Week 5.1 Cog Neuro Flashcards
representations
properties that are manifested in cog systems and neural systems
single-cell recordings
measure the responsiveness of a neuron to a given stimulus
electroencephalography (EEG)
measurements of electrical signals generated by the brain through electrodes places on the scalp
event-related potential (ERP)
average change in voltage at the scalp that are linked to the timing of cog events e.g. stimulus, response
reaction time
time taken between onset of stimulus and production of behavioural response
multi-cell recordings
electrical activity of many individually recorded neurons recorded at electrode(s)
(in terms of action potentials per second)
multi-cell recordings
electrical activity of many individually recorded neurons recorded at electrode(s)
(in terms of action potentials per second)
grandmother cell
hypothetical neuron that responds to one particular stimulus
rate coding
the informational content of a neuron may be related to the number of action potentials per second
temporal coding
the synchrony of firing may be used by a pop. of neurons to code the same stimulus
mental chronometry
study of the time course of info processing in the nervous system
additive factors method
general method for dividing reaction times into diff stages
N170
ERP component (neg potential at 170 ms) linked to perceiving facial structure
associative priming
reaction times = faster to stimulus X after being presented to stimulus Y (if X and Y previously associated)
exogenous
related to properties of the stimulus
endogenous
related to properties off the task
inverse problem
difficulty of locating the sources of electrical activity from measurements taken at the scalp in ERP research
dipole modeling
attempt to solve inverse problem involving assuming how many dipoles (regions of elec. activity) contribute to the signal recorded at the scalp
magnetoencephalography (MEG)
noninvasive method for recording magnetic fields generated by the brain at the scalp
neuronal activity generates
elec + magnetic fields that can be measured invasively/noninvasively
studies of single-cell recordings are based on
measuring number of action potentials generated + provide clues about neurons coding info by measuring their responses to stimuli
when populations of neurons are active in synchrony they produce
an active electric field that can be detected at the scalp (EEG)
when many such waves are averaged together + linked to stimulus –> event-related potential (ERP) is obtained
neurons communicate with each other by
- receiving electrical potentials (excitatory/inhibitory) from other neurons
- once threshold for excitation is surpasses –> action potential propagates along axon
- this triggers release of neurotransmitters at synapses with other neurons
what is firing/spiking
tiggering of an action potential
single-cell recording measures
the firing rates of individual neurons in non-human animals
EEG and MEG measure the
summed activity of large populations of neurons in humans
steps in single-cell recording in animals
- electrodes surgically implanted in brains of experimental animals
- can monitor firing rates of neurons when animal perceives diff stimuli
- provides info on how + where diff classes of stimulus are coded in the brain
feline visual system
single-cell recording in cats = instrumental in mapping organisation of visual cortex
- hubel and weisel found certain neurons in primary visual cortex fired strongly when cat saw straight line
selectivity
specific neurons respond to particular types of visual stimulus
hierarchal organisation
higher-level neurons respond to increasingly complex stimuli
sparse coding
neurons at top of hierarchy only respond to one specific stimulus
sparse distributed code
particular stimuli causes firing across specific set of neurons
steps in electroencephalography - EEG
- direct neural recording = fine-grained info but rarely possible in humans
- place electrodes on scalp + record changes in electrical potentials caused by neural firing in brain
- potential around 2-10 microvolt
- combined response of large numbers of neurons to generate measurable response
EEG has poor spatial resolution
- studies typically use 32 or 64 electrodes placed over participant’s head
- electrical signal is conducted through the skull so source may be distant from electrode where it is measured
- EEG most useful for learning when not where neural activity occurs
EEG signals are noisy
EEG measures tiny electrical signals
have to compete with noise:
- random neural firing
- elec activity from eye/facial movements
- electrical equipment interference
signal-to-noise ratio = poor
deal with this by averaging over large N
event-related potentials (ERPs) are produced by
- diff types of stimuli produce characteristic ERPs at diff points in time
- ERPs given names reflecting polarity and timing (N170, P600, N400) + location (N2pc)
- peaks pos/neg but doesn’t explain significance
- polarity depends on spatial arrangement of neurons
using ERPs to track timing
- ERPs often used to track time course of cog processes involved in a task
- components at diff points in time may be influenced by diff factors
stages of coding for facial recognition annd associated ERP
- perceptual coding of face
N170 (affected by perceptual changes to image)
- larger for human/animal faces - face recognition (identity processing)
N250 (unaffected by view changes, affected by familiarity)
- larger with familiar faces - person recognition (faces and names)
P400-600 (affected by both faces and names)
- similar effects for faces/written names
magnetoencephalography (MEG)
same basic principle of EEG
- but signals measured by SQUID sensors recording fluctuations in magnetic field
Pros:
- same temporal resolution as EGG
- better spatial resolution
Cons:
- not widely available
- expensive
