psy393: cognitive neuroscience ct, mri .1 psy393: cognitive neuroscience prof. anderson department

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    Psy393: Cognitive Neuroscience

    Prof. Anderson Department of Psychology

    Week 3

    Functional imaging Brain recording in neurologically intact brains

    Not anatomical/structural imaging: Static CT, MRI

    Physiological/functional imaging: Dynamic 2 classes

    Electrical EEG, ERP

    Metabolic fMRI, PET

    Large populations of synchronous neural firing

    Produce electrical potentials

    Skull and scalp passively conduct signals that can be amplified and measured

    Stadium/microphone analogy

    Single voice Cheering crowd

    Electroencephalography (EEG) EEG signal: Dipoles

    Excitatory inputs (EPSPs) Relative depolarization of dendrites relative to cell body Creates voltage

    difference dipole

    Important for studying sleep, diagnosing epilepsy and brain damage

    Signature rhythms relate to state of arousal

    Beta: alert, low amplitude, high frequency Alpha: resting with eyes closed, high amplitude Theta: deeply relaxed

    EEG signal: Brainwaves

    EEG records global brain activity over long time period Represents neural rhythms Not relative to a stimulus

    ERPs are a special case of EEG Align signal to onset of a stimulus or response

    Event-Related Potential (ERP)

    Average EEG trace from a large number of trials

    Noise cancels out

    Evoked Response Potentials: Evoked brainwaves

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    Downward waves: positive (P) Upward waves: negative (N) Each wave produced by a different generator

    Serial order Exogenous components

    I – V: brainstem generators Detect infant deafness

    Endogenous components N1, P2, N2 Cognitive

    Its all in the timing: Endogenous & Exogenous components

    Within the first few milliseconds


    Endogenous Pros Really good temporal resolution Specific physiological markers (components)

    e.g., N1, P3 etc., can be linked to known cognitive processes

    Cons Poor spatial resolution Largely cortical

    Difficult to get at some brain regions e.g., medial temporal lobes, subcortical structures

    ERP: The good and the bad

    MRI: Magnetic Resonance Imaging

    Quest for better resolution, brain coverage Requires very, very strong magnet

    x 80,000 =

    4 Tesla = 4 x 10,000 ÷ 0.5 = 80,000 X Earth’s magnetic field


    1 Tesla (T) = 10,000 Gauss

    Earth’s magnetic field = 0.5 Gauss

    Protons spin around a given axis (random axis): “Precession”

    When placed in a magnetic field the protons become aligned in parallel

    Resonance: A Radio Frequency (RF) pulse is used in MRI to push protons out of alignment with the magnetic field

    Imagine tuning fork

    Localization: Resonance freq depends on strength of magnetic field Signal: Loss of RF energy (“Relaxation)

    Many organic elements are magnetic Hydrogen most abundant human body

    Structural MRI

    MRI studies brain anatomy. Functional MRI (fMRI) studies brain function.

    Reminder: MRI vs. fMRI MRI vs. fMRI MRI fMRI

    •High resolution (1 mm)

    •One image …

    • Low resolution (~ 3 mm)

    • Many images (e.g. every 2 s for 5 minutes)

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    E = mc2 ???

    Where does the signal come from? The first brain imaging exp

    “[In Mosso’s experiments] the subject to be observed lay on a delicately balanced table which could tip downward either at the head or at the foot if the weight of either end were increased. The moment emotional or intellectual activity began in the subject, down went the balance at the head-end, in consequence of the redistribution of blood in his system.”

    -- William James, Principles of Psychology (1890)

    Angelo Mosso Italian physiologist


    Origin of fMRI signal: BOLD Blood Oxygenation Level Dependent signal (BOLD)

    Why? Deoxy hemoglobin has increased magnetic properties (paramagnetic) Ratio of oxygenated blood (arteries) to deoxy (veins) increases with neural activity

    Do to increased blood flow, but same O2 extraction Results in decreased magnetic susceptibility

    Increased fMRI signal

    ↑ neural activity ↑ blood flow/ O2 ↑ fMRI signal

    Hemodynamic Response Hemodynamic response (HR): Blood flow change Neural response: milliseconds HR: peak 5-10 s

    Block designs Examine extended HR

    across same trial type Event-related designs (ER)

    HR for individual trials Slow vs Rapid ER ER allows examination of trial specific HR

    E.g., Can examine what brain response predicts later memory

    - Contrast cond1 and cond2 - Functional images are

    subtracted from one another. - Superimposed on anatomical


    Anatomical image Functional images

    Condition 1 Condition 2

    Statistical map of difference

    fMRI: Subtractive logic

    Group activation vs ROIs

    Brains are different in size, shape, etc. Can “warp” into common brain space See what is consistent across people

    Regions of interest (ROI) Predefine anatomical regions Examine signal No warping

    Pros Non-invasive, no radiation Multiple sessions with same subject High spatial resolution Good temporal resolution

    Cons Expensive Correlational

    MRI: Pros and cons

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    Measures local changes in cerebral blood flow (rCBF)

    Measures rCBF over a few minute period

    Positron Emission Tomography (PET)

    Radioactive isotopes tracers Isotopes rapidly decay

    (~2 min half life) Emit positrons Positrons collide with electrons

    2 photons (or gamma rays) are emitted

    Photons travel in opposite directions Allows location of collision to be determined

    Positron Emission Tomography (PET)

    Pros Track multiple metabolic processes

    labeling of various substances imaging of some neurotransmitters

    Cons Invasive

    radioactive isotopes can only be administered limited number of times

    Limited spatial resolution Highly limited temporal resolution

    Limited by the half life of the isotope used

    PET: Pros and cons End of Part 1

    Perception and Encoding

    Eye to brain: Evidence for parallel processing

    Brain to mind: How does neural organization relate to human perception?

    Review: Is vision analytic or synthetic?

    Visual maps: Multiple neural representations of reality

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    Vision as analytic vs. synthetic

    Analytic/constructivist Construct perception through assembly of its parts Feature extraction —> Object perception

    Synthetic/gestalt Whole more than sum of parts Object perception —> feature extraction

    Neural divergence

    Neural convergence

    This week

    Overview of visual neural pathways Parallel processing I: Two main receptor types

    Two types of vision Cones: High acuity, lower sensitivity Rods: Low acuity, higher sensitivity

    Different topography Origin of M & P

    Cones: Parvo Rods: Magno

    Other receptor types as well: Retina-SCN: Regulation of circadian rhythms

    Ganglion cells

    Middle layer

    Receptor cells





    Eye to CNS: Parallel processing II

    Two pathways Retino-geniculate-striate pathway Retino-collicular-pulvinar pathway

    Retino-geniculate-striate path Vision for perception: “What” systems

    Conscious vision Cortical blindness: Hemianopia

    “Blindsight” Weiskrantz

    Nonconscious sight May be due to spared

    Cortex Spared retino-collicular


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    Retino-collicular-pulvinar path Vision for action: “Where” systems

    Evidence for action vs. perception Stimulus present in intact and blind fields slowed during eye movement, not detection

    Retina—>Suprachiasmatic nucleus

    Other forms of nonconscious vision Non-rod, non-cone, melatonin based photoreceptors

    Regulation of circadian behavior Mutant mice lacking rods and cones demonstrate phase shifting to light Supported by connection between retina and SCN Conclude: Many types of “vision”

    Retino-geniculate pathway Organization of LGN: Laminar structure

    Retinal origin Temporal/Nasal adjacent (Same VF)

    Retino-geniculate pathway: Parallel processing III

    Organization of LGN: 2. Retinotopy

    6 representations of retina in register

    Retino-geniculate pathway

    Organization of LGN: 3. Morphology Not all retinal maps the same

    Parvocellular (P) Small cells Top 4 layers

    Magnocellular (M) Large cells Bottom 2 layers

    Organization of visual cortex: Divide & Conquer!

    Bifurcations and more bifurcations

    LGN —> V1 2 divisions

    M & P

    V1 —> extrastriate Even greater divergence Maintain M & P origin

    Differ in features (Parallel) & complexity (Hierarchical)

    Increase in RF size



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    Primary visual cortex: Striate cortex/V1/Area 17

    First cortical synapse in vision: Calcarine sulcus

    Striate cortex (V1): Retinotopy

    6 LGN maps—> 1 striate map

    Striate cortex (V1): M & P segregation

    Distinct laminar projections

    Striate cortex (V1): Eye, orientation selectivity

    Ocular dominance columns (Retained from LGN) Diff from LGN: Orientation selectivity

    Increase in complexity to LGN (center-surround)

    Higher order visual cort


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