Summary of all the lectures (including seminar and guest lecture) of Cognitive Neuropsychology! It includes class notes (all information on slides and more) and extra information out of the book (blue text)
Summary Cognitive Neuropscyhology (blue = book and Q&A session
incorporated)
Week 1 – Lecture 1 – Introduction
Cognitive Neuropsychology
Definition
= The study of the relation between structure and function of the brain and specific cognitive
functions (e.g. language, memory, attention, ...)
- 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)/lesions
- First only this was done
Brain enthusiasm
Scientific potential vs science fiction
- Claim by Verbeke (2009): in 5 years, brain scans will be common when applying for
important jobs
- Brain scan can tell us whether someone is good fit for the job and whether their
behaviour is good or detrimental (= schadelijk) for the position
- 2020: brain scans are still not standard practice
- Not reliable to state about a single person
- Need more data, a group
- Brain scans as evidence in court of law
- Personality assessment
- Control of actions
- "Don't blame me, blame my brain."
- Lie detection
- Brain scans might be overinterpreted by laypersons
- (more than =) > expert witness
- Because of persuasive power of “neuro-”
- Brain scan provides just as much information as psychiatrist (expert witness)
- Brain imaging can be used to test the state of consciousness of patients in vegetative state or
locked-in syndrome
Persuasive power of “neuro-”
- Ali et al. (2014): How much are individuals ready to believe when encountering improbable
information through the guise of neuroscience?
- Students could easily be convinced that fake neuroimaging instrument (salon hair dryer)
could predict/read their thoughts
- Students deemed technique highly plausible and were hardly skeptical
Objective diagnosis of diseases?
- Good progress for several neurological syndromes
- Brain tumors, dementia, mild cognitive impairment, ...
- But less progress for psychiatric and mental syndromes
- Depression, autism spectrum disorder, schizophrenia, ...
1
, - Differences on a group level
- But not large and consistent enough to allow diagnosis of an individual subject
Basis of neural signals
- Neurons, with cell bodies in grey matter of cerebral cortex and subcortical structures;
white matter contains long axons
- Action potential travels along the axon to all terminals (synapse)
- Action potential is generated at a difference of 55 mV
- Neurons provide excitatory (more active; e.g. glutamate) or inhibitory signals (less active;
e.g. GABA)
- Without input (at rest), cell membrane of a neuron has an electrical potential difference
between in- and outside of -70 mV (= micro Volt)
- Resting potential
- Post-synaptic potential is determined by integrating input of many synapses at the dendrites.
It can hyper- and depolarize
Neural communication
- Input neurons (through neurotransmitters): action potentials over time
- Membrane potential of post-synaptic neuron depolarizes (less negative: -70 mV
→ -65) or hyperpolarizes (more negative: -70 → -73)
- Over time, membrane potential of post-synaptic neuron changes in function of input it
receives
= Signal
- Summary of level of input, relative degree excitatory/inhibitory input, when action
potential is triggered
- Schematic potential at axon hillock
- Potential difference reaches a critical level → further decrease of potential difference →
overshoot so that the difference becomes positive → very quick restoration of a negative
difference
= Action potential
Signal description
- Simplest signal = sinusoidal oscillation of just one frequency, for example a pure tone
- Frequency: rate of change of signal, e.g. in the time or space dimension
- 1 Hz = completing a full cycle (going up & down) in one second
- 2 seconds for 0,5 Hz (whole signal) & 4 seconds for 0,25 Hz
- Biological signals never contain just one frequency (happens in artificial signals, e.g.
pure tone)
- Complex signals can be decomposed into frequency components
- Each has a particular frequency (e.g., 1 Hz, 2 Hz, 3 Hz, ...)
- Amplitude: how much it goes up and down
- Phase: when it goes up and down
- Frequency spectrum: measured range of frequencies
- Highest frequency
- Limited by sampling frequency (how often the signal is measured)
2
, - 1⁄2 * sampling frequency (Nyquist sampling theorem)
- Lowest frequency
- Limited by how long the signal is measured
- 1 / number of seconds measured
- Filtering: attenuating or excluding certain part of measured frequency spectrum
- Low-pass = no high frequencies (weakened or completely removed)
- Smoothing
- High-pass = no low frequencies
- Band-pass = particular phase
- Spectogram: strength of each signal component at each moment in time
- Often displayed by a colored diagram
- X-as: time & Y-as: frequency
- Zero strength/amplitude = blue & highest amplitude = red
- Patch clamping: sucking part of membrane with the tip of a pipette and then measuring the
membrane potential
- Highly invasive
- Requires very stable substrate
- Not used in human research
Molecular and hemodynamic signals
- Electrophysiological changes are connected to other kind of changes...
- At a smaller scale: movement of chemical substances and molecules
- E.g. depolarization: influx of Na+ (= sodium/natrium), repolarization: outward
current/efflux of K+ (= potassium/kalium)
- E.g. calcium concentration high in electrically active neurons → two-photon calcium
imaging
- Calcium is involved in processes such as neurotransmitter release, plasticity
and gene transcription
- At a larger scale: hemodynamics (= blood)
- Blood supply is adjusted to current energy needs and changes over time
Energy consumption
- Electrophysiological events require energy
- Amplitude of potential changes not necessarily best predictor of energy consumption
- Action potential = passive chain of events that does not consume much energy
- Restoring resting potential (afterwards) requires energy → energy consumption of neuron
could correlate with number of action potentials
- Pre- and post-synaptic factors (e.g., neurotransmitter release: presynaptic, functioning of
postsynaptic receptors, maintenance of resting potential in the absence of any action
potentials or synaptic input) also require energy
- Exact energy distribution to different processes can vary (species, neuron type)
- When region receives a lot of inhibitory input → many presynaptic terminals that release
neurotransmitter that inhibits the postsynaptic neurons → very little action potentials fired →
percentage of energy consumption related to presynaptic functioning might be higher overall
3
, Maps in the brain
Clustering
- Noninvasive methods cannot achieve single neuron resolution
- Methods with highest spatial resolution still average signal from many neurons
- Neurons of similar functional properties are clustered together
- Clustering = the tendency of neurons with similar functional properties to be
physically nearby
- The more clustering, the more the averaged signal from many neurons corresponds to
the signal of the individual neurons
→ Sensitivity of a noninvasive imaging technique depends upon amount of clustering
present
- Clustering on different spatial scales
- At different levels of the brain
- Columnar organization in many brain regions
- Column = cylinder-like volume in the cortex that runs through all cortical layers all
the way from the surface of the brain to where gray matter is bordered by white matter
- Cortical thickness: 2-4 mm
- Neurons
- Within column, neurons have very similar response properties
- Topographical: part of body (arm) clustered in same place in brain
- Area: a particular region has a specific function in the cortex
- Middle temporal (MT) area: neurons show a strong selectivity for the direction of
motion of a visual stimulus
- At largest scale, areas show a preferential connectivity and overlap in functional
properties with other areas (usually areas that have a close proximity)
- Areas form cortical structures
Illustration
- Orientation columns (containing neurons with similar preference for line orientation):
not in all species
- Imaging at 20 μm (= micrometers) resolution (invasive optical imaging): orientation
columns visible
- Imaging at lower resolution: blurred, no location would contain the strong selectivity as is
actually present at the level of the single columns
Overview of methods
- Three dimensions:
1. Temporal resolution: the smallest unit of time that can be differentiated by a method
- Resolution of ms is needed to measure individual action potentials
2. Spatial resolution: the smallest unit of space which can be resolved
- Which scale of organization can be picked up
- High = single-neuron
3. Invasiveness: majority of methods are either fully invasive (skull needs to be
penetrated) or not invasive at all
- Focus on less invasive techniques (=> can be applied in humans)
- No methods available that have high spatial resolution combined with high temporal
resolution
4
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