History & Methods

8 important questions on History & Methods

What are the benefits of cognitive neuroscience?

1. It addresses many of the limitations of cognitive neuropsychology

2. It can address new questions e.g. Where are cognitive functions localised? When do different processes happen? How do different brain areas interact during recognition?

What are 2 limitations of cognitive neuroscience?

1. often need to combine several techniques to compensate for limitations e.g. fMRI and TMS

2. neuroscientific techniques often simply confirm existing theories rather than generating new ones

What is a benefit of computational cognitive science?

It can create more highly specified theories of cognition e.g. demonstrate assumptions of vague terms & can be used to predict behaviour
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What are the two systems in computational cognitive science?

Production systems - information is in a single node
Connectionist Networks - information is distributed across the cognitive systems

What is the production systems?

IF...THEN rules

Characteristics
1. Numerous IF...THEN rules held in long-term memory
2. A working memory to hold information
3. Operates by matching content of working memory to IF parts of rules, and then executing THEN parts

What is the connectionist network?

1. Nodes or units are linked together
2. Nodes excite or inhibit each other
3. Each node produces an output if the input exceeds a threshold
= a pattern of activation

What are 4 limitations of computational cognitive science?

1. models rarely make testable predictions i.e. don't spur new research
2. it is difficult to compare the two models as cognitive processes are so complicated
3. analogy with human brain is unconvincing i.e the brain has many neuron types, and no evidence of massive interconnection
4. don't take account of factors such as motivation or emotion

What is an example task of connectionism?

Task: identity if a letter is a vowel or a constant.

Proposed cognitive process:
  • Input layers - excited by the incoming information (recognising the letter/ identifying what the letter is)
  • Intermediate layers - more layers to allow the representation of more complex concepts
  • Output layers - information that can be used to guide behaviour (associating concepts about that letter = the letter A is a vowel) 

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