Kori Johnson

The contribution of genes to cortical thickness and volume.

We analyzed brain MRI data from 372 young adult twins toidentify cortical regions in which gray matter thickness and volume are influenced by genetics. This was achieved using an A/C/E structural equation model that divides the variance of these traits, at each point on the cortex, into additive genetic (A), shared (C), and unique environmental (E) components. A strong genetic influencewas found in frontal and parietal regions. Inaddition, we correlated cortical thickness with full-scale intelligence quotient for comparison with the A/C/E maps, and several regions where cortical structure was correlated with intelligence quotient are under genetic control. These cortical measures may be useful phenotypes to narrow the searchfor quantitative trait lociinfluencing brain structure.

Relationship of a Variant in the NTRK1 Gene to White Matter Microstructure in Young Adults

The NTRK1 gene (also known as TRKA) encodes a high-affinity receptor for NGF, a neurotrophin involved in nervous system development and myelination. NTRK1 has been implicated in neurological function via links between the T allele at rs6336 (NTRK1-T) and schizophrenia risk. A variant in the neurotrophin gene, BDNF, was previously associated with white matter integrity in young adults, highlighting the importance of neurotrophins to white matter development. We hypothesized that NTRK1-T would relate to lower fractional anisotropy in healthy adults. We scanned 391 healthy adult human twins and their siblings (mean age: 23.6 ± 2.2 years; 31 NTRK1-T carriers, 360 non-carriers) using 105-gradient diffusion tensor imaging at 4 tesla. We evaluated in brain white matter how NTRK1-T and NTRK1 rs4661063 allele A (rs4661063-A, which is in moderate linkage disequilibrium with rs6336) related to voxelwise fractional anisotropy—a common diffusion tensor imaging measure of white matter microstructure. We used mixed-model regression to control for family relatedness, age, and sex. The sample was split in half to test reproducibility of results. The false discovery rate method corrected for voxelwise multiple comparisons. NTRK1-T and rs4661063-A correlated with lower white matter fractional anisotropy, independent of age and sex (multiple-comparisons corrected: false discovery rate critical p = 0.038 for NTRK1-T and 0.013 for rs4661063-A). In each half-sample, the NTRK1-T effect was replicated in the cingulum, corpus callosum, superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculus, superior corona radiata, and uncinate fasciculus. Our results suggest that NTRK1-T is important for developing white matter microstructure.

Priming picture naming with a semantic task: An fMRI investigation

Prior semantic processing can enhance subsequent picture naming performance, yet the neurocognitive mechanisms underlying this effect and its longevity are unknown. This functional magnetic resonance imaging study examined whether different neurological mechanisms underlie short-term (within minutes) and long-term (within days) facilitation effects from a semantic task in healthy older adults. Both short- and long-term facilitated items were named significantly faster than unfacilitated items, with short-term items significantly faster than long-term items. Region of interest results identified decreased activity for long-term facilitated items compared to unfacilitated and short-term facilitated items in the mid-portion of the middle temporal gyrus, indicating lexical-semantic priming. Additionally, in the whole brain results, increased activity for short-term facilitated items was identified in regions previously linked to episodic memory and object recognition, including the right lingual gyrus (extending to the precuneus region) and the left inferior occipital gyrus (extending to the left fusiform region). These findings suggest that distinct neurocognitive mechanisms underlie short- and long-term facilitation of picture naming by a semantic task, with long-term effects driven by lexical-semantic priming and short-term effects by episodic memory and visual object recognition mechanisms.

Neural mechanisms underlying the facilitation of naming in aphasia using a semantic task: an fMRI study

BackgroundPrevious attempts to investigate the effects of semantic tasks on picture naming in both healthy controls and people with aphasia have typically been confounded by inclusion of the phonological word form of the target item. As a result, it is difficult to isolate any facilitatory effects of a semantically-focused task to either lexical-semantic or phonological processing. This functional magnetic resonance imaging (fMRI) study examined the neurological mechanisms underlying short-term (within minutes) and long-term (within days) facilitation of naming from a semantic task that did not include the phonological word form, in both participants with aphasia and age-matched controls.ResultsBehavioral results showed that a semantic task that did not include the phonological word form can successfully facilitate subsequent picture naming in both healthy controls and individuals with aphasia. The whole brain neuroimaging results for control participants identified a repetition enhancement effect in the short-term, with modulation of activity found in regions that have not traditionally been associated with semantic processing, such as the right lingual gyrus (extending to the precuneus) and the left inferior occipital gyrus (extending to the fusiform gyrus). In contrast, the participants with aphasia showed significant differences in activation over both the short- and the long-term for facilitated items, predominantly within either left hemisphere regions linked to semantic processing or their right hemisphere homologues.ConclusionsFor control participants in this study, the short-lived facilitation effects of a prior semantic task that did not include the phonological word form were primarily driven by object priming and episodic memory mechanisms. However, facilitation effects appeared to engage a predominantly semantic network in participants with aphasia over both the short- and the long-term. The findings of the present study also suggest that right hemisphere involvement may be supportive rather than maladaptive, and that a large distributed perisylvian network in both cerebral hemispheres supports the facilitation of naming in individuals with aphasia.

Independent distractor frequency and age-of-acquisition effects in picture-word interference: Fmri evidence for post-lexical and lexical accounts according to distractor type

In two fMRI experiments, participants named pictures with superimposed distractors that were high or low in frequency or varied in terms of age of acquisition. Pictures superimposed with low-frequency words were named more slowly than those superimposed with high-frequency words, and late-acquired words interfered with picture naming to a greater extent than early-acquired words. The distractor frequency effect (Experiment 1) was associated with increased activity in left premotor and posterior superior temporal cortices, consistent with the operation of an articulatory response buffer and verbal self-monitoring system. Conversely, the distractor age-of-acquisition effect (Experiment 2) was associated with increased activity in the left middle and posterior middle temporal cortex, consistent with the operation of lexical level processes such as lemma and phonological word form retrieval. The spatially dissociated patterns of activity across the two experiments indicate that distractor effects in picture–word interference may occur at lexical or postlexical levels of processing in speech production.

Facilitation of naming in aphasia with auditory repetition: an investigation of neurocognitive mechanisms.

Prior phonological processing can enhance subsequent picture naming performance in individuals with aphasia, yet the neurocognitive mechanisms underlying this effect and its longevity are unknown. This study used functional magnetic resonance imaging to examine the short-term (within minutes) and long-term (within days) facilitation effects from a phonological task in both participants with aphasia and age-matched controls. Results for control participants suggested that long-term facilitation of subsequent picture naming may be driven by a strengthening of semantic-phonological connections, while semantic and object recognition mechanisms underlie more short-term effects. All participants with aphasia significantly improved in naming accuracy following both short- and long-term facilitation. A descriptive comparison of the neuroimaging results identified different patterns of activation for each individual with aphasia. The exclusive engagement of a left hemisphere phonological network underlying facilitation was not revealed. The findings suggest that improved naming in aphasia with phonological tasks may be supported by changes in right hemisphere activity in some individuals and reveal the potential contribution of the cerebellum to improved naming following phonological facilitation. Conclusions must be interpreted with caution, however, due to the comparison of corrected group control results to that of individual participants with aphasia, which were not corrected for multiple comparisons.

Neuroimaging the short- and long-term effects of repeated picture naming in healthy older adults.

Repeated attempts to name pictures can improve subsequent naming for aphasic individuals with anomia, however, the neurocognitive mechanisms responsible for such improvements are unknown. This study investigated repeated picture naming in healthy older adults over a period of minutes (short-term) after one repetition and a period of days (long-term) after multiple repetitions. Compared to unprimed pictures, both repeated conditions showed faster naming latencies with the fastest latencies evident for the short-term condition. Neuroimaging results identified repetition suppression effects across three left inferior frontal gyrus regions of interest: for both the short- and long-term conditions in the pars orbitalis, and for long-term items in the pars triangularis and pars opercularis regions. The whole brain analysis also showed a repetition suppression effect in bilateral pars triangularis regions for the long-term condition. These findings within the inferior frontal gyrus suggest that effects of repeated naming may be driven by a mapping mechanism across multiple levels of representation, possibly reflecting different levels of learning, and lend support to the idea that processing may be hierarchically organised in the left inferior frontal gyrus. The whole brain analysis also revealed repetition suppression for the long-term condition within the posterior portion of bilateral inferior temporal gyri, which may reflect attenuation of integration processes within this region following the learning of task-relevant information.

Changes in anatomical brain connectivity between ages 12 and 30: A HARDI study of 467 adolescents and adults

Graph theory can be applied to matrices that represent the brains anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and “small-world” topology. Network analysis is popular in adult studies of connectivity, but only one study - in just 30 subjects - has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age2 effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.

Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.