According to most textbooks, our brain is divided into separate areas that are dedicated to specific senses. We have a visual cortex for vision, a tactile cortex for touch, and so on. However, researchers suspect that this division might not be as fixed as the textbooks say. For example, blind people can switch their 'leftover' visual cortex to non-visual purposes, such as reading Braille – a tactile alphabet.

Can this switch in functional organization also happen in healthy people with normal vision? To investigate this, Siuda-Krzywicka, Bola et al. taught a group of healthy, sighted people to read Braille by touch, and monitored the changes in brain activity that this caused using a technique called functional magnetic resonance imaging. According to textbooks, tactile reading should engage the tactile cortex. Yet, the experiment revealed that the brain activity critical for reading Braille by touch did not occur in the volunteers’ tactile cortex, but in their visual cortex.

Further experiments used a technique called transcranial magnetic stimulation to suppress the activity of the visual cortex of the volunteers. This impaired their ability to read Braille by touch. This is a clear-cut proof that sighted adults can re-program their visual cortex for non-visual, tactile purposes.

These results show that intensive training in a complex task can overcome the sensory division-of-labor of our brain. This indicates that our brain is much more flexible than previously thought, and that such flexibility might occur when we learn everyday, complex skills such as driving a car or playing a musical instrument.

The next question that follows from this work is: what enables the brain’s activity to change after learning to read Braille? To understand this, Siuda-Krzywicka, Bola et al. are currently exploring how the physical structure of the brain changes as a result of a person acquiring the ability to read Braille by touch.

The current view of neural plasticity in the adult brain sees it as ubiquitous but generally constrained by functional boundaries (Hoffman and Logothetis, 2009). At the systems level, experience-driven plasticity is thought to operate within the limits of sensory divisions, where the visual cortex processes visual stimuli and responds to visual training, the tactile cortex processes tactile stimuli and responds to tactile training, and so on. A departure from this rule is usually reported only during large-scale reorganization induced by sensory loss or injury (Hirsch et al., 2015; Lomber et al., 2011; Merabet and Pascual-Leone, 2010; Pavani and Roder, 2012). The ventral visual cortex, in particular, is activated in blind subjects who read Braille (Büchel et al., 1998; Reich et al., 2011; Sadato et al., 2002, 1996) and lesions of this area impair Braille reading (Hamilton et al., 2000). This visual cortex thus has the innate connectivity required to carry out a complex perceptual task – reading – in a modality different than vision. It is unclear, however, to what extent this connectivity is preserved and functional in the normal, adult brain.

A growing amount of evidence suggests that some form of cross-modal recruitment of the visual cortex could be possible in the normal healthy adults (Amedi et al., 2007; Kim and Zatorre, 2011; Powers et al., 2012; Saito et al., 2006; Zangenehpour and Zatorre, 2010; Merabet et al., 2004; Zangaladze et al., 1999). Nonetheless, the behavioural relevance of these cortical mechanisms remains unclear, especially for complex stimuli. Notably, several experiments failed to find such cross-modal reorganization in sighted subjects, even after extensive training (Kupers et al., 2006; Ptito et al., 2005). One study found cross-modal plastic changes in subjects that were blindfolded for several days (Merabet et al., 2008), but these plastic changes quickly vanished once the subjects removed their blindfolds.

Here, for the first time, we show that large-scale, cross-modal cortical reorganization is a viable, adaptive mechanism in the sighted, adult brain. In our experiment, sighted adults followed a 9-month Braille reading course. The resulting cortical changes were tracked using task-based and resting-state functional Magnetic Resonance Imaging (fMRI) and manipulated with Transcranial Magnetic Stimulation (TMS).

Twenty-nine sighted adults, Braille teachers and professionals, students specializing in the education of the blind, and family members of blind people, took part in the study. Some subjects were familiar with Braille signs visually (some teachers actually knew how to read visual Braille upside-down, as upside-down was the usual orientation at which they viewed their students’ work laid out on school benches). All of them were naive in tactile Braille reading (Appendix 1.1). All the participants completed an intensive, tailor-made, 9-month-long tactile Braille reading course (Materials and methods). The majority progressed significantly in tactile reading, reaching an average performance of 6.20 words per minute read aloud (WPM) (SD=3.94, range = 0–17, Appendix 1.1) at the end of the course. Because the course curriculum included learning to recognize Braille letters by sight, the subjects also improved in reading Braille characters visually (Appendix 1.2).

Before and after the tactile Braille reading course, the subjects took part in an fMRI experiment (Figure 1A–C; 'Materials and methods'), in which they viewed regular visual words, Braille words displayed visually on a screen (visual Braille words) and touched tactile Braille words. Additional control conditions included visual strings of hash symbols (control for visual words), visual strings of pseudo-Braille characters (control for visual Braille), and tactile strings of pseudo-Braille characters (control for tactile Braille) (Figure 1B and 'Materials and methods'; a pseudo-Braille character contains six dots and has no meaning). The subjects could not see any of the tactile stimuli. Subjects also performed a control mental imagery fMRI experiment ('Materials and methods', Figure 1—figure supplements 1 and 2, Appendix 1.5).

Figure 1 with 3 supplements see all

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Representation similarity analysis

Visual words, visual Braille and tactile Braille all elicited activity in the VWFA. How similar are the neural representations of these three scripts? The similarity of neural representations can be studied with multivariate pattern analysis-representational similarity analysis (MVPA-RSA). This method is based on the premise that stimuli that share similar neural representations will generate similar voxel activation patterns (Kriegeskorte et al., 2008; Rothlein and Rapp, 2014). Using MVPA-RSA ('Materials and methods'), we found that the two Braille conditions (visual and tactile) had the most similar activation patterns in the VWFA (Figure 2A,r=0.48), despite very large differences in the magnitude of the two activations (see Figure 2B). The correlations of the two Braille conditions with visual words were much weaker (Figure 2A, 'Materials and methods' and Appendix 1.6). Despite a difference in modality (visual vs. tactile), the neural representations of the two versions of Braille script were partially similar and distinct from the well-established representation for visual words.

Figure 2

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Effects on resting-state fMRI

Learning can impact the resting-state activity of the brain (e.g. Lewis et al., 2009). Following the course, we observed an increase in resting-state functional connectivity between the VWFA seed and the left primary somatosensory cortex (Figure 3A, red; p<0.001, corrected for multiple comparisons; Z=4.57; MNI: -57 -24 45; 'Materials and methods'). This increase was the only statistically significant positive effect found. The same comparison showed a decrease in the VWFA’s functional connectivity with other visual areas, bilaterally. Furthermore, after the course, the VWFA-S1 functional connectivity level was correlated with the subjects’ progress in tactile Braille reading speed (in the month preceding the after-course scan, Figure 3; r(27)=0.49, p=0.007). The VWFA thus increased its coupling with the somatosensory cortex while decreasing its coupling with other visual areas. This VWFA-S1 functional connectivity was behaviorally relevant for tactile reading and was likely to be dynamically modulated in a relatively short learning period (similar to: Lewis et al., 2009) (see also Appendix 1.7).

Figure 3

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Transcranial magnetic stimulation

Finally, to test the role of the VWFA in Braille reading, we performed a repetitive Transcranial Magnetic Stimulation (rTMS) experiment in which nine subjects were tested after the course in tactile Braille reading (reading speeds: 3–17 WPM). rTMS was applied to the VWFA and to two control sites – the lateral occipital area and the vertex. Both the VWFA and the lateral occipital area were localized using the individual subjects’ fMRI results ('Materials and methods'). Similar to a previous visual reading study (Duncan et al., 2010), we chose the lateral occipital area as an additional, negative control site, because TMS to this region evokes muscle contractions indistinguishable from VWFA stimulation. rTMS was applied while subjects performed a lexical decision task on words and pseudowords written in tactile Braille (see Figure 4A; 'Materials and methods'). Based on a previous visual reading study (Duncan et al., 2010), we expected that stimulation to the VWFA during the performance of the task would decrease accuracy for lexical decisions on Braille words. As predicted, TMS to the VWFA decreased the accuracy of reading Braille words (t(8)=3.02, p=0.016, Figure 4B). This TMS result shows that the VWFA is necessary for reading tactile Braille words.

Figure 4

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We also tested for effects of TMS on control stimuli (Braille pseudowords) and control sites (lateral occipital area, vertex) (Figure 4B) and none of these tests resulted in significant effects (VWFA, Braille pseudowords: t(8)=0.03, p=0.977; lateral occipital area, Braille words: t(8)=0.18, p=0.859; lateral occipital area, Braille pseudowords: t(8)=0.03, p=0.979; vertex, Braille words: t(8)=1.26, p=0.243; vertex, Braille pseudowords: t(8)=0.02, p=0.986). However, given the small number of subjects in this part of our study, our TMS experiment was underpowered to statistically verify the specificity of the TMS effect: ANOVAs testing for specificity of our effect of interest showed a trend for an interaction between the stimulus type and TMS for the VWFA (F(1,8)=3.59, p=0.095), no interaction between the stimulus type, TMS, and the stimulation site (F(2,16)=0.41, p=0.580), and no interaction between TMS and the stimulation site for Braille words (F(2,16)=1.5, p=0.253).

Several experiments have already indicated that in some contexts, the sighted’s ventral visual cortex can contribute to the perception of tactile (reviewed in: Amedi et al., 2005) or auditory (Amedi et al., 2007) stimuli. It is also known that regions higher up in the sensory processing hierarchy, notably the antero-medial parts of the ventral temporal cortex (MNI y>-40), can host multisensory, abstract object representations (e.g. Fairhall and Caramazza, 2013; Kassuba et al., 2014). The left fusiform gyrus in particular is suggested to process object-specific crossmodal interactions (Kassuba et al., 2011). Our results demonstrate that the occipitotemporal visual cortex (VWFA, MNI y≈-60) can represent stimuli in a modality other than vision. The fact that TMS to the VWFA can disrupt tactile reading demonstrates the importance of this representation for sensory processing.

ROI analysis (Figure 2B) revealed that lateral occipital area (LOA) presented a pattern of activity increase to tactile words due to the course similar to the VWFA. However, TMS applied to LOA did not disturb tactile reading process (Figure 4). While the LOA is activated in various visual word recognition tasks (Duncan et al., 2009; Wright et al., 2008), its lesions seems not to affect reading itself (Cavina-Pratesi et al., 2015; Milner et al., 1991; Philipose et al., 2007). The increase of activity in both LOA and VWFA for tactile reading thus suggest that visual and tactile reading share similar neural correlates along the ventral visual stream. However, the exact function of LOA in reading seems to be more accessory than critical.

The ventral visual cortex was also activated when subjects heard auditory words and then imagined reading them in tactile Braille (Figure 1—figure supplement 2, Table 4). We also observed robust object activations in the object imagery task (ventral visual stream, left: MNI -45 -67 -9, Z=6.68, right: MNI 45 -67 -5, Z=5.94) which confirms that subjects successfully engaged in imagery during the experiment.

There are several reasons to rule out the possibility that the visual activation for tactile reading is a side-effect of mental imagery. First, if the visual activations were only a by-product of mental imagery, TMS to the VWFA would not interfere with Braille reading; yet, it did (Figure 4B). Second, training did not produce any changes in the activations to imagining tactile Braille (Appendix 1.5). Third, activations to imagining Braille in the VWFA did not correlate with tactile Braille reading proficiency (Appendix 1.4). Thus, visual cortex activations for tactile reading cannot be explained as a by-product of visual imagery. Instead, they constitute the signature of a new, tactile script representation emerging in the visual cortex.

Cortical reorganization that crosses the sensory boundaries is prominent in blind and deaf humans (Hirsch et al., 2015; Pavani and Roder, 2012; Sadato et al., 2002) and in congenitally deaf cats (Lomber et al., 2011). In the latter, the deprived auditory areas play a vital role in the deaf cats’ superior visual perception. The above-mentioned studies used the same paradigms in non-deprived humans and cats, but did not find any signs of cross-modal reorganization (e.g. Figure 7 in Sadato et al., 2002). One could have thus expected that learning to read by touch would lead to the emergence of a tactile reading area in the somatosensory cortex. Yet, our study produced a different result. Specific responses to tactile reading emerged not in somatosensory areas, but in visual areas.

This result might seem incompatible with a large body of data showing that tactile training leads to changes in somatosensory activation to tactile stimuli (Guic et al., 2008; Kupers et al., 2006; Pleger et al., 2003; Ptito et al., 2005), or decision-level frontal cortex changes (Sathian et al., 2013), but no visual cortex changes. However, all the above-mentioned experiments used simple stimuli, such as gratings, and short learning periods. Our experiment was longer (9 months) and used complex stimuli - entire Braille words. Experiments that study learning-related plasticity at multiple time points (Lövdén et al., 2013) suggest that at the initial stage of Braille learning, the somatosensory cortex might have increased its response to Braille words. Then, as the effects of early sensory learning consolidated in the somatosensory cortex, the cortical focus of learning shifted elsewhere, in our case the ventral visual stream.

Previous studies (Büchel et al., 1998; Lomber et al., 2011; Merabet and Pascual-Leone, 2010; Sadato et al., 2002, 1996) have suggested that cross-modal plasticity is possible mainly as a result of massive sensory deprivation or injury. Our results demonstrate that given a long training period and a complex task, the normal brain is capable of large-scale plasticity that overcomes the division into separate sensory cortices. The exact mechanisms of this plasticity might of course be different in deprived and non-deprived subjects.

Earlier reports of cross-modal plasticity in the normal brain might have already hinted at the possibility of cross-modal plasticity in the normal brain. Indeed, it was shown that some parts of the visual cortex can be activated during auditory or tactile tasks (Amedi et al., 2007; Kim and Zatorre, 2011; Powers et al., 2012; Saito et al., 2006; Zangenehpour and Zatorre, 2010). Professional pianists, for example, were shown to activate their auditory cortex when viewing mute video recordings of a piano key being pressed (Haslinger et al., 2005). The behavioral relevance of such activations, however, was demonstrated only for simple tactile stimuli: grating orientation (Zangaladze et al., 1999) and distance judgment (Merabet et al., 2004). Our study used a controlled, within-subject design and precise behavioral measures supplemented with a causal method, TMS. Its results suggest that large-scale plasticity is a viable mechanism recruited when learning complex skills. This conclusion is congruent with a recent comparative study showing that the morphology of cerebral cortex is substantially less genetically heritable in humans than in chimpanzees (Gomez-Robles et al., 2015). Such relaxed genetic control might be the reason for homo sapiens’ increased learning abilities and greater behavioral flexibility.

Despite evidence for cross-modal plasticity of the human brain, the dominant view still describes it as necessarily constrained by the sensory boundaries (e.g. Figure 18–2 in: Kandel et al., 2012). Our study provides a clear-cut evidence that learning-related neuroplasticity can overcome the sensory division. This calls for a re-assessment of our view of the functional organization of the brain.

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Author details

1. Katarzyna Siuda-Krzywicka

   1. Department of Psychology, Jagiellonian University, Kraków, Poland
   2. INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France

   Contribution

   KS-K, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Contributed equally with

   Łukasz Bola

   Competing interests

   The authors declare that no competing interests exist.

2. Łukasz Bola

   1. Department of Psychology, Jagiellonian University, Kraków, Poland
   2. Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology, Warsaw, Poland

   Contribution

   ŁB, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Contributed equally with

   Katarzyna Siuda-Krzywicka

   Competing interests

   The authors declare that no competing interests exist.

3. Małgorzata Paplińska

   Academy of Special Education in Warsaw, Warsaw, Poland

   Contribution

   MP, Designed and taught the Braille course

   Competing interests

   The authors declare that no competing interests exist.

4. Ewa Sumera

   Institute for the Blind and Partially Sighted Children in Krakow, Kraków, Poland

   Contribution

   ES, Designed and taught the Braille course

   Competing interests

   The authors declare that no competing interests exist.

5. Katarzyna Jednoróg

   Laboratory of Psychophysiology, Department of Neurophysiology, Nencki Institute of Experimental Biology, Warsaw, Poland

   Contribution

   KJ, Additional contributions to acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

6. Artur Marchewka

   Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology, Warsaw, Poland

   Contribution

   AM, Additional contributions to acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

7. Magdalena W Śliwińska

   Department of Experimental Psychology, University College London, London, United Kingdom

   Contribution

   MWŚ, Additional contributions to acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

8. Amir Amedi

   1. The Cognitive Science Program, The Hebrew University of Jerusalem, Jerusalem, Israel
   2. Department of Medical Neurobiology, The Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
   3. The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
   4. Sorbonne Universite´s, UPMC Univ Paris 06, Institut de la Vision, Paris, France

   Contribution

   AA, Additional contributions to conception and design, data analysis, and revising the article

   Competing interests

   The authors declare that no competing interests exist.

9. Marcin Szwed

   Department of Psychology, Jagiellonian University, Kraków, Poland

   Contribution

   MS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   For correspondence

   mfszwed@gmail.com

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-2153-7793

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