The Role of Visual Factors in Dyslexia

What are the causes of dyslexia? Decades of research reflect a determined search for a single cause where a common assumption is that dyslexia is a consequence of problems with converting phonological information into lexical codes. But reading is a highly complex activity requiring many well-functioning mechanisms, and several different visual problems have been documented in dyslexic readers. We critically review evidence from various sources for the role of visual factors in dyslexia, from magnocellular dysfunction through accounts based on abnormal eye movements and attentional processing, to recent proposals that problems with high-level vision contribute to dyslexia. We believe that the role of visual problems in dyslexia has been underestimated in the literature, to the detriment of the understanding and treatment of the disorder. We propose that rather than focusing on a single core cause, the role of visual factors in dyslexia fits well with risk and resilience models that assume that several variables interact throughout prenatal and postnatal development to either promote or hinder efficient reading

On the insufficiency of laterality-based accounts of face perception and corresponding visual field asymmetries

It has been known for nearly a century that the left half of a face is better recognized than the right half (Wolff, 1933). This left half-face advantage is commonly thought to reflect a combination of right hemisphere (RH) superiority for face recognition and a contralateral hemifield-hemisphere correspondence between the RH and the left visual field (LVF). The purpose of this set of experiments was to determine whether RH superiority for faces and contralateral hemifield-hemisphere correspondence is sufficient to explain the LVF half-face advantage. We set out four aims to accomplish this: (1) Use behavioral and fMRI methods to demonstrate the LVF half-face advantage and identify its neural basis in ventral occipital-temporal cortex (VOTC); (2) use behavioral methods to show that RH superiority is insufficient to explain the LVF half-face advantage; (3) use behavioral methods to show that we perceive only one half of a face at a time; and (4), albeit not initially proposed, use methods developed to accomplish aims 1-3 to distinguish retinotopic face representation from face-centered representation.In our first set of experiments (behavioral and fMRI), we identified for the first time a neural LVF half-face bias in RH face-selective cortex. We also found that the neural LVF bias in right FFA underlies the relationship between FFA laterality and the LVF half-face advantage. This revealed an explicit neural mechanism to describe the commonly assumed basis of the LVF advantage for centrally-viewed faces. In our next set of experiments (behavioral) we addressed the second aim, and found that LVF half-face advantage is contingent upon the simultaneous presence of both an upright LVF and RVF half-face, and does not reflect inherently superior processing of LVF over RVF half-face information. This challenged the sufficiency of the mechanism we discovered in Aim 1 as an explanation of the LVF half-face advantage. In our next set of behavioral experiments (which addressed our third aim) we found that half-face identities compete for limited processing resources, and only one identity can be processed at a time. Furthermore, we found that this does not apply to faces in which half-face identities are similar enough to be perceived as a normal (i.e. non-chimeric) face. In our final set of experiments (behavioral) we addressed our additional Aim 4, and found that the LVF half-face advantage occurs regardless of the location of the face in the visual field. This suggests that faces are represented to some degree in an object-centered reference frame, and the LVF half-face bias reflects a bias to the left half of a face, rather than a retinotopic bias to the left half of visual space

Prior experience modulates top-down predictive processing in the ventral visual areas

Repetition suppression(RS)refers to that the reduction of neural activities for repeated presentations of a given stimulus compared to its first presentation. Summerfield et al(2008) found the magnitude of RS is affected by the repetition probability of stimuli, called as P(rep) effect. Based on the predictive coding theory, prior experience about the sensory inputs is necessary to optimally achieve cognitive processes. But it remains unclear how prior experience modulates predictive processes. To address this issue, in Study I, we estimated the P(rep) effects for Chinese characters and German words in native Chinese and German participants to test whether prior experience affects the P(rep) effect of lexical stimuli. The results showed that the P(rep) effect is only manifest for words of a language with which participants had prior experience. Study II performed fMRI measurements before and after a 10-day perceptual learning (PL) training for cars to test the modulation of short-term experience on the P(rep) effect. The results replicated the P(rep) effect for faces and cars. More interestingly, the P(rep) effect can be temporarily abolished by the short-term PL experience. The third study investigated how prior experience modulates sensory inputs. Study 3a adopted a classic stimulus repetition paradigm to measure RS for faces, together with either concurrent short-term memory (STM) load or a control condition. The results showed that RS is significantly attenuated when visual STM is loaded. Study 3b manipulates attention by a face inversion detection task. The results showed that the RS effect appears in the STM condition when participants attend to faces. The main conclusions: i) predictive processes, as measured by the P(rep) effect, require extensive prior experiences with stimuli, but ii) these can also be modulated by short-term learning experience. Further, iii) STM and attention are two modulators of prior experiences on predictive processes