Detecting language activations with functional magnetic resonance imaging

This thesis investigates a number of factors that affect sensitivity to language activations in functional Magnetic Resonance Imaging (fMRI). In the first part, I investigate the impact of experimental design parameters on the ability to detect language activations. These parameters include stimulus rate, stimulus duration, stimulus amplitude, epoch length and stimulus ordering. Crucially, they may affect sensitivity in multiple ways that include neurophysiological, efficiency-mediated and BOLD saturation effects. I illustrate and discuss these effects by presenting biophysical simulations and fMRI studies of single word and pseudoword reading. In addition, I focus on the differential effects of the above parameters in Positron Emission Tomography and fMRI studies. In the second part, I investigate the impact of the analysis used to estimate effects of interest from the data. I compare event-related and epoch analyses and show that, even in the context of blocked design fMRI, an event-related model may provide greater sensitivity than an epoch model. I then address the notion that experimentally-induced effects may be detected not only as task-dependent changes in regional responses but also as changes in connectivity amongst functionally connected regions. These two complementary approaches are motivated by two fundamental principles of brain organisation: functional specialisation and functional integration. I present two fMRI studies investigating the neural correlates of reading words and pseudowords in terms of functional specialisation and functional integration. Furthermore, in both studies I address the issue of inter-subject variability, which may be a critical determinant of sensitivity. Men

Where Bottom-up Meets Top-down: Neuronal Interactions during Perception and Imagery

Functional magnetic resonance imaging (fMRI) studies have identified category-selective regions in ventral occipito-temporal cortex that respond preferentially to faces and other objects. The extent to which these patterns of activation are modulated by bottom-up or top-down mechanisms is currently unknown. We combined fMRI and dynamic causal modelling to investigate neuronal interactions between occipito-temporal, parietal and frontal regions, during visual perception and visual imagery of faces, houses and chairs. Our results indicate that, during visual perception, category-selective patterns of activation in extrastriate cortex are mediated by content-sensitive forward connections from early visual areas. In contrast, during visual imagery, category-selective activation is mediated by content-sensitive backward connections from prefrontal cortex. Additionally, we report content-unrelated connectivity between parietal cortex and the category-selective regions, during both perception and imagery. Thus, our investigation revealed that neuronal interactions between occipito-temporal, parietal and frontal regions are task- and stimulus-dependent. Sensory representations of faces and objects are mediated by bottom-up mechanisms arising in early visual areas and top-down mechanisms arising in prefrontal cortex, during perception and imagery respectively. Additionally non-selective, top-down processes, originating in superior parietal areas, contribute to the generation of mental images, regardless of their content, and their maintenance in the ‘mind's eye

Fusiform activation to animals is driven by the process, not the stimulus

Previous studies have found that the lateral posterior fusiform gyri respond more robustly to pictures of animals than pictures of manmade objects and suggested that these regions encode the visual properties characteristic of animals. We suggest that such effects actually reflect processing demands arising when items with similar representations must be finely discriminated. In a positron emission tomography (PET) study of category verification with colored photographs of animals and vehicles, there was robust animal-specific activation in the lateral posterior fusiform gyri when stimuli were categorized at an intermediate level of specificity (e.g., dog or car). However, when the same photographs were categorized at a more specific level (e.g., Labrador or BMW), these regions responded equally strongly to animals and vehicles. We conclude that the lateral posterior fusiform does not encode domain-specific representations of animals or visual properties characteristic of animals. Instead, these regions are strongly activated whenever an item must be discriminated from many close visual or semantic competitors. Apparent category effects arise because, at an intermediate level of specificity, animals have more visual and semantic competitors than do artifacts

When the Single Matters more than the Group (II): Addressing the Problem of High False Positive Rates in Single Case Voxel Based Morphometry Using Non-parametric Statistics

In recent years, an increasing number of studies have used Voxel Based Morphometry (VBM) to compare a single patient with a psychiatric or neurological condition of interest against a group of healthy controls. However, the validity of this approach critically relies on the assumption that the single patient is drawn from a hypothetical population with a normal distribution and variance equal to that of the control group. In a previous investigation, we demonstrated that family-wise false positive error rate (i.e. the proportion of statistical comparisons yielding at least one false positive) in single case VBM are much higher than expected (Scarpazza et al. 2013). Here we examine whether the use of non-parametric statistics, which does not rely on the assumptions of normal distribution and equal variance, would enable the investigation of single subjects with good control of false positive risk. We empirically estimated false positive rates in single case non-parametric VBM, by performing 400 statistical comparisons between a single disease-free individual and a group of 100 disease-free controls. The impact of smoothing (4, 8 and 12 mm) and type of pre-processing (Modulated, Unmodulated) was also examined, as these factors have been found to influence false positive rates in previous investigations using parametric statistics. The 400 statistical comparisons were repeated using two independent, freely available data sets in order to maximize the generalizability of the results. We found that the family-wise error rate was 5% for increases and 3.6% for decreases in one data set; and 5.6% for increases and 6.3% for decreases in the other data set (5% nominal). Further, these results were not dependent on the level of smoothing and modulation. Therefore, the present study provides empirical evidence that single case VBM studies with non-parametric statistics are not susceptible to high false positive rates. The critical implication of this finding is that VBM can be used to characterize neuroanatomical alterations in individual subjects as long as non-parametric statistics are employed

Neuroanatomical abnormalities in first-episode psychosis across independent samples: a multi-centre mega-analysis

Background. Neuroanatomical abnormalities in first-episode psychosis (FEP) tend to be sub tle and widespread. The vast majority of previous studies have used small samples, and there fore may have been underpowered. In addition, most studies have examined participants at a single research site, and therefore the results may be specific to the local sample investigated. Consequently, the findings reported in the existing literature are highly heterogeneous. This study aimed to overcome these issues by testing for neuroanatomical abnormalities in indivi duals with FEP that are expressed consistently across several independent samples. Methods. Structural Magnetic Resonance Imaging data were acquired from a total of 572 FEP and 502 age and gender comparable healthy controls at five sites. Voxel-based morphometry was used to investigate differences in grey matter volume (GMV) between the two groups. Statistical inferences were made at p < 0.05 after family-wise error correction for multiple comparisons. Results. FEP showed a widespread pattern of decreased GMV in fronto-temporal, insular and occipital regions bilaterally; these decreases were not dependent on anti-psychotic medication. The region with the most pronounced decrease – gyrus rectus – was negatively correlated with the severity of positive and negative symptoms. Conclusions. This study identified a consistent pattern of fronto-temporal, insular and occipi tal abnormalities in five independent FEP samples; furthermore, the extent of these alterations is dependent on the severity of symptoms and duration of illness. This provides evidence for reliable neuroanatomical alternations in FEP, expressed above and beyond site-related differ ences in anti-psychotic medication, scanning parameters and recruitment criteri

Transcriptome Analysis of Canine Cutaneous Melanoma and Melanocytoma Reveals a Modulation of Genes Regulating Extracellular Matrix Metabolism and Cell Cycle

Interactions between tumor cells and tumor microenvironment are considered critical in carcinogenesis, tumor invasion and metastasis. To examine transcriptome changes and to explore the relationship with tumor microenvironment in canine cutaneous melanocytoma and melanoma, we extracted RNA from formalin-fixed, paraffin-embedded (FFPE) specimens and analyzed them by means of RNA-seq for transcriptional analysis. Melanocytoma and melanoma samples were compared to detect differential gene expressions and significant enriched pathways were explored to reveal functional relations between differentially expressed genes. The study demonstrated a differential expression of 60 genes in melanomas compared to melanocytomas. The differentially expressed genes cluster in the extracellular matrix-receptor interaction, protein digestion and absorption, focal adhesion and PI3K-Akt (phosphoinositide 3-kinase/protein kinase B) signaling pathways. Genes encoding for several collagen proteins were more commonly differentially expressed. Results of the RNA-seq were validated by qRT-PCR and protein expression of some target molecules was investigated by means of immunohistochemistry. We hypothesize that the developing melanoma actively promotes collagen metabolism and extracellular matrix remodeling as well as enhancing cell proliferation and survival contributing to disease progression and metastasis. In this study, we also detected unidentified genes in human melanoma expression studies and uncover new candidate drug targets for further testing in canine melanoma

Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer’s disease in a cross-sectional multi-cohort study

Abstract Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning models have been implemented to develop normative models to investigate brain disorders, including regression, support vector machines and Gaussian process models. With the advance of deep learning technology, the use of deep neural networks has also been proposed. In this study, we assessed normative models based on deep autoencoders using structural neuroimaging data from patients with Alzheimer’s disease (n = 206) and mild cognitive impairment (n = 354). We first trained the autoencoder on an independent dataset (UK Biobank dataset) with 11,034 healthy controls. Then, we estimated how each patient deviated from this norm and established which brain regions were associated to this deviation. Finally, we compared the performance of our normative model against traditional classifiers. As expected, we found that patients exhibited deviations according to the severity of their clinical condition. The model identified medial temporal regions, including the hippocampus, and the ventricular system as critical regions for the calculation of the deviation score. Overall, the normative model had comparable cross-cohort generalizability to traditional classifiers. To promote open science, we are making all scripts and the trained models available to the wider research community

The Impact of Second Language Learning on Semantic and Nonsemantic First Language Reading

The relationship between orthography (spelling) and phonology (speech sounds) varies across alphabetic languages. Consequently, learning to read a second alphabetic language, that uses the same letters as the first, increases the phonological associations that can be linked to the same orthographic units. In subjects with English as their first language, previous functional imaging studies have reported increased left ventral prefrontal activation for reading words with spellings that are inconsistent with their orthographic neighbors (e.g., PINT) compared with words that are consistent with their orthographic neighbors (e.g., SHIP). Here, using functional magnetic resonance imaging (fMRI) in 17 Italian–English and 13 English–Italian bilinguals, we demonstrate that left ventral prefrontal activation for first language reading increases with second language vocabulary knowledge. This suggests that learning a second alphabetic language changes the way that words are read in the first alphabetic language. Specifically, first language reading is more reliant on both lexical/semantic and nonlexical processing when new orthographic to phonological mappings are introduced by second language learning. Our observations were in a context that required participants to switch between languages. They motivate future fMRI studies to test whether first language reading is also altered in contexts when the second language is not in use