Interpreting response time effects in functional imaging studies

It has been suggested that differential neural activity in imaging studies is most informative if it is independent of response time (RT) differences. However, others view RT as a behavioural index of key cognitive processes, which is likely linked to underlying neural activity. Here, we reconcile these views using the effort and engagement framework developed by Taylor, Rastle, and Davis (2013) and data from the domain of reading aloud. We propose that differences in neural engagement should be independent of RT, whereas, differences in neural effort should co-vary with RT. We illustrate these different mechanisms using data from an fMRI study of neural activity during reading aloud of regular words, irregular words, and pseudowords. In line with our proposals, activation revealed by contrasts designed to tap differences in neural engagement (e.g., words are meaningful and therefore engage semantic representations more than pseudowords) survived correction for RT, whereas activation for contrasts designed to tap differences in neural effort (e.g., it is more difficult to generate the pronunciation of pseudowords than words) correlated with RT. However, even for contrasts designed to tap neural effort, activity remained after factoring out the RT-BOLD response correlation. This may reveal unpredicted differences in neural engagement (e.g., learning phonological forms for pseudowords. >. words) that could further the development of cognitive models of reading aloud. Our framework provides a theoretically well-grounded and easily implemented method for analysing and interpreting RT effects in neuroimaging studies of cognitive processes

Visual Experience Shapes Orthographic Representations in the Visual Word Form Area

Current neurocognitive research suggests that the efficiency of visual word recognition rests on abstract memory representations of written letters and words stored in the visual word form area (VWFA) in the left ventral occipitotemporal cortex. These representations are assumed to be invariant to visual characteristics such as font and case. In the present functional MRI study, we tested this assumption by presenting written words and varying the case format of the initial letter of German nouns (which are always capitalized) as well as German adjectives and adverbs (both usually in lowercase). As evident from a Word Type × Case Format interaction, activation in the VWFA was greater to words presented in unfamiliar case formats relative to familiar case formats. Our results suggest that neural representations of written words in the VWFA are not fully abstract and still contain information about the visual format in which words are most frequently perceived

Distribution of Response Time, Cortical, and Cardiac Correlates during Emotional Interference in Persons with Subclinical Psychotic Symptoms

A psychosis phenotype can be observed below the threshold of clinical detection. The study aimed to investigate whether subclinical psychotic symptoms are associated with deficits in controlling emotional interference, and whether cortical brain and cardiac correlates of these deficits can be detected using functional near-infrared spectroscopy (fNIRS). A data set derived from a community sample was obtained from the Zurich Program for Sustainable Development of Mental Health Services. 174 subjects (mean age 29.67 ± 6.41, 91 females) were assigned to four groups ranging from low to high levels of subclinical psychotic symptoms (derived from the Symptom Checklist-90-R). Emotional interference was assessed using the emotional Stroop task comprising neutral, positive, and negative conditions. Statistical distributional methods based on delta plots [behavioral response time (RT) data] and quantile analysis (fNIRS data) were applied to evaluate the emotional interference effects. Results showed that both interference effects and disorder-specific (i.e., group-specific) effects could be detected, based on behavioral RTs, cortical hemodynamic signals (brain correlates), and heart rate variability (cardiac correlates). Subjects with high compared to low subclinical psychotic symptoms revealed significantly reduced amplitudes in dorsolateral prefrontal cortices (interference effect, p < 0.001) and middle temporal gyrus (disorder-specific group effect, p < 0.001), supported by behavioral and heart rate results. The present findings indicate that distributional analyses methods can support the detection of emotional interference effects in the emotional Stroop. The results suggested that subjects with high subclinical psychosis exhibit enhanced emotional interference effects. Based on these observations, subclinical psychosis may therefore prove to represent a valid extension of the clinical psychosis phenotype

A learning perspective on individual differences in skilled reading: Exploring and exploiting orthographic and semantic discrimination cues

The goal of the present study is to understand the role orthographic and semantic information play in the behaviour of skilled readers. Reading latencies from a self-paced sentence reading experiment in which Russian near-synonymous verbs were manipulated appear well-predicted by a combination of bottom-up sub-lexical letter triplets (trigraphs) and top-down semantic generalizations, modelled using the Naive Discrimination Learner. The results reveal a complex interplay of bottom-up and top-down support from orthography and semantics to the target verbs, whereby activations from orthography only are modulated by individual differences. Using performance on a serial reaction time task for a novel operationalization of the mental speed hypothesis, we explain the observed individual differences in reading behaviour in terms of the exploration/exploitation hypothesis from Reinforcement Learning, where initially slower and more variable behaviour leads to better performance overall

Dynamic nodes, edges, and subnetworks in brain connectivity

Dept. of Medical Science/석사Recent brain research has been expedited by the network brain theory and neuroimaging methods for constructing whole-brain structural and functional brain networks. Functional brain networks are constructed based on the synchronous fMRI signal fluctuations among brain regions during resting state. Numerous studies have utilized functional brain network analysis to characterize individuals, to understand diseases and to test effects of treatments. All these applications of resting state functional brain networks were based on the assumption that functional brain networks are sufficiently stationary enough to describe a relatively long-lasting brain state. However, recent studies have shown dynamic natures of resting state brain networks within a relatively short time period. Thus, this study investigates dynamicity of network nodes, edges, and subnetworks of the whole brain using repeatedly measured fMRI data. We particularly focused on the hypothesis that integration among subregions of each node is highly dynamic, i.e., dynamic heterogeneity among voxels within a node. We also hypothesized that brain regions for highly dynamic membership for whole brain modules (high entropy) may correspond to hub regions. To test this hypothesis, we used resting state fMRI data from 12 healthy subjects measured at eight sessions during a 24-hour period. To evaluate the dynamicity of nodes, edges and other network properties, we used intra-class correlation (ICC). We found that highly stable node strength, node efficiency and clustering coefficient (ICC>0.5) at the bilateral superior parietal gyri, right precuneus, left hippocampus, and lateral inferior parietal lobule. We also found high entropy at bilateral parahippocampal gyri, bilateral hippocampus, and bilateral superior frontal gyri. These regions overlap with rich-club brain areas in previous studies. When we measured principal component analysis of each ROI time series, highly heterogeneous integration within ROI were found especially higher order brain regions. Furthermore, we examined the temporal consistency of effective connectivity of brain network submodules by looking at correlation between eight sessions. The higher order frontal area showed more dynamicity than lower sensory areas such as primary visual and auditory cortices. All these results reveal dynamic natures of the brain even during a 24-hour period. These dynamicity is not only node properties, edge strengths but also within node heterogeneous integrations, membership complexities and effective connectivities.ope

Psychological Science / Visual experience shapes orthographic representations in the visual word form area

Current neurocognitive research suggests that the efficiency of visual word recognition rests on abstract memory representations of written letters and words stored in the visual word form area (VWFA) in the left ventral occipitotemporal cortex. These representations are assumed to be invariant to visual characteristics such as font and case. In the present functional MRI study, we tested this assumption by presenting written words and varying the case format of the initial letter of German nouns (which are always capitalized) as well as German adjectives and adverbs (both usually in lowercase). As evident from a Word Type Case Format interaction, activation in the VWFA was greater to words presented in unfamiliar case formats relative to familiar case formats. Our results suggest that neural representations of written words in the VWFA are not fully abstract and still contain information about the visual format in which words are most frequently perceived.(VLID)238996

Functional neuroanatomy of reading in Czech: Evidence of a dual-route processing architecture in a shallow orthography

IntroductionAccording to the strong version of the orthographic depth hypothesis, in languages with transparent letter-sound mappings (shallow orthographies) the reading of both familiar words and unfamiliar nonwords may be accomplished by a sublexical pathway that relies on serial grapheme-to-phoneme conversion. However, in languages such as English characterized by inconsistent letter-sound relationships (deep orthographies), word reading is mediated by a lexical-semantic pathway that relies on mappings between word-specific orthographic, semantic, and phonological representations, whereas the sublexical pathway is used primarily to read nonwords.MethodsIn this study, we used functional magnetic resonance imaging to elucidate neural substrates of reading in Czech, a language characterized by a shallo worthography. Specifically, we contrasted patterns of brain activation and connectivity during word and nonword reading to determine whether similar or different neural mechanisms are involved. Neural correlates were measured as differences in simple whole-brain voxel-wise activation, and differences in visual word form area (VWFA) task-related connectivity were computed on the group level from data of 24 young subject. Trial-to-trial reading reaction times were used as a measure of task difficulty, and these effects were subtracted from the activation and connectivity effects in order to eliminate difference in cognitive effort which is naturally higher for nonwords and may mask the true lexicality effects.ResultsWe observed pattern of activity well described in the literature mostly derived from data of English speakers – nonword reading (as compared to word reading) activated the sublexical pathway to a greater extent whereas word reading was associated with greater activation of semantic networks. VWFA connectivity analysis also revealed stronger connectivity to a component of the sublexical pathway - left inferior frontal gyrus (IFG), for nonword compared to word reading.DiscussionThese converging results suggest that the brain mechanism of skilled reading in shallow orthography languages are similar to those engaged when reading in languages with a deep orthography and are supported by a universal dual-pathway neural architecture

Structural Brain Connectivity Constrains within-a-Day Variability of Direct Functional Connectivity

The idea that structural white matter connectivity constrains functional connectivity (interactions among brain regions) has widely been explored in studies of brain networks; studies have mostly focused on the "average" strength of functional connectivity. The question of how structural connectivity constrains the "variability" of functional connectivity remains unresolved. In this study, we investigated the variability of resting state functional connectivity that was acquired every 3 h within a single day from 12 participants (eight time sessions within a 24-h period, 165 scans per session). Three different types of functional connectivity (functional connectivity based on Pearson correlation, direct functional connectivity based on partial correlation, and the pseudo functional connectivity produced by their difference) were estimated from resting state functional magnetic resonance imaging data along with structural connectivity defined using fiber tractography of diffusion tensor imaging. Those types of functional connectivity were evaluated with regard to properties of structural connectivity (fiber streamline counts and lengths) and types of structural connectivity such as intra-/inter-hemispheric edges and topological edge types in the rich club organization. We observed that the structural connectivity constrained the variability of direct functional connectivity more than pseudo-functional connectivity and that the constraints depended strongly on structural connectivity types. The structural constraints were greater for intra-hemispheric and heterologous inter-hemispheric edges than homologous inter-hemispheric edges, and feeder and local edges than rich club edges in the rich club architecture. While each edge was highly variable, the multivariate patterns of edge involvement, especially the direct functional connectivity patterns among the rich club brain regions, showed low variability over time. This study suggests that structural connectivity not only constrains the strength of functional connectivity, but also the within-a-day variability of functional connectivity and connectivity patterns, particularly the direct functional connectivity among brain regions.ope

Graph-theoretical analysis for energy landscape reveals the organization of state transitions in the resting-state human cerebral cortex

The resting-state brain is often considered a nonlinear dynamic system transitioning among multiple coexisting stable states. Despite the increasing number of studies on the multistability of the brain system, the processes of state transitions have rarely been systematically explored. Thus, we investigated the state transition processes of the human cerebral cortex system at rest by introducing a graph-theoretical analysis of the state transition network. The energy landscape analysis of brain state occurrences, estimated using the pairwise maximum entropy model for resting-state fMRI data, identified multiple local minima, some of which mediate multi-step transitions toward the global minimum. The state transition among local minima is clustered into two groups according to state transition rates and most inter-group state transitions were mediated by a hub transition state. The distance to the hub transition state determined the path length of the inter-group transition. The cortical system appeared to have redundancy in inter-group transitions when the hub transition state was removed. Such a hub-like organization of transition processes disappeared when the connectivity of the cortical system was altered from the resting-state configuration. In the state transition, the default mode network acts as a transition hub, while coactivation of the prefrontal cortex and default mode network is captured as the global minimum. In summary, the resting-state cerebral cortex has a well-organized architecture of state transitions among stable states, when evaluated by a graph-theoretical analysis of the nonlinear state transition network of the brain.ope

Individual Differences in the Neural and Cognitive Mechanisms of Single Word Reading

Written language is a human invention that our brains did not evolve for. Yet, most research has focused on finding a single theory of reading, identifying the common set of cognitive and neural processes shared across individuals, neglecting individual differences. In contrast, we investigated variation in single word reading. Using a novel statistical method for analyzing heterogeneity in multi-subject task-based functional magnetic resonance imaging (fMRI), we clustered readers based on their brain’s response to written stimuli. Separate behavioral testing and neuroimaging analysis shows that these clusters differed in the role of the sublexical pathway in processing written language, but not in reading skill. Taken together, these results suggest that individuals vary in the cognitive and neural mechanisms involved in word reading. In general, neurocognitive theories need to account not only for what tends to be true of the population, but also the types of variation that exist, even within a neurotypical population