L25 - Computational Modelling

Question 1

What is a model?

Answer 1

Any description of a process is a model of that process – can be good or bad

Question 2

Can a model be verbal?

Answer 2

Yes – a description which does not specify a quantitative r/ship b/w elements, can be falsifiable

Question 3

All models must make wshat?

Answer 3

Testible predictions! or else it will be useless

Question 4

Why computer simulation?

Answer 4

Typical biological models use stereotyped stimuli and do not reveal the full response patterns involved in a behaviour

In many cases, the interactions between specific neurons controlling a behaviour are too difficult to determine

Question 5

Emergent properties

Answer 5

Properties of a system that cannot be predicted simply from the properties of its individual elements

• E.g In NS, content addressable memory (e.g. know someone’s name hence we know someone’s face, sound of voice, location you met) is an emergent property of networks obeying Hebb’s rule (Discovered by Hopfield and Tank)
• HOWEVER, content addressable memory may not always be correct as surrounds of memory overlap so you could get things mixed up

Question 6

Compartmental models

Answer 6

• Subset of realistic models with maths descriptions
• Has spatial relationships
• Can activate one neuron at a time
• Heavy comp requirements so not used for large networks

Question 7

Network Models

Answer 7

Depict the process in a network, but requires a degree of abstraction (simplification) as to the computational process of the network. It simplifies the properties of the neurons so that we may interpret data.
E.g. removal of voltage dependence

Question 8

Realistic models look at maths descriptions while abstract models?

Answer 8

–Assumptions made about specific components to obtain general rules for the system
–Can vary from completely top-down to various hybrids of realism and abstraction

Question 9

Example of Abstracted models - Integrate-and-fire neurons

Answer 9

• Basis of most neural network models that try to simulate cognitive processes
• Each neuron simply adds the synaptic inputs via some mathematical rule and if a threshold is exceeded an action potential is generated
• The classic version is the McCulloch – Pitts neurons (originally an electronic model).

Question 10

Conclusions from model

Answer 10

Blocking AHP causes change in periods of activity but periods of quiescence do not change

•Accounts for effects of changing AHP on contractile activity of jejunum in presence of decanoic acid
•Requires feedback from contracting muscle and that synaptic transmission in ascending EXCITATORY pathway is fast EPSP, but is slow EPSP in descending INHIBITORY pathway
•Predicts that blocking serotonin will suppress motor activity
–Result supported by pharmacological analysis