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Macaques preferentially attend to visual patterns with higher fractal dimension contours.
Animals' sensory systems evolved to efficiently process information from their environmental niches. Niches often include irregular shapes and rough textures (e.g., jagged terrain, canopy outlines) that must be navigated to find food, escape predators, and master other fitness-related challenges. For most primates, vision is the dominant sensory modality and thus, primates have evolved systems for processing complicated visual stimuli. One way to quantify information present in visual stimuli in natural scenes is evaluating their fractal dimension. We hypothesized that sensitivity to complicated geometric forms, indexed by fractal dimension, is an evolutionarily conserved capacity, and tested this capacity in rhesus macaques (Macaca mulatta). Monkeys viewed paired black and white images of simulated self-similar contours that systematically varied in fractal dimension while their attention to the stimuli was measured using noninvasive infrared eye tracking. They fixated more frequently on, dwelled for longer durations on, and had attentional biases towards images that contain boundary contours with higher fractal dimensions. This indicates that, like humans, they discriminate between visual stimuli on the basis of fractal dimension and may prefer viewing informationally rich visual stimuli. Our findings suggest that sensitivity to fractal dimension may be a wider ability of the vertebrate vision system
Wholeness as a Hierarchical Graph to Capture the Nature of Space
According to Christopher Alexander's theory of centers, a whole comprises
numerous, recursively defined centers for things or spaces surrounding us.
Wholeness is a type of global structure or life-giving order emerging from the
whole as a field of the centers. The wholeness is an essential part of any
complex system and exists, to some degree or other, in spaces. This paper
defines wholeness as a hierarchical graph, in which individual centers are
represented as the nodes and their relationships as the directed links. The
hierarchical graph gets its name from the inherent scaling hierarchy revealed
by the head/tail breaks, which is a classification scheme and visualization
tool for data with a heavy-tailed distribution. We suggest that (1) the degrees
of wholeness for individual centers should be measured by PageRank (PR) scores
based on the notion that high-degree-of-life centers are those to which many
high-degree-of-life centers point, and (2) that the hierarchical levels, or the
ht-index of the PR scores induced by the head/tail breaks can characterize the
degree of wholeness for the whole: the higher the ht-index, the more life or
wholeness in the whole. Three case studies applied to the Alhambra building
complex and the street networks of Manhattan and Sweden illustrate that the
defined wholeness captures fairly well human intuitions on the degree of life
for the geographic spaces. We further suggest that the mathematical model of
wholeness be an important model of geographic representation, because it is
topological oriented that enables us to see the underlying scaling structure.
The model can guide geodesign, which should be considered as the
wholeness-extending transformations that are essentially like the unfolding
processes of seeds or embryos, for creating beautiful built and natural
environments or with a high degree of wholeness.Comment: 14 pages, 7 figures, 2 table
Spatial networks with wireless applications
Many networks have nodes located in physical space, with links more common
between closely spaced pairs of nodes. For example, the nodes could be wireless
devices and links communication channels in a wireless mesh network. We
describe recent work involving such networks, considering effects due to the
geometry (convex,non-convex, and fractal), node distribution,
distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina
The speed of range shifts in fragmented landscapes
Peer reviewedPublisher PD
Defining Urban Boundaries by Characteristic Scales
Defining an objective boundary for a city is a difficult problem, which
remains to be solved by an effective method. Recent years, new methods for
identifying urban boundary have been developed by means of spatial search
techniques (e.g. CCA). However, the new algorithms are involved with another
problem, that is, how to determine the characteristic radius of spatial search.
This paper proposes new approaches to looking for the most advisable spatial
searching radius for determining urban boundary. We found that the
relationships between the spatial searching radius and the corresponding number
of clusters take on an exponential function. In the exponential model, the
scale parameter just represents the characteristic length that we can use to
define the most objective urban boundary objectively. Two sets of China's
cities are employed to test this method, and the results lend support to the
judgment that the characteristic parameter can well serve for the spatial
searching radius. The research may be revealing for making urban spatial
analysis in methodology and implementing identification of urban boundaries in
practice.Comment: 26 pages, 5 figures, 7 table
Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience
This essay is presented with two principal objectives in mind: first, to
document the prevalence of fractals at all levels of the nervous system, giving
credence to the notion of their functional relevance; and second, to draw
attention to the as yet still unresolved issues of the detailed relationships
among power law scaling, self-similarity, and self-organized criticality. As
regards criticality, I will document that it has become a pivotal reference
point in Neurodynamics. Furthermore, I will emphasize the not yet fully
appreciated significance of allometric control processes. For dynamic fractals,
I will assemble reasons for attributing to them the capacity to adapt task
execution to contextual changes across a range of scales. The final Section
consists of general reflections on the implications of the reviewed data, and
identifies what appear to be issues of fundamental importance for future
research in the rapidly evolving topic of this review
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