Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility

Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person’s brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model’s stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications

The ciliary protein cystin forms a regulatory complex with necdin to modulate Myc expression

Cystin is a novel cilia-associated protein that is disrupted in the cpk mouse, a well-characterized mouse model of autosomal recessive polycystic kidney disease (ARPKD). Interestingly, overexpression of the Myc gene is evident in animal models of ARPKD and is thought to contribute to the renal cystic phenotype. Using a yeast two-hybrid approach, the growth suppressor protein necdin, known to modulate Myc expression, was found as an interacting partner of cystin. Deletion mapping demonstrated that the C-terminus of cystin and both termini of necdin are required for their mutual interaction. Speculating that these two proteins may function to regulate gene expression, we developed a luciferase reporter assay and observed that necdin strongly activated the Myc P1 promoter, and cystin did so more modestly. Interestingly, the necdin effect was significantly abrogated when cystin was co-transfected. Chromatin immunoprecipitation and electrophoretic mobility shift assays revealed a physical interaction with both necdin and cystin and the Myc P1 promoter, as well as between these proteins. The data suggest that these proteins likely function in a regulatory complex. Thus, we speculate that Myc overexpression in the cpk kidney results from the dysregulation of the cystin-necdin regulatory complex and c-Myc, in turn, contributes to cystogenesis in the cpk mouse

Genetic and Informatic Analyses Implicate Kif12 as a Candidate Gene within the Mpkd2 Locus That Modulates Renal Cystic Disease Severity in the Cys1cpk Mouse.

We have previously mapped the interval on Chromosome 4 for a major polycystic kidney disease modifier (Mpkd) of the B6(Cg)-Cys1cpk/J mouse model of recessive polycystic kidney disease (PKD). Informatic analyses predicted that this interval contains at least three individual renal cystic disease severity-modulating loci (Mpkd1-3). In the current study, we provide further validation of these predicted effects using a congenic mouse line carrying the entire CAST/EiJ (CAST)-derived Mpkd1-3 interval on the C57BL/6J background. We have also generated a derivative congenic line with a refined CAST-derived Mpkd1-2 interval and demonstrated its dominantly-acting disease-modulating effects (e.g., 4.2-fold increase in total cyst area;

Magnetic resonance microscopy of renal and biliary abnormalities in excised tissues from a mouse model of autosomal recessive polycystic kidney disease.

Polycystic kidney disease (PKD) is transmitted as either an autosomal dominant or recessive trait and is a major cause of renal failure and liver fibrosis. The cpk mouse model of autosomal recessive PKD (ARPKD) has been extensively characterized using standard histopathological techniques after euthanasia. In the current study, we sought to validate magnetic resonance microscopy (MRM) as a robust tool for assessing the ARPKD phenotype. We used MRM to evaluate the liver and kidney of wild-type and cpk animals at resolutions \u3c100 \u3eμm and generated three-dimensional (3D) renderings for pathological evaluation. Our study demonstrates that MRM is an excellent method for evaluating the complex, 3D structural defects in this ARPKD mouse model. We found that MRM was equivalent to water displacement in assessing kidney volume. Additionally, using MRM we demonstrated for the first time that the cpk liver exhibits less extensive ductal arborization, that it was reduced in volume, and that the ductal volume was disproportionately smaller. Histopathology indicates that this is a consequence of bile duct malformation. With its reduced processing time, volumetric information, and 3D capabilities, MRM will be a useful tool for future in vivo and longitudinal studies of disease progression in ARPKD. In addition, MRM will provide a unique tool to determine whether the human disease shares the newly appreciated features of the murine biliary phenotype

Pkhd1

Autosomal-recessive polycystic kidney disease (ARPKD; MIM #263200) is a severe, hereditary, hepato-renal fibrocystic disorder that causes early childhood morbidity and mortality. Mutations in the polycystic kidney and hepatic disease 1 (PKHD1) gene, which encodes the protein fibrocystin/polyductin complex (FPC), cause all typical forms of ARPKD. Several mouse lines carrying diverse, genetically engineered disruptions in the orthologous Pkhd1 gene have been generated, but none expresses the classic ARPKD renal phenotype. In the current study, we characterized a spontaneous mouse Pkhd1 mutation that is transmitted as a recessive trait and causes cysticliver (cyli), similar to the hepato-biliary disease in ARPKD, but which is exacerbated by age, sex, and parity. We mapped the mutation to Chromosome 1 and determined that an insertion/deletion mutation causes a frameshift within Pkhd1 exon 48, which is predicted to result in a premature termination codon (UGA). Pkhd

Spontaneous Brain Activity in the Default Mode Network Is Sensitive to Different Resting-State Conditions with Limited Cognitive Load

BACKGROUND: Recent functional MRI (fMRI) studies have demonstrated that there is an intrinsically organized default mode network (DMN) in the resting brain, primarily made up of the posterior cingulate cortex (PCC) and the medial prefrontal cortex (MPFC). Several previous studies have found that the DMN is minimally disturbed during different resting-state conditions with limited cognitive demand. However, this conclusion was drawn from the visual inspection of the functional connectivity patterns within the DMN and no statistical comparison was performed. METHODOLOGY/PRINCIPAL FINDINGS: Four resting-state fMRI sessions were acquired: 1) eyes-closed (EC) (used to generate the DMN mask); 2) EC; 3) eyes-open with no fixation (EO); and 4) eyes-open with a fixation (EO-F). The 2-4 sessions were counterbalanced across participants (n = 20, 10 males). We examined the statistical differences in both functional connectivity and regional amplitude of low frequency fluctuation (ALFF) within the DMN among the 2-4 resting-state conditions (i.e., EC, EO, and EO-F). Although the connectivity patterns of the DMN were visually similar across these three different conditions, we observed significantly higher functional connectivity and ALFF in both the EO and the EO-F conditions as compared to the EC condition. In addition, the first and second resting EC conditions showed significant differences within the DMN, suggesting an order effect on the DMN activity. CONCLUSIONS/SIGNIFICANCE: Our findings of the higher DMN connectivity and regional spontaneous activities in the resting state with the eyes open suggest that the participants might have more non-specific or non-goal-directed visual information gathering and evaluation, and mind wandering or daydreaming during the resting state with the eyes open as compared to that with the eyes closed, thus providing insights into the understanding of unconstrained mental activity within the DMN. Our results also suggest that it should be cautious when choosing the type of a resting condition and designating the order of the resting condition in multiple scanning sessions in experimental design

Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans

The characterization of topological architecture of complex brain networks is one of the most challenging issues in neuroscience. Slow (<0.1 Hz), spontaneous fluctuations of the blood oxygen level dependent (BOLD) signal in functional magnetic resonance imaging are thought to be potentially important for the reflection of spontaneous neuronal activity. Many studies have shown that these fluctuations are highly coherent within anatomically or functionally linked areas of the brain. However, the underlying topological mechanisms responsible for these coherent intrinsic or spontaneous fluctuations are still poorly understood. Here, we apply modern network analysis techniques to investigate how spontaneous neuronal activities in the human brain derived from the resting-state BOLD signals are topologically organized at both the temporal and spatial scales. We first show that the spontaneous brain functional networks have an intrinsically cohesive modular structure in which the connections between regions are much denser within modules than between them. These identified modules are found to be closely associated with several well known functionally interconnected subsystems such as the somatosensory/motor, auditory, attention, visual, subcortical, and the “default” system. Specifically, we demonstrate that the module-specific topological features can not be captured by means of computing the corresponding global network parameters, suggesting a unique organization within each module. Finally, we identify several pivotal network connectors and paths (predominantly associated with the association and limbic/paralimbic cortex regions) that are vital for the global coordination of information flow over the whole network, and we find that their lesions (deletions) critically affect the stability and robustness of the brain functional system. Together, our results demonstrate the highly organized modular architecture and associated topological properties in the temporal and spatial brain functional networks of the human brain that underlie spontaneous neuronal dynamics, which provides important implications for our understanding of how intrinsically coherent spontaneous brain activity has evolved into an optimal neuronal architecture to support global computation and information integration in the absence of specific stimuli or behaviors

Resting-State Brain Activity in Adult Males Who Stutter

Although developmental stuttering has been extensively studied with structural and task-based functional magnetic resonance imaging (fMRI), few studies have focused on resting-state brain activity in this disorder. We investigated resting-state brain activity of stuttering subjects by analyzing the amplitude of low-frequency fluctuation (ALFF), region of interest (ROI)-based functional connectivity (FC) and independent component analysis (ICA)-based FC. Forty-four adult males with developmental stuttering and 46 age-matched fluent male controls were scanned using resting-state fMRI. ALFF, ROI-based FCs and ICA-based FCs were compared between male stuttering subjects and fluent controls in a voxel-wise manner. Compared with fluent controls, stuttering subjects showed increased ALFF in left brain areas related to speech motor and auditory functions and bilateral prefrontal cortices related to cognitive control. However, stuttering subjects showed decreased ALFF in the left posterior language reception area and bilateral non-speech motor areas. ROI-based FC analysis revealed decreased FC between the posterior language area involved in the perception and decoding of sensory information and anterior brain area involved in the initiation of speech motor function, as well as increased FC within anterior or posterior speech- and language-associated areas and between the prefrontal areas and default-mode network (DMN) in stuttering subjects. ICA showed that stuttering subjects had decreased FC in the DMN and increased FC in the sensorimotor network. Our findings support the concept that stuttering subjects have deficits in multiple functional systems (motor, language, auditory and DMN) and in the connections between them

Fingerprint Registration by Maximization of Mutual Information

Fingerprint registration is a critical step in fingerprint matching. Although a variety of registration alignment algorithms have been proposed, accurate fingerprint registration remains an unresolved problem. We propose a new algorithm for fingerprint registration using orientation field. This algorithm finds the correct alignment by maximization of mutual information between features extracted from orientation fields of template and input fingerprint images. Orientation field, representing the flow of ridges, is a relatively stable global feature of fingerprint images. This method uses the statistics and distribution of global feature of fingerprint images so that it is robust to image quality and local changes in images. The primary characteristic of this method is that it uses this stable global feature to align fingerprints, and that its behavior may resemble the way humans compare fingerprints. Experimental results show that the occurrence of misalignment is dramatically reduced and that registration accuracy is greatly improved at the same time, leading to enhanced matching performance

The ciliary protein cystin forms a regulatory complex with necdin to modulate Myc expression.

Cystin is a novel cilia-associated protein that is disrupted in the cpk mouse, a well-characterized mouse model of autosomal recessive polycystic kidney disease (ARPKD). Interestingly, overexpression of the Myc gene is evident in animal models of ARPKD and is thought to contribute to the renal cystic phenotype. Using a yeast two-hybrid approach, the growth suppressor protein necdin, known to modulate Myc expression, was found as an interacting partner of cystin. Deletion mapping demonstrated that the C-terminus of cystin and both termini of necdin are required for their mutual interaction. Speculating that these two proteins may function to regulate gene expression, we developed a luciferase reporter assay and observed that necdin strongly activated the Myc P1 promoter, and cystin did so more modestly. Interestingly, the necdin effect was significantly abrogated when cystin was co-transfected. Chromatin immunoprecipitation and electrophoretic mobility shift assays revealed a physical interaction with both necdin and cystin and the Myc P1 promoter, as well as between these proteins. The data suggest that these proteins likely function in a regulatory complex. Thus, we speculate that Myc overexpression in the cpk kidney results from the dysregulation of the cystin-necdin regulatory complex and c-Myc, in turn, contributes to cystogenesis in the cpk mouse