How you read affects what you gain: Individual differences in the functional organization of the reading system predict intervention gains in children with reading disabilities.

There is now considerable evidence regarding the types of interventions that are effective at remediating reading disabilities on average. It is generally unclear, however, what predicts the magnitude of individual-level change following a given intervention. We examine new predictors of intervention gains that are theoretically grounded in computational models of reading and focus on individual differences in the functional organization of the reading system. Specifically, we estimate the extent to which children with reading disabilities (n=118 3rd-4th graders) rely on two sources of information during an oral word reading task - print-speech correspondences and semantic imageability - before and after a phonologically-weighted intervention. We show that children who relied more on print-speech regularities and less on imageability pre-intervention had better intervention gains. In parallel, children who over the course of the intervention exhibited greater increases in their reliance on print-speech correspondences and greater decreases in their reliance on imageability had better intervention outcomes. Importantly, these two factors were differentially related to specific reading task outcomes, with greater reliance on print-speech correspondences associated with pseudoword naming, while (lesser) reliance on imageability related to word reading and comprehension. We discuss the implications of these findings for theoretical models of reading acquisition and educational practice.

Universal brain signature of proficient reading: Evidence from four contrasting languages.

We propose and test a theoretical perspective in which a universal hallmark of successful literacy acquisition is the convergence of the speech and orthographic processing systems onto a common network of neural structures, regardless of how spoken words are represented orthographically in a writing system. During functional MRI, skilled adult readers of four distinct and highly contrasting languages, Spanish, English, Hebrew, and Chinese, performed an identical semantic categorization task to spoken and written words. Results from three complementary analytic approaches demonstrate limited language variation, with speech-print convergence emerging as a common brain signature of reading proficiency across the wide spectrum of selected languages, whether their writing system is alphabetic or logographic, whether it is opaque or transparent, and regardless of the phonological and morphological structure it represents.

Decoding the neural representation of story meanings across languages.

Drawing from a common lexicon of semantic units, humans fashion narratives whose meaning transcends that of their individual utterances. However, while brain regions that represent lower-level semantic units, such as words and sentences, have been identified, questions remain about the neural representation of narrative comprehension, which involves inferring cumulative meaning. To address these questions, we exposed English, Mandarin, and Farsi native speakers to native language translations of the same stories during fMRI scanning. Using a new technique in natural language processing, we calculated the distributed representations of these stories (capturing the meaning of the stories in high-dimensional semantic space), and demonstrate that using these representations we can identify the specific story a participant was reading from the neural data. Notably, this was possible even when the distributed representations were calculated using stories in a different language than the participant was reading. Our results reveal that identification relied on a collection of brain regions most prominently located in the default mode network. These results demonstrate that neuro-semantic encoding of narratives happens at levels higher than individual semantic units and that this encoding is systematic across both individuals and languages. Hum Brain Mapp 38:6096-6106, 2017. © 2017 Wiley Periodicals, Inc.

Introduction to the Special Issue: Advancing the State-of-the-Science in Reading Research through Modeling.

Reading research is increasingly a multi-disciplinary endeavor involving more complex, team-based science approaches. These approaches offer the potential of capturing the complexity of reading development, the emergence of individual differences in reading performance over time, how these differences relate to the development of reading difficulties and disability, and more fully understanding the nature of skilled reading in adults. This special issue focuses on the potential opportunities and insights that early and richly integrated advanced statistical and computational modeling approaches can provide to our foundational (and translational) understanding of reading. The issue explores how computational and statistical modeling, using both observed and simulated data, can serve as a contact point among research domains and topics, complement other data sources and critically provide analytic advantages over current approaches.

On the same wavelength: predictable language enhances speaker-listener brain-to-brain synchrony in posterior superior temporal gyrus.

Recent research has shown that the degree to which speakers and listeners exhibit similar brain activity patterns during human linguistic interaction is correlated with communicative success. Here, we used an intersubject correlation approach in fMRI to test the hypothesis that a listener's ability to predict a speaker's utterance increases such neural coupling between speakers and listeners. Nine subjects listened to recordings of a speaker describing visual scenes that varied in the degree to which they permitted specific linguistic predictions. In line with our hypothesis, the temporal profile of listeners' brain activity was significantly more synchronous with the speaker's brain activity for highly predictive contexts in left posterior superior temporal gyrus (pSTG), an area previously associated with predictive auditory language processing. In this region, predictability differentially affected the temporal profiles of brain responses in the speaker and listeners respectively, in turn affecting correlated activity between the two: whereas pSTG activation increased with predictability in the speaker, listeners' pSTG activity instead decreased for more predictable sentences. Listeners additionally showed stronger BOLD responses for predictive images before sentence onset, suggesting that highly predictable contexts lead comprehenders to preactivate predicted words.

Selective attention to phonology dynamically modulates initial encoding of auditory words within the left hemisphere.

Selective attention to phonology, i.e., the ability to attend to sub-syllabic units within spoken words, is a critical precursor to literacy acquisition. Recent functional magnetic resonance imaging evidence has demonstrated that a left-lateralized network of frontal, temporal, and posterior language regions, including the visual word form area, supports this skill. The current event-related potential (ERP) study investigated the temporal dynamics of selective attention to phonology during spoken word perception. We tested the hypothesis that selective attention to phonology dynamically modulates stimulus encoding by recruiting left-lateralized processes specifically while the information critical for performance is unfolding. Selective attention to phonology was captured by manipulating listening goals: skilled adult readers attended to either rhyme or melody within auditory stimulus pairs. Each pair superimposed rhyming and melodic information ensuring identical sensory stimulation. Selective attention to phonology produced distinct early and late topographic ERP effects during stimulus encoding. Data-driven source localization analyses revealed that selective attention to phonology led to significantly greater recruitment of left-lateralized posterior and extensive temporal regions, which was notably concurrent with the rhyme-relevant information within the word. Furthermore, selective attention effects were specific to auditory stimulus encoding and not observed in response to cues, arguing against the notion that they reflect sustained task setting. Collectively, these results demonstrate that selective attention to phonology dynamically engages a left-lateralized network during the critical time-period of perception for achieving phonological analysis goals. These findings suggest a key role for selective attention in on-line phonological computations. Furthermore, these findings motivate future research on the role that neural mechanisms of attention may play in phonological awareness impairments thought to underlie developmental reading disabilities.

Statistical learning of syllable sequences as trajectories through a perceptual similarity space.

Learning from sequential statistics is a general capacity common across many cognitive domains and species. One form of statistical learning (SL) - learning to segment "words" from continuous streams of speech syllables in which the only segmentation cue is ostensibly the transitional (or conditional) probability from one syllable to the next - has been studied in great detail. Typically, this phenomenon is modeled as the calculation of probabilities over discrete, featureless units. Here we present an alternative model, in which sequences are learned as trajectories through a similarity space. A simple recurrent network coding syllables with representations that capture the similarity relations among them correctly simulated the result of a classic SL study, as did a similar model that encoded syllables as three dimensional points in a continuous similarity space. We then used the simulations to identify a sequence of "words" that produces the reverse of the typical SL effect, i.e., part-words are predicted to be more familiar than Words. Results from two experiments with human participants are consistent with simulation results. Additional analyses identified features that drive differences in what is learned from a set of artificial languages that have the same transitional probabilities among syllables.

Task by stimulus interactions in brain responses during Chinese character processing.

In the visual word recognition literature, it is well understood that various stimulus effects interact with behavioral task. For example, effects of word frequency are exaggerated and effects of spelling-to-sound regularity are reduced in the lexical decision task, relative to reading aloud. Neuroimaging studies of reading often examine effects of task and stimulus properties on brain activity independently, but potential interactions between task demands and stimulus effects have not been extensively explored. To address this issue, we conducted lexical decision and symbol detection tasks using stimuli that varied parametrically in their word-likeness, and tested for task by stimulus class interactions. Interactions were found throughout the reading system, such that stimulus selectivity was observed during the lexical decision task, but not during the symbol detection task. Further, the pattern of stimulus selectivity was directly related to task difficulty, so that the strongest brain activity was observed to the most word-like stimuli that required "no" responses, whereas brain activity to words, which elicit rapid and accurate "yes" responses were relatively weak. This is in line with models that argue for task-dependent specialization of brain regions, and contrasts with the notion of task-independent stimulus selectivity in the reading system.

A sensitive period for shibboleths: the long tail and changing goals of speech perception over the course of development.

It is clear that the ability to learn new speech contrasts changes over development, such that learning to categorize speech sounds as native speakers of a language do is more difficult in adulthood than it is earlier in development. There is also a wealth of data concerning changes in the perception of speech sounds during infancy, such that infants quite rapidly progress from language-general to more language-specific perceptual biases. It is often suggested that the perceptual narrowing observed during infancy plays a causal role in the loss of plasticity observed in adulthood, but the relationship between these two phenomena is complicated. Here I consider the relationship between changes in sensitivity to speech sound categorization over the first 2 years of life, when they appear to reorganize quite rapidly, to the "long tail" of development throughout childhood, in the context of understanding the sensitive period for speech perception.

Sensitive periods for language and recovery from stroke: conceptual and practical parallels.

In this review, we consider the literature on sensitive periods for language acquisition from the perspective of the stroke recovery literature treated in this Special Issue. Conceptually, the two areas of study are linked in a number of ways. For example, the fact that learning itself can set the stage for future failures to learn (in second language learning) or to remediate (as described in constraint therapy) is an important insight in both areas, as is the increasing awareness that limits on learning can be overcome by creating the appropriate environmental context. Similar practical issues, such as distinguishing native-like language acquisition or recovery of function from compensatory mechanisms, arise in both areas as well.

Domain general change detection accounts for "dishabituation" effects in temporal-parietal regions in functional magnetic resonance imaging studies of speech perception.

Functional magnetic resonance imaging (fMRI) studies of speech sound categorization often compare conditions in which a stimulus is presented repeatedly to conditions in which multiple stimuli are presented. This approach has established that a set of superior temporal and inferior parietal regions respond more strongly to conditions containing stimulus change. Here, we examine whether this contrast is driven by habituation to a repeating condition or by selective responding to change. Experiment 1 directly tests this by comparing the observed response to long trains of stimuli against a constructed hemodynamic response modeling the hypothesis that no habituation occurs. The results are consistent with the view that enhanced response to conditions involving phonemic variability reflect change detection. In a second experiment, the specificity of these responses to linguistically relevant stimulus variability was studied by including a condition in which the talker, rather than phonemic category, was variable from stimulus to stimulus. In this context, strong change detection responses were observed to changes in talker, but not to changes in phoneme category. The results prompt a reconsideration of two assumptions common to fMRI studies of speech sound categorization: they suggest that temporoparietal responses in passive paradigms such as those used here are better characterized as reflecting change detection than habituation, and that their apparent selectivity to speech sound categories may reflect a more general preference for variability in highly salient or behaviorally relevant stimulus dimensions.

Left fusiform BOLD responses are inversely related to word-likeness in a one-back task.

Although its precise functional contribution to reading remains unclear, there is broad consensus that an activity in the left mid-fusiform gyrus is highly sensitive to written words and word-like stimuli. In the current study, we take advantage of a particularity of the Chinese writing system in order to manipulate word-likeness parametrically, from real characters, to pseudo-characters that vary in whether they contain phonological and semantic cues, to artificial stimuli with varying surface similarity to real characters. In a one-back task, BOLD activity in the left mid-fusiform was inversely related to word-likeness, such that the least activity was observed in response to real characters, and the greatest to artificial stimuli that violate the orthotactic constraints of the writing system. One possible explanation for this surprising result is that the short-term memory demands of the one-back task put more pressure on the visual system when other sources of information cannot be used to aid in detecting repeated stimuli. For real characters and, to a lesser extent for pseudo-characters, information about meaning and pronunciation can contribute to performance, whereas artificial stimuli are entirely dependent on visual information. Consistent with this view, functional connectivity analyses revealed a strong positive relationship between left mid-fusiform and other visual areas, whereas areas typically involved in phonological and semantic processing for text were negatively correlated with this region.

Auditory selective attention to speech modulates activity in the visual word form area.

Selective attention to speech versus nonspeech signals in complex auditory input could produce top-down modulation of cortical regions previously linked to perception of spoken, and even visual, words. To isolate such top-down attentional effects, we contrasted 2 equally challenging active listening tasks, performed on the same complex auditory stimuli (words overlaid with a series of 3 tones). Instructions required selectively attending to either the speech signals (in service of rhyme judgment) or the melodic signals (tone-triplet matching). Selective attention to speech, relative to attention to melody, was associated with blood oxygenation level-dependent (BOLD) increases during functional magnetic resonance imaging (fMRI) in left inferior frontal gyrus, temporal regions, and the visual word form area (VWFA). Further investigation of the activity in visual regions revealed overall deactivation relative to baseline rest for both attention conditions. Topographic analysis demonstrated that while attending to melody drove deactivation equivalently across all fusiform regions of interest examined, attending to speech produced a regionally specific modulation: deactivation of all fusiform regions, except the VWFA. Results indicate that selective attention to speech can topographically tune extrastriate cortex, leading to increased activity in VWFA relative to surrounding regions, in line with the well-established connectivity between areas related to spoken and visual word perception in skilled readers.

Top-down grouping affects adjacent dependency learning.

A large body of research has demonstrated that humans attend to adjacent co-occurrence statistics when processing sequential information, and bottom-up prosodic information can influence learning. In this study, we investigated how top-down grouping cues can influence statistical learning. Specifically, we presented English sentences that were structurally equivalent to each other, which induced top-down expectations of grouping in the artificial language sequences that immediately followed. We show that adjacent dependencies in the artificial language are learnable when these entrained boundaries bracket the adjacent dependencies into the same sub-sequence, but are not learnable when the elements cross an induced boundary, even though that boundary is not present in the bottom-up sensory input. We argue that when there is top-down bracketing information in the learning sequence, statistical learning takes place for elements bracketed within sub-sequences rather than all the elements in the continuous sequence. This limits the amount of linguistic computations that need to be performed, providing a domain over which statistical learning can operate.

Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills.

Statistical views of literacy development maintain that proficient reading requires the assimilation of myriad statistical regularities present in the writing system. Indeed, previous studies have tied statistical learning (SL) abilities to reading skills, establishing the existence of a link between the two. However, some issues are currently left unanswered, including questions regarding the underlying bases for these associations as well as the types of statistical regularities actually assimilated by developing readers. Here we present an alternative approach to study the role of SL in literacy development, focusing on individual differences among beginning readers. Instead of using an artificial task to estimate SL abilities, our approach identifies individual differences in children's reliance on statistical regularities as reflected by actual reading behavior. We specifically focus on individuals' reliance on regularities in the mapping between print and speech versus associations between print and meaning in a word naming task. We present data from 399 children, showing that those whose oral naming performance is impacted more by print-speech regularities and less by associations between print and meaning have better reading skills. These findings suggest that a key route by which SL mechanisms impact developing reading abilities is via their role in the assimilation of sub-lexical regularities between printed and spoken language -and more generally, in detecting regularities that are more reliable than others. We discuss the implications of our findings to both SL and reading theories.

Statistical Learning of Unfamiliar Sounds as Trajectories Through a Perceptual Similarity Space.

In typical statistical learning studies, researchers define sequences in terms of the probability of the next item in the sequence given the current item (or items), and they show that high probability sequences are treated as more familiar than low probability sequences. Existing accounts of these phenomena all assume that participants represent statistical regularities more or less as they are defined by the experimenters-as sequential probabilities of symbols in a string. Here we offer an alternative, or possibly supplementary, hypothesis. Specifically, rather than identifying or labeling individual stimuli discretely in order to predict the next item in a sequence, we need only assume that the participant is able to represent the stimuli as evincing particular similarity relations to one another, with sequences represented as trajectories through this similarity space. We present experiments in which this hypothesis makes sharply different predictions from hypotheses based on the assumption that sequences are learned over discrete, labeled stimuli. We also present a series of simulation models that encode stimuli as positions in a continuous two-dimensional space, and predict the next location from the current location. Although no model captures all of the data presented here, the results of three critical experiments are more consistent with the view that participants represent trajectories through similarity space rather than sequences of discrete labels under particular conditions.

Top-down structure influences learning of nonadjacent dependencies in an artificial language.

Because of the hierarchical organization of natural languages, words that are syntactically related are not always linearly adjacent. For example, the subject and verb in the child always runs agree in person and number, although they are not adjacent in the sequences of words. Since such dependencies are indicative of abstract linguist structure, it is of significant theoretical interest how these relationships are acquired by language learners. Most experiments that investigate nonadjacent dependency (NAD) learning have used artificial languages in which the to-be-learned dependencies are isolated, by presenting the minimal sequences that contain the dependent elements. However, dependencies in natural language are not typically isolated in this way. We report the first demonstration to our knowledge of successful learning of embedded NADs, in which silences do not mark dependency boundaries. Subjects heard passages of English with a predictable structure, interspersed with passages of the artificial language. The English sentences were designed to induce boundaries in the artificial languages. In Experiment 1 & 3 the artificial NADs were contained within the induced boundaries and subjects learned them, whereas in Experiment 2 & 4, the NADs crossed the induced boundaries and subjects did not learn them. We take this as evidence that sentential structure was "carried over" from the English sentences and used to organize the artificial language. This approach provides several new insights into the basic mechanisms of NAD learning in particular and statistical learning in general. (PsycINFO Database Record

Functional MR imaging at 3.0 T versus 1.5 T: a practical review.

This article reviews and discusses recent findings in functional MRI at 1.5 and 3.0 T magnetic field strengths, in research and clinical applications. Particular attention is paid to comparative studies and to an explanation of the physical and biological dependencies leading to potential gains and tradeoffs of functional scanning at magnets with a high field strength.

The Neural Correlates of the Interaction between Semantic and Phonological Processing for Chinese Character Reading.

Visual word recognition involves mappings among orthographic, phonological, and semantic codes. In alphabetic languages, it is hard to disentangle the effects of these codes, because orthographically well-formed words are typically pronounceable, confounding orthographic and phonological processes, and orthographic cues to meaning are rare, and where they occur are morphological, confounding orthographic and semantic processes. In Chinese character recognition, it is possible to explore orthography to phonology (O-P) and orthography to semantics (O-S) processes independently by taking advantage of the distinct phonetic and semantic components in Chinese phonograms. We analyzed data from an fMRI experiment using lexical decision for Chinese characters to explore the sensitivity of areas associated with character recognition to orthographic, phonological, and semantic processing. First, a correlation approach was used to identify regions associated with reaction time, frequency, consistency and visual complexity. Then, these ROIs were examined for their responses to stimuli with different types of information available. These results revealed two neural pathways, one for O-S processing relying on left middle temporal gyrus and angular gyrus, and the other for O-P processing relying on inferior frontal gyrus and insula. The two neural routes form a shared neural network both for real and pseudo-characters, and their cooperative division of labor reflects the neural basis for processing different types of characters. Results are broadly consistent with findings from alphabetic languages, as predicted by reading models that assume the same general architecture for logographic and alphabetic scripts.

Limits on reacquisition of song in adult zebra finches exposed to white noise.

Zebra finches (Taeniopygia guttata) learn a specific song pattern during a sensitive period of development, after which song changes little or not at all. However, recent studies have demonstrated substantial behavioral plasticity in song behavior during adulthood under a range of conditions. The current experiment examined song behavior of adult zebra finches temporarily deprived of auditory feedback by chronic exposure to loud white noise (WN). Long-term exposure to continuous WN resulted in disruption of song similar to that observed after deafening. When auditory feedback was restored by discontinuing WN, birds were either tutored using tape-recorded playback or housed with adult conspecific tutors. No evidence of learning new tutor syllables was observed, and recovery of pre-WN song patterns was very limited after restoration of hearing. However, many birds did reacquire some aspects of their pretreatment song, suggesting an adult form of learning that may retain some of the initial aspects of sensorimotor acquisition of song in which vocalizations are shaped to match a stored template representation. The failure to learn novel song elements and the modest degree of recovery observed overall suggest a limit on plasticity in adult birds that have acquired species-typical song patterns and may reflect an important species difference between zebra finches and Bengalese finches.