Ajay D. Halai

A comparison of dual gradient-echo and spin-echo fMRI of the inferior temporal lobe

Magnetic susceptibility differences at tissue interfaces lead to signal loss in conventional gradient‐echo (GE) EPI. This poses a problem for fMRI in language and memory paradigms, which activate the most affected regions. Two methods proposed to overcome this are spin‐echo EPI and dual GE EPI, where two EPI read‐outs are serially collected at a short and longer echo time. The spin‐echo method applies a refocusing pulse to recover dephased MR signal due to static field inhomogeneities, but is known to have a relatively low blood oxygenation level dependant (BOLD) sensitivity. In comparison, GE has superior BOLD sensitivity, and by employing an additional shorter echo, in a dual GE sequence, it can reduce signal loss due to spin dephasing. We directly compared dual GE and spin‐echo fMRI during a semantic categorization task, which has been shown to activate the inferior temporal region—a region known to be affected by magnetic susceptibility. A whole brain analysis showed that the dual GE resulted in significantly higher activation within the left inferior temporal fusiform (ITF) cortex, compared to spin‐echo. The inferior frontal gyrus (IFG) was activated for dual GE, but not spin‐echo. Regions of interest analysis was carried out on the anterior and posterior ITF, left and right IFG, and part of the cerebellum. Dual GE outperformed spin‐echo in the anterior and posterior ITF and bilateral IFG regions, whilst being equal in the cerebellum. Hence, dual GE should be the method of choice for fMRI studies of inferior temporal regions. Hum Brain Mapp 35:4118–4128, 2014.

Using principal component analysis to capture individual differences within a unified neuropsychological model of chronic post-stroke aphasia: Revealing the unique neural correlates of speech fluency, phonology and semantics

Individual differences in the performance profiles of neuropsychologically-impaired patients are pervasive yet there is still no resolution on the best way to model and account for the variation in their behavioural impairments and the associated neural correlates. To date, researchers have generally taken one of three different approaches: a single-case study methodology in which each case is considered separately; a case-series design in which all individual patients from a small coherent group are examined and directly compared; or, group studies, in which a sample of cases are investigated as one group with the assumption that they are drawn from a homogenous category and that performance differences are of no interest. In recent research, we have developed a complementary alternative through the use of principal component analysis (PCA) of individual data from large patient cohorts. This data-driven approach not only generates a single unified model for the group as a whole (expressed in terms of the emergent principal components) but is also able to capture the individual differences between patients (in terms of their relative positions along the principal behavioural axes). We demonstrate the use of this approach by considering speech fluency, phonology and semantics in aphasia diagnosis and classification, as well as their unique neural correlates. PCA of the behavioural data from 31 patients with chronic post-stroke aphasia resulted in four statistically-independent behavioural components reflecting phonological, semantic, executive–cognitive and fluency abilities. Even after accounting for lesion volume, entering the four behavioural components simultaneously into a voxel-based correlational methodology (VBCM) analysis revealed that speech fluency (speech quanta) was uniquely correlated with left motor cortex and underlying white matter (including the anterior section of the arcuate fasciculus and the frontal aslant tract), phonological skills with regions in the superior temporal gyrus and pars opercularis, and semantics with the anterior temporal stem.

Dual-echo fMRI can detect activations in inferior temporal lobe during intelligible speech comprehension.

The neural basis of speech comprehension has been investigated intensively during the past few decades. Incoming auditory signals are analysed for speech-like patterns and meaningful information can be extracted by mapping these sounds onto stored semantic representations. Investigation into the neural basis of speech comprehension has largely focused on the temporal lobe, in particular the superior and posterior regions. The ventral anterior temporal lobe (vATL), which includes the inferior temporal gyrus (ITG) and temporal fusiform gyrus (TFG) is consistently omitted in fMRI studies. In contrast, PET studies have shown the involvement of these ventral temporal regions. One crucial factor is the signal loss experienced using conventional echo planar imaging (EPI) for fMRI, at tissue interfaces such as the vATL. One method to overcome this signal loss is to employ a dual-echo EPI technique. The aim of this study was to use intelligible and unintelligible (spectrally rotated) sentences to determine if the vATL could be detected during a passive speech comprehension task using a dual-echo acquisition. A whole brain analysis for an intelligibility contrast showed bilateral superior temporal lobe activations and a cluster of activation within the left vATL. Converging evidence implicates the same ventral temporal regions during semantic processing tasks, which include language processing. The specific role of the ventral temporal region during intelligible speech processing cannot be determined from this data alone, but the converging evidence from PET, MEG, TMS and neuropsychology strongly suggest that it contains the stored semantic representations, which are activated by the speech decoding process.

Unification of behavioural, computational and neural accounts of word production errors in post-stroke aphasia

Neuropsychological assessment, brain imaging and computational modelling have augmented our understanding of the multifaceted functional deficits in people with language disorders after stroke. Despite the volume of research using each technique, no studies have attempted to assimilate all three approaches in order to generate a unified behavioural-computational-neural model of post-stroke aphasia. The present study included data from 53 participants with chronic post-stroke aphasia and merged: aphasiological profiles based on a detailed neuropsychological assessment battery which was analysed with principal component and correlational analyses; measures of the impairment taken from Dells computational model of word production; and the neural correlates of both behavioural and computational accounts analysed by voxel-based correlational methodology. As a result, all three strands coincide with the separation of semantic and phonological stages of aphasic naming, revealing the prominence of these dimensions for the explanation of aphasic performance. Over and above three previously described principal components (phonological ability, semantic ability, executive-demand), we observed auditory working memory as a novel factor. While the phonological Dell parameter was uniquely related to phonological errors/factor, the semantic parameter was less clear-cut, being related to both semantic errors and omissions, and loading heavily with semantic ability and auditory working memory factors. The close relationship between the semantic Dell parameter and omission errors recurred in their high lesion-correlate overlap in the anterior middle temporal gyrus. In addition, the simultaneous overlap of the lesion correlate of omission errors with more dorsal temporal regions, associated with the phonological parameter, highlights the multiple drivers that underpin this error type. The novel auditory working memory factor was located along left superior/middle temporal gyrus and ventral inferior parietal lobe. The present study fused computational, behavioural and neural data to gain comprehensive insights into the nature of the multifaceted presentations in aphasia. Our unified account contributes enhanced knowledge on dimensions explaining chronic post-stroke aphasia, the variety of factors affecting inter-individual variability, the neural basis of performance, and potential clinical implications.

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.

Mapping the intersection of language and reading: The neural bases of the primary systems hypothesis

The primary systems framework has been used to relate behavioural performance across many different language activities to the status of core underpinning domain-general cognitive systems. This study provided the first quantitative investigation of this account at both behavioural and neural levels in a group of patients with chronic post-stroke aphasia. Principal components analysis was used to distil orthogonal measures of phonological and semantic processing, which were then related to reading performance and the underlying lesion distributions using voxel-based correlational methodology. Concrete word reading involved both a ventral semantic pathway, and inferior and anterior aspects of the dorsal phonological pathway. Abstract word reading overlapped with the ventral semantic pathway but also drew more extensively on the superior and posterior aspects of the dorsal phonological pathway. Nonword reading was related to phonological processing along the dorsal pathway and was also supported by a more superior set of regions previously associated with speech motor output. The use of continuous measures of behavioural performance and neural integrity allowed us to elucidate for the first time both the lesion and behavioural correlates for the semantic and phonological components of the primary systems hypothesis and to extend these by identifying the importance of an additional dorsal speech motor output system. These results provide a target for future neuroanatomically constrained computational models of reading.

The relationship between the multidimensionality of aphasia and psycholinguistic features

Background and aim: Naming deficits are one of the most prominent symptoms in aphasia. Successful naming can depend on certain psycholinguistic features of the word, and most crucially word imageability, frequency, and age-of-acquisition (Alyahya et al., 2018; Cuetos et al., 2002; Nickels & Howard, 1995). There is a large body of literature on the influence of psycholinguistic features in neurotypical adults and people with aphasia; however, the relationship between the influence of these features and the multidimensionality of aphasia has not been explored. The main aim of this study was to systematically relate the influence of psycholinguistic features to participants’ aphasiological profiles using a novel approach. Methods: Forty-two participants with a diverse range of chronic post-stroke aphasia classifications and severities, resulting from a single left hemisphere stroke, completed an extensive battery of aphasiological assessments. This battery assesses language and cognitive abilities, and it includes repetition, single-word naming, auditory discrimination, single-word and sentence comprehension tests, as well as fluency measures, digit span, and executive function tests. Principal component analysis (PCA) was performed on participants’ scores on all assessments, in order to identify the fundamental language and cognitive components of aphasia. Participants also completed a picture naming task (130 stimuli), and values for seven psycholinguistic features of the stimuli were defined: word frequency, familiarity, age-ofacquisition, imageability, semantic diversity, length, and phonological-neighbourhooddensity. To identify the unique effects of these features on each participant, logistic regression analyses were carried out on the naming profile of each participant using the seven features as predictors. Subsequently, correlation analyses were performed between participants’ factor scores extracted from the PCA and participant’s beta values identified from the logistic regression analyses. Results: The simultaneous multiple regression analysis carried out on the naming accuracy of the whole group was significant, with imageability, familiarity, and phonological-neighbourhood-density appearing as significant predictors. However, the individual logistic regression analyses showed huge between-subject variability. The overall direction of the effects can be interpreted from the beta weights, and these indicated that performance was better in response to high imageable words among the majority of the participants, as well as high familiar, shorter words, with less semantic diversity, that were