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Adult hippocampal neurogenesis (AHN) is associated with cognitive reserve and mental health, and can be supported by environmental enrichment, such as spatial complexity, as a form of cognitive enrichment. Studies on human subjects show that navigating complex landscapes and higher geospatial complexity at a zipcode level are associated with greater hippocampal volume and lower risk of Alzheimer's disease, while laboratory studies show that spatial complexity can enhance AHN in mice and rats. However, the role of architectural spatial complexity remains unexplored, despite people spending ∼90% of their time indoors, which can pose a risk to AHN. To address this gap, first, this study developed a novel tool, the Architectural Spatial Complexity Index (A-SCI). The A-SCI was calculated based on seven layout variables and seven points of interest to maintain a balanced ratio, and the index scores were normalised to range from 0 to 1. Second, this study theoretically validated the A-SCI's ability to differentiate between enriched housing models that enhance AHN and non-enriched laboratory housing. It showed that enriched environments, using layout complexity, points of interest, or both, scored significantly higher than non-enriched animal housing models, with no difference between enrichment subtypes (layout complexity versus points of interest), demonstrating the theoretical validity of the A-SCI tool. Third, floor area did not independently predict the index scores after controlling for complexity. Fourth, exploratory assessments of human layouts demonstrate that multi-storey houses outscored single-storey apartments. Adding landscape and museum mazes yielded index scores comparable to those of multi-storey houses, both higher than those of apartments. Lastly, using an expanded dataset (n = 63), historical palaces and contemporary shopping malls scored relatively higher, while hotel apartments and student accommodation scored similarly to apartments. Points of interest, which may provide cognitive enrichment independent of layout complexity, were not assessed in this study due to their dependence on social and economic factors that require separate investigation. The A-SCI tool offers a neuroscience-informed approach to architectural enrichment by design, which can support AHN in humans and help predict the risk of cognitive decline and mental health conditions such as depression. This paper encourages the use of the A-SCI tool for future research in architecture and neuroscience. Applications can span public health, space syntax, historical, and socioeconomic perspectives.

Adult hippocampal neurogenesis persists throughout the lifespan in mammals and can be enhanced by environmental enrichment, including spatial complexity. Whilst maze-based enrichment has been suggested to increase neurogenesis in rodents, the relative complexity of different maze architectures has not been quantified, limiting translational research to human environments. This study used the Architectural Spatial Complexity Index (A-SCI), a novel tool, to compare spatial complexity across 16 rodent maze configurations, including mazes suggested to increase neurogenesis. Results confirm that the A-SCI significantly differentiates environmental enrichment from standard housing, whilst post-hoc analysis suggests no significant difference between maze-based and object-based enrichment, consistent with previous research reporting almost similar effects on cortical thickness. Comparative analysis revealed substantial variation in complexity across rodent maze architectures. Future research can use the A-SCI tool to validate the effect of maze complexity on adult hippocampal neurogenesis, while the Hampton Court maze may be a promising translational paradigm from rodents to humans.

Hippocampal neurogenesis is critical for improving learning, memory, and spatial navigation. Inhabiting and navigating spatial complexity is key to stimulating adult hippocampal neurogenesis (AHN) in rodents because they share similar hippocampal neuroplasticity characteristics with humans. AHN in humans has recently been found to persist until the tenth decade of life, but it declines with aging and is influenced by environmental enrichment. This systematic review investigated the impact of spatial complexity on neurogenesis and hippocampal plasticity in rodents, and discussed the translatability of these findings to human interventions. Comprehensive searches were conducted on three databases in English: PubMed, Web of Science, and Scopus. All literature published until December 2023 was screened and assessed for eligibility. A total of 32 studies with original data were included, and the process is reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement and checklist. The studies evaluated various models of spatial complexity in rodents, including environmental enrichment, changes to in-cage elements, complex layouts, and navigational mazes featuring novelty and intermittent complexity. A regression equation was formulated to synthesize key factors influencing neurogenesis, such as duration, physical activity, frequency of changes, diversity of complexity, age, living space size, and temperature. Findings underscore the cognitive benefits of spatial complexity interventions and inform future translational research from rodents to humans. Home-cage enrichment and models like the Hamlet complex maze and the Marlau cage offer insight into how architectural design and urban navigational complexity can impact neurogenesis in humans. In-space changing complexity, with and without physical activity, is effective for stimulating neurogenesis. While evidence on intermittent spatial complexity in humans is limited, data from the COVID-19 pandemic lockdowns provide preliminary evidence. Existing equations relating rodent and human ages may allow for the translation of enrichment protocol durations from rodents to humans.

Distal astrocytic processes have a complex morphology, reminiscent of branchlets and leaflets. Astrocytic branchlets are rod-like processes containing mitochondria and endoplasmic reticulum, capable of generating inositol-3-phosphate (IP )-dependent Ca signals. Leaflets are small and flat processes that protrude from branchlets and fill the space between synapses. Here we use three-dimensional (3D) reconstructions from serial section electron microscopy (EM) of rat CA1 hippocampal neuropil to determine the astrocytic coverage of dendritic spines, shafts and axonal boutons. The distance to the maximum of the astrocyte volume fraction (VF) correlated with the size of the spine when calculated from the center of mass of the postsynaptic density (PSD) or from the edge of the PSD, but not from the spine surface. This suggests that the astrocytic coverage of small and larger spines is similar in hippocampal neuropil. Diffusion simulations showed that such synaptic microenvironment favors glutamate spillover and extrasynaptic receptor activation at smaller spines. We used complexity and entropy measures to characterize astrocytic branchlets and leaflets. The 2D projections of astrocytic branchlets had smaller spatial complexity and entropy than leaflets, consistent with the higher structural complexity and less organized distribution of leaflets. The VF of astrocytic leaflets was highest around dendritic spines, lower around axonal boutons and lowest around dendritic shafts. In contrast, the VF of astrocytic branchlets was similarly low around these three neuronal compartments. Taken together, these results suggest that astrocytic leaflets preferentially contact synapses as opposed to the dendritic shaft, an arrangement that might favor neurotransmitter spillover and extrasynaptic receptor activation along dendritic shafts.

We pose the central problem of defining a measure of complexity, specifically for spatial systems in general, city systems in particular. The measures we adopt are based on Shannon’s (in Bell Syst Tech J 27:379–423, 623–656, 1948 ) definition of information. We introduce this measure and argue that increasing information is equivalent to increasing complexity, and we show that for spatial distributions, this involves a trade-off between the density of the distribution and the number of events that characterize it; as cities get bigger and are characterized by more events—more places or locations, information increases, all other things being equal. But sometimes the distribution changes at a faster rate than the number of events and thus information can decrease even if a city grows. We develop these ideas using various information measures. We first demonstrate their applicability to various distributions of population in London over the last 100 years, then to a wider region of London which is divided into bands of zones at increasing distances from the core, and finally to the evolution of the street system that characterizes the built-up area of London from 1786 to the present day. We conclude by arguing that we need to relate these measures to other measures of complexity, to choose a wider array of examples, and to extend the analysis to two-dimensional spatial systems.

This paper bridges critical gaps through proposing a novel, environmentally mediated brain-derived neurotrophic factor (BDNF)-interactive model that promises to sustain adult hippocampal neurogenesis in humans. It explains how three environmental enrichment mechanisms (physical activity, cognitive stimulation, and mindfulness) can integratively regulate BDNF and other growth factors and neurotransmitters to support neurogenesis at various stages, and how those mechanisms can be promoted by the physical environment. The approach enables the isolation of specific environmental factors and their molecular effects to promote sustainable BDNF regulation by testing the environment’s ability to increase BDNF immediately or shortly before it is consumed for muscle repair or brain update. This model offers a novel, feasible method to research environment enrichment and neurogenesis dynamics in real-world human contexts at the immediate molecular level, overcoming the confounds of complex environment settings and challenges of long-term exposure and structural plasticity changes. The model promises to advance understanding of environmental influences on the hippocampus to enhance brain health and cognition. This work bridges fundamental gaps in methodology and knowledge to facilitate more research on the enrichment–neuroplasticity interplay for humans without methodological limitations.

Orientation entropy serves as a critical metric for assessing the directional disorder of urban street networks. However, conventional two-dimensional (2D) approaches neglect vertical variations, limiting their applicability in cities with complex terrains. This study proposes a three-dimensional (3D) orientation entropy framework by integrating elevation data, providing a more comprehensive assessment of urban spatial complexity. We developed a computational workflow combining ArcGIS 10.8 for spatial data extraction and Python 3.10.10 for entropy calculation. A case study in Chongqing, China, explores the relationship between 3D orientation entropy and residents’ perceptions of spatial disorder through a small-scale survey. Although no statistically significant correlation was observed, the findings suggest emerging patterns and underscore the necessity of multidimensional frameworks in evaluating urban spatial experience. This research contributes a novel metric to urban design assessment, particularly in topographically diverse environments, and offers a foundation for future empirical studies.

Background Splice site prediction in plant genomes poses substantial challenges that can be addressed using deep learning models. U2-type introns are especially useful for such studies given their ubiquity in plant genomes and the availability of rich datasets. We formulated two hypotheses: one proposing that short introns may enhance prediction effectiveness due to reduced spatial complexity, and another suggesting that sequences with multiple introns provide a richer context for splicing events. Results Our findings demonstrate that (1) models trained on datasets containing shorter introns achieve improved effectiveness for acceptor splice sites, but not for donor splice sites, indicating a more nuanced relationship between intron length and splice site prediction than initially hypothesized, and (2) models trained on datasets with multiple introns per sequence show higher effectiveness compared to those trained on datasets with a single intron per sequence. Notably, among the 402 bp sequences analyzed, 72% contained single introns while 28% contained multiple introns for donor sites (36,399 versus 13,987 sequences), with similar proportions observed for acceptor sites (37,236 versus 14,112 sequences). These computational insights align with biological observations, particularly regarding the conserved spatial relationship between branch points and acceptor splice sites, as well as the synergistic effects of multiple introns on splicing efficiency. Conclusions The obtained results contribute to a deeper understanding of how intronic features influence splice site prediction and suggest that future prediction models should consider factors such as intron length, multiplicity, and the spatial arrangement of splice-related signals.

Monitoring land use and land cover (LULC) transformations is essential for understanding socio-ecological dynamics. This study assesses structural shifts in Romania’s landscapes between 1990 and 2018 by integrating algorithmic complexity, fractal analysis, and Grey-Level Co-occurrence Matrix (GLCM) texture analysis. Multi-year maps were used to compute Kolmogorov complexity, fractal measures, and 15 GLCM metrics. The measures were compiled into a unified matrix, and temporal trajectories were explored with principal component analysis and k-means clustering to identify inflection points. Informational complexity and Higuchi 2D decline over time, while homogeneity and angular second moment rise, indicating greater local uniformity. A structural transition around 2006 separates an early heterogeneous regime from a more ordered state; 2012 appears as a turning point when several indices reach extreme values. Strong correlations between fractal and texture measures imply that geometric and radiometric complexity co-evolve, whereas large-scale fractal dimensions remain nearly stable. The multi-index approach provides a replicable framework for identifying critical transitions in LULC. It can support landscape monitoring, and future work should integrate finer temporal data and socio-economic drivers.

Accumulating evidence suggests that the brain is highly dynamic; thus, investigation of brain dynamics especially in brain connectivity would provide crucial information that stationary functional connectivity could miss. This study investigated temporal expressions of spatial modes within the default mode network (DMN), salience network (SN) and cognitive control network (CCN) using a reliable data-driven co-activation pattern (CAP) analysis in two independent data sets. We found enhanced CAP-to-CAP transitions of the SN in patients with MDD. Results suggested enhanced flexibility of this network in the patients. By contrast, we also found reduced spatial consistency and persistence of the DMN in the patients, indicating reduced variability and stability in individuals with MDD. In addition, the patients were characterized by prominent activation of mPFC. Moreover, further correlation analysis revealed that persistence and transitions of RCCN were associated with the severity of depression. Our findings suggest that functional connectivity in the patients may not be simply attenuated or potentiated, but just alternating faster or slower among more complex patterns. The aberrant temporal–spatial complexity of intrinsic fluctuations reflects functional diaschisis of resting-state networks as characteristic of patients with MDD.