The following are some projects which are
currently being pursued in the Higgins laboratory.
Background information on many of them can be found by looking at
laboratory publications.
Dipteran Elementary Motion Detection
In a collaborative project with the
Strausfeld laboratory,
a novel computational neuronal
model of elementary motion detection based on anatomical, physiological,
and behavioral observations of flies has been developed that serves as a
working functional hypothesis as to how the underlying neuronal machinery may be
organized.
We are currently augmenting the existing EMD model with two
important stages, working towards a more realistic model of the insect visual system.
In the optics stage, light information is collected by each facet of the
simulated compound eye. Collected light is then focused onto photoreceptors which further process the light information.
A mathematical model of the photoreceptor stage
is being used to simulate contrast adaptation under steady-state and dynamic conditions.
Honeybee Speed Estimation
The goal of this research is to mathematically describe how the brain processes
and uses sensory information to generate appropriate behavioral responses.
These mathematical models can then be used as a basis to understand higher-level
behaviors or to design more intelligent robotic systems. The human brain
contains around 10 billion neurons (the functional cells of the brain), making
it a dauntingly large and complex structure to study. Because of this
complexity, we study the honeybee, an organism with a much smaller brain (with around 1
million neurons) that still exhibits a variety of complex social, visual, and
navigational behaviors. Of particular interest to us is the "waggle
dance", in which a foraging honeybee communicates the location of a distant
food source to other honeybees in the hive. Specifically, our research looks at
how honeybees estimate the distance they have traveled based solely on a visual
estimate of their flight speed. To accomplish this goal we combine information
from multiple levels of analysis, from biophysics to neuroanatomy, to create a
mathematical model of early visual processing. We then refine the model by
studying the responses of tethered honeybees in a virtual flight arena. The model
can then be programmed into a robotic system.
Insect Robot Interfacing
The field of neuroscience is moving toward understanding how sensory systems compute under closed-loop control. It is important to step away from open-loop experiments, i.e. where an animal cannot interact with its sensory inputs, because in the real world sensory neurons are passengers on a moving body whose sensory inputs are intimately related to its behavior. The challenge with performing these experiments under natural conditions is that conventional electrophysiology equipment is too bulky to be placed on a freely behaving animal. To solve this problem, we have designed a robotic electrophysiology instrument whose velocity is determined by bioelectrical signals from an animal, in our case the hawk moths and flies (model organisms for visual motion detection, olfaction, and insect flight). This robotic instrument allows us to perform electrophysiological experiments while a moth is onboard and controlling the robot, which, in engineering terms, closes the loop. With
this instrument we will characterize visual motion detection neurons and investigate the use of these neurons as biosensors for robots.
This page updated on 9/18/08.