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PS2061: The Sensing Brain - Coggle Diagram
PS2061: The Sensing Brain
Structure & Function
Historical Perspectives\n- Localist view\n- Anti-localist view
Localist View (Flourens, 1822)\n- Brain composed of specialised areas\n - Info processing in each local & specific\n- Discrete areas responsible for discrete functions
Localist View (Gall & Spurzheim, 1810)\n- Believed function to be localised to specific brain areas\n- Reflected in morphology of skull\n - Pseudoscience of Phrenology
Localist View (Broca 1861)\n- Reported case of productive aphasia\n- Brain contained lesion in specific area of frontal lobe\n - Today referred to as Broca's Area
Anti-Localist View (Lashley, 1929)\n- Brain collection of networks\n - Info processing distributed\n- All areas equally responsible for all functions
Brain Architecture
Cytoarchitecture\n- Cellular composition of cortex varies\n- Way info processed across cortex therefore cannot be uniform\n- Mapping variation can distinguish cortical areas involved in diff forms of info processing
Connectivity\n- Flow of info across brain networks integral part of info processing in brain\n- Understanding architecture of networks important to understand relationship between neural & cog processes
Histological Analysis\n- Reveals terminal sites
Animal Studies\n- Tracers injected into one end of neurone in one area\n- Transported to other end
Systems
Visual System\n- Retinal ganglion neurones\n- Lateral geniculate nucleus neurones\n- Primary visual cortex neurones
Auditory System\n- Coclea\n- Auditory nerve\n- Dorsal cochlear nucleus\n- Ventral conchlear nucleus\n- Superior olivary nucleus\n- Inferior coliculus\n- Medial geniculate nucleus\n- Auditory cortex
Limitation\n- Across just few synapses info travels auditory nerve to cortex
Measures
Behavioural Neurophysiologiy\n- Direct neural measure\n- Electrodes inserted into/directly onto small area of brain
Types of Recording\n- Single-unit\n- Multi-unit
Single-Unit Recordings\n- Recording activity of individual neurones
Multi-Unit Recordings\n- Recording summed activity from small populations neurones
Advantage\n- Important in animal studies\n - Determine exactly where signal coming from\n- High temporal & spatial resolution
Size tuning\n- Optimal size of stimulus for neurone\n - Is selective
Retinal Ganglion Cells\n- On centre = Excitatory response\n - Light landing makes more likely neurone will spike\n- Off surround = Inhibitory response\n - Light landing will make less likely neurone will spike
Measures
Electroencephalography
Magnetoencephalography
Transcranial magnetic stimulation
EEG
Indicate how neural activity changes over time
Average traces to cancel out noise to capture event-related potentials
Detect responses specific to particular signals
Measure brainwaves/oscillations
Function
Electric potentials produced by single neurones small
Signal from several neurones active together can be measured
Advantage
High temporal resolution
Limitation
Poor spatial resolution
Signal distorted by tissues between brain & electrode
Measuring EEG
Describe diff components
Characteristic changes in voltage
Components
Electrode
Amplitude
Latency
MEG
Indicate how neural activity changes over time
Average traces to cancel out noise & capture evoked responses
Measure brainwaves/oscillations
Advantages
Very high temporal resolution
Better spatial resolution
Magnetic signals not as distorted
TMS
Target specific processes that occur at particular time point in experiment
Disruption for small amount of time at localised area of cortex
Act like temporary lesion
Function
Brief & rapidly changing high intensity electrical current passed through loop of conducting wire onto area of scalp
Generates powerful magnetic field
Capable of inducting electric current in excitable tissue
Induced current depolarises nearby located neurone assemblies beneath coil when applied onto cortical areas
Generates neurophysiological/behaviour effects depending on contributing functions
Results (Valero-Cabre et al., 2017)
Characterised quant by recording latency & amplitude of motor evoked potentials
By means of electromyography on specific hand/forearm muscles
TMS of Primary Visual Cortex
Induces percept of phenomenon
Reported as appearing in central visual field
TMS of Primary Motor Region
Triggers involuntary twitches of muscles
In segments of upper limb contralateral to stimulated hemisphere
Follows somatotopic organisation in motor cortex
fMRI
Detects diff in magnetism caused by increased oxygenated blood
Neurones increasing firing rate requires more oxygen
In response to increased firing rate more oxygenated blood supplied in veins to neurones
Relies on BOLD
Blood oxygen level dependent signal
Advantage
Higher spatial resolution
3x3x3 mm
Limitation
Lower temporal resolution
Signal not direct measure of brain activity
Diff between oxygenated & deoxygenated blood
Data Analysis (Lindquist, 2008)
Statistical parametric maps used to present results of statistical analyses
Voxels w. p-value below threshold colour-coded
Signify contain significant task-related signal
Results superimposed onto high-resolution anatomical image for presentation
Ocular Dominance Columns (Adams et al., 2007)
Cortical surface
Deeper layers
Basic Processing
Basic Processing
Description of tuning curves
Mapped response over range of values
Hierarchical integration of neurones generates novel receptive field properties
Used to decode physical properties of world
Types of Tuning Curve
Orientation
Auditory
Somatosensory
Orientation Tuning Curve
Some neurones respond preferably to specific orientation
Receptive field organisation has circular centre surrounf
Elongation orientation tuned
Single Cell Macaque Data (Hubel & Wiesel, 1968)
Showed not simply on/off
Combination of tuning curves allowed to detect all orientations
Auditory Tuning
Loudness of broad & narrow turned neurone used to code location of sound
Ipsilateral (same side as neurone)
Azimuth (L/R horizontal plane)
Contralateral (opposite side of neurone)
Types of Auditory Tuning
Frequency
Location
Auditory Frequency Turning
Firing rate @ diff frequencies
Auditory Location Tuning
Inter-aural delay @ diff frequencies
Inter-aural temporal difference turning
Somatosensory Tuning (Hsiao et al., 2002)
Spikes @ diff orientations in response to stimulus
Structure & Function
Several codes can co-exist in same area
Some populations may code for diff features
Can see using diff methods
Population Coding
Think of population code
Population response
By knowing properties of neurones a population can help decode orientation in stimulus
Significance
Evidence for localised & distributed info processing
Help explain brain-behaviour relationships in terms of processing
Future Research
Aim to integrate levels of explanation
Functional segregation
Functional integration
Functional Segregation
How function emerges from specialised info processing
In individual brain areas
Functional Integration
How function emerges from distributed info processing
Across networks of areas
