Spatial Dynamics
spatial dynamics
Workshop: Spatial Brain Dynamics
Traditionally, the term dynamics means changes in a system evolving over time. However, in the brain action potentials propagate along axons to induce postsynaptic currents with different delays at many sites simultaneously. This fundamental computational mechanism evolves spatially to engage the neuron populations involved in brain functions. To identify and understand the spatial processing in brains, this workshop will focus on the spatial principles of brain dynamics that determine how action potentials and membrane currents propagate in the networks of neurons that brains are made of. We will focus on non-artificial dynamics, which excludes in vitro dynamics, interference, electrical and optogenetic stimulations of brains in vivo. Recent non-artificial studies of spatial brain dynamics can actually explain how sensory, motor and internal brain functions evolve. The purpose of this workshop is to discuss these recent results and identify common principles of spatial brain dynamics.
Workshop: Spatial Brain Dynamics
Traditionally, the term dynamics means changes in a system evolving over time. However, in the brain action potentials propagate along axons to induce postsynaptic currents with different delays at many sites simultaneously. This fundamental computational mechanism evolves spatially to engage the neuron populations involved in brain functions. To identify and understand the spatial processing in brains, this workshop will focus on the spatial principles of brain dynamics that determine how action potentials and membrane currents propagate in the networks of neurons that brains are made of. We will focus on non-artificial dynamics, which excludes in vitro dynamics, interference, electrical and optogenetic stimulations of brains in vivo. Recent non-artificial studies of spatial brain dynamics can actually explain how sensory, motor and internal brain functions evolve. The purpose of this workshop is to discuss these recent results and identify common principles of spatial brain dynamics.
Workshop: Spatial Brain Dynamics
Traditionally, the term dynamics means changes in a system evolving over time. However, in the brain action potentials propagate along axons to induce postsynaptic currents with different delays at many sites simultaneously. This fundamental computational mechanism evolves spatially to engage the neuron populations involved in brain functions. To identify and understand the spatial processing in brains, this workshop will focus on the spatial principles of brain dynamics that determine how action potentials and membrane currents propagate in the networks of neurons that brains are made of. We will focus on non-artificial dynamics, which excludes in vitro dynamics, interference, electrical and optogenetic stimulations of brains in vivo. Recent non-artificial studies of spatial brain dynamics can actually explain how sensory, motor and internal brain functions evolve. The purpose of this workshop is to discuss these recent results and identify common principles of spatial brain dynamics.
The Evolution of Looking and Seeing: New Insights from Colorful Jumping Spiders
During communication, alignment between signals and sensors can be critical. Signals are often best perceived from specific angles, and sensory systems can also exhibit strong directional biases. However, we know little about how animals establish and maintain such signaling alignment during communication. To investigate this, we characterized the spatial dynamics of visual courtship signal- ing in the jumping spider Habronattus pyrrithrix. The male performs forward-facing displays involving complex color and movement patterns, with distinct long- and short-range phases. The female views displays with 2 distinct eye types and can only perceive colors and fine patterns of male displays when they are presented in her frontal field of view. Whether and how courtship interactions pro- duce such alignment between male display and female field of view is unknown. We recorded relative positions and orientations of both actors throughout courtship and established the role of each sex in maintaining signaling alignment. Males always oriented their displays toward the female. However, when females were free to move, male displays were consistently aligned with female princi- pal eyes only during short-range courtship. When female position was fixed, signaling alignment consistently occurred during both phases, suggesting that female movement reduces communication efficacy. When female models were experimentally rotated to face away during courtship, males rarely repositioned themselves to re-align their display. However, males were more likely to present cer- tain display elements after females turned to face them. Thus, although signaling alignment is a function of both sexes, males appear to rely on female behavior for effective communication
Context and Comparison During Open-Ended Induction
A key component of humans' striking creativity in solving problems is our ability to construct novel descriptions to help us characterize novel categories. Bongard problems, which challenge the problem solver to come up with a rule for distinguishing visual scenes that fall into two categories, provide an elegant test of this ability. Bongard problems are challenging for both human and machine category learners because only a handful of example scenes are presented for each category, and they often require the open-ended creation of new descriptions. A new sub-type of Bongard problem called Physical Bongard Problems (PBPs) is introduced, which require solvers to perceive and predict the physical spatial dynamics implicit in the depicted scenes. The PATHS (Perceiving And Testing Hypotheses on Structures) computational model which can solve many PBPs is presented, and compared to human performance on the same problems. PATHS and humans are similarly affected by the ordering of scenes within a PBP, with spatially and temporally juxtaposed scenes promoting category learning when they are similar and belong to different categories, or dissimilar and belong to the same category. The core theoretical commitments of PATHS which we believe to also exemplify human open-ended category learning are a) the continual perception of new scene descriptions over the course of category learning; b) the context-dependent nature of that perceptual process, in which the scenes establish the context for one another; c) hypothesis construction by combining descriptions into logical expressions; and d) bi-directional interactions between perceiving new aspects of scenes and constructing hypotheses for the rule that distinguishes categories.