Interactive learning and teaching system with two neurosimulators for experiments covering nerve cells and nerve cell interactions.
- Experience processes in the nerve cell and between nerve cells "hands-on"
- Make all properties of a nerve cell easy to understand - action potential, membrane potential, functions of synapses (e.g. synaptic learning and forgetting)
- Discover how nerve cells interact to study the conditioned reflex and synaptic learning
- Scale up easily to perform further experiments studying neural networks (e.g. short-term memory) by adding additional modules
- Ideal for projects at schools and for lab courses in the degree course Neurobiology
- When using one nerve cell: use the nerve function model to study the following aspects of a nerve cell: intercellular potential, action potential, the different types of synapses.
- When using two nerve cells: motoneuron signals with recurrent inhibition by Renshaw cell, motoneuron signals without recurrent inhibition, functional characteristics of Renshaw inhibition, lateral inhibition, contrast improvement, conditioned reflex, reversed stimulus succession does not bring about a conditioned reflex.
What you can learn about
- When using one nerve cell: comparison between low and high threshold and stimulus levels, membrane time constant and low pass filtering, low-pass filtering, excitatory synapse, depolarisation, temporal summation, spatial summation, synaptic amplification by terminal branches, effect of decreasing stimulus, Hebbian synapse, synaptic learning and forgetting, inhibitory synapse, hyperpolarization, spacial inhibitory-excitatory summation, veto synapse.
- When using two nerve cells: lateral inhibition, contrast improvement, nerve cell interaction, conditioned reflex, Renshaw inhibition, motoneuron.
The system can be upgraded with one or two additional neurosimulators to perform experiments about
- neural networks (transient, i.e. phasic responses: focus on visual sense, body clock, short-term memory, special anatomical circuits: cerebral cortex and sensoric learning, functional characteristic of a triad).
- complex neural networks (direction selectivity by unilateral inhibition, self-calibration of paired sensory channels).
Operating system-independent software included. Computer not provided.