Individuals learn to read by gradually recognizing repeated letter combinations. However, it is unclear how or when neural mechanisms associated with repetition of basic stimuli (i.e., strings of letters) shift to involvement of higher-order language networks. The present study investigated this question by repeatedly presenting unfamiliar letter strings in a one-back matching task during an hour-long period. Activation patterns indicated that only brain areas associated with visual processing were activated during the early period, but additional regions that are usually associated with semantic and phonological processing in inferior frontal gyrus were recruited after stimuli became more familiar. Changes in activation were also observed in bilateral superior temporal cortex, also suggestive of a shift toward a more language-based processing strategy. Connectivity analyses reveal two distinct networks that correspond to phonological and visual processing, which may reflect the indirect and direct routes of reading. The phonological route maintained a similar degree of connectivity throughout the experiment, whereas visual areas increased connectivity with language areas as stimuli became more familiar, suggesting early recruitment of the direct route. This study provides insight about plasticity of the brain as individuals become familiar with unfamiliar combinations of letters (i.e., words in a new language, new acronyms) and has implications for engaging these linguistic networks during development of language remediation therapies.

Working memory impairments are frequent in Attention Deficit/Hyperactivity Disorder (ADHD) and create problems along numerous functional dimensions. The present study utilized the Visual Serial Addition Task (VSAT) and functional magnetic resonance imaging (fMRI) to explore working memory processes in thirteen typically developing (TD) control and thirteen children with ADHD, Combined type. Analysis of Variance (ANOVA) was used to examine both main effects and interactions. Working memory-specific activity was found in TD children in the bilateral prefrontal cortex. In contrast the within-group map in ADHD did not reveal any working-memory specific regions. Main effects of condition suggested that the right middle frontal gyrus (BA6) and the right precuneus were engaged by both groups during working memory processing. Group differences were driven by significantly greater, non-working memory-specific, activation in the ADHD relative to TD group in the bilateral insula extending into basal ganglia and the medial prefrontal cortex. A region of interest analysis revealed a region in left middle frontal gyrus that was more active during working memory in TD controls. Thus, only the TD group appeared to display working memory-modulated brain activation. In conclusion, children with ADHD demonstrated reduced working memory task specific brain activation in comparison to their peers. These data suggest inefficiency in functional recruitment by individuals with ADHD represented by a poor match between task demands and appropriate levels of brain activity.

Relational learning, which is learning the relationship among items, is impaired in schizophrenia but can be improved with training. This study investigated neural changes with functional magnetic resonance imaging before and after training on a relational learning task in schizophrenia and healthy control subjects. Despite their acquiring similar relational learning performance, the groups exhibited different neural activation patterns before and following training. Controls engaged regions within the relational learning network that included frontal, parietal, and medial temporal lobe, before and following training. Controls also exhibited activation reductions in region and spatial extent with relational learning proficiency, a commonly observed phenomenon in successful learning. In contrast, subjects with schizophrenia displayed no positive activations compared with the control condition before training. After training, subjects with schizophrenia displayed bilateral inferior parietal region activation as predicted. Contrary to hypothesis, hippocampal activation was not observed following training in schizophrenia. These findings suggest that the parietal lobe may be receptive to cognitive training interventions and that successful relational learning may be achieved in schizophrenia through the use of alternative extrahippocampal brain regions.

Patients with phonologic alexia can be trained to read semantically impoverished words (e.g., functors) by pairing them with phonologically-related semantically rich words (e.g, nouns). What mechanisms underlie success in this cognitive re-training approach? Does the mechanism change if the skill is “overlearned”, i.e., practiced beyond criterion? We utilized fMRI pre- and post-treatment, and after overlearning, to assess treatment-related functional reorganization in a patient with phonologic alexia, two years post left temporoparietal stroke. Pre-treatment, there were no statistically significant differences in activation profiles across the sets of words. Post-treatment, accuracy on the two trained sets improved. Compared with untrained words, reading trained words recruited larger and more significant clusters of activation in the right hemisphere, including right inferior frontal and inferior parietal cortex. Post-overlearning, with near normal performance on overlearned words, predominant activation shifted to left hemisphere regions, including perilesional activation in superior parietal lobe, when reading overlearned vs. untrained words.

Imaging studies show that in normal language correlated activity between anterior and posterior brain regions increases as the linguistic and semantic content (i.e., from false fonts, letter strings, pseudo words, to words) of stimuli increase. In schizophrenia however, disrupted functional connectivity between frontal and posterior brain regions has been frequently reported and these disruptions may change the nature of language organization. We characterized basic linguistic operations in word and letter string processing in a region-of-interest network using structural equation modeling (SEM). Healthy volunteers and volunteers with schizophrenia performed an fMRI one-back matching task with real words and consonant letter strings. We hypothesized that left hemisphere network dysfunction in schizophrenia would be present during processes dealing with linguistic/semantic content. The modeling results suggest aberrant left hemisphere function in schizophrenia, even in tasks requiring minimal access to language. Alternative mechanisms included increases in right hemisphere involvement and increased top-down influence from frontal to posterior regions.

Although progress has been made in relating neuronal events to changes in brain metabolism and blood flow, the interpretation of functional neuroimaging data in terms of the underlying brain circuits is still poorly understood. Computational modeling of connection patterns both among and within regions can be helpful in this interpretation. We present a neural network model of the ventral visual pathway and its relevant functional connections. This includes a new learning method that adjusts the magnitude of interregional connections in order to match experimental results of an arbitrary functional magnetic resonance imaging (fMRI) data set. We demonstrate that this method finds the appropriate connection strengths when trained on a model system with known, randomly chosen connection weights. We then use the method for examining fMRI results from a one-back matching task in human subjects, both healthy and those with schizophrenia. The results discovered by the learning method support previous findings of a disconnection between left temporal and frontal cortices in the group with schizophrenia, and a concomitant increase of right-sided temporo-frontal connection strengths. We then demonstrate that the disconnection may be explained by reduced local recurrent circuitry in frontal cortex. This method extends currently available methods for estimating functional connectivity from human imaging data by including both local circuits and features of inter-regional connections, such as topography and sparseness, in addition to total connection strengths. Furthermore, our results suggest how fronto-temporal functional disconnection in schizophrenia can result from reduced local synaptic connections within frontal cortex rather than compromised inter-regional connections.