Introduction to the N170 Response to Words

Accessibility:  Intermediate-Advanced

This month is N170 month. I'm going to be going through a bunch of papers by Urs Maurer on the N170 ERP component and how it relates to word processing. EEG is not my specialty, so hopefully I won't mess anything up.



For this post, we'll start with the basics. The N170 is an ERP component measured in EEG experiments. The N means that it is a negative potential, and the 170 means that it peaks roughly at around 170 ms, although the timing can vary. The N170 tends to be elicited by certain categories of visual images (like faces), and is enhanced for categories for which the subject has some expertise (for example, enhanced N170 response for bird experts when viewing birds).

This last characteristic makes the N170 helpful for studying word processing. Urs Maurer and colleagues tested adults by showing them words, pseudowords, and symbol strings*. The adults showed a greater N170 to words than symbol strings, which would be consistent with an expertise for words acquired over years of reading. The N170 was also more left lateralized for words than to symbol strings, which is not surprising given the general left lateralization of language. Also, the N170 seems to be stronger over the inferior occipital temporal channels, close to the visual word form area.

So those are the basics for the N170 in normal reading adults. It's a useful tool for studying word processing in populations like children and people with dyslexia, so that is where we will continue.

*the task was to detect repetitions


Maurer U, Brandeis D, & McCandliss BD (2005). Fast, visual specialization for reading in English revealed by the topography of the N170 ERP response. Behavioral and brain functions : BBF, 1 PMID: 16091138

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Brain Measures Predict Future Improvement in Children With Dyslexia

Accessibility: Intermediate

Disclaimer: My PI is an author on this paper.

There is a lot of variability in outcomes for children diagnosed with dyslexia. Some children improve greatly over time, while others don't. Today, we're looking at a paper that asks whether it's possible to predict improvement in children with dyslexia.

Fumiko Hoeft and colleagues scanned children with and without dyslexia while performing a word rhyme task. They also tested the children on several reading measures. Two and half years later, they retested the children again on the same reading measures. Some of the children improved, while others didn't . The question then, is whether there is something from the brain scans or test scores in the first session that can predict performance 2 1/2 years later.



The researchers found two brain measures that predicted improvement in reading skills: greater white matter integrity in the right superior longitudinal fasciculus, and activation in the right inferior frontal gyrus during the rhyming task. Note that these regions are not your typical language regions. In fact, they are the right hemisphere counterparts of language processing regions in typical readers. Also, these didn’t correlate with reading improvement in control readers.This suggests that rather than imitating what typical readers are doing, the dyslexics who improve are bringing in compensatory mechanisms.

So if we have a dyslexic child, how accurately can we predict future improvement? The researchers found that brain data from those two regions by themselves predicted reading gains with 72% accuracy. When the researchers used data from the entire brain, they predicted reading gains with 90% accuracy. (Chance would be 50%. The researchers were trying to predict whether a child’s improvement was below or above the median improvement for the entire group.)

These results are an interesting case of brain data giving us more information the behavioral measures. None of the behavioral measures predicted which children would improve, but the brain data did.

One might ask how useful these results would be for dyslexics. On the one hand, any information is helpful. On the other, if you are in the group predicted to not show improvements, would you really want to know? One good thing about this type of research is that perhaps if we keep going in this direction, we might be able to not only predict improvement, but predict improvement to different types of interventions, thus leading to better treatment.


Hoeft F, McCandliss BD, Black JM, Gantman A, Zakerani N, Hulme C, Lyytinen H, Whitfield-Gabrieli S, Glover GH, Reiss AL, & Gabrieli JD (2011). Neural systems predicting long-term outcome in dyslexia. Proceedings of the National Academy of Sciences of the United States of America, 108 (1), 361-6 PMID: 21173250

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Don't Assume that fMRI and MEG Will Give You Comparable Results

Accessibility: Intermediate/Advanced

There are three common methods of studying brain function in normal human populations: fMRI, MEG, an EEG. There is surprisingly little crosstalk between the techniques, mostly due to practical issues.For better or worse, labs tend to specialize in one technology.

It's often assumed that the relationship with techniques is straightforward, that it's simple to map results from one technique onto another. However, a recent study by Johanna Vartianen and colleagues suggests otherwise.



The group wanted to study reading using all three brain techniques. Participants performed the same experimental paradigm twice: once with simultaneous EEG and fMRI, and once with simultaneous EEG and MEG. Participants saw words, pseudowords, consonant strings, and symbol strings, and words embedded in noise. Their task was to detect immediate repetitions. The EEG results from the two sessions were comparable, so the researchers went on to compare the fMRI and MEG activation patterns for the experiment.

To summarize, activation patterns between MEG and fMRI did not show a straightforward relationship. In some regions, the two techniques showed the same pattern. For example, in the occipital lobe, both MEG and fMRI measures had more activation to noisy words than other types of stimuli.

If you look at the occipitaltemporal lobe however, the two techniques had opposite results. MEG showed more activation to real letters than symbols, while FMRI showed more activation to symbols then letters.

In the left frontal cortex the two regions had completely different patterns. FMRI activation was higher for words and pseudowords than symbols and noisy words. The MEG results showed no difference at all between stimulus types.

I guess this is one of these results that you don't see going in, but in hindsight make you hit yourself over the head. FMRI and MEG measure very different things, so it’s entirely possible that results would come out differently. FMRI measures cerebral blood flow on a timescale of several seconds, while MEG measures synchronous electrical activation with millisecond resolution. So ( as the authors suggest) non-synchronous activity may be lost in MEG. Meanwhile, fMRI picks up average activity over a longer time period and may miss short-term activity.

Interestingly, the authers mentioned that previous MEG results for the visual word form area were fairly robust to task differences, while fMRI results do seem to vary with task. Now I don't know the MEG literature well, but they're certainly right about the fMRI literature. In that case, I wonder what it is about the MEG that makes its results relatively task independent. Is it the better temporal resolution? Perhaps MEG analyses focus on early, bottom up processing, which may be relatively task independent?


Vartiainen J, Liljeström M, Koskinen M, Renvall H, & Salmelin R (2011). Functional magnetic resonance imaging blood oxygenation level-dependent signal and magnetoencephalography evoked responses yield different neural functionality in reading. The Journal of neuroscience : the official journal of the Society for Neuroscience, 31 (3), 1048-58 PMID: 21248130

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Recycling Neurons for Reading

Accesibility: Intermediate-Advanced

Our brains have evolved to be good at certain things: seeing, hearing, learning language, and interacting with other similar brains, to name a few examples. But say you want it to do something new – look at symbols on a page and map them to language. In other words, you want to teach your brain to read. How would you go about doing this? What parts of the brain would you use?

Unless you plan on developing a completely new region, it makes sense to repurpose the brain regions you already have -- a process that neuroscientist Stanislas Dehaene refers to as “neuronal recycling.” This raises the question -- what regions are recycled? And do the regions that get co-opted become worse at their original function?



Dehaene and colleagues explored this question by scanning adults at different levels of literacy: literates, ex-literates (adults who used to be illiterate but learned to read in adulthood), and illiterate adults. They had several interesting findings:

1. They first looked at whether learning to read changes brain activation when looking at words. Not surprisingly, it does. Reading performance was correlated with increased brain activation in much of the left hemisphere language network, including the visual word form area. And this increased activation appeared to be specific to word-like stimuli.

2. During reading, ex-literates have more bilateral activation and also recruited more posterior brain regions. This is similar to what we find in children, who also show more spread out activation while reading. This suggests that unskilled readers recruit a wider set of brain regions as they are learning to read. As readers become more skilled, their brains become more efficient and recruit fewer regions

3. In literate adults, response to checker boards and faces in the visual word form area was lower in the visual word form area compared to non-readers. This suggests that learning to process words may actually be taking resources away from processing other stimuli.

4. The researchers looked more closely at responses to other faces and houses to see how exactly learning to read competed with other visual functions. They found that activation in the peak voxels for faces and houses did not change with literacy. However, activation in surrounding voxels did decrease.

5. And here's an interesting result. Since reading is a horizontal process (at least in the languages they were testing), the researchers checked to see if the visual system became more attuned to horizontal stimuli. They found that literacy enhanced response to horizontal but not vertical checker boards in some primary visual areas.


Dehaene S, Pegado F, Braga LW, Ventura P, Nunes Filho G, Jobert A, Dehaene-Lambertz G, Kolinsky R, Morais J, & Cohen L (2010). How learning to read changes the cortical networks for vision and language. Science (New York, N.Y.), 330 (6009), 1359-64 PMID: 21071632

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White Matter and Reading Ability

Accessibility:  Intermediate-Advanced

Hello folks.  Things are pretty busy over here and I might be having to review a lot of papers soon, so there's a possibility that entries here will get shorter and a bit more technical.  But we'll see.

Since reading is by nature a multimodal task involving both visual and language regions, it makes sense to look at brain connections in dyslexia. I've written once about white matter in dyslexia, when I blogged Bernard Chang’s PNH study. Today I'll cover two other studies that look at white matter and reading.



As a quick recap, brain tissue is often categorized into gray and white matter. White matter consists mostly of axons, the parts of neurons that send signals to other neurons. Therefore, white matter tracts carry information between brain regions and diffusion tensor imaging is a technique often used to study white matter.  You can take several measures with DTI, but one common one is fractional anisotropy, a measure of the directionality of water diffusion.  You can think of it as a measure of white matter integrity.

In one study, James Andrews and colleagues measured white matter integrity in preterm*  and term children. They found a correlation between reading skill and fractional anisotropy  in the corpus callosum, the large white matter tract that connects the two hemispheres. They also found a trend toward a correlation between reading skill and fractional anisotropy in the left temporal parietal region, a region often associated with reading. I'm surprised by the corpus callosum finding, and wonder its role might be in reading. Is the corpus callosum connecting language regions to their right hemisphere homologues? I also wonder if this is something general to the population, or a difference unique to preterm children. I guess we’ll have to see if this finding comes up in later studies.

Another DTI study found some more predictable results. Rimrodt and colleagues scanned the brains of children with dyslexia and normal-reading children between the ages of seven and 16 years. They found that children with dyslexia had lower FA in the left inferior frontal gyrus and the left temporoparietal region, both areas previously implicated in reading. Interestingly, they also found that the FA in some posterior areas involved in visual word processing (including the left fusiform) were correlated with speeded word reading.

*mean gestational age 30.5 weeks

ANDREWS, J., BEN-SHACHAR, M., YEATMAN, J., FLOM, L., LUNA, B., & FELDMAN, H. (2009). Reading performance correlates with white-matter properties in preterm and term children Developmental Medicine & Child Neurology, 52 (6) DOI: 10.1111/j.1469-8749.2009.03456.x

Rimrodt, S., Peterson, D., Denckla, M., Kaufmann, W., & Cutting, L. (2010). White matter microstructural differences linked to left perisylvian language network in children with dyslexia Cortex, 46 (6), 739-749 DOI: 10.1016/j.cortex.2009.07.008

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Noise Exclusion Deficits in Dyslexia

Accessibility:  Intermediate-Advanced

The human visual system includes two pathways, magnocellular and parvocellular, deriving from two types of retinal ganglion cells that project to different layers of the lateral geniculate nucleus. Generally speaking, the magnocelluar pathway is specialized for movement while the parvocellular pathway is specialized for color and detail.  Some researchers have found dyslexia to be associated with magnocelluar impairment, although evidence has been mixed.

A paper from Sperling and colleagues argues that magnocelluar deficits in dyslexica may actually be a deficit in noise exclusion.  The authors tested children with and without dyslexia using stimuli that were designed to activate the magnocellular or parvocellular pathways. The magnocellular stimulus was a patch with white bars that alternated rapidly between light and dark. The parvocellular stimulus had thin light and dark bars that did not alternate.



In addition to the two stimulus types, there was a high noise and low noise condition. In the low noise condition, one of the stimuli appeared to the left or right of the fixation mark. In the high noise condition, noise patches appeared on either side of fixation and the stimulus was overlaid onto one of the noise patches. In both cases, child had to say on which side the stimulus appeared.

The authors calculated contrast thresholds (the amount of contrast needed between the light and dark bars for accurate detection) for both groups of children. They found no difference in the contrast thresholds for the low noise condition. In the high noise condition, dyslexic children had higher contrast thresholds (more difficulty detecting) for both the magnocellular and parvocellular stimuli. In addition, thresholds in the high noise condition were correlated with language measures.

These are interesting results. While one study cannot rule out the magnocellular theory of dyslexia, this does open the possibility that many of the results that pointed to a magnocellular deficit were actually cases of noise exclusion deficit.   I do remember one paper about motion perception and dyslexia that can't be explained by noise, so I'll see if I can write about that later.

Another question is, how does noise exclusion lead to dyslexia? It could be that a noise exclusion deficit results in difficulties building phonological categories, which in turn affect reading. The authors also mention that noise exclusion could affect learning in the visual modality by making it harder to extract regularities from different fonts and scripts.


Sperling, A., Lu, Z., Manis, F., & Seidenberg, M. (2005). Deficits in perceptual noise exclusion in developmental dyslexia Nature Neuroscience DOI: 10.1038/nn1474

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Sensitivity and Specialization in the Occipitatemporal Region: Differences in Dyslexic Children

Accessibility: Advanced/intermediate

Early research on the role of the occipitotemporal region in reading often focused on characterizing a single region in the mid fusiform, commonly called the visual word form area. Since then, focus has gradually shifted from a single region to the entire length of the occipitotemporal region, looking at how the sensitivity and tuning changes as you move from posterior to anterior regions.



Van der mark used an approach like this to look at dyslexic and control children aged 9-12 years. Eighteen normal reading and twenty four dyslexic children performed a phonological lexical decision task in the scanner. Children saw words, pseudohomophones (words that sounded like real words but spelled differently, like “taksi”), pseudowords (pronounceable nonwords), and false fonts. The children were asked to decide whether something sounded like a real word. For example, the correct response would be “yes” for words and pseudohomophones and “no” for pseudowords and false fonts.

The children with dyslexia did worse for pseudohomophones and pseudowords and performed similarly to the controls for words and false fonts.

The authors report two main findings. First, the control children showed a gradient of print specialization in the occipitotemporal region, with more activation to false fonts in posterior regions and more activation to real letters and anterior regions. The control children did not show this trend.

Second, control showed more activation for pseudowords and pseudohomophones than words, while children with dyslexia didn't.

This is a nice study that takes a more nuanced approach to dyslexia brain differences. Brem and colleagues also got similar results with the words and false fonts.

By now there's quite a bit of literature on the specialization of the visual word form area. My own struggle, as I’m also doing this type of research, is the question of what does it all mean? We have all the studies now showing brain differences between control and dyslexic children, but what does it mean to have more or less activation? That the brains of dyslexic children process words differently? I could've told you that before we stared.

So what would help? Perhaps the next step in dyslexia research, now that we've mapped out the basic differences, is to zoom in as much as we can on the relationships between brain differences and behavioral differences. Perhaps more fine grained behavioral measures would help, or more interventional studies that looked at brain activation before and after training. It may also help to look at functional connectivity and how different brain regions interact. Anyone else have ideas?



van der Mark S, Bucher K, Maurer U, Schulz E, Brem S, Buckelmüller J, Kronbichler M, Loenneker T, Klaver P, Martin E, & Brandeis D (2009). Children with dyslexia lack multiple specializations along the visual word-form (VWF) system. NeuroImage, 47 (4), 1940-9 PMID: 19446640

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