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cognition & emotion ii > Reading & the Brain > Flashcards

Reading & the Brain Flashcards

1
Q

COHEN ET AL. (2000): ‘VISUAL WORD FORM’ AREA

A
  • left ventral occipito-temporal cortex
  • “brain letter box”/gate to reading system
  • activated specifically by letter strings acceptable in language (ie. NGTH but not TGNH in English) & via existing words (Glezer et al. (2015))
  • area proximity to other regions coding faces/objects supports idea that brain has evolved to perceive letters/words as complex objects
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2
Q

WHY IS THE RIGHT VISUAL FIELD CODED BY THE LEFT HEMISPHERE (VICE VERSA)?

A
  • inner retinas send info across to opposite hemispheres; outer retinas send info to hemispheres on same side
  • aka. what is presented in right hemi-field -> left hemisphere (vice versa); NOT projection
  • relates to before info in right occipital pole crosses via corpus callosum to reach brain letter box/visual form area (normally developing in left hemisphere)
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3
Q

COHEN ET AL. (2000): VISUAL STAGES

A

S1) Processing restricted to contralateral hemisphere (V4; occipital pole)
S2) Info transfer from both occipital poles -> ^ ventral region of left occipital love (visual word form area) via corpus callosum (hemisphere bridge) from right -> left; goes straight there if left

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4
Q

COHEN ET AL. (2004)

A
  • kids’ reading networks = more flexible > adults
  • early age lesion -> visual word form area can swap to right hemisphere
  • highly plastic brain nature early on allowed development of visual word form area in the right hemisphere (as corresponding left hemisphere region is not there anymore)
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5
Q

MARINKOVIC ET AL. (2003)

A
  • looked at time-course of visual word processing using magneto-encephalography (MEG)
  • estimated peaks of cortical activity & progression over time
  • reading = activation starts in both occipital poles
  • 170ms = shifts to left occipito-temporal region
  • 230ms = activity explodes in both temporal lobe regions
  • 300ms = extends over prefrontal/other temporal regions esp. in left hemisphere before falling back in part to posterior visual areas (occipital pole)
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6
Q

CATANI ET AL. (2003)

A
  • U fibres (occipito-temporal projection system (OTPS)) = info transport port-to-port; located laterally to ILF; connect adjacent gyri of lateral occipito-temporal cortices to form OTPS
  • inferior longitudinal fasciculus (ILF) fibres = work like motorways
  • both in right hemisphere
  • particularly important in left hemisphere (reading system) to transfer info from ventro-occipital regions (VMFA) -> posterior frontal lobe areas/temporal regions
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7
Q

GLEZER ET AL. (2015): PROCEDURE

A

VENTRO-OCCIPITAL REGIONS (VMFA)
- repetition suppression = stimulus repetition leads to reduced neural response
- if VWFA only codes info about familiar letter strings (“ght” (S1) VS “htg” (S2)) -> the more S2 is similar to S1 the weaker the neural response
- ie. vight-vight (S) < pight-vight (1L) < falm-vight (D)
- BUT if VMFA contains neuron populations each coding a familiar word then repetition suppression should be abolished by just changing 1 letter between 2 real words (did find this!)
- ie. right-right (S) < light-right (1L) = calm-right (D)

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8
Q

GLEZER ET AL. (2015): RESULTS

A
  • VMFA contains neuron populations each coding familiar word; repetition suppression = abolished by changing 1 letter between 2 real words
  • pseudoword pairs showed graded effect; real words/trained psuedowords showed all-or-none repetition suppression
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9
Q

TAYLOR ET AL. (2012): BACKGROUND

A
  • cognitive models make predictions about functional overlap between brain regions involved in reading
  • word > nonword
  • irregular > regular
  • aka. brain regions sensitive to such contrasts should correspond to model’s components (ie. input lexicon/grapheme-to-phoneme transcoding)
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10
Q

TAYLOR ET AL. (2012): PILOT PROCEDURE

A
  • examined if 36 neuroimaging studies of reading pointed at same brain regions regarding 2 main contrasting DRC dimensions:
    1) lexical status (ie. words VS nonwords aka. is stimulus part of LTM?)
    2) regularity (ie. regular/irregular aka. can the word be read correctly by both routes?)
  • both provide 2 contrasts distinguishing between types of acquired dyslexia as cognitive models = partly derived from reading disorder observation
  • distinguished between engagement VS effort in how dimensions translate into BOLD (blood oxygen lvl dependent) signal (ie. oxygen amount needed by regions)
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11
Q

TAYLOR ET AL. (2012): PILOT METHODOLOGY

A
  • peaks in BOLD signal do NOT = region “liking” stimulus; instead that it’s having a hard time processing it
  • engagement = whether brain region in question can deal w/stimulus; aka. capacity of stimulus to evoke knowledge in said region
  • effort = amount of resources/fuel required to code/process region stimulus once region = engaged
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12
Q

TAYLOR ET AL. (2012): PILOT

A
  • first tested if distinction between engagement/effort made sense in DRC
  • check relevance by looking at activity in input lexicon (computerised version)
  • results obtained by giving computer-implemented version of dual-route model word/nonword list which model had to recognise/reject
  • words in input lexicon earn points in proportion to matching stimulus (ie. letters in correct positions); the more they earn points/frequency in language, the more able they are to deplete competitors; word is recognised once its activation lvl = ligher than its competitors by minimum distance
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13
Q

TAYLOR ET AL. (2017): PILOT RESULTS

A
  • confirm engagement/effort distinction = valid
  • existing words generate stronger engagement > unknown words (pseudowords)
  • longer for low frequency strings to reach same activity lvl > high frequency words
  • activity remains longer in that region of system for low > high frequency words; altogether reflects that recognition isn’t easy for low-frequency words
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14
Q

THE SUBTRACTION LOGIC: WORDS > PSEUDOWORDS

A
  • to isolate regions specifically involved in recognising existing words:
    1) take brain activity elicited by word stimuli
    2) subtract from it the activity elicited by unknown words
  • aka. this removes activity common to processing 2 stimuli kinds from brain map generated by existing words; this identifies neural activity specific to lexical processing (ie. lexical route)
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15
Q

DRC MODEL: SYSTEMATIC APPROACH I

A
  • lexical pathway engages words BUT not/weakly pseudoword strings
  • taxed more by low-frequency words > high-frequency words
  • aka. 2 contrasts pointing towards:
    1) lexical route = words - pseudowords
    2) lexical route = low-frequency words - high-frequency words
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16
Q

DRC MODEL: SYSTEMATIC APPROACH II

A
  • irregular words should engage lexicon ^ > non-orthographic strings (ie. &%^%)
  • latter = not represented in lexical memory; obvs not gonna activate any word neighbour
  • mental dictionary should be taxed ^ by irregular words > regular esp. less-frequency words in language (faint lexical representations)
  • lexical memory = only way to reach exception words aka. low frequency irregular words -> ^ effort
  • aka. 2 contrasts pointing towards:
    1) lexicon = irregular words - non-orthographic strings
    2) lexicon = (low-frequency) irregular - regular
17
Q

DRC MODEL: REGULARITY CONTRASTS

A
  • points specifically to lexicon
  • excludes semantic system as model does not assume ^ engagement of semantics for irregular words > regular
18
Q

NON-LEXICAL PRINT-TO-SOUND CONVERSION ROUTE

A
  • contrasts regular PTSCR
  • should engage both words/psuedowords BUT not non-orthographic strings (not linguistically relevant)
  • should also be taxed ^ by pseudowords > words as even though pseudowords engage non-lexical route, it’s less accustomed to them VS regulars; same applies to phoneme output system (ie. inner speech)
  • words are also taken care of by lexical route aka. engagement of all parts in word case = ^ even
19
Q

NON-LEXICAL ROUTE & PHONEME OUTPUT SYSTEM

A
  • both should be struggling w/irregular words as DRC produces 2 conflicting responses
  • w/this arising conflict it’s likely that activity should linger particularly at lvl of phoneme output system w/some reverberation upwards into print-to-sound conversion region
20
Q

LEXICO-SEMANTIC PATHWAY

A

1) words - pseudowords
2) low-frequency - high-frequency

21
Q

INPUT LEXICON

A

1) irregular words - non-orthographic strings
2) (low-frequency) irregular words - (high-frequency) regular words

22
Q

CONVERSION ROUTE & PHONEMIC OUTPUT BUFFER

A

1) pseudowords - non-orthographic strings
2) irregular words - non-orthographic strings
3) pseudowords - regular words
4) irregular words - regular words

23
Q

SUMMARY I

A
  • 1 component may be isolated by multiple contrasts:
    LEXICO-SEMANTIC PATHWAY
    1) engagement = words - pseudowords
    2) effort = low-frequency - high-frequency words
    INPUT LEXICON
    1) engagement = irregular words - non-orthographic strings
    2) effort = (low-F) irregular words - (high-F) regular words
    PRINT-TO-SOUND CONVERSION/PHONEME OUTPUT BUFFER
    1) engagement = pseudowords/irregular - non-orthographic strings
    2) effort = pseudowords/irregular - regular words
24
Q

TAYLOR ET AL. (2012): PROCEDURE

A
  • 36 fMRI/PET studies included in meta-analysis
  • same task on both words/pseudowords or regular/irregular words
    TASKS
  • reading aloud/silently
  • lexical decision (ie. is “brain” a word?)
  • visual feature detection (ie. is there a “x” in “brain”?)
  • phonological lexical decision (ie. does “brane” sound like a word?)
  • stimulus repetition detection (ie. “brain” x2)
  • rhyme judgement (do “brain” & “train” sound the same?)
25
Q

TAYLOR ET AL. (2012): RESULTS

A
  • print-to-sound conversion = inferior parietal cortex
  • phoneme system = inferior frontal gyrus
  • spoken response/not -> further separation between input (orthographic) VS output (phonological) lexicon & between grapheme to phoneme conversion system VS phoneme system

cognition & emotion ii (15 decks)

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