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Developmental TimelineFertilizationFirst TrimesterSecond TrimesterThird TrimesterFirst Thin Layer of Skin AppearsEnd of Embryonic PeriodEnd of Embryonic PeriodFemale Reproductive SystemBeginning Cerebral HemispheresA Four Chambered HeartFirst Detectable Brain WavesThe Appearance of SomitesBasic Brain Structure in PlaceHeartbeat can be detectedHeartbeat can be detectedFinger and toe prints appearFinger and toe prints appearFetal sexual organs visibleBrown fat surrounds lymphatic systemBone marrow starts making blood cellsBone marrow starts making blood cellsInner Ear Bones HardenSensory brain waves begin to activateSensory brain waves begin to activateLungs begin to produce surfactantBrain convolutions beginPeriod of rapid brain growthImmune system beginningImmune system beginningHead may position into pelvisWhite fat begins to be madeWhite fat begins to be madeFull TermBrain convolutions beginHead may position into pelvisFetal liver is producing blood cells
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Home | Pregnancy Timeline | News Alerts |News Archive July 15, 2014

Evasive tadpoles help probe brain circuitry
Researchers found that tadpoles use the optic tectum region of their brain
to determine that something is approaching and avoid collision.
The finding helps scientists better understand how different neurons
work together to control simple behavior in many animals.
Illustration by Arseny Khakhalin

Human brain stem regions showing the optic tectum


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Reverse engineering brain circuits

In a new study, Brown University neuroscientists looked cell-by-cell at the brain circuitry that tadpoles, and possibly other animals like ourselves, use to avoid collisions.

The study produced a model of how individual inhibitory and excitatory neurons work together to control a simple behavior, providing new insight into very basic brain circuits involved in avoiding collisions, and perhaps a general model of how neurons process information.

In the study, Brown University scientists tracked the cell-by-cell progress of neural signals from the eyes through the brains of tadpoles reacting to stimuli including an "approaching" black circle.

Tracking the brain response to visual stimulation caused by the "approaching" black circle, researchers were able to understand how individual cells contribute to a broad network of input to identify impending collisions. This basic brain circuitry is present in a wide variety of animals, including humans.

“Imagine yourself walking in a forest while keeping a conversation with your friend. You keep the conversation going, at the same time avoiding tree trunks and shrubs without giving them conscious attention. That's because a whole region in our brain is dedicated, among other things, to this task.”

Arseny Khakhalin, PhD, lead author, department of neuroscience, Brown University.

The work appears in European Journal of Neuroscience.

Khakhalin studied collision avoidance using tadpoles as the model organism because, as senior author and neuroscience professor Carlos Aizenman put it, tadpoles are “sufficiently complex to produce interesting behavior, but have nervous systems sufficiently simple to address in an integrated experimental approach.”

They began by tracking avoidance behavior. With tadpoles swimming in a dish sitting atop a projector screen, digital black dots of varying widths and located at varying angles were projected onto the screen to appear to be approaching the tadpoles. Other black dots blinked randomly on the screen, but remained stationary in one location. The tadpoles fled "approaching" dots, but rarely reacted to dots which merely blinked. This response confirmed tadpoles react to movement towards them rather than a simply blinking stimuli.

Researchers then wanted to determine how tadpoles neurologically process different stimuli. To do that, tadpoles were restrained in place while a variety of simple animations were delivered via a fiber optic cable held next to a tadpole eye. The animations included a blinking circle, an "approaching" circle (it became larger and larger over a brief time interval), and a circle which gradually faded into view.

While tadpoles were exposed to the animations, a high-speed camera tracked individual tail movements to determine any "fleeing maneuvers." At the same time, electrical signals along the optic nerve leading from the retina to the brain’s tectum region were recorded. In this way, “excitatory” and “inhibitory” synaptic input to and output from neurons in the optic tectum were recorded.

What the scientists found was that the tectum, rather than the retina, appears to be where the tadpoles determine that something is approaching rather than merely present.

How did they know? The strongest difference between responses to the "approaching" circle, versus responses to "blinking" or "fading" circles, was detected at the output from tectal neurons.

Moreover, the difference in activity related to "approaching" circles increased as the signal moved from the optic nerve, then through tectum input to tectum output.

“The tectum is the first place that responded to approaching stimuli not just differently, but stronger,” Khakhalin added.

The results of the experiments imply that individual neurons in the tectum are uniquely activated by an "approaching" stimulus, which then generates a signal to the tail to move and avoid collision.

These excited - or excitatory - neurons are balanced by inhibitory neurons in the tectum. To confirm this idea, researchers chemically blocked inhibitory neurons in the tectum of one group of tadpoles, chemically enhanced excitatory neurons in another group, and left another group of tadpoles unaltered to act as a control group for comparison.

They found that when inhibition was blocked, individual excitatory cells lost their selectivity. When inhibition was enhanced, individual excitatory cells retained their selectivity but could not project a signal all at one time. Khakhalin’s hypothesis is that this inhibitory - excitatory balance allows the brain stem tectum region to build up a degree of excitement about the stimulus (in this case: "something nearby is getting bigger") while balancing it with inhibitory or“calming” intervals which allow for momentary consideration before confirmation from another wave of input (as in: "it just got bigger again").

Aizenman believes their paper illustrates a broader approach to fundamental neuroscience research: “It is a greater project to be able to take an entire behavior and break it down into all of its neural components, in order to create a model of how single neurons and their connections interact and produce a single behavior.”

Information processing in the vertebrate brain is thought to be mediated through distributed neural networks, but it is still unclear how sensory stimuli are encoded and detected by these networks, and what role synaptic inhibition plays in this process. Here we used a collision avoidance behavior in Xenopus tadpoles as a model for stimulus discrimination and recognition. We showed that the visual system of the tadpole is selective for behaviorally relevant looming stimuli, and that the detection of these stimuli first occurs in the optic tectum. By comparing visually guided behavior, optic nerve recordings, excitatory and inhibitory synaptic currents, and the spike output of tectal neurons, we showed that collision detection in the tadpole relies on the emergent properties of distributed recurrent networks within the tectum. We found that synaptic inhibition was temporally correlated with excitation, and did not actively sculpt stimulus selectivity, but rather it regulated the amount of integration between direct inputs from the retina and recurrent inputs from the tectum. Both pharmacological suppression and enhancement of synaptic inhibition disrupted emergent selectivity for looming stimuli. Taken together these findings suggested that, by regulating the amount of network activity, inhibition plays a critical role in maintaining selective sensitivity to behaviorally-relevant visual stimuli.

In addition to Khakhalin and Aizenman, other authors are former Brown undergraduates David Koren and Jenny Gu, and physics graduate student Heng Xu.

The National Science Foundation, the National Eye Institute and the Fox Foundation Fellowship for the Visual Sciences supported the research.
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