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the 'visual word form' area (Cohen et al., 2000)

Ventral occipito-temporal cortex.

‘Brain letter box’, or gate to the reading system.

Activated specifically by letter strings acceptable in the language (e.g. NGTH but not TGNH, in English). - combination of letters useful in language

The proximity of this area to other regions coding faces and objects supports the idea that the brain has evolved to perceive letters and words as complex objects.


Cohen et al. (2000)

see notes

Stage 1: Processing restricted to the contralateral hemisphere (Visual area 4, occipital pole). - code mere visual properties

Stage 2: Transfer of information from both occipital poles to a more ventral region of the left occipital lobe (Visual word form area).

Activation moved forward – more ventrally – entering visual word form area – this area is left localised

Because the visual word form area is located in the left hemisphere, information coded in the primary visual areas in the right hemisphere (i.e., the left visual hemi-field) has to cross to the left hemisphere.

This transfer from right to left is done via the corpus callosum, which connects the two hemispheres.

In contrast, the information already coded in the left hemisphere (i.e.., the right visual hemi-field) does not have to cross.

It is sent within the same hemisphere instead


why is the RVF coded by the left hem and vice versa

see notes

The left retina of each eye captures the right visual field, whereas the right retina of each eye captures the left visual field.

But, and this is the key element, the inner retinas send information across, to the opposite hemispheres, whereas the outer retinas send information to the hemisphere on the same side (for this, follow the optical nerves coded in orange vs. green).

As a result, what is presented in the right hemi-field ends up in the left hemisphere, whereas what is presented in the left hemi-field ends up in the right hemisphere.

(This is not that right eye projects to the left, and vice versa for the left eye.)

This relates to the upper graph of my demonstration on the previous slide, before the information in the right occipital pole crosses via the corpus callosum to reach the brain letter box (or visual form area), normally developing in the left hemisphere.


lesions and visual word form area

can swap to the right hemisphere


spatiotemporal dynamics of word processing in the human cortex (Marinkovic et al., 2003)

Looked at the timecourse of visual word processing, using magneto-encephalography (MEG).

Estimated the peaks of cortical activity and its progression over time.

During reading, activation starts in both occipital poles.

At about 170ms it shifts to the left occipito-temporal region.

At about 230ms activity explodes in regions of both temporal lobes.

From 300ms onwards it extends over prefrontal and other temporal regions especially in the left hemisphere, before falling back in part to the posterior visual areas (occipital pole).

see notes


Catani et al. (2003)

see notes

Fibres depicted in red convey information from port-to-port, in an omnibus fashion; those depicted in green work like motorways.

In the reading system, obviously, these two types of fibers are especially important in the left hemisphere (unlike on the picture), to transfer information from the ventro-occipital regions (VWFA) to both posterior areas of the frontal lobe and temporal regions (see previous slide).


can cognitive models explain brain activation during word and pseudo word reading? a meta-analysis of 36 neuroimaging studies - Taylor et al. (2012)

see notes

Cognitive models make predictions about the functional overlap between brain regions involved in reading.

Thus, brain regions sensitive to these contrasts should correspond to the model’s components (e.g., input lexicon, grapheme-to-phoneme transcoding, etc. ).

They examined whether 36 neuroimaging studies of reading pointed at the same brain regions regarding two main contrasting dimensions in DRC:
1) lexical status (i.e., words vs. nonwords; Is the stimulus part of your long-term memory?)
2) regularity (i.e., regular/irregular; Can the word be read correctly by both routes?)

They distinguished between engagement vs. effort in how these dimensions translate into BOLD (Blood Oxygen Level Dependent) signal (i.e., amount of oxygen needed by a region). – no linear r’ship – inverted U shape r’ship

Note: peaks in BOLD signal (brain activity) do not mean that a region “likes” the stimulus, but instead, that it is having a hard time processing it.

see notes

Engagement refers to whether or not the brain region in question is able to deal with the stimulus - In other words, it refers to the capacity of the stimulus to evoke knowledge in that region.

Effort refers to the amount of resources/fuel required to code and process the stimulus in that region, once the region is engaged.

Is given region good for given stimulus?

One region engaged, how effortful will processing be? – hard to process = need more oxygen

Distinguish between those easy and painful to process

But first, they tested whether the distinction between engagement and effort made sense in DRC

Check their relevance by looking at the activity in the input lexicon (in the computerized version).


Taylor et al. (2012) results

These results were obtained by giving the computer-implemented version of the dual-route model a list of words and nonwords, which the model had to recognize or reject.

Words in the input lexicon earn points in proportion to how well they match the stimulus (i.e., in terms of letters in the correct positions), and the more they earn points and also the more they are frequent in the language, the more able they are to deplete their competitors.

The word is recognised once its activation level is higher than that of its competitors by a minimum distance.

The graphs shows how much activity there is in the input lexicon.

As can be seen, firstly, existing words generate a strong engagement from that part of the model, in comparison to unknown words (i.e., pseudowords).

Secondly, in the word case, it takes longer for low frequency strings to reach the same activity level compared to high frequency words (Fig. A).

Thirdly, activity remains for longer in that region of the system for low- (as opposed to high-) frequency words, which altogether reflects that recognition is not as easy for low-frequency words (Fig. B).


the subtraction logic

Left with pool of photos taken while brain doing task– measure engagement of various regions

Where is vocab knowledge?

If want to locate given region, have to take photo of activation for words and subtract images for pseudowords