Thomas M. H. Hope

The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke.

The PLORAS Database is a relational repository of anatomical and functional imaging data that has primarily been acquired from stroke survivors, along with standardized scores on a wide range of sensory, motor and cognitive abilities, demographic details and medical history. As of January 2015, we have data from 750 patients with an expected accrual rate of 200 patients per year. Expansion will accelerate as we extend our collaborations. The main aim of the database is to Predict Language Outcome and Recovery After Stroke (PLORAS) on the basis of a single structural (anatomical) brain scan that indexes the stereotactic location and extent of brain damage. Predictions are made for individual patients by indicating how other patients with the most similar brain damage, cognitive abilities and demographic details recovered their language skills over time. Predictions are validated by longitudinal follow-ups of patients who initially presented with speech and language difficulties. The PLORAS Database can also be used to predict recovery of other cognitive abilities on the basis of anatomical brain scans. The functional imaging data can be used to understand the neural mechanisms that support recovery from brain damage; and all the data can be used to understand the main sources of inter-subject variability in structure–function mappings in the human brain. Data will be made available for sharing, subject to: funding, ethical approval and patient consent.

Sensory-to-motor integration during auditory repetition: A combined fMRI and lesion study

The aim of this paper was to investigate the neurological underpinnings of auditory-to-motor translation during auditory repetition of unfamiliar pseudowords. We tested two different hypotheses. First we used functional magnetic resonance imaging in 25 healthy subjects to determine whether a functionally defined area in the left temporo-parietal junction (TPJ), referred to as Sylvian-parietal-temporal region (Spt), reflected the demands on auditory-to-motor integration during the repetition of pseudowords relative to a semantically mediated nonverbal sound-naming task. The experiment also allowed us to test alternative accounts of Spt function, namely that Spt is involved in subvocal articulation or auditory processing that can be driven either bottom-up or top-down. The results did not provide convincing evidence that activation increased in either Spt or any other cortical area when non-semantic auditory inputs were being translated into motor outputs. Instead, the results were most consistent with Spt responding to bottom up or top down auditory processing, independent of the demands on auditory-to-motor integration. Second, we investigated the lesion sites in eight patients who had selective difficulties repeating heard words but with preserved word comprehension, picture naming and verbal fluency (i.e., conduction aphasia). All eight patients had white-matter tract damage in the vicinity of the arcuate fasciculus and only one of the eight patients had additional damage to the Spt region, defined functionally in our fMRI data. Our results are therefore most consistent with the neurological tradition that emphasizes the importance of the arcuate fasciculus in the non-semantic integration of auditory and motor speech processing.

Dissecting the functional anatomy of auditory word repetition

This fMRI study used a single, multi-factorial, within-subjects design to dissociate multiple linguistic and non-linguistic processing areas that are all involved in repeating back heard words. The study compared: (1) auditory to visual inputs; (2) phonological to non-phonological inputs; (3) semantic to non-semantic inputs; and (4) speech production to finger-press responses. The stimuli included words (semantic and phonological inputs), pseudowords (phonological input), pictures and sounds of animals or objects (semantic input), and colored patterns and hums (non-semantic and non-phonological). The speech production tasks involved auditory repetition, reading, and naming while the finger press tasks involved one-back matching. The results from the main effects and interactions were compared to predictions from a previously reported functional anatomical model of language based on a meta-analysis of many different neuroimaging experiments. Although many findings from the current experiment replicated many of those predicted, our within-subject design also revealed novel results by providing sufficient anatomical precision to dissect several different regions within the anterior insula, pars orbitalis, anterior cingulate, SMA, and cerebellum. For example, we found one part of the pars orbitalis was involved in phonological processing and another in semantic processing. We also dissociated four different types of phonological effects in the left superior temporal sulcus (STS), left putamen, left ventral premotor cortex, and left pars orbitalis. Our findings challenge some of the commonly-held opinions on the functional anatomy of language, and resolve some previously conflicting findings about specific brain regions—and our experimental design reveals details of the word repetition process that are not well captured by current models.

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 individuals 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.

Comparing language outcomes in monolingual and bilingual stroke patients.

Hope et al. compare language outcomes in monolingual and bilingual stroke patients, and find that prognostic models based on monolingual data alone overestimate language skills in bilingual patients. Both groups seem sensitive to damage in the same brain regions, but bilinguals appear more sensitive to that damage than monolinguals.

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.

Distinguishing the effect of lesion load from tract disconnection in the arcuate and uncinate fasciculi

Brain imaging studies of functional outcomes after white matter damage have quantified the severity of white matter damage in different ways. Here we compared how the outcome of such studies depends on two different types of measurements: the proportion of the target tract that has been destroyed (‘lesion load’) and tract disconnection. We demonstrate that conclusions from analyses based on two examples of these measures diverge and that conclusions based solely on lesion load may be misleading. First, we reproduce a recent lesion-load-only analysis which suggests that damage to the arcuate fasciculus, and not to the uncinate fasciculus, is significantly associated with deficits in fluency and naming skills. Next, we repeat the analysis after replacing the measures of lesion load with measures of tract disconnection for both tracts, and observe significant associations between both tracts and both language skills: i.e. the change increases the apparent relevance of the uncinate fasciculus to fluency and naming skills. Finally we show that, in this dataset, disconnection data explains significant variance in both language skills that is not accounted for by lesion load or volume, but lesion load data explains no unique variance in those skills, once disconnection and lesion volume are taken into account.

Right hemisphere structural adaptation and changing language skills years after left hemisphere stroke

Language difficulties after stroke are commonly thought to stabilise within a year. Hope et al. report surprising evidence to the contrary, showing that the language skills of patients with post-stroke aphasia continue to change even years after stroke. The changes are associated with structural adaptation in the intact right hemisphere.

Dissociating the semantic function of two neighbouring subregions in the left lateral anterior temporal lobe

We used fMRI in 35 healthy participants to investigate how two neighbouring subregions in the lateral anterior temporal lobe (LATL) contribute to semantic matching and object naming. Four different levels of processing were considered: (A) recognition of the object concepts; (B) search for semantic associations related to object stimuli; (C) retrieval of semantic concepts of interest; and (D) retrieval of stimulus specific concepts as required for naming. During semantic association matching on picture stimuli or heard object names, we found that activation in both subregions was higher when the objects were semantically related (mug–kettle) than unrelated (car–teapot). This is consistent with both LATL subregions playing a role in (C), the successful retrieval of amodal semantic concepts. In addition, one subregion was more activated for object naming than matching semantically related objects, consistent with (D), the retrieval of a specific concept for naming. We discuss the implications of these novel findings for cognitive models of semantic processing and left anterior temporal lobe function.

Predicting IQ change from brain structure: a cross-validation study.

Highlights • We quantify how well IQ changes in teenagers can be predicted from brain scans.• We compare different ways to cross-validate predictions from neuroimaging.• We demonstrate the advantage of using Leave-One-Out cross-validation.• We illustrate the limitations of using IQ as a measure of cognitive potential.