Inter-subject variability in the use of two different neuronal networks for reading aloud familiar words

Constraining current neuroanatomical models of reading: the view from Arabic

There is a growing interest in imaging understudied orthographies to unravel their neuronal correlates and their implications for existing computational and neuroanatomical models. Here, we review current brain mapping literature about Arabic words. We first offer a succinct description of some unique linguistic features of Arabic that challenge current cognitive models of reading. We then appraise the existing functional neuroimaging studies that investigated written Arabic word processing. Our review revealed that (1) Arabic is still understudied, (2) the most investigated features concerned the effects of vowelling and diglossia in Arabic reading, (3) findings were not always discussed in the light of existing reading models such as the dual route cascaded, the triangle, and the connectionist dual process models, and (4) current evidence is unreliable when it comes to the exact neuronal pathways that sustain Arabic word processing. Overall, despite the fact that Arabic has some unique linguistic features that challenge and ultimately enrich current reading models, the existing functional neuroimaging literature falls short of offering a reliable evidence about brain networks of Arabic reading. We conclude by highlighting the need for more systematic studies of the linguistic features of Arabic to build theoretical and neuroanatomical models that are concurrently specific and general.

Individual differences in the neural architecture in semantic processing

Neural mechanisms underlying semantic processing have been extensively studied by using functional magnetic resonance imaging, nevertheless, the individual differences of it are yet to be unveiled. To further our understanding of functional and anatomical brain organization underlying semantic processing to the level of individual humans, we used out-of-scanner language behavioral data, T1, resting-state, and story comprehension task-evoked functional image data in the Human Connectome Project, to investigate individual variability in the task-evoked semantic processing network, and attempted to predict individuals' language skills based on task and intrinsic functional connectivity of highly variable regions, by employing a machine-learning framework. Our findings first confirmed that individual variability in both functional and anatomical markers were heterogeneously distributed throughout the semantic processing network, and that the variability increased towards higher levels in the processing hierarchy. Furthermore, intrinsic functional connectivities among these highly variable regions were found to contribute to predict individual reading decoding abilities. The contributing nodes in the overall network were distributed in the left superior, inferior frontal, and temporo-parietal cortices. Our results suggested that the individual differences of neurobiological markers were heterogeneously distributed in the semantic processing network, and that neurobiological markers of highly variable areas are not only linked to individual variability in language skills, but can predict language skills at the individual level.

Quantifying the contribution of subject and group factors in brain activation

Research in neuroscience often assumes universal neural mechanisms, but increasing evidence points toward sizeable individual differences in brain activations. What remains unclear is the extent of the idiosyncrasy and whether different types of analyses are associated with different levels of idiosyncrasy. Here we develop a new method for addressing these questions. The method consists of computing the within-subject reliability and subject-to-group similarity of brain activations and submitting these values to a computational model that quantifies the relative strength of group- and subject-level factors. We apply this method to a perceptual decision-making task (n = 50) and find that activations related to task, reaction time, and confidence are influenced equally strongly by group- and subject-level factors. Both group- and subject-level factors are dwarfed by a noise factor, though higher levels of smoothing increases their contributions relative to noise. Overall, our method allows for the quantification of group- and subject-level factors of brain activations and thus provides a more detailed understanding of the idiosyncrasy levels in brain activations.

Neural pathways of phonological and semantic processing and its relations to children's reading skills

Behavioral research shows that children's phonological ability is strongly associated with better word reading skills, whereas semantic knowledge is strongly related to better reading comprehension. However, most neuroscience research has investigated how brain activation during phonological and semantic processing is related to word reading skill. This study examines if connectivity during phonological processing in the dorsal inferior frontal gyrus (dIFG) to posterior superior temporal gyrus (pSTG) pathway is related to word reading skill, whereas connectivity during semantic processing in the ventral inferior frontal gyrus (vIFG) to posterior middle temporal gyrus (pMTG) pathway is related to reading comprehension skill. We used behavioral and functional magnetic resonance imaging (fMRI) data from a publicly accessible dataset on OpenNeuro.org. The research hypotheses and analytical plan were pre-registered on the Open Science Framework. Forty-six children ages 8-15 years old were included in the final analyses. Participants completed an in-scanner reading task tapping into phonology (i.e., word rhyming) and semantics (i.e., word meaning) as well as standardized measures of word reading and reading comprehension skill. In a series of registered and exploratory analyses, we correlated connectivity coefficients from generalized psychophysiological interactions (gPPI) with behavioral measures and used z-scores to test the equality of two correlation coefficients. Results from the preregistered and exploratory analyses indicated weak evidence that functional connectivity of dIFG to pSTG during phonological processing is positively correlated with better word reading skill, but no evidence that connectivity in the vIFG-pMTG pathway during semantic processing is related to better reading comprehension skill. Moreover, there was no evidence to support the differentiation between the dorsal pathway's relation to word reading and the ventral pathway's relation to reading comprehension skills. Our finding suggesting the importance of phonological processing to word reading is in line with prior behavioral and neurodevelopmental models.

Inter-individual variability in dorsal stream dynamics during word production

The current standard model of language production involves a sensorimotor dorsal stream connecting areas in the temporo-parietal junction with those in the inferior frontal gyrus and lateral premotor cortex. These regions have been linked to various aspects of word production such as phonological processing or articulatory programming, primarily through neuropsychological and functional imaging group studies. Most if not all the theoretical descriptions of this model imply that the same network should be identifiable across individual speakers. We tested this hypothesis by quantifying the variability of activation observed across individuals within each dorsal stream anatomical region. This estimate was based on electrical activity recorded directly from the cerebral cortex with millisecond accuracy in awake epileptic patients clinically implanted with intracerebral depth electrodes for pre-surgical diagnosis. Each region's activity was quantified using two different metrics-intra-cerebral evoked related potentials and high gamma activity-at the level of the group, the individual and the recording contact. The two metrics show simultaneous activation of parietal and frontal regions during a picture naming task, in line with models that posit interactive processing during word retrieval. They also reveal different levels of between-patient variability across brain regions, except in core auditory and motor regions. The independence and non-uniformity of cortical activity estimated through the two metrics push the current model towards sub-second and sub-region explorations focused on individualized language speech production. Several hypotheses are considered for this within-region heterogeneity.

An fMRI meta-analysis of the role of the striatum in everyday-life vs laboratory-developed habits

The dorsolateral striatum plays a critical role in the acquisition and expression of stimulus-response habits that are learned in experimental laboratories. Here, we use meta-analytic procedures to contrast the neural circuits activated by laboratory-acquired habits with those activated by stimulus-response behaviours acquired in everyday-life. We confirmed that newly learned habits rely more on the anterior putamen with activation extending into caudate and nucleus accumbens. Motor and associative components of everyday-life habits were identified. We found that motor-dominant stimulus-response associations developed outside the laboratory primarily engaged posterior dorsal putamen, supplementary motor area (SMA) and cerebellum. Importantly, associative components were also represented in the posterior putamen. Thus, common neural representations for both naturalistic and laboratory-based habits were found in the left posterior and right anterior putamen. These findings suggest a partial common striatal substrate for habitual actions that are performed predominantly by stimulus-response associations represented in the posterior striatum. The overlapping neural substrates for laboratory and everyday-life habits supports the use of both methods for the analysis of habitual behaviour.

Unsupervised classification reveals consistency and degeneracy in neural network patterns of emotion

In the present study, we used an unsupervised classification algorithm to reveal both consistency and degeneracy in neural network connectivity during anger and anxiety. Degeneracy refers to the ability of different biological pathways to produce the same outcomes. Previous research is suggestive of degeneracy in emotion, but little research has explicitly examined whether degenerate functional connectivity patterns exist for emotion categories such as anger and anxiety. Twenty-four subjects underwent functional magnetic resonance imaging (fMRI) while listening to unpleasant music and self-generating experiences of anger and anxiety. A data-driven model building algorithm with unsupervised classification (subgrouping Group Iterative Multiple Model Estimation) identified patterns of connectivity among 11 intrinsic networks that were associated with anger vs anxiety. As predicted, degenerate functional connectivity patterns existed within these overarching consistent patterns. Degenerate patterns were not attributable to differences in emotional experience or other individual-level factors. These findings are consistent with the constructionist account that emotions emerge from flexible functional neuronal assemblies and that emotion categories such as anger and anxiety each describe populations of highly variable instances.

Neural processing of vision and language in kindergarten is associated with prereading skills and predicts future literacy

The main objective of this longitudinal study was to investigate the neural predictors of reading acquisition. For this purpose, we followed a sample of 54 children from the end of kindergarten to the end of second grade. Preliterate children were tested for visual symbol (checkerboards, houses, faces, written words) and auditory language processing (spoken words) using a passive functional magnetic resonance imaging paradigm. To examine brain-behavior relationships, we also tested cognitive-linguistic prereading skills at kindergarten age and reading performance of 48 of the same children 2 years later. Face-selective response in the bilateral fusiform gyrus was positively associated with rapid automatized naming (RAN). Response to both spoken and written words at preliterate age was negatively associated with RAN in the dorsal temporo-parietal language system. Longitudinally, neural response to faces in the ventral stream predicted future reading fluency. Here, stronger neural activity in inferior and middle temporal gyri at kindergarten age was associated with higher reading performance. Our results suggest that interindividual differences in the neural system of language and reading affect literacy acquisition and thus might serve as a marker for successful reading acquisition in preliterate children.

Aberrant Cerebellar Resting-State Functional Connectivity Related to Reading Performance in Struggling Readers

Reading is a critical neurodevelopmental skill for school-aged children, which requires a distributed network of brain regions including the cerebellum. However, we do not know how functional connectivity between the cerebellum and other brain regions contributes to reading. Here we used resting-state functional connectivity to understand the cerebellum's role in decoding, reading speed, and comprehension in a group of struggling readers (RD) and a group of adolescents and children with typical reading abilities (TD). We observed an increase in functional connectivity between the sensorimotor network and the left angular gyrus, left lateral occipital cortex, and right inferior frontal gyrus in the RD group relative to the TD group. Additionally, functional connectivity between the cerebellum network and the precentral gyrus was decreased and was related to reading fluency in the RD group. Seed-based analysis revealed increased functional connectivity between crus 1, lobule 6, and lobule 8 of the cerebellum and brain regions related to the default mode network and the motor system for the RD group. We also found associations between reading performance and the functional connectivity between lobule 8 of the cerebellum and the left angular gyrus for both groups, with stronger relationships in the TD group. Specifically, the RD group displayed a positive relationship between functional connectivity, whereas the TD group displayed the opposite relationship. These results suggest that the cerebellum is involved in multiple components of reading performance and that functional connectivity differences observed in the RD group may contribute to poor reading performance.

Differential associations of neurobehavioral traits and cognitive ability to academic achievement in higher education

BACKGROUND

People vary between each other on several neurobehavioral traits, which may have implications for understanding academic achievement.

METHODS

University-level Psychology or Engineering students were assessed for neurobehavioral traits, intelligence, and current psychological distress. Scores were compared with their grade point average (GPA) data.

RESULTS

Factors associated with higher GPA differed markedly between groups. For Engineers, intelligence, but not neurobehavioral traits or psychological distress, was a strong correlate of grades. For Psychologists, grades were not correlated with intelligence but they were with the neurobehavioral traits of executive dysfunction, disinhibition, apathy, and positive schizotypy. However, only the latter two were associated independently of psychological distress. Additionally, higher mixed-handedness was associated with higher GPA in the combined sample.

CONCLUSIONS

Neurological factors (i.e., neurobehavioral traits and intelligence), are differentially associated with university-level grades, depending on the major studied. However, mixed-handedness may prove to be a better general predictor of academic performance across disciplines.

Educational fMRI: From the Lab to the Classroom

Functional MRI (fMRI) findings hold many potential applications for education, and yet, the translation of fMRI findings to education has not flowed. Here, we address the types of fMRI that could better support applications of neuroscience to the classroom. This 'educational fMRI' comprises eight main challenges: (1) collecting artifact-free fMRI data in school-aged participants and in vulnerable young populations, (2) investigating heterogenous cohorts with wide variability in learning abilities and disabilities, (3) studying the brain under natural and ecological conditions, given that many practical topics of interest for education can be addressed only in ecological contexts, (4) depicting complex age-dependent associations of brain and behaviour with multi-modal imaging, (5) assessing changes in brain function related to developmental trajectories and instructional intervention with longitudinal designs, (6) providing system-level mechanistic explanations of brain function, so that useful individualized predictions about learning can be generated, (7) reporting negative findings, so that resources are not wasted on developing ineffective interventions, and (8) sharing data and creating large-scale longitudinal data repositories to ensure transparency and reproducibility of fMRI findings for education. These issues are of paramount importance to the development of optimal fMRI practices for educational applications.

The Ventral Anterior Temporal Lobe has a Necessary Role in Exception Word Reading

An influential account of reading holds that words with exceptional spelling-to-sound correspondences (e.g., PINT) are read via activation of their lexical-semantic representations, supported by the anterior temporal lobe (ATL). This account has been inconclusive because it is based on neuropsychological evidence, in which lesion-deficit relationships are difficult to localize precisely, and functional neuroimaging data, which is spatially precise but cannot demonstrate whether the ATL activity is necessary for exception word reading. To address these issues, we used a technique with good spatial specificity-repetitive transcranial magnetic stimulation (rTMS)-to demonstrate a necessary role of ATL in exception word reading. Following rTMS to left ventral ATL, healthy Japanese adults made more regularization errors in reading Japanese exception words. We successfully simulated these results in a computational model in which exception word reading was underpinned by semantic activations. The ATL is critically and selectively involved in reading exception words.

Dissociating the functions of superior and inferior parts of the left ventral occipito-temporal cortex during visual word and object processing

During word and object recognition, extensive activation has consistently been observed in the left ventral occipito-temporal cortex (vOT), focused around the occipito-temporal sulcus (OTs). Previous studies have shown that there is a hierarchy of responses from posterior to anterior vOT regions (along the y-axis) that corresponds with increasing levels of recognition - from perceptual to semantic processing, respectively. In contrast, the functional differences between superior and inferior vOT responses (i.e. along the z-axis) have not yet been elucidated. To investigate, we conducted an extensive review of the literature and found that peak activation for reading varies by more than 1 cm in the z-axis. In addition, we investigated functional differences between superior and inferior parts of left vOT by analysing functional MRI data from 58 neurologically normal skilled readers performing 8 different visual processing tasks. We found that group activation in superior vOT was significantly more sensitive than inferior vOT to the type of task, with more superior vOT activation when participants were matching visual stimuli for their semantic or perceptual content than producing speech to the same stimuli. This functional difference along the z-axis was compared to existing boundaries between cytoarchitectonic areas around the OTs. In addition, using dynamic causal modelling, we show that connectivity from superior vOT to anterior vOT increased with semantic content during matching tasks but not during speaking tasks whereas connectivity from inferior vOT to anterior vOT was sensitive to semantic content for matching and speaking tasks. The finding of a functional dissociation between superior and inferior parts of vOT has implications for predicting deficits and response to rehabilitation for patients with partial damage to vOT following stroke or neurosurgery.

Computational modeling of interventions for developmental disorders

We evaluate the potential of connectionist models of developmental disorders to offer insights into the efficacy of interventions. Based on a range of computational simulation results, we assess factors that influence the effectiveness of interventions for reading, language, and other cognitive developmental disorders. The analysis provides a level of mechanistic detail that is generally lacking in behavioral approaches to intervention. We review an extended program of modeling work in four sections. In the first, we consider long-term outcomes and the possibility of compensated outcomes and resolution of early delays. In the second section, we address methods to remediate atypical development in a single network. In the third section, we address interventions to encourage compensation via alternative pathways. In the final section, we consider the key issue of individual differences in response to intervention. Together with advances in understanding the neural basis of developmental disorders and neural responses to training, formal computational approaches can spur theoretical progress to narrow the gap between the theory and practice of intervention.

The evolution of cognitive models: From neuropsychology to neuroimaging and back

This paper provides a historical and future perspective on how neuropsychology and neuroimaging can be used to develop cognitive models of human brain functions. Section 1 focuses on the emergence of cognitive modelling from neuropsychology, why lesion location was considered to be unimportant and the challenges faced when mapping symptoms to impaired cognitive processes. Section 2 describes how established cognitive models based on behavioural data alone cannot explain the complex patterns of distributed brain activity that are observed in functional neuroimaging studies. This has led to proposals for new cognitive processes, new cognitive strategies and new functional ontologies for cognition. Section 3 considers how the integration of data from lesion, behavioural and functional neuroimaging studies of large cohorts of brain damaged patients can be used to determine whether inter-patient variability in behaviour is due to differences in the premorbid function of each brain region, lesion site or cognitive strategy. This combination of neuroimaging and neuropsychology is providing a deeper understanding of how cognitive functions can be lost and re-learnt after brain damage - an understanding that will transform our ability to generate and validate cognitive models that are both physiologically plausible and clinically useful.

Individual Differences in the Neural and Cognitive Mechanisms of Single Word Reading

Written language is a human invention that our brains did not evolve for. Yet, most research has focused on finding a single theory of reading, identifying the common set of cognitive and neural processes shared across individuals, neglecting individual differences. In contrast, we investigated variation in single word reading. Using a novel statistical method for analyzing heterogeneity in multi-subject task-based functional magnetic resonance imaging (fMRI), we clustered readers based on their brain's response to written stimuli. Separate behavioral testing and neuroimaging analysis shows that these clusters differed in the role of the sublexical pathway in processing written language, but not in reading skill. Taken together, these results suggest that individuals vary in the cognitive and neural mechanisms involved in word reading. In general, neurocognitive theories need to account not only for what tends to be true of the population, but also the types of variation that exist, even within a neurotypical population.

Interpreting and Utilising Intersubject Variability in Brain Function

We consider between-subject variance in brain function as data rather than noise. We describe variability as a natural output of a noisy plastic system (the brain) where each subject embodies a particular parameterisation of that system. In this context, variability becomes an opportunity to: (i) better characterise typical versus atypical brain functions; (ii) reveal the different cognitive strategies and processing networks that can sustain similar tasks; and (iii) predict recovery capacity after brain damage by taking into account both damaged and spared processing pathways. This has many ramifications for understanding individual learning preferences and explaining the wide differences in human abilities and disabilities. Understanding variability boosts the translational potential of neuroimaging findings, in particular in clinical and educational neuroscience.

Three Research Strategies of Neuroscience and the Future of Legal Imaging Evidence

Neuroscientific imaging evidence (NIE) has become an integral part of the criminal justice system in the United States. However, in most legal cases, NIE is submitted and used only to mitigate penalties because the court does not recognize it as substantial evidence, considering its lack of reliability. Nevertheless, we here discuss how neuroscience is expected to improve the use of NIE in the legal system. For this purpose, we classified the efforts of neuroscientists into three research strategies: cognitive subtraction, the data-driven approach, and the brain-manipulation approach. Cognitive subtraction is outdated and problematic; consequently, the court deemed it to be an inadequate approach in terms of legal evidence in 2012. In contrast, the data-driven and brain manipulation approaches, which are state-of-the-art approaches, have overcome the limitations of cognitive subtraction. The data-driven approach brings data science into the field and is benefiting immensely from the development of research platforms that allow automatized collection, analysis, and sharing of data. This broadens the scale of imaging evidence. The brain-manipulation approach uses high-functioning tools that facilitate non-invasive and precise human brain manipulation. These two approaches are expected to have synergistic effects. Neuroscience has strived to improve the evidential reliability of NIE, with considerable success. With the support of cutting-edge technologies, and the progress of these approaches, the evidential status of NIE will be improved and NIE will become an increasingly important part of legal practice.

Predicting the pattern and severity of chronic post-stroke language deficits from functionally-partitioned structural lesions

There is an ever-increasing wealth of knowledge arising from basic cognitive and clinical neuroscience on how speech and language capabilities are organised in the brain. It is, therefore, timely to use this accumulated knowledge and expertise to address critical research challenges, including the ability to predict the pattern and level of language deficits found in aphasic patients (a third of all stroke cases). Previous studies have mainly focused on discriminating between broad aphasia dichotomies from purely anatomically-defined lesion information. In the current study, we developed and assessed a novel approach in which core language areas were mapped using principal component analysis in combination with correlational lesion mapping and the resultant ‘functionally-partitioned’ lesion maps were used to predict a battery of 21 individual test scores as well as aphasia subtype for 70 patients with chronic post-stroke aphasia. Specifically, we used lesion information to predict behavioural scores in regression models (cross-validated using 5-folds). The winning model was identified through the adjusted R² (model fit to data) and performance in predicting holdout folds (generalisation to new cases). We also used logistic regression to predict fluent/non-fluent status and aphasia subtype. Functionally-partitioned models generally outperformed other models at predicting individual tests, fluency status and aphasia subtype.

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Predict the pattern and level of language deficits found in chronic aphasic patients

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Use principal component analysis to identify functional lesion maps

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Functionally-partitioned lesion maps used as predictor variables instead of lesion volume

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Functionally-partitioned lesion model plus age produced the best regression model

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Model can successfully predict fluent/non-fluent types and aphasia classification

Neurofunctionally dissecting the reading system in children

The reading system can be broken down into four basic subcomponents in charge of prelexical, orthographic, phonological, and lexico-semantic processes. These processes need to jointly work together to become a fluent and efficient reader. Using functional magnetic resonance imaging (fMRI), we systematically analyzed differences in neural activation patterns of these four basic subcomponents in children (N=41, 9-13 years) using tasks specifically tapping each component (letter identification, orthographic decision, phonological decision, and semantic categorization). Regions of interest (ROI) were selected based on a meta-analysis of child reading and included the left ventral occipito-temporal cortex (vOT), left posterior parietal cortex (PPC), left inferior frontal gyrus (IFG), and bilateral supplementary motor area (SMA). Compared to a visual baseline task, enhanced activation in vOT and IFG was observed for all tasks with very little differences between tasks. Activity in the dorsal PPC system was confined to prelexical and phonological processing. Activity in the SMA was found in orthographic, phonological, and lexico-semantic tasks. Our results are consistent with the idea of an early engagement of the vOT accompanied by executive control functions in the frontal system, including the bilateral SMA.

Clinical Concepts Emerging from fMRI Functional Connectomics

Recent advances in connectomics have led to a synthesis of perspectives regarding the brain's functional organization that reconciles classical concepts of localized specialization with an appreciation for properties that emerge from interactions across distributed functional networks. This provides a more comprehensive framework for understanding neural mechanisms of normal cognition and disease. Although fMRI has not become a routine clinical tool, research has already had important influences on clinical concepts guiding diagnosis and patient management. Here we review illustrative examples. Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease both have had substantial impact on modern concepts of disease evolution and expression. Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes (and thus also ways of extending indications for, or "re-purposing," current treatments). Large datasets from prospective, longitudinal studies promise to enable the discovery and validation of functional connectomic biomarkers with the potential to identify people at high risk of disease before clinical onset, at a time when treatments may be most effective. Studies of pain and consciousness have catalyzed reconsiderations of approaches to clinical management, but also have stimulated debate about the clinical meaningfulness of differences in internal perceptual or cognitive states inferred from functional connectomics or other physiological correlates. By way of a closing summary, we offer a personal view of immediate challenges and potential opportunities for clinically relevant applications of fMRI-based functional connectomics.

Longitudinal changes in reading network connectivity related to skill improvement

Attempts to characterize the neural differences between individuals with and without dyslexia generally point to reduced activation in and connectivity between brain areas in a reading network composed of the inferior frontal gyrus, the ventral occipito-temporal cortex, and the dorsal temporo-parietal circuit. However, developmental work on brain activity during reading has indicated that some brain areas show developmental decreases in activation with age. Thus, reading network connectivity may also show decreases that are positively associated with increases in reading ability. However, the developmental trajectory of reading network connectivity in typically developing readers is not yet well established. In the current study, we use a longitudinal design to determine how connectivity changes over time, and how these changes relate to changes in reading skill. We find that longitudinal increases in reading ability are associated with higher initial connectivity in the dorsal stream between fusiform and inferior parietal cortex, implicated in phonological decoding, followed by decreases in connectivity in this stream over time. We further find that increases in reading ability are supported by maintenance of connectivity in the ventral stream between inferior occipital and fusiform cortex, suggesting a more mature automatic orthographic recognition strategy. Readers who show little reading improvement over time do not attain high levels of connectivity in the dorsal stream at any time point, and their ventral stream connectivity decreases over time. These results together suggest that superior reading ability is initially supported by phonological decoding, with a decreased reliance on this strategy as reading becomes more automated. Our results indicate that development of the dorsal and ventral streams are closely linked, and support the hypothesis that a decrease in the dorsal stream is important for ventral stream development.

Disentangling subgroups of participants recruiting shared as well as different brain regions for the execution of the verb generation task: A data-driven fMRI study

The spatial pattern of task-related brain activity in fMRI studies might be expected to change according to several variables such as handedness and age. However this spatial heterogeneity might also be due to other unmodeled sources of inter-subject variability. Since group-level results reflect patterns of task-evoked brain activity common to most of the subjects in the sample, they could conceal the presence of subgroups recruiting other brain regions beyond the common pattern. To deal with these issues, data-driven methods can be used to detect the presence of sources of inter-subject variability that might be hard to identify and therefore model a priori. Here we assess the potential of Independent Component Analysis (ICA) to detect the presence of unexpected subgroups of participants. To this end, we acquired task-evoked fMRI data on 45 healthy adults using the verb generation (VGEN) task, in which participants are visually presented with the noun of an object of everyday use, and asked to covertly generate a verb describing the corresponding action. As expected, the task elicited activity in a temporo-parieto-frontal network typically found in previous VGEN experiments. We then quantified the contribution of every subject to nine task-related spatio-temporal processes identified by ICA. A cluster analysis of this quantity yielded three subgroups of participants. Differences between the three identified subgroups were distributed in left and right prefrontal, posterior parietal and extrastriate occipital regions. These results could not be explained by differences in sex, age or handedness across the participants. Furthermore, some regions where a significant difference was found between subgroups were not present in the group-level pattern of task-related activity. We discuss the potential application of this approach for characterizing brain activity in different subgroups of patients with neuropsychiatric or neurological conditions.

Learning and retrieving holistic and componential visual-verbal associations in reading and object naming

Understanding the neural processes that underlie learning to read can provide a scientific foundation for literacy education but studying these processes in real-world contexts remains challenging. We present behavioural data from adult participants learning to read artificial words and name artificial objects over two days. Learning profiles and generalisation confirmed that componential learning of visual-verbal associations distinguishes reading from object naming. Functional MRI data collected on the second day allowed us to identify the neural systems that support componential reading as distinct from systems supporting holistic visual-verbal associations in object naming. Results showed increased activation in posterior ventral occipitotemporal (vOT), parietal, and frontal cortices when reading an artificial orthography compared to naming artificial objects, and the reverse profile in anterior vOT regions. However, activation differences between trained and untrained words were absent, suggesting a lack of cortical representations for whole words. Despite this, hippocampal responses provided some evidence for overnight consolidation of both words and objects learned on day 1. The comparison between neural activity for artificial words and objects showed extensive overlap with systems differentially engaged for real object naming and English word/pseudoword reading in the same participants. These findings therefore provide evidence that artificial learning paradigms offer an alternative method for studying the neural systems supporting language and literacy. Implications for literacy acquisition are discussed.

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Generalisation of novel orthography shows componential processing in reading.

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Real and artificial words and objects rely upon the same neural systems.

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Different neural systems support reading novel orthography and naming novel objects.

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No evidence of whole-word cortical representations for artificial written words.

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Reduced hippocampal responses suggest overnight consolidation of artificial items.

Dough, tough, cough, rough: A "fast" fMRI localizer of component processes in reading

In the current study, we present a novel fMRI protocol in which words, pseudowords, and other word-like stimuli are passively presented in a rapid, sequential fashion. In this "fast" localizer paradigm, items are presented in groups of four; within sets, words are related in orthographic, phonological, and/or semantic properties. We tested this protocol with a group of skilled adult readers (N=18). Analyses uncovered key regions of the reading network that were sensitive to different component processes at the group level; namely, left fusiform gyrus as well as the pars opercularis subregion of inferior frontal gyrus were sensitive to lexicality; several regions including left precentral gyrus and left supramarginal gyrus were sensitive to spelling-sound consistency; the pars triangularis subregion of inferior frontal gyrus was sensitive to semantic similarity. Additionally, in a number of key brain regions, activation in response to semantically similar words was related to individual differences in reading comprehension outside the scanner. Importantly, these findings are in line with previous investigations of the reading network, yet data were obtained using much less imaging time than comparable paradigms currently available, especially relative to the number of indices of component processes obtained. This feature, combined with the relatively simple nature of the task, renders it appropriate for groups of subjects with a wide range of reading abilities, including children with impairments.

Ten problems and solutions when predicting individual outcome from lesion site after stroke

In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients.

A brain-region-based meta-analysis method utilizing the Apriori algorithm

Background

Brain network connectivity modeling is a crucial method for studying the brain’s cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity.

Results

In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816–847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price.

Conclusions

The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

Triangulation of the neurocomputational architecture underpinning reading aloud

The goal of cognitive neuroscience is to integrate cognitive models with knowledge about underlying neural machinery. This significant challenge was explored in relation to word reading, where sophisticated computational-cognitive models exist but have made limited contact with neural data. Using distortion-corrected functional MRI and dynamic causal modeling, we investigated the interactions between brain regions dedicated to orthographic, semantic, and phonological processing while participants read words aloud. We found that the lateral anterior temporal lobe exhibited increased activation when participants read words with irregular spellings. This area is implicated in semantic processing but has not previously been considered part of the reading network. We also found meaningful individual differences in the activation of this region: Activity was predicted by an independent measure of the degree to which participants use semantic knowledge to read. These characteristics are predicted by the connectionist Triangle Model of reading and indicate a key role for semantic knowledge in reading aloud. Premotor regions associated with phonological processing displayed the reverse characteristics. Changes in the functional connectivity of the reading network during irregular word reading also were consistent with semantic recruitment. These data support the view that reading aloud is underpinned by the joint operation of two neural pathways. They reveal that (i) the ATL is an important element of the ventral semantic pathway and (ii) the division of labor between the two routes varies according to both the properties of the words being read and individual differences in the degree to which participants rely on each route.

A trade-off between somatosensory and auditory related brain activity during object naming but not reading

The parietal operculum, particularly the cytoarchitectonic area OP1 of the secondary somatosensory area (SII), is involved in somatosensory feedback. Using fMRI with 58 human subjects, we investigated task-dependent differences in SII/OP1 activity during three familiar speech production tasks: object naming, reading and repeatedly saying "1-2-3." Bilateral SII/OP1 was significantly suppressed (relative to rest) during object naming, to a lesser extent when repeatedly saying "1-2-3" and not at all during reading. These results cannot be explained by task difficulty but the contrasting difference between naming and reading illustrates how the demands on somatosensory activity change with task, even when motor output (i.e., production of object names) is matched. To investigate what determined SII/OP1 deactivation during object naming, we searched the whole brain for areas where activity increased as that in SII/OP1 decreased. This across subject covariance analysis revealed a region in the right superior temporal sulcus (STS) that lies within the auditory cortex, and is activated by auditory feedback during speech production. The tradeoff between activity in SII/OP1 and STS was not observed during reading, which showed significantly more activation than naming in both SII/OP1 and STS bilaterally. These findings suggest that, although object naming is more error prone than reading, subjects can afford to rely more or less on somatosensory or auditory feedback during naming. In contrast, fast and efficient error-free reading places more consistent demands on both types of feedback, perhaps because of the potential for increased competition between lexical and sublexical codes at the articulatory level.

The connectomics of brain disorders

Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation. We then show how knowledge of network topology allows us not only to describe pathological processes but also to generate predictive models of the spread and functional consequences of brain disease.

The importance of premotor cortex for supporting speech production after left capsular-putaminal damage

The left putamen is known to be important for speech production, but some patients with left putamen damage can produce speech remarkably well. We investigated the neural mechanisms that support this recovery by using a combination of techniques to identify the neural regions and pathways that compensate for loss of the left putamen during speech production. First, we used fMRI to identify the brain regions that were activated during reading aloud and picture naming in a patient with left putamen damage. This revealed that the patient had abnormally high activity in the left premotor cortex. Second, we used dynamic causal modeling of the patient's fMRI data to understand how this premotor activity influenced other speech production regions and whether the same neural pathway was used by our 24 neurologically normal control subjects. Third, we validated the compensatory relationship between putamen and premotor cortex by showing, in the control subjects, that lower connectivity through the putamen increased connectivity through premotor cortex. Finally, in a lesion-deficit analysis, we demonstrate the explanatory power of our fMRI results in new patients who had damage to the left putamen, left premotor cortex, or both. Those with damage to both had worse reading and naming scores. The results of our four-pronged approach therefore have clinical implications for predicting which patients are more or less likely to recover their speech after left putaminal damage.

Anatomy is strategy: skilled reading differences associated with structural connectivity differences in the reading network

Are there multiple ways to be a skilled reader? To address this longstanding, unresolved question, we hypothesized that individual variability in using semantic information in reading aloud would be associated with neuroanatomical variation in pathways linking semantics and phonology. Left-hemisphere regions of interest for diffusion tensor imaging analysis were defined based on fMRI results, including two regions linked with semantic processing - angular gyrus (AG) and inferior temporal sulcus (ITS) - and two linked with phonological processing - posterior superior temporal gyrus (pSTG) and posterior middle temporal gyrus (pMTG). Effects of imageability (a semantic measure) on response times varied widely among individuals and covaried with the volume of pathways through the ITS and pMTG, and through AG and pSTG, partially overlapping the inferior longitudinal fasciculus and the posterior branch of the arcuate fasciculus. These results suggest strategy differences among skilled readers associated with structural variation in the neural reading network.

Functional neuroanatomy of developmental dyslexia: the role of orthographic depth

Orthographic depth (OD) (i.e., the complexity, consistency, or transparency of grapheme-phoneme correspondences in written alphabetic language) plays an important role in the acquisition of reading skills. Correspondingly, developmental dyslexia is characterized by different behavioral manifestations across languages varying in OD. This review focuses on the question of whether these different behavioral manifestations are associated with different functional neuroanatomical manifestations. It provides a review and critique of cross-linguistic brain imaging studies of developmental dyslexia. In addition, it includes an analysis of state-of-the-art functional neuroanatomical models of developmental dyslexia together with orthography-specific predictions derived from these models. These predictions should be tested in future brain imaging studies of typical and atypical reading in order to refine the current neurobiological understanding of developmental dyslexia, especially with respect to orthography-specific and universal aspects.

Why is it difficult to predict language impairment and outcome in patients with aphasia after stroke?

One of the most devastating consequences of stroke is aphasia. Communication problems after stroke can severely impair the patient's quality of life and make even simple everyday tasks challenging. Despite intense research in the field of aphasiology, the type of language impairment has not yet been localized and correlated with brain damage, making it difficult to predict the language outcome for stroke patients with aphasia. Our primary objective is to present the available evidence that highlights the difficulties of predicting language impairment after stroke. The different levels of complexity involved in predicting the lesion site from language impairment and ultimately predicting the long-term outcome in stroke patients with aphasia were explored. Future directions and potential implications for research and clinical practice are highlighted.

Different neural capacity limitations for articulatory and non-articulatory maintenance of verbal information

Many studies have demonstrated attenuated verbal working memory (WM) under articulatory suppression. However, performance is not completely abolished, suggesting a less efficient, non-articulatory mechanism for the maintenance of verbal information. The neural causes for the reduced efficiency of such a putative complementary maintenance system have not yet been addressed. The present study was conducted to fill this gap. Subjects performed a Sternberg task (a) under articulatory maintenance at low, high, and supracapacity set sizes and (b) under non-articulatory maintenance at low and high set sizes. With functional magnetic resonance imaging, set-size related increases in activity were compared between subvocal articulatory rehearsal and non-articulatory maintenance. First, the results replicate previous findings showing different networks underlying these two maintenance strategies. Second, activation of all key nodes of the articulatory maintenance network increased with the amount of memorized information, showing no plateau at high set sizes. In contrast, for non-articulatory maintenance, there was evidence for a plateau at high set sizes in all relevant areas of the network. Third, for articulatory maintenance, the non-articulatory maintenance network was additionally recruited at supracapacity set sizes, presumably to assist processing in this highly demanding condition. This is the first demonstration of differential neural bottlenecks for articulatory and non-articulatory maintenance. This study adds to our understanding of the performance differences between these two strategies supporting verbal WM.

Hidden word learning capacity through orthography in aphasia

The ability to learn to use new words is thought to depend on the integrity of the left dorsal temporo-frontal speech processing pathway. We tested this assumption in a chronic aphasic individual (AA) with an extensive left temporal lesion using a new-word learning paradigm. She exhibited severe phonological problems and Magnetic Resonance Imaging (MRI) suggested a complete disconnection of this left-sided white-matter pathway comprising the arcuate fasciculus (AF). Diffusion imaging tractography confirmed the disconnection of the direct segment and the posterior indirect segment of her left AF, essential components of the left dorsal speech processing pathway. Despite her left-hemispheric damage and moderate aphasia, AA learned to name and maintain the novel words in her active vocabulary on par with healthy controls up to 6 months after learning. This exceeds previous demonstrations of word learning ability in aphasia. Interestingly, AA's preserved word learning ability was modality-specific as it was observed exclusively for written words. Functional magnetic resonance imaging (fMRI) revealed that in contrast to normals, AA showed a significantly right-lateralized activation pattern in the temporal and parietal regions when engaged in reading. Moreover, learning of visually presented novel word-picture pairs also activated the right temporal lobe in AA. Both AA and the controls showed increased activation during learning of novel versus familiar word-picture pairs in the hippocampus, an area critical for associative learning. AA's structural and functional imaging results suggest that in a literate person, a right-hemispheric network can provide an effective alternative route for learning of novel active vocabulary. Importantly, AA's previously undetected word learning ability translated directly into therapy, as she could use written input also to successfully re-learn and maintain familiar words that she had lost due to her left hemisphere lesion.

Neural networks underlying contributions from semantics in reading aloud

Reading is an essential part of contemporary society, yet much is still unknown about the physiological underpinnings of its information processing components. Two influential cognitive models of reading, the connectionist and dual-route cascaded models, offer very different accounts, yet evidence for one or the other remains equivocal. These models differ in several ways, including the role of semantics (word meaning) in mapping spelling to sound. We used a new effective connectivity algorithm, IMaGES, to provide a network-level perspective on these network-level models. Left hemisphere regions of interest were defined based on main effects in functional magnetic resonance imaging and included two regions linked with semantic processing—angular gyrus (AG) and inferior temporal sulcus (ITS)—and two regions linked with phonological processing—posterior superior temporal gyrus (pSTG) and posterior middle temporal gyrus (pMTG). Participants read aloud words of high or low spelling-sound consistency, word frequency, and imageability. Only the connectionist model predicted increased contributions from semantic areas with those computing phonology for low-consistency words. Effective connectivity analyses revealed that areas supporting semantic processing (e.g., the ITS) interacted with phonological areas (e.g., the pSTG), with the pattern changing as a function of word properties. Connectivity from semantic to phonological areas emerged for high- compared to low-imageability words, and a similar pattern emerged for low-consistency words, though only under certain conditions. Analyses of individual differences also showed that variation in the strength of modulation of ITS by AG was associated with reading aloud performance. Overall, these results suggest that connections with semantic processing areas are not only associated with reading aloud, but that these connections are also associated with optimal reading performance.

Dissociable temporo-parietal memory networks revealed by functional connectivity during episodic retrieval

Episodic memory retrieval most often recruits multiple separate processes that are thought to involve different temporal regions. Previous studies suggest dissociable regions in the left lateral parietal cortex that are associated with the retrieval processes. Moreover, studies using resting-state functional connectivity (RSFC) have provided evidence for the temporo-parietal memory networks that may support the retrieval processes. In this functional MRI study, we tested functional significance of the memory networks by examining functional connectivity of brain activity during episodic retrieval in the temporal and parietal regions of the memory networks. Recency judgments, judgments of the temporal order of past events, can be achieved by at least two retrieval processes, relational and item-based. Neuroimaging results revealed several temporal and parietal activations associated with relational/item-based recency judgments. Significant RSFC was observed between one parahippocampal region and one left lateral parietal region associated with relational recency judgments, and between four lateral temporal regions and another left lateral parietal region associated with item-based recency judgments. Functional connectivity during task was found to be significant between the parahippocampal region and the parietal region in the RSFC network associated with relational recency judgments. However, out of the four tempo-parietal RSFC networks associated with item-based recency judgments, only one of them (between the left posterior lateral temporal region and the left lateral parietal region) showed significant functional connectivity during task. These results highlight the contrasting roles of the parahippocampal and the lateral temporal regions in recency judgments, and suggest that only a part of the tempo-parietal RSFC networks are recruited to support particular retrieval processes.

Dissociating frontal regions that co-lateralize with different ventral occipitotemporal regions during word processing

The ventral occipitotemporal sulcus (vOT) sustains strong interactions with the inferior frontal cortex during word processing. Consequently, activation in both regions co-lateralize towards the same hemisphere in healthy subjects. Because the determinants of lateralisation differ across posterior, middle and anterior vOT subregions, we investigated whether lateralisation in different inferior frontal regions would co-vary with lateralisation in the three different vOT subregions. A whole brain analysis found that, during semantic decisions on written words, laterality covaried in (1) posterior vOT and the precentral gyrus; (2) middle vOT and the pars opercularis, pars triangularis, and supramarginal gyrus; and (3) anterior vOT and the pars orbitalis, middle frontal gyrus and thalamus. These findings increase the spatial resolution of our understanding of how vOT interacts with other brain areas during semantic categorisation on words.

Network discovery with large DCMs

In this work, we address the problem of using dynamic causal modelling (DCM) to estimate the coupling parameters (effective connectivity) of large models with many regions. This is a potentially important problem because meaningful graph theoretic analyses of effective connectivity rest upon the statistics of the connections (edges). This calls for characterisations of networks with an appreciable number of regions (nodes). The problem here is that the number of coupling parameters grows quadratically with the number of nodes-leading to severe conditional dependencies among their estimates and a computational load that quickly becomes unsustainable. Here, we describe a simple solution, in which we use functional connectivity to provide prior constraints that bound the effective number of free parameters. In brief, we assume that priors over connections between individual nodes can be replaced by priors over connections between modes (patterns over nodes). By using a small number of modes, we can reduce the dimensionality of the problem in an informed way. The modes we use are the principal components or eigenvectors of the functional connectivity matrix. However, this approach begs the question of how many modes to use. This question can be addressed using Bayesian model comparison to optimise the number of modes. We imagine that this form of prior - over the extrinsic (endogenous) connections in large DCMs - may be useful for people interested in applying graph theory to distributed networks in the brain or to characterise connectivity beyond the subgraphs normally examined in DCM.

Functional near-infrared spectroscopy for the assessment of overt reading

Functional near-infrared spectroscopy (fNIRS) has become increasingly established as a promising technique for monitoring functional brain activity. To our knowledge, no study has yet used fNIRS to investigate overt reading of irregular words and nonwords with a full coverage of the cerebral regions involved in reading processes. The aim of our study was to design and validate a protocol using fNIRS for the assessment of overt reading. Twelve healthy French-speaking adults underwent one session of fNIRS recording while performing an overt reading of 13 blocks of irregular words and nonwords. Reading blocks were separated by baseline periods during which participants were instructed to fixate a cross. Sources (n = 55) and detectors (n = 16) were placed bilaterally over frontal, temporal, parietal, and occipital regions. Two wavelengths were used: 690 nm, more sensitive to deoxyhemoglobin (HbR) concentration changes, and 830 nm, more sensitive to oxyhemoglobin (HbO) concentration changes. For all participants, total hemoglobin (HbT) concentrations (HbO + HbR) were significantly higher than baseline for both irregular word and nonword reading in the inferior frontal gyri, the middle and superior temporal gyri, and the occipital cortices bilaterally. In the temporal gyri, although the difference was not significant, [HbT] values were higher in the left hemisphere. In the bilateral inferior frontal gyri, higher [HbT] values were found in nonword than in irregular word reading. This activation could be related to the grapheme-to-phoneme conversion characterizing the phonological pathway of reading. Our findings confirm that fNIRS is an appropriate technique to assess the neural correlates of overt reading.

Reading without the left ventral occipito-temporal cortex

The left ventral occipito-temporal cortex (LvOT) is thought to be essential for the rapid parallel letter processing that is required for skilled reading. Here we investigate whether rapid written word identification in skilled readers can be supported by neural pathways that do not involve LvOT. Hypotheses were derived from a stroke patient who acquired dyslexia following extensive LvOT damage. The patient followed a reading trajectory typical of that associated with pure alexia, re-gaining the ability to read aloud many words with declining performance as the length of words increased. Using functional MRI and dynamic causal modelling (DCM), we found that, when short (three to five letter) familiar words were read successfully, visual inputs to the patient’s occipital cortex were connected to left motor and premotor regions via activity in a central part of the left superior temporal sulcus (STS). The patient analysis therefore implied a left hemisphere “reading-without-LvOT” pathway that involved STS. We then investigated whether the same reading-without-LvOT pathway could be identified in 29 skilled readers and whether there was inter-subject variability in the degree to which skilled reading engaged LvOT. We found that functional connectivity in the reading-without-LvOT pathway was strongest in individuals who had the weakest functional connectivity in the LvOT pathway. This observation validates the findings of our patient’s case study. Our findings highlight the contribution of a left hemisphere reading pathway that is activated during the rapid identification of short familiar written words, particularly when LvOT is not involved. Preservation and use of this pathway may explain how patients are still able to read short words accurately when LvOT has been damaged.

A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading

The anatomy of language has been investigated with PET or fMRI for more than 20 years. Here I attempt to provide an overview of the brain areas associated with heard speech, speech production and reading. The conclusions of many hundreds of studies were considered, grouped according to the type of processing, and reported in the order that they were published. Many findings have been replicated time and time again leading to some consistent and undisputable conclusions. These are summarised in an anatomical model that indicates the location of the language areas and the most consistent functions that have been assigned to them. The implications for cognitive models of language processing are also considered. In particular, a distinction can be made between processes that are localized to specific structures (e.g. sensory and motor processing) and processes where specialisation arises in the distributed pattern of activation over many different areas that each participate in multiple functions. For example, phonological processing of heard speech is supported by the functional integration of auditory processing and articulation; and orthographic processing is supported by the functional integration of visual processing, articulation and semantics. Future studies will undoubtedly be able to improve the spatial precision with which functional regions can be dissociated but the greatest challenge will be to understand how different brain regions interact with one another in their attempts to comprehend and produce language.

Explaining left lateralization for words in the ventral occipitotemporal cortex

Reading is a uniquely human task and therefore any sign of neuronal activation that is specific to reading is of considerable interest. One intriguing observation is that ventral occipitotemporal (vOT) activation is more strongly left lateralized for written words than other visual stimuli. This has contributed to claims that left vOT plays a special role in reading. Here, we investigated whether left lateralized vOT responses for words were the consequence of visual feature processing, visual word form selectivity, or higher level language processing. Using fMRI in 82 skilled readers, our paradigm compared activation and lateralization for words and nonlinguistic stimuli during different tasks. We found that increased left lateralization for words relative to pictures was the consequence of reduced activation in right vOT rather than increased activation in left vOT. We also found that the determinants of lateralization varied with the subregion of vOT tested. In posterior vOT, lateralization depended on the spatial frequency of the visual inputs. In anterior vOT, lateralization depended on the semantic demands of the task. In middle vOT, lateralization depended on a combination of visual expertise in the right hemisphere and semantics in the left hemisphere. These results have implications for interpreting left lateralized vOT activation during reading. Specifically, left lateralized activation in vOT does not necessarily indicate an increase in left vOT processing but is instead a consequence of decreased right vOT function. Moreover, the determinants of lateralization include both visual and semantic factors depending on the subregion tested.

Neural plasticity after pre-linguistic injury to the arcuate and superior longitudinal fasciculi

We describe the case of girl who was born prematurely and diagnosed periventricular leukomalacia, a condition characterized by severe injury to the white matter tracts primarily surrounding the ventricles. At 12 years of age, we obtained diffusion tensor imaging (DTI) data on this child as part of a research protocol. Multiple analyses of DTI data, including tractography, showed that the left and right arcuate and superior longitudinal fasciculi were missing in the child though all other major white matter tracts were present. Standardized psychometric tests at age 12 years revealed that despite early language delays, she had average scores on expressive language, sentence repetition, and reading, functions that have been hypothesized to depend on signals carried by the arcuate fasciculus. We identified intact ventral connections between the temporal and frontal lobes through the extreme capsule fiber system and uncinate fasciculus. Preserved language and reading function after serious injury to the arcuate fasciculus highlights the plasticity of the developing brain after severe white matter injury early in life.

Modules and brain mapping

This review highlights the key role of modularity and the additive factors method in functional neuroimaging. Our focus is on structure–function mappings in the human brain and how these are disclosed by brain mapping. We describe how modularity of processing (and possibly processes) was a key point of reference for establishing functional segregation as a principle of brain organization. Furthermore, modularity plays a crucial role when trying to characterize distributed brain responses in terms of functional integration or coupling among brain areas. We consider additive factors logic and how it helped to shape the design and interpretation of studies at the inception of brain mapping, with a special focus on factorial designs. We look at factorial designs in activation experiments and in the context of lesion–deficit mapping. In both cases, the presence or absence of interactions among various experimental factors has proven essential in understanding the context-sensitive nature of distributed but modular processing and discerning the nature of (potentially degenerate) structure–function relationships in cognitive neuroscience.