Assessment of assumptions underlying models of prokaryotic pangenome evolution.

BACKGROUND: The genomes of bacteria and archaea evolve by extensive loss and gain of genes which, for any group of related prokaryotic genomes, result in the formation of a pangenome with the universal, asymmetrical U-shaped distribution of gene commonality. However, the evolutionary factors that define the specific shape of this distribution are not thoroughly understood. RESULTS: We investigate the fit of simple models of genome evolution to the empirically observed gene commonality distributions and genome intersections for 33 groups of closely related bacterial genomes. A model with an infinite external gene pool available for gene acquisition and constant genome size (IGP-CGS model), and two gene turnover rates, one for slow- and the other one for fast-evolving genes, allows two approaches to estimate the parameters for gene content dynamics. One is by fitting the model prediction to the distribution of the number of genes shared by precisely k genomes (gene commonality distribution) and another by analyzing the distribution of the number of genes common for k genome sets (k-cores). Both approaches produce a comparable overall quality of fit, although the former significantly overestimates the number of the universally conserved genes, while the latter overestimates the number of singletons. We further explore the effect of dropping each of the assumptions of the IGP-CGS model on the fit to the gene commonality distributions and show that models with either a finite gene pool or unequal rates of gene loss and gain (greater gene loss rate) eliminate the overestimate of the number of singletons or the core genome size. CONCLUSIONS: We examine the assumptions that are usually adopted for modeling the evolution of the U-shaped gene commonality distributions in prokaryote genomes, namely, those of infinitely many genes and constant genome size. The combined analysis of genome intersections and gene commonality suggests that at least one of these assumptions is invalid. The violation of both these assumptions reflects the limited ability of prokaryotes to gain new genes. This limitation seems to stem, at least partly, from the horizontal gene transfer barrier, i.e., the cost of accommodation of foreign genes by prokaryotes. Further development of models taking into account the complexity of microbial evolution is necessary for an improved understanding of the evolution of prokaryotes.

Multiple Sequence Alignment Averaging Improves Phylogeny Reconstruction.

The classic methodology of inferring a phylogenetic tree from sequence data is composed of two steps. First, a multiple sequence alignment (MSA) is computed. Then, a tree is reconstructed assuming the MSA is correct. Yet, inferred MSAs were shown to be inaccurate and alignment errors reduce tree inference accuracy. It was previously proposed that filtering unreliable alignment regions can increase the accuracy of tree inference. However, it was also demonstrated that the benefit of this filtering is often obscured by the resulting loss of phylogenetic signal. In this work we explore an approach, in which instead of relying on a single MSA, we generate a large set of alternative MSAs and concatenate them into a single SuperMSA. By doing so, we account for phylogenetic signals contained in columns that are not present in the single MSA computed by alignment algorithms. Using simulations, we demonstrate that this approach results, on average, in more accurate trees compared to 1) using an unfiltered MSA and 2) using a single MSA with weights assigned to columns according to their reliability. Next, we explore in which regions of the MSA space our approach is expected to be beneficial. Finally, we provide a simple criterion for deciding whether or not the extra effort of computing a SuperMSA and inferring a tree from it is beneficial. Based on these assessments, we expect our methodology to be useful for many cases in which diverged sequences are analyzed. The option to generate such a SuperMSA is available at http://guidance.tau.ac.il.

Crossing fitness valleys via double substitutions within codons.

BACKGROUND: Single nucleotide substitutions in protein-coding genes can be divided into synonymous (S), with little fitness effect, and non-synonymous (N) ones that alter amino acids and thus generally have a greater effect. Most of the N substitutions are affected by purifying selection that eliminates them from evolving populations. However, additional mutations of nearby bases potentially could alleviate the deleterious effect of single substitutions, making them subject to positive selection. To elucidate the effects of selection on double substitutions in all codons, it is critical to differentiate selection from mutational biases. RESULTS: We addressed the evolutionary regimes of within-codon double substitutions in 37 groups of closely related prokaryotic genomes from diverse phyla by comparing the fractions of double substitutions within codons to those of the equivalent double S substitutions in adjacent codons. Under the assumption that substitutions occur one at a time, all within-codon double substitutions can be represented as "ancestral-intermediate-final" sequences (where "intermediate" refers to the first single substitution and "final" refers to the second substitution) and can be partitioned into four classes: (1) SS, S intermediate-S final; (2) SN, S intermediate-N final; (3) NS, N intermediate-S final; and (4) NN, N intermediate-N final. We found that the selective pressure on the second substitution markedly differs among these classes of double substitutions. Analogous to single S (synonymous) substitutions, SS double substitutions evolve neutrally, whereas analogous to single N (non-synonymous) substitutions, SN double substitutions are subject to purifying selection. In contrast, NS show positive selection on the second step because the original amino acid is recovered. The NN double substitutions are heterogeneous and can be subject to either purifying or positive selection, or evolve neutrally, depending on the amino acid similarity between the final or intermediate and the ancestral states. CONCLUSIONS: The results of the present, comprehensive analysis of the evolutionary landscape of within-codon double substitutions reaffirm the largely conservative regime of protein evolution. However, the second step of a double substitution can be subject to positive selection when the first step is deleterious. Such positive selection can result in frequent crossing of valleys on the fitness landscape.

Theory of prokaryotic genome evolution.

Bacteria and archaea typically possess small genomes that are tightly packed with protein-coding genes. The compactness of prokaryotic genomes is commonly perceived as evidence of adaptive genome streamlining caused by strong purifying selection in large microbial populations. In such populations, even the small cost incurred by nonfunctional DNA because of extra energy and time expenditure is thought to be sufficient for this extra genetic material to be eliminated by selection. However, contrary to the predictions of this model, there exists a consistent, positive correlation between the strength of selection at the protein sequence level, measured as the ratio of nonsynonymous to synonymous substitution rates, and microbial genome size. Here, by fitting the genome size distributions in multiple groups of prokaryotes to predictions of mathematical models of population evolution, we show that only models in which acquisition of additional genes is, on average, slightly beneficial yield a good fit to genomic data. These results suggest that the number of genes in prokaryotic genomes reflects the equilibrium between the benefit of additional genes that diminishes as the genome grows and deletion bias (i.e., the rate of deletion of genetic material being slightly greater than the rate of acquisition). Thus, new genes acquired by microbial genomes, on average, appear to be adaptive. The tight spacing of protein-coding genes likely results from a combination of the deletion bias and purifying selection that efficiently eliminates nonfunctional, noncoding sequences.

GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters.

Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il.

Neck motion kinematics: an inter-tester reliability study using an interactive neck VR assessment in asymptomatic individuals.

BACKGROUND AND PURPOSE: The use of virtual reality (VR) for assessment and intervention of neck pain has previously been used and shown reliable for cervical range of motion measures. Neck VR enables analysis of task-oriented neck movement by stimulating responsive movements to external stimuli. Therefore, the purpose of this study was to establish inter-tester reliability of neck kinematic measures so that it can be used as a reliable assessment and treatment tool between clinicians. METHODS: This reliability study included 46 asymptomatic participants, who were assessed using the neck VR system which displayed an interactive VR scenario via a head-mounted device, controlled by neck movements. The objective of the interactive assessment was to hit 16 targets, randomly appearing in four directions, as fast as possible. Each participant was tested twice by two different testers. RESULTS: Good reliability was found of neck motion kinematic measures in flexion, extension, and rotation (0.64-0.93 inter-class correlation). High reliability was shown for peak velocity globally (0.93), in left rotation (0.9), right rotation and extension (0.88), and flexion (0.86). Mean velocity had a good global reliability (0.84), except for left rotation directed movement with moderate reliability (0.68). Minimal detectable change for peak velocity ranged from 41 to 53 °/s, while mean velocity ranged from 20 to 25 °/s. CONCLUSIONS: The results suggest high reliability for peak and mean velocity as measured by the interactive Neck VR assessment of neck motion kinematics. VR appears to provide a reliable and more ecologically valid method of cervical motion evaluation than previous conventional methodologies.

Impact of PROphet Test in Changing Physicians' Therapeutic Decision-Making for Checkpoint Immunotherapy in Non-Small-Cell Lung Cancer.

PURPOSE: Immune Checkpoint Inhibitor (ICI) regimens are approved for first-line treatment of metastatic nononcogene-driven NSCLC. Guidelines do not differentiate which patients with PD-L1 ≥ 50% should receive ICI monotherapy. The clinically validated PROphet NSCLC plasma proteomic-based test is designed to inform this therapeutic decision. METHODS: One hundred oncologists were presented with 3 "virtual" metastatic NSCLC cases with PD-L1 scores and asked to recommend an approved first-line regimen. They then watched an online educational webinar on the PROphetNSCLC test. Postwebinar, the same cases were represented with the addition of a PROphet result, and oncologists again recommended a first-line regimen. Responses were compared to assess the impact on first-line treatment selection. RESULTS: Treatment recommendation changed in 39.6% of PROphet-tested cases, with 93% of physicians changing at least 1 case. In the PD-L1 ≥ 50% group, 89% of physicians changed their recommendation, followed by 77%, in PD-L1 < 1%, and 36% in PD-L1 1% to 49%. ​In the PD-L1 ≥ 50%, PROphet POSITIVE group, the recommendation for ICI monotherapy increased from 60% to 89%. ​For the PD-L1 ≥ 50%, PROphet NEGATIVE group, the recommendation for monotherapy dropped from 60% to 9%. In the PD-L1 < 1%, PROphet NEGATIVE group, 35% of patients were spared toxicity from ICI compared to 11% in PROphet untested cases. CONCLUSION: Adding PROphet to PD-L1 expression impacted therapeutic decision making in first-line NSCLC. PROphet identifies those predicted to have an overall survival benefit from ICI monotherapy versus combination versus chemotherapy, improving the probability of efficacy and reducing toxicity for some patients.

Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy.

Introduction: Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance. Methods: Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes. Results: The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage. Conclusions: Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.

Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer.

PURPOSE: Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. PATIENTS AND METHODS: We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247) of patients undergoing PD-1/PD-L1 inhibitor-based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. RESULTS: Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor-based treatments, evidenced by high concordance between predicted and observed CB (R2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). CONCLUSION: Plasma proteome-based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor-based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood. METHODS: We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group. RESULTS: We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins. CONCLUSIONS: Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

DNA sequence correlations shape nonspecific transcription factor-DNA binding affinity.

Transcription factors (TFs) are regulatory proteins that bind DNA in promoter regions of the genome and either promote or repress gene expression. Here, we predict analytically that enhanced homooligonucleotide sequence correlations, such as poly(dA:dT) and poly(dC:dG) tracts, statistically enhance nonspecific TF-DNA binding affinity. This prediction is generic and qualitatively independent of microscopic parameters of the model. We show that nonspecific TF binding affinity is universally controlled by the strength and symmetry of DNA sequence correlations. We perform correlation analysis of the yeast genome and show that DNA regions highly occupied by TFs exhibit stronger homooligonucleotide sequence correlations, and thus a higher propensity for nonspecific binding, than do poorly occupied regions. We suggest that this effect plays the role of an effective localization potential that enhances quasi-one-dimensional diffusion of TFs in the vicinity of DNA, speeding up the stochastic search process for specific TF binding sites. The effect is also predicted to impose an upper bound on the size of TF-DNA binding motifs.

Nonspecific transcription-factor-DNA binding influences nucleosome occupancy in yeast.

Quantitative understanding of the principles regulating nucleosome occupancy on a genome-wide level is a central issue in eukaryotic genomics. Here, we address this question using budding yeast, Saccharomyces cerevisiae, as a model organism. We perform a genome-wide computational analysis of the nonspecific transcription factor (TF)-DNA binding free-energy landscape and compare this landscape with experimentally determined nucleosome-binding preferences. We show that DNA regions with enhanced nonspecific TF-DNA binding are statistically significantly depleted of nucleosomes. We suggest therefore that the competition between TFs with histones for nonspecific binding to genomic sequences might be an important mechanism influencing nucleosome-binding preferences in vivo. We also predict that poly(dA:dT) and poly(dC:dG) tracts represent genomic elements with the strongest propensity for nonspecific TF-DNA binding, thus allowing TFs to outcompete nucleosomes at these elements. Our results suggest that nonspecific TF-DNA binding might provide a barrier for statistical positioning of nucleosomes throughout the yeast genome. We predict that the strength of this barrier increases with the concentration of DNA binding proteins in a cell. We discuss the connection of the proposed mechanism with the recently discovered pathway of active nucleosome reconstitution.

Gene gain and loss push prokaryotes beyond the homologous recombination barrier and accelerate genome sequence divergence.

Bacterial and archaeal evolution involve extensive gene gain and loss. Thus, phylogenetic trees of prokaryotes can be constructed both by traditional sequence-based methods (gene trees) and by comparison of gene compositions (genome trees). Comparing the branch lengths in gene and genome trees with identical topologies for 34 clusters of closely related bacterial and archaeal genomes, we show here that terminal branches of gene trees are systematically compressed compared to those of genome trees. Thus, sequence evolution is delayed compared to genome evolution by gene gain and loss. The extent of this delay differs widely among bacteria and archaea. Mathematical modeling shows that the divergence delay can result from sequence homogenization by homologous recombination. The model explains how homologous recombination maintains the cohesiveness of the core genome of a species while allowing extensive gene gain and loss within the accessory genome. Once evolving genomes become isolated by barriers impeding homologous recombination, gene and genome evolution processes settle into parallel trajectories, and genomes diverge, resulting in speciation.

Estimation of universal and taxon-specific parameters of prokaryotic genome evolution.

The results of our recent study on mathematical modeling of microbial genome evolution indicate that, on average, genomes of bacteria and archaea evolve in the regime of mutation-selection balance defined by positive selection coefficients associated with gene acquisition that is counter-acted by the intrinsic deletion bias. This analysis was based on the strong assumption that parameters of genome evolution are universal across the diversity of bacteria and archaea, and yielded extremely low values of the selection coefficient. Here we further refine the modeling approach by taking into account evolutionary factors specific for individual groups of microbes using two independent fitting strategies, an ad hoc hard fitting scheme and a mixture model. The resulting estimate of the mean selection coefficient of s∼10-10 associated with the gain of one gene implies that, on average, acquisition of a gene is beneficial, and that microbial genomes typically evolve under a weak selection regime that might transition to strong selection in highly abundant organisms with large effective population sizes. The apparent selective pressure towards larger genomes is balanced by the deletion bias, which is estimated to be consistently greater than unity for all analyzed groups of microbes. The estimated values of s are more realistic than the lower values obtained previously, indicating that global and group-specific evolutionary factors synergistically affect microbial genome evolution that seems to be driven primarily by adaptation to existence in diverse niches.

Balance maintenance as an acquired motor skill: Delayed gains and robust retention after a single session of training in a virtual environment.

Does the learning of a balance and stability skill exhibit time-course phases and transfer limitations characteristic of the acquisition and consolidation of voluntary movement sequences? Here we followed the performance of young adults trained in maintaining balance while standing on a moving platform synchronized with a virtual reality road travel scene. The training protocol included eight 3 min long iterations of the road scene. Center of Pressure (CoP) displacements were analyzed for each task iteration within the training session, as well as during tests at 24h, 4 weeks and 12 weeks post-training to test for consolidation phase ("offline") gains and assess retention. In addition, CoP displacements in reaction to external perturbations were assessed before and after the training session and in the 3 subsequent post-training assessments (stability tests). There were significant reductions in CoP displacements as experience accumulated within session, with performance stabilizing by the end of the session. However, CoP displacements were further reduced at 24h post-training (delayed "offline" gains) and these gains were robustly retained. There was no transfer of the practice-related gains to performance in the stability tests. The time-course of learning the balance maintenance task, as well as the limitation on generalizing the gains to untrained conditions, are in line with the results of studies of manual movement skill learning. The current results support the conjecture that a similar repertoire of basic neuronal mechanisms of plasticity may underlay skill (procedural, "how to" knowledge) acquisition and skill memory consolidation in voluntary and balance maintenance tasks.

Visual and auditory synchronization deficits among dyslexic readers as compared to non-impaired readers: a cross-correlation algorithm analysis.

Visual and auditory temporal processing and crossmodal integration are crucial factors in the word decoding process. The speed of processing (SOP) gap (Asynchrony) between these two modalities, which has been suggested as related to the dyslexia phenomenon, is the focus of the current study. Nineteen dyslexic and 17 non-impaired University adult readers were given stimuli in a reaction time (RT) procedure where participants were asked to identify whether the stimulus type was only visual, only auditory or crossmodally integrated. Accuracy, RT, and Event Related Potential (ERP) measures were obtained for each of the three conditions. An algorithm to measure the contribution of the temporal SOP of each modality to the crossmodal integration in each group of participants was developed. Results obtained using this model for the analysis of the current study data, indicated that in the crossmodal integration condition the presence of the auditory modality at the pre-response time frame (between 170 and 240 ms after stimulus presentation), increased processing speed in the visual modality among the non-impaired readers, but not in the dyslexic group. The differences between the temporal SOP of the modalities among the dyslexics and the non-impaired readers give additional support to the theory that an asynchrony between the visual and auditory modalities is a cause of dyslexia.

A functional near-infrared spectroscopy study of lexical decision task supports the dual route model and the phonological deficit theory of dyslexia.

The dual route model (DRM) of reading suggests two routes of reading development: the phonological and the orthographic routes. It was proposed that although the two routes are active in the process of reading; the first is more involved at the initial stages of reading acquisition, whereas the latter needs more reading training to mature. A number of studies have shown that deficient phonological processing is a core deficit in developmental dyslexia. According to the DRM, when the Lexical Decision Task (LDT) is performed, the orthographic route should also be involved when decoding words, whereas it is clear that when decoding pseudowords the phonological route should be activated. Previous functional near-infrared spectroscopy (fNIR) studies have suggested that the upper left frontal lobe is involved in decision making in the LDT. The current study used fNIR to compare left frontal lobe activity during LDT performance among three reading-level groups: 12-year-old children, young adult dyslexic readers, and young adult typical readers. Compared to typical readers, the children demonstrated lower activity under the word condition only, whereas the dyslexic readers showed lower activity under the pseudoword condition only. The results provide evidence for upper left frontal lobe involvement in LDT and support the DRM and the phonological deficit theory of dyslexia.

Enhanced reading by training with imposed time constraint in typical and dyslexic adults.

Poor reading skills of developmental dyslexics persist into adulthood with standard remediation protocols having little effect. Nevertheless, reading improves if readers are induced to read faster. Here we show that this improvement can be enhanced by training. Training follows a multi-session procedure adapted to silent sentence reading, with individually set, increasingly more demanding, time constraints (letter-by-letter masking). In both typical and dyslexic adult readers, reading times are shortened and comprehension improves. After training, the dyslexic readers' performance is similar to that of typical readers; moreover, their connected text reading times and comprehension scores significantly improve in standard reading tests and are retained at 6 months post training. Identical training without time constraints proves ineffective. Our results suggest that fluent reading depends in part on rapid information processing, which then might affect perception, cognitive processing and possibly eye movements. These processes remain malleable in adulthood, even in individuals with developmental dyslexia.

Differences in learning volitional (manual) and non-volitional (posture) aspects of a complex motor skill in young adult dyslexic and skilled readers.

The 'Cerebellar Deficit Theory' of developmental dyslexia proposes that a subtle developmental cerebellar dysfunction leads to deficits in attaining 'automatic' procedures and therefore manifests as subtle motor impairments (e.g., balance control, motor skill learning) in addition to the reading and phonological difficulties. A more recent version of the theory suggests a core deficit in motor skill acquisition. This study was undertaken to compare the time-course and the nature of practice-related changes in volitional (manual) and non-volitional (posture) motor performance in dyslexic and typical readers while learning a new movement sequence. Seventeen dyslexic and 26 skilled young adult readers underwent a three-session training program in which they practiced a novel sequence of manual movements while standing in a quiet stance position. Both groups exhibited robust and well-retained gains in speed, with no loss of accuracy, on the volitional, manual, aspects of the task, with a time-course characteristic of procedural learning. However, the dyslexic readers exhibited a pervasive slowness in the initiation of volitional performance. In addition, while typical readers showed clear and well-retained task-related adaptation of the balance and posture control system, the dyslexic readers had significantly larger sway and variance of sway throughout the three sessions and were less efficient in adapting the posture control system to support the acquisition of the novel movement sequence. These results support the notion of a non-language-related deficit in developmental dyslexia, one related to the recruitment of motor systems for effective task performance rather than to a general motor learning disability.

A working memory deficit among dyslexic readers with no phonological impairment as measured using the n-back task: an fNIR study.

Data indicated that dyslexic individuals exhibited difficulties on tasks involving Working Memory (WM). Previous studies have suggested that these deficits stem from impaired processing in the Phonological Loop (PL). The PL impairment was connected to poor phonological processing. However, recent data has pointed to the Central Executive (CE) system as another source of WM deficit in dyslexic readers. This opened a debate whether the WM deficit stems solely from PL or can also be seen as an outcome of poor CE processing. In an attempt to verify this question, the current study compared adult skilled and compensated dyslexic readers with no impairment of phonological skills. The participants' PL and CE processing were tested by using the fNIR device attached to the frontal lobe and measured the changes in brain oxygen values when performing N-back task. As it was previously suggested, the N = 0 represented PL and N = 1 to 3 represent CE processing. It was hypothesized that dyslexic readers who show non-impaired phonological skills will exhibit deficits mainly in the CE subsystem and to a lesser extent in the PL. Results indicated that the two reading level groups did not differ in their accuracy and reaction times in any of the N-Back conditions. However, the dyslexic readers demonstrated significant lower maximum oxyHb values in the upper left frontal lobe, mainly caused due to a significant lower activity under the N = 1 condition. Significant task effects were found in the medial left hemisphere, and the high medial right hemisphere. In addition, significant correlations between fNIR-features, reading performance and speed of processing were found. The higher oxyHb values, the better reading and speed of processing performance obtained. The results of the current study support the hypothesis that at least for the group of dyslexics with non-impaired PL, WM deficit stems from poor CE activity.