA sequencing analysis revealed the activation of the MAPK signaling pathway following hematoma, and the addition of MAPK inhibitor revealed a decrease in neuronal circuit damage, leading to alleviation of motor dysfunction in mice. Taken together, our study highlights the crucial role of hematoma size as a determinant of circuit injury in ICH. These findings have important implications for clinical evaluations and treatment strategies, offering opportunities for precise therapeutic approaches to mitigate the detrimental effects of ICH and improve patient outcomes.

Spatial multi-omics at subcellular resolution via high-throughput in situ pairwise sequencing.

Technology for spatial multi-omics aids the discovery of new insights into cellular functions and disease mechanisms. Here we report the development and applicability of multi-omics in situ pairwise sequencing (MiP-seq), a method for the simultaneous detection of DNAs, RNAs, proteins and biomolecules at subcellular resolution. Compared with other in situ sequencing methods, MiP-seq enhances decoding capacity and reduces sequencing and imaging costs while maintaining the efficacy of detection of gene mutations, allele-specific expression and RNA modifications. MiP-seq can be integrated with in vivo calcium imaging and Raman imaging, which enabled us to generate a spatial multi-omics atlas of mouse brain tissues and to correlate gene expression with neuronal activity and cellular biochemical fingerprints. We also report a sequential dilution strategy for resolving optically crowded signals during in situ sequencing. High-throughput in situ pairwise sequencing may facilitate the multidimensional analysis of molecular and functional maps of tissues.

ReMIND: The Brain Resection Multimodal Imaging Database

The standard of care for brain tumors is maximal safe surgical resection. Neuronavigation augments the surgeon’s ability to achieve this but loses validity as surgery progresses due to brain shift. Moreover, gliomas are often indistinguishable from surrounding healthy brain tissue. Intraoperative magnetic resonance imaging (iMRI) and ultrasound (iUS) help visualize the tumor and brain shift. iUS is faster and easier to incorporate into surgical workflows but offers a lower contrast between tumorous and healthy tissues than iMRI. With the success of data-hungry Artificial Intelligence algorithms in medical image analysis, the benefits of sharing well-curated data cannot be overstated. To this end, we provide the largest publicly available MRI and iUS database of surgically treated brain tumors, including gliomas (n = 92), metastases (n = 11), and others (n = 11). This collection contains 369 preoperative MRI series, 320 3D iUS series, 301 iMRI series, and 356 segmentations collected from 114 consecutive patients at a single institution. This database is expected to help brain shift and image analysis research and neurosurgical training in interpreting iUS and iMRI.

Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22–37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92–0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.

Anti-phasic oscillatory development for speech and noise processing in cochlear implanted toddlers.

Human brain demonstrates amazing readiness for speech and language learning at birth, but the auditory development preceding such readiness remains unknown. Cochlear implanted (CI) children (n = 67; mean age 2.77 year ± 1.31 SD; 28 females) with prelingual deafness provide a unique opportunity to study this stage. Using functional near-infrared spectroscopy, it was revealed that the brain of CI children was irresponsive to sounds at CI hearing onset. With increasing CI experiences up to 32 months, the brain demonstrated function, region and hemisphere specific development. Most strikingly, the left anterior temporal lobe showed an oscillatory trajectory, changing in opposite phases for speech and noise. The study provides the first longitudinal brain imaging evidence for early auditory development preceding speech acquisition.

MicroRNA-451 Regulates Angiogenesis in Intracerebral Hemorrhage by Targeting Macrophage Migration Inhibitory Factor.

Intracerebral hemorrhage (ICH) is a subtype of stroke with the highest fatality and disability rate. Up to now, commonly used first-line therapies have limited value in improving prognosis. Angiogenesis is essential to neurological recovery after ICH. Recent studies have shown that microRNA-451(miR-451) plays an important role in angiogenesis by regulating the function of vascular endothelial cells. We found miR-451 was significantly decreased in the peripheral blood of ICH patients in the acute stage. Based on the clinical findings, we conducted this study to investigate the potential regulatory effect of miR-451 on angiogenesis after ICH. The expression of miR-451 in ICH mouse model and in a hemin toxicity model of human brain microvascular endothelial cells (hBMECs) was decreased the same as in ICH patients. MiR-451 negatively regulated the proliferation, migration, and tube formation of hBMECs in vitro. MiR-451 negatively regulated the microvessel density in the perihematoma tissue and affected neural functional recovery of ICH mouse model. Knockdown of miR-451 could recovered tight junction and protect the integrity of blood-brain barrier after ICH. Based on bioinformatic programs, macrophage migration inhibitory factor (MIF) was predicted to be the target gene and identified to be regulated by miR-451 inhibiting the protein translation. And p-AKT and p-ERK were verified to be downstream of MIF in angiogenesis. These results all suggest that miR-451 will be a potential target for regulating angiogenesis in ICH.

The Time-Course of Food Representation in the Human Brain.

Humans make decisions about food every day. The visual system provides important information that forms a basis for these food decisions. Although previous research has focused on visual object and category representations in the brain, it is still unclear how visually presented food is encoded by the brain. Here, we investigate the time-course of food representations in the brain. We used time-resolved multivariate analyses of electroencephalography (EEG) data, obtained from human participants (both sexes), to determine which food features are represented in the brain, and whether focused attention is needed for this. We recorded EEG while participants engaged in one of two tasks. In one task the stimuli were task relevant, whereas in the other task the stimuli were not task relevant. Our findings indicate that the brain can differentiate between food and non-food items from approximately 112 milliseconds after stimulus onset. The neural signal at later latencies contained information about food naturalness, how much the food was transformed, as well as the perceived caloric content. This information was present regardless of the task. Information about whether food is immediately ready to eat, however, was only present when the food was task relevant and presented at a slow presentation rate. Furthermore, the recorded brain activity correlated with the behavioural responses in an odd-item-out task. The fast representation of these food features, along with the finding that this information is used to guide food categorisation decision-making, suggests that these features are important dimensions along which the representation of foods is organised.Significance statement The visual domain forms an important basis for food decisions. This study sheds light on how the human brain processes food. Our results provide evidence for factors such as food naturalness, transformation level, and perceived caloric content as key organising principles in the representational structure of foods. These factors are represented rapidly in the brain and are used by participants to make food categorisation decisions. Finally, this study highlights the potential of multivariate EEG analysis as a tool for investigating food processing in the human brain.

Utility of intracranial EEG networks depends on re-referencing and connectivity choice

Abstract Studies of intracranial EEG (iEEG) networks have been used to reveal seizure generators in patients with drug-resistant epilepsy. iEEG is implanted to capture the epileptic network, the collection of brain tissue that forms a substrate for seizures to start and spread. Interictal iEEG measures brain activity at baseline and networks computed during this state can reveal aberrant brain tissue without requiring seizure recordings. iEEG network analyses require choosing a reference and applying statistical measures of functional connectivity. Approaches to these technical choices vary widely across studies, and the impact of these technical choices on downstream analyses is poorly understood. Our objective was to examine the effects of different re-referencing and connectivity approaches on connectivity results and on the ability to lateralize the seizure onset zone in patients with drug-resistant epilepsy. We applied 48 pre-processing pipelines to a cohort of 125 patients with drug-resistant epilepsy recorded with interictal iEEG across two epilepsy centers to generate iEEG functional connectivity networks. 24 functional connectivity measures across time and frequency domains were applied in combination with common average re-referencing (CAR) or bipolar re-referencing (BR). We applied an unsupervised clustering algorithm to identify groups of pre-processing pipelines. We subjected each pre-processing approach to three quality tests: 1) the introduction of spurious correlations, 2) robustness to incomplete spatial sampling, and 3) the ability to lateralize the clinician-defined seizure onset zone. Three groups of similar pre-processing pipelines emerged: CAR pipelines, BR pipelines, and relative entropy-based connectivity pipelines. Relative entropy and CAR networks were more robust to incomplete electrode sampling than BR and other connectivity methods (Friedman test, Dunn-Sˇidák test p < 0.0001). BR reduced spurious correlations at non-adjacent channels better than CAR (Δ mean from machine ref = -0.36 vs -0.22), and worse in adjacent channels (Δ mean from machine ref = -0.14 vs -0.40). Relative entropy-based network measures lateralized the seizure onset hemisphere better than other measures in patients with temporal lobe epilepsy (BH-corrected p < 0.05, Cohen’s d: 0.60 - 0.76). Finally, we present an interface where users can rapidly evaluate iEEG pre-processing choices to select the optimal preprocessing methods tailored to specific research questions. The choice of preprocessing methods affects downstream network analyses. Choosing a single method among highly correlated approaches can reduce redundancy in processing. Relative entropy outperforms other connectivity methods in multiple quality tests. We present a method and interface for researchers to optimize their preprocessing methods for deriving iEEG brain networks.

MSC Promotes the Secretion of Exosomal lncRNA KLF3-AS1 to Regulate Sphk1 Through YY1-Musashi-1 Axis and Improve Cerebral Ischemia-Reperfusion Injury.

Stroke remains the 3rd leading cause of long-term disability globally. Over the past decade, mesenchymal stem cell (MSC) transplantation has been proven as an effective therapy for ischemic stroke. However, the mechanism of MSC-derived exosomal lncRNAs during cerebral ischemia/reperfusion (I/R) remains ambiguous. The oxygen-glucose deprivation/reoxygenation (OGD/R) and middle cerebral artery occlusion (MCAO) rat model were generated. MSCs were isolated and characterized by flow cytometry and histochemical staining, and MSC exosomes were purified and characterized by transmission electron microscopy, flow cytometry and Western blot. Western blot, RT-qPCR and ELISA assay were employed to examine the expression or secretion of key molecules. CCK-8 and TUNEL assays were used to assess cell viability and apoptosis. RNA immunoprecipitation and RNA pull-down were used to investigate the direct association between krüppel-like factor 3 antisense RNA 1 (KLF3-AS1) and musashi-1(MSI1). Yin Yang 1 (YY1)-mediated transcriptional regulation was assessed by chromatin immunoprecipitation and luciferase assays. The histological changes and immunoreactivity of key molecules in brain tissues were examined by H&E and immunohistochemistry. MSCs were successfully isolated and exhibited directionally differential potentials. MSC exosomal KLF3-AS1 alleviated OGD/R-induced inflammation in SK-N-SH and SH-SY5Y cells via modulating Sphk1. Mechanistical studies showed that MSI1 positively regulated KLF3-AS1 expression through its direct binding to KLF3-AS1. YY1 was identified as a transcription activator of MSI1 in MSCs. Functionally, YY1/MSI1 axis regulated the release of MSC exosomal KLF3-AS1 to modulate sphingosine kinase 1 (Sphk1)/NF-κB pathway, thereby ameliorating OGD/R- or cerebral I/R-induced injury. MSCs promote the release of exosomal KLF3-AS1 to regulate Sphk1 through YY1/MSI axis and improve cerebral I/R injury.

Crop Yield Prediction using CNN

Deep learning is a branch of Machine Learning which is completely based on artificial neural networks, as neural networks are going to mimic the human brain so deep learning is also a kind of mimic of the human brain. Farming is the main occupation of India. Crop yield has a direct impact on nation and international economies annually and the yield predicted plays a significant part in the food management and agriculture sector. The task is to build a prediction model for crop production . A prerequisite of intelligent systems has brought artificial neural networks to become a new technology which provides assorted solutions for complex problems in agriculture research. Performance of the agriculture sector mainly hinges on natural forces such as spatio-temporal distribution of rainfall, temperature, climate etc, with the result any deviation of monsoon from the normal pattern brings about numerous fluctuations in area and production. Crop yield has a direct impact on nation and international economies annually and the yield predicted plays a significant part in the food management and agriculture sector. The task is to build a prediction model for crop production. The basic principle of ANN architecture, Data Modeling for Prediction involves four stages namely historical data analysis (Descriptive), Data preprocessing, modeling of Data and Performance Estimation. First classify data based on different attributes. Regression analysis using CNN, it observes the relation between an independent (predictor) and dependent (target) variables. Based on relation training the model will predict crop yield production. application of ANN in predicting crop yield by using various crop performance features as input parameter

SLC22A17 as a Cell Death-Linked Regulator of Tight Junctions in Cerebral Ischemia.

Beyond neuronal injury, cell death pathways may also contribute to vascular injury after stroke. We examined protein networks linked to major cell death pathways and identified SLC22A17 (solute carrier family 22 member 17) as a novel mediator that regulates endothelial tight junctions after ischemia and inflammatory stress. Protein-protein interactions and brain enrichment analyses were performed using STRING, Cytoscape, and a human tissue-specific expression RNA-seq database. In vivo experiments were performed using mouse models of transient focal cerebral ischemia. Human stroke brain tissues were used to detect SLC22A17 by immunostaining. In vitro experiments were performed using human brain endothelial cultures subjected to inflammatory stress. Immunostaining and Western blot were used to assess responses in SLC22A17 and endothelial tight junctional proteins. Water content, dextran permeability, and electrical resistance assays were used to assess edema and blood-brain barrier (BBB) integrity. Gain and loss-of-function studies were performed using lentiviral overexpression of SLC22A17 or short interfering RNA against SLC22A17, respectively. Protein-protein interaction analysis showed that core proteins from apoptosis, necroptosis, ferroptosis, and autophagy cell death pathways were closely linked. Among the 20 proteins identified in the network, the iron-handling solute carrier SLC22A17 emerged as the mediator enriched in the brain. After cerebral ischemia in vivo, endothelial expression of SLC22A17 increases in both human and mouse brains along with BBB leakage. In human brain endothelial cultures, short interfering RNA against SLC22A17 prevents TNF-α (tumor necrosis factor alpha)-induced ferroptosis and downregulation in tight junction proteins and disruption in transcellular permeability. Notably, SLC22A17 could repress the transcription of tight junctional genes. Finally, short interfering RNA against SLC22A17 ameliorates BBB leakage in a mouse model of focal cerebral ischemia. Using a combination of cell culture, human stroke samples, and mouse models, our data suggest that SLC22A17 may play a role in the control of BBB function after cerebral ischemia. These findings may offer a novel mechanism and target for ameliorating BBB injury and edema after stroke.

Insights from a proteomic atlas of human Alzheimer’s disease brain tissue

Insights from a proteomic atlas of human Alzheimer’s disease brain tissue

Reduction of spermine synthase enhances autophagy to suppress Tau accumulation

Precise polyamine metabolism regulation is vital for cells and organisms. Mutations in spermine synthase (SMS) cause Snyder–Robinson intellectual disability syndrome (SRS), characterized by significant spermidine accumulation and autophagy blockage in the nervous system. Emerging evidence connects polyamine metabolism with other autophagy-related diseases, such as Tauopathy, however, the functional intersection between polyamine metabolism and autophagy in the context of these diseases remains unclear. Here, we altered SMS expression level to investigate the regulation of autophagy by modulated polyamine metabolism in Tauopathy in Drosophila and human cellular models. Interestingly, while complete loss of Drosophila spermine synthase (dSms) impairs lysosomal function and blocks autophagic flux recapitulating SRS disease phenotype, partial loss of dSms enhanced autophagic flux, reduced Tau protein accumulation, and led to extended lifespan and improved climbing performance in Tauopathy flies. Measurement of polyamine levels detected a mild elevation of spermidine in flies with partial loss of dSms. Similarly, in human neuronal or glial cells, partial loss of SMS by siRNA-mediated knockdown upregulated autophagic flux and reduced Tau protein accumulation. Importantly, proteomics analysis of postmortem brain tissue from Alzheimer’s disease (AD) patients showed a significant albeit modest elevation of SMS level. Taken together, our study uncovers a functional correlation between polyamine metabolism and autophagy in AD: SMS reduction upregulates autophagy, suppresses Tau accumulation, and ameliorates neurodegeneration and cell death. These findings provide a new potential therapeutic target for AD.

At the Origin of Brain Malformations: Embryology of the Central and Peripheral Nervous System

AbstractDevelopment of the central nervous system is a time-ordered and multistepped process that begins in the third week of development and continues after birth. Understanding of its normal embryologic development is fundamental to understand how specific malformations develop. This article provides a summary of human brain development and serves as a base to introduce the various malformations presented in this issue.

Development and characterization of lipid nanocapsules loaded with iron oxide nanoparticles for magnetic targeting to the blood-brain barrier.

Brain drug delivery is severely hindered by the presence of the blood-brain barrier (BBB). Its functionality relies on the interactions of the brain endothelial cells with additional cellular constituents, including pericytes, astrocytes, neurons, or microglia. To boost brain drug delivery, nanomedicines have been designed to exploit distinct delivery strategies, including magnetically driven nanocarriers as a form of external physical targeting to the BBB. Herein, a lipid-based magnetic nanocarrier prepared by a low-energy method is first described. Magnetic nanocapsules with a hydrodynamic diameter of 256.7 ± 8.5nm (polydispersity index: 0.089 ± 0.034) and a ξ-potential of -30.4 ± 0.3mV were obtained. Transmission electron microscopy-energy dispersive X-ray spectroscopy analysis revealed efficient encapsulation of iron oxide nanoparticles within the oily core of the nanocapsules. Both thermogravimetric analysis and phenanthroline-based colorimetric assay showed that the iron oxide percentage in the final formulation was 12 wt.%, in agreement with vibrating sample magnetometry analysis, as the specific saturation magnetization of the magnetic nanocapsules was 12% that of the bare iron oxide nanoparticles. Magnetic nanocapsules were non-toxic in the range of 50-300μg/mL over 72h against both the human cerebral endothelial hCMEC/D3 and Human Brain Vascular Pericytes cell lines. Interestingly, higher uptake of magnetic nanocapsules in both cell types was evidenced in the presence of an external magnetic field than in the absence of it after 24h. This increase in nanocapsules uptake was also evidenced in pericytes after only 3h. Altogether, these results highlight the potential for magnetic targeting to the BBB of our formulation.

Topological state-space estimation of functional human brain networks.

We introduce an innovative, data-driven topological data analysis (TDA) technique for estimating the state spaces of dynamically changing functional human brain networks at rest. Our method utilizes the Wasserstein distance to measure topological differences, enabling the clustering of brain networks into distinct topological states. This technique outperforms the commonly used k-means clustering in identifying brain network state spaces by effectively incorporating the temporal dynamics of the data without the need for explicit model specification. We further investigate the genetic underpinnings of these topological features using a twin study design, examining the heritability of such state changes. Our findings suggest that the topology of brain networks, particularly in their dynamic state changes, may hold significant hidden genetic information.

Low-intensity ultrasound ameliorates brain organoid integration and rescues microcephaly deficits.

Human brain organoids represent a remarkable platform for modeling neurological disorders and a promising brain repair approach. However, the effects of physical stimulation on their development and integration remain unclear. Here, we report that low-intensity ultrasound significantly increases neural progenitor cell proliferation and neuronal maturation in cortical organoids. Histological assays and single-cell gene expression analyses reveal that low-intensity ultrasound improves the neural development in cortical organoids. Following organoid grafts transplantation into the injured somatosensory cortices of adult mice, longitudinal electrophysiological recordings and histological assays reveal that ultrasound-treated organoid grafts undergo advanced maturation. They also exhibit enhanced pain-related gamma-band activity and more disseminated projections into the host brain than the untreated groups. Finally, low-intensity ultrasound ameliorates neuropathological deficits in a microcephaly brain organoid model. Hence, low-intensity ultrasound stimulation advances the development and integration of brain organoids, providing a strategy for treating neurodevelopmental disorders and repairing cortical damage.

Comparing mouse and human cingulate cortex organization using functional connectivity.

The subdivisions of the extended cingulate cortex of the human brain are implicated in a number of high-level behaviors and affected by a range of neuropsychiatric disorders. Its anatomy, function, and response to therapeutics are often studied using non-human animals, including the mouse. However, the similarity of human and mouse frontal cortex, including cingulate areas, is still not fully understood. Some accounts emphasize resemblances between mouse cingulate cortex and human cingulate cortex while others emphasize similarities with human granular prefrontal cortex. We use comparative neuroimaging to study the connectivity of the cingulate cortex in the mouse and human, allowing comparisons between mouse 'gold standard' tracer and imaging data, and, in addition, comparison between the mouse and the human using comparable imaging data. We find overall similarities in organization of the cingulate between species, including anterior and midcingulate areas and a retrosplenial area. However, human cingulate contains subareas with a more fine-grained organization than is apparent in the mouse and it has connections to prefrontal areas not present in the mouse. Results such as these help formally address between-species brain organization and aim to improve the translation from preclinical to human results.