Intro slides - week 1 (Chris) Flashcards
(18 cards)
Behaviourism (1950s/60s)
Skinner, Watson
Psychology should only concern itself with observable behaviour, which can be explained without recourse to internal mental events
Behaviourists focused on inputs and outputs
Inputs = external stimuli
Outputs = behaviour
Tried to establish rules governing the translation of inputs into outputs (i.e. learning)
Cognitive science (1970s/80s)
Internal mental events are essential for explaining behaviour and can be characterised as the computational operations of a computer program
Chomsky: Language development cannot be explained in purely behavioural learning terms
Development of computers provided new technological metaphor
Mind as the software running on the hardware of the brain
The specific form of the hardware is irrelevant
Cognitive scientists studied behaviour (reaction times etc.) but inferred the operation of ‘mental modules’
Cognitive neuropsychology (1980s/90s)
Behaviour can be explained by internal mental events and these events can be localised to discrete brain regions
Driven by developments in imaging technology (MRI) and observations of loss of specific functions after defined brain lesions, e.g. hippocampus lesions leading to memory problems
Double dissociation logic
2 patients
Patient 1: Lesion to area A: Function X impaired but function Y spared
Patient 2: Lesion to area B: Function Y impaired but function X spared
Cognitive neuroscience (1990s onwards)
Driven by the development of new tools for measuring and manipulating brain function (including functional brain imaging techniques)
At least in its early stages, adopted the logic of cognitive neuropsychology and combined it with the extra precision afforded by these new tools
‘Activation’ methods
functional Magnetic Resonance Imaging (fMRI)
Electroencephalography (EEG)
‘Deactivation’ methods
Transcranial Magnetic Stimulation (TMS)
Neuropsychology (lesion-deficit mapping)
Theory of cognitive neuroscience
Depends on converging evidence from different methodologies
Activation techniques (functional imaging methods) rely on correlation analysis, therefore can’t provide causal evidence regarding brain-behavior relationships
Deactivation techniques (TMS, neuropsychology) allow causal statements but can be spatially imprecise
Cognitive neuroscience - the search for the mind in the brain
Can we reduce all mental phenomena to physical (brain) processes?
Cognitive neuroscience doesn’t require you to accept that complex mental phenomena can be reduced to the firing of individual neurons
Cognitive neuroscience suggests there is an intermediate level of description at the level of neuronal systems
Systems do not necessarily have to be mapped to discrete brain regions (although they may be)
Techniques of cognitive neuroscience can be used to ask different kinds of questions about brain:behaviour relationships…
- Functional localisation
- Mechanics
- Connectivity
Functional localisation
As mentioned, an important aim of cognitive neuroscience has been to try to map cognitive processes onto brain regions.
However, this is more difficult when we don’t actually know what the basic building blocks of cognition actually are.
And this doesn’t seem to be a problem we can solve without looking at data from the brain.
So functional localization is a 2-step process:
We need to define the basic building blocks of cognition
And we need to map these onto different brain regions.
But the process is iterative – we can use brain data to inform our knowledge of what the basic building blocks of cognition are.
Indeed, sometimes brain data can lead us to question whether certain building blocks even exist in any fundamental way.
Mechanics
Cognitive neuroscience can also go beyond localization (and I would argue that it should) to ask mechanistic questions about how the different parts of the brain mediate these various cognitive functions.
By designing clever experiments, we can ask questions not only about where in the brain specific processes are to be found, but also how these neurocognitive modules operate.
For example, it is well known that working memory has a limited capacity in terms of the number of items people can retain in memory.
Can we use for example imaging tools to understand where in the brain this bottleneck occurs and perhaps even how it is achieved.
Connectivity
Finally, cognitive neuroscience can also begin to ask questions about how different localized brain modules might interact with each other – which ones show particularly strong connections, and how they communicate with each other.
This is a key next step in our understanding of the complexity of the brain.
Neuropsychology
Inferring the function of brain regions from the pattern of deficit when damaged
Originally double dissociation logic
More recent studies use large samples and lesion mapping techniques
Allows definitive causal statements about brain-behaviour relationships
Problem is the brain regions are so large that such statements sometimes quite imprecise
Functional magnetic resonance imaging (fMRI)
Visualising functional brain activity during task or at rest
Actually measures Blood Oxygen Level Dependent signal (BOLD) – a proxy for neural activity
Advantages: High spatial resolution (mm3)
Disadvantages: Low temporal resolution (seconds)
Electroencephalography (EEG)
Recording electrical (neuronal) signals from the scalp
Transcranial magnetic stimulation (TMS)
Magnetic field generator placed on surface of head
This produces electrical currents in the brain region under the coil via electromagnetic induction
The idea is to produce a ‘virtual lesion’ in the brain
By delivering a ‘pulse’ time-locked to a specific part of a task that the subject performs, possible to investigate the effects of localised neuronal disruption on specific cognitive processes
Advantages and disadvantages of TMS
Advantages:
High temporal precision (ms)
Can make inferences about whether brain region is necessary for a particular process
Disadvantages:
Limited to brain regions near the scalp (can’t stimulate subcortical structures)
Advantages and disadvantages of EEG
Advantages: Very fine temporal resolution (ms)
Disadvantages: Poor spatial resolution
Monkey single unit (neuron) recordings
Monkey (usually macaque) is trained on a computerised task
Then anaesthetised, skull opened and an electrode array inserted into the brain
On awaking, monkey performs trained task while neuronal activity recorded
Advantages and disadvantages of monkey individual unit (neuron) recordings
Advantages: Excellent temporal and spatial resolution
Disadvantages
Arguably unethical
Translation to humans can be tenuous
