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

Visualising inter-subject variability in fMRI using threshold-weighted overlap maps

Functional neuroimaging studies are revealing the neural systems sustaining many sensory, motor and cognitive abilities. A proper understanding of these systems requires an appreciation of the degree to which they vary across subjects. Some sources of inter-subject variability might be easy to measure (demographics, behavioural scores, or experimental factors), while others are more difficult (cognitive strategies, learning effects, and other hidden sources). Here, we introduce a simple way of visualising whole-brain consistency and variability in brain responses across subjects using threshold-weighted voxel-based overlap maps. The output quantifies the proportion of subjects activating a particular voxel or region over a wide range of statistical thresholds. The sensitivity of our approach was assessed in 30 healthy adults performing a matching task with their dominant hand. We show how overlap maps revealed many effects that were only present in a subsample of our group; we discuss how overlap maps can provide information that may be missed or misrepresented by standard group analysis, and how this information can help users to understand their data. In particular, we emphasize that functional overlap maps can be particularly useful when it comes to explaining typical (or atypical) compensatory mechanisms used by patients following brain damage

Interpreting and validating complexity and causality in lesion-symptom prognoses

This paper considers the steps needed to generate pragmatic and interpretable lesion-symptom mappings that can be used for clinically reliable prognoses. The novel contributions are 3-fold. We first define and inter-relate five neurobiological and five methodological constraints that need to be accounted for when interpreting lesion-symptom associations and generating synthetic lesion data. The first implication is that, because of these constraints, lesion-symptom mapping needs to focus on probabilistic relationships between Lesion and Symptom, with Lesion as a multivariate spatial pattern, Symptom as a time-dependent behavioural profile and evidence that Lesion raises the probability of Symptom. The second implication is that in order to assess the strength of probabilistic causality, we need to distinguish between causal lesion sites, incidental lesion sites, spared but dysfunctional sites and intact sites, all of which might affect the accuracy of the predictions and prognoses generated. We then formulate lesion-symptom mappings in logical notations, including combinatorial rules, that are then used to evaluate and better understand complex brain-behaviour relationships. The logical and theoretical framework presented applies to any type of neurological disorder but is primarily discussed in relationship to stroke damage. Accommodating the identified constraints, we discuss how the 1965 Bradford Hill criteria for inferring probabilistic causality, post hoc, from observed correlations in epidemiology - can be applied to lesion-symptom mapping in stroke survivors. Finally, we propose that rather than rely on post hoc evaluation of how well the causality criteria have been met, the neurobiological and methodological constraints should be addressed, a priori, by changing the experimental design of lesion-symptom mappings and setting up an open platform to share and validate the discovery of reliable and accurate lesion rules that are clinically useful

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

A Data-Based Approach for Selecting Pre- and Intra-Operative Language Mapping Tasks

Background: Pre- and intra-operative language mapping in neurosurgery patients frequently involves an object naming task. The choice of the optimal object naming paradigm remains challenging due to lack of normative data and standardization in mapping practices. The aim of this study was to identify object naming paradigms that robustly and consistently activate classical language regions and could therefore be used to improve the sensitivity of language mapping in brain tumor and epilepsy patients. Methods: Functional magnetic resonance imaging (fMRI) data from two independent groups of healthy controls (total = 79) were used to generate threshold-weighted voxel-based consistency maps. This novel approach allowed us to compare inter-subject consistency of activation for naming single objects in the visual and auditory modality and naming two objects in a phrase or a sentence. Results: We found that the consistency of activation in language regions was greater for naming two objects per picture than one object per picture, even when controlling for the number of names produced in 5 s. Conclusion: More consistent activation in language areas for naming two objects compared to one object suggests that two-object naming tasks may be more suitable for delimiting language eloquent regions with pre- and intra-operative language testing. More broadly, we propose that the functional specificity of brain mapping paradigms for a whole range of different linguistic and non-linguistic functions could be enhanced by referring to databased models of inter-subject consistency and variability in typical and atypical brain responses

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

The influence of reading ability on subsequent changes in verbal IQ in the teenage years

Intelligence Quotient (IQ) is regularly used in both education and employment as a measure of cognitive ability. Although an individual's IQ is generally assumed to stay constant across the lifespan, a few studies have suggested that there may be substantial variation at the individual level. Motivated by previous reports that reading quality/quantity has a positive influence on vocabulary acquisition, we hypothesised that reading ability in the early teenage years might contribute to changes in verbal IQ (VIQ) over the next few years. We found that good readers were more likely to experience relative improvements in VIQ over time, with the reverse true for poor readers. These effects were largest when there was a discrepancy between Time 1 reading ability and Time 1 VIQ. In other words, VIQ increases tended to be greatest when reading ability was high relative to VIQ. Additional analyses supported these findings by showing that variance in VIQ change associated with Time 1 behaviour was also associated with independent measurements of brain structure. Our finding that reading in the early teenage years can predict a significant proportion of the variance in subsequent VIQ change has implications for targeted education in both home and school environments

Functionally distinct contributions of the anterior and posterior putamen during sublexical and lexical reading.

Previous studies have investigated orthographic-to-phonological mapping during reading by comparing brain activation for (1) reading words to object naming, or (2) reading pseudowords (e.g., "phume") to words (e.g., "plume"). Here we combined both approaches to provide new insights into the underlying neural mechanisms. In fMRI data from 25 healthy adult readers, we first identified activation that was greater for reading words and pseudowords relative to picture and color naming. The most significant effect was observed in the left putamen, extending to both anterior and posterior borders. Second, consistent with previous studies, we show that both the anterior and posterior putamen are involved in articulating speech with greater activation during our overt speech production tasks (reading, repetition, object naming, and color naming) than silent one-back-matching on the same stimuli. Third, we compared putamen activation for words versus pseudowords during overt reading and auditory repetition. This revealed that the anterior putamen was most activated by reading pseudowords, whereas the posterior putamen was most activated by words irrespective of whether the task was reading words or auditory word repetition. The pseudoword effect in the anterior putamen is consistent with prior studies that associated this region with the initiation of novel sequences of movements. In contrast, the heightened word response in the posterior putamen is consistent with other studies that associated this region with "memory guided movement." Our results illustrate how the functional dissociation between the anterior and posterior putamen supports sublexical and lexical processing during reading

Four Functionally Distinct Regions in the Left Supramarginal Gyrus Support Word Processing

We used fMRI in 85 healthy participants to investigate whether different parts of the left supramarginal gyrus (SMG) are involved in processing phonological inputs and outputs. The experiment involved 2 tasks (speech production (SP) and one-back (OB) matching) on 8 different types of stimuli that systematically varied the demands on sensory processing (visual vs. auditory), sublexical phonological input (words and pseudowords vs. nonverbal stimuli), and semantic content (words and objects vs. pseudowords and meaningless baseline stimuli). In ventral SMG, we found an anterior subregion associated with articulatory sequencing (for SP > OB matching) and a posterior subregion associated with auditory short-term memory (for all auditory > visual stimuli and written words and pseudowords > objects). In dorsal SMG, a posterior subregion was most highly activated by words, indicating a role in the integration of sublexical and lexical cues. In anterior dorsal SMG, activation was higher for both pseudoword reading and object naming compared with word reading, which is more consistent with executive demands than phonological processing. The dissociation of these four “functionally-distinct” regions, all within left SMG, has implications for differentiating between different types of phonological processing, understanding the functional anatomy of language and predicting the effect of brain damage

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