Introduction in Neuropsychology Flashcards
(41 cards)
Cognitive Neurpsychology
The study of the relation between structure and function of the brain and specific cognitive functions (e.g., language, memory, attention etc.)
How do we research cognitive neuropsycholgy
- By investigating these cognitive processes in normal healthy people
- By investigating the breakdown of these processes in brain-damaged individuals (as a result of acquired brain damage or as a result of a developmental disorder
Enthusiasm about Neuropsychology
Neuroscience information affects people’s judgement
–> How much are individuals ready to blieve when encountering improbable information through the guise of neuroscience
- they are very ready!
Example brain enthusiasm Verbeke
Said that in 2009 that 5 years from then, brain scans would be used in application processes for jobs.
–> People are very interested in the brain and the future in this science
Brain scans as evidence in court of law
- Personality assessment
- Lie detection
- Control of actions (‘don’t blame me, blame my brain.
–> Neuroscientific evidence impacts juror’s perception of responsibility and judgement of self-control
Using brain imaging techniques for diagnosing
For neurological syndromes is works really well (think of tumors, dementia, strokes etc.)
For psychiatric and mental syndromes you can’t really use brain imaging methods
- Depression and anxiety
- You can see on group level, but in individuals it is not clear enough for diagnosis
Neurons
Nerve cells that you can see as white and grey matter:
- White matter: axons, the endings of the neuron
- Grey matter: the cell bodies of the neuron
Action potential
At rest the cell membrane of the neuron has a -70 mV difference
With the help of neurotransmitters this potential changes and can be pushed over the threshold of -55 mV, which causes the signal to go to the next neuron
Schematics of the action potential
- -70 mV is rest
- -55 mV is threshold for potential
- depolarization until about 40 mV
- action reaches 40 mV
- Repolarization back to the negatives
- Hyperpolarization goes a little below -70 mV
Neural communication
Imput neurons thruogh the neurotransmitters
- depolarization and hypoerpolarization, cause the signal
Inhibitory and excitatory input
Inhibitory: neurotransmitters that hyperpolarize, which results into the action potential to not happen
Excitatory: neurotransmitters that depolarize, which result into the action potential
Sinusoidal oscillation
The simplest signal
- One wave of up and down in 1 second (1Hz)
Frequency
Rate of change of signal, e.g. in the time dimension
- 1 Hz = completing a full cycle in one second
- Biological signals never contain just one frequency
Complex signals
Signals that have multiple frequencies -> they can be decomposed into frequency components
Parts of a frequency component
- each one has a particular frequency
- Amplitude: how high it goes up and down
- Phase: when it goed up and down (interval)
Frequency spectrum
Measured range of frequency (we cannot measure all)
- Highest frequency
- Lowest frequency
-> filtering
Highest frequency
- Limited by sampling frequency (how msny waves are in one second)
- 1/2 * sampling frequency (Nyquist sampling theorem)
-> if you measure 100 waves per second, the highest frequency is 50 Hz
Lowest frequency
- Limited by how long the signal is measured
- 1 / number of seconds measured
-> if you measure for 2 seconds, the lowest frequency is 0.5 Hz
Filtering
Attenuating or excluding certain part of measured frequency spectrum
- low-pass (everything below a threshold -> low Hz)
- high-pass (everything above a threshold -> high Hz)
- band-pass (everything within 2 limits -> middle Hz)
Spectogram
Strength of each signal component at each moment in time
- shows different amplitudes of the signals
Molecular signals
Movement of chemical substances and molecules can cause changes in EEG’s
- depolarization and repolarization
- calciu concentration in active neurons
-> hemodynamics on larger scale
Hemodynamics
Blood supply is adjusted to current energy needs
-> blood brings glucose to the neurons to stay alive
Energy consumption
- not entirely clear on the relation
Electrophysiological events require energy
-> Amplitude of potential changes is not the best predictor of energy consumption, because it is a passive chain of events
–> restoring the potential requires the energy, so energy consumption could correlate with number of potentials
Clustering
Noninvasive methods cannot achieve single neuron resolution
–> neurons of similar functional properties are clustered together
- more clustering, the more the averaged signal corresponds to the individual neuron
- clustering on different levels are measurable by different methods
