Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study.

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

Multivariate linear mixture models for the prediction of febrile seizure risk and recurrence: a prospective case-control study.

Our goal was to identify highly accurate empirical models for the prediction of the risk of febrile seizure (FS) and FS recurrence. In a prospective, three-arm, case-control study, we enrolled 162 children (age 25.8 ± 17.1 months old, 71 females). Participants formed one case group (patients with FS) and two control groups (febrile patients without seizures and healthy controls). The impact of blood iron status, peak body temperature, and participants' demographics on FS risk and recurrence was investigated with univariate and multivariate statistics. Serum iron concentration, iron saturation, and unsaturated iron-binding capacity differed between the three investigated groups (pFWE < 0.05). These serum analytes were key variables in the design of novel multivariate linear mixture models. The models classified FS risk with higher accuracy than univariate approaches. The designed bi-linear classifier achieved a sensitivity/specificity of 82%/89% and was closest to the gold-standard classifier. A multivariate model assessing FS recurrence provided a difference (pFWE < 0.05) with a separating sensitivity/specificity of 72%/69%. Iron deficiency, height percentile, and age were significant FS risk factors. In addition, height percentile and hemoglobin concentration were linked to FS recurrence. Novel multivariate models utilizing blood iron status and demographic variables predicted FS risk and recurrence among infants and young children with fever.

Heart rate and age modulate retinal pulsatile patterns.

Theoretical models of retinal hemodynamics showed the modulation of retinal pulsatile patterns (RPPs) by heart rate (HR), yet in-vivo validation and scientific merit of this biological process is lacking. Such evidence is critical for result interpretation, study design, and (patho-)physiological modeling of human biology spanning applications in various medical specialties. In retinal hemodynamic video-recordings, we characterize the morphology of RPPs and assess the impact of modulation by HR or other variables. Principal component analysis isolated two RPPs, i.e., spontaneous venous pulsation (SVP) and optic cup pulsation (OCP). Heart rate modulated SVP and OCP morphology (pFDR < 0.05); age modulated SVP morphology (pFDR < 0.05). In addition, age and HR demonstrated the effect on between-group differences. This knowledge greatly affects future study designs, analyses of between-group differences in RPPs, and biophysical models investigating relationships between RPPs, intracranial, intraocular pressures, and cardiovascular physiology.

Tralesinidase Alfa Enzyme Replacement Therapy Prevents Disease Manifestations in a Canine Model of Mucopolysaccharidosis Type IIIB.

Mucopolysaccharidosis type IIIB (MPS IIIB; Sanfilippo syndrome B; OMIM #252920) is a lethal, pediatric, neuropathic, autosomal recessive, and lysosomal storage disease with no approved therapy. Patients are deficient in the activity of N-acetyl-alpha-glucosaminidase (NAGLU; EC 3.2.150), necessary for normal lysosomal degradation of the glycosaminoglycan heparan sulfate (HS). Tralesinidase alfa (TA), a fusion protein comprised of recombinant human NAGLU and a modified human insulin-like growth factor 2, is in development as an enzyme replacement therapy that is administered via intracerebroventricular (ICV) infusion, thus circumventing the blood brain barrier. Previous studies have confirmed ICV infusion results in widespread distribution of TA throughout the brains of mice and nonhuman primates. We assessed the long-term tolerability, pharmacology, and clinical efficacy of TA in a canine model of MPS IIIB over a 20-month study. Long-term administration of TA was well tolerated as compared with administration of vehicle. TA was widely distributed across brain regions, which was confirmed in a follow-up 8-week pharmacokinetic/pharmacodynamic study. MPS IIIB dogs treated for up to 20 months had near-normal levels of HS and nonreducing ends of HS in cerebrospinal fluid and central nervous system (CNS) tissues. TA-treated MPS IIIB dogs performed better on cognitive tests and had improved CNS pathology and decreased cerebellar volume loss relative to vehicle-treated MPS IIIB dogs. These findings demonstrate the ability of TA to prevent or limit the biochemical, pathologic, and cognitive manifestations of canine MPS IIIB disease, thus providing support of its potential long-term tolerability and efficacy in MPS IIIB subjects. SIGNIFICANCE STATEMENT: This work illustrates the efficacy and tolerability of tralesinidase alfa as a potential therapeutic for patients with mucopolysaccharidosis type IIIB (MPS IIIB) by documenting that administration to the central nervous system of MPS IIIB dogs prevents the accumulation of disease-associated glycosaminoglycans in lysosomes, hepatomegaly, cerebellar atrophy, and cognitive decline.

Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter.

PURPOSE: Spinal cord gray-matter imaging is valuable for a number of applications, but remains challenging. The purpose of this work was to compare various MRI protocols at 1.5 T, 3 T, and 7 T for visualizing the gray matter. METHODS: In vivo data of the cervical spinal cord were collected from nine different imaging centers. Data processing consisted of automatically segmenting the spinal cord and its gray matter and co-registering back-to-back scans. We computed the SNR using two methods (SNR_single using a single scan and SNR_diff using the difference between back-to-back scans) and the white/gray matter contrast-to-noise ratio per unit time. Synthetic phantom data were generated to evaluate the metrics performance. Experienced radiologists qualitatively scored the images. We ran the same processing on an open-access multicenter data set of the spinal cord MRI (N = 267 participants). RESULTS: Qualitative assessments indicated comparable image quality for 3T and 7T scans. Spatial resolution was higher at higher field strength, and image quality at 1.5 T was found to be moderate to low. The proposed quantitative metrics were found to be robust to underlying changes to the SNR and contrast; however, the SNR_single method lacked accuracy when there were excessive partial-volume effects. CONCLUSION: We propose quality assessment criteria and metrics for gray-matter visualization and apply them to different protocols. The proposed criteria and metrics, the analyzed protocols, and our open-source code can serve as a benchmark for future optimization of spinal cord gray-matter imaging protocols.

Diffusion magnetic resonance imaging reveals tract-specific microstructural correlates of electrophysiological impairments in non-myelopathic and myelopathic spinal cord compression.

BACKGROUND AND PURPOSE: Non-myelopathic degenerative cervical spinal cord compression (NMDC) frequently occurs throughout aging and may progress to potentially irreversible degenerative cervical myelopathy (DCM). Whereas standard clinical magnetic resonance imaging (MRI) and electrophysiological measures assess compression severity and neurological dysfunction, respectively, underlying microstructural deficits still have to be established in NMDC and DCM patients. The study aims to establish tract-specific diffusion MRI markers of electrophysiological deficits to predict the progression of asymptomatic NMDC to symptomatic DCM. METHODS: High-resolution 3 T diffusion MRI was acquired for 103 NMDC and 21 DCM patients compared to 60 healthy controls to reveal diffusion alterations and relationships between tract-specific diffusion metrics and corresponding electrophysiological measures and compression severity. Relationship between the degree of DCM disability, assessed by the modified Japanese Orthopaedic Association scale, and tract-specific microstructural changes in DCM patients was also explored. RESULTS: The study identified diffusion-derived abnormalities in the gray matter, dorsal and lateral tracts congruent with trans-synaptic degeneration and demyelination in chronic degenerative spinal cord compression with more profound alterations in DCM than NMDC. Diffusion metrics were affected in the C3-6 area as well as above the compression level at C3 with more profound rostral deficits in DCM than NMDC. Alterations in lateral motor and dorsal sensory tracts correlated with motor and sensory evoked potentials, respectively, whereas electromyography outcomes corresponded with gray matter microstructure. DCM disability corresponded with microstructure alteration in lateral columns. CONCLUSIONS: Outcomes imply the necessity of high-resolution tract-specific diffusion MRI for monitoring degenerative spinal pathology in longitudinal studies.

Blind Visualization of Task-Related Networks From Visual Oddball Simultaneous EEG-fMRI Data: Spectral or Spatiospectral Model?

Various disease conditions can alter EEG event-related responses and fMRI-BOLD signals. We hypothesized that event-related responses and their clinical alterations are imprinted in the EEG spectral domain as event-related (spatio)spectral patterns (ERSPat). We tested four EEG-fMRI fusion models utilizing EEG power spectra fluctuations (i.e., absolute spectral model - ASM; relative spectral model - RSM; absolute spatiospectral model - ASSM; and relative spatiospectral model - RSSM) for fully automated and blind visualization of task-related neural networks. Two (spatio)spectral patterns (high δ 4 band and low ß 1 band) demonstrated significant negative linear relationship (p FWE < 0.05) to the frequent stimulus and three patterns (two low δ 2 and δ 3 bands, and narrow θ 1 band) demonstrated significant positive relationship (p < 0.05) to the target stimulus. These patterns were identified as ERSPats. EEG-fMRI F-map of each δ 4 model showed strong engagement of insula, cuneus, precuneus, basal ganglia, sensory-motor, motor and dorsal part of fronto-parietal control (FPCN) networks with fast HRF peak and noticeable trough. ASM and RSSM emphasized spatial statistics, and the relative power amplified the relationship to the frequent stimulus. For the δ 4 model, we detected a reduced HRF peak amplitude and a magnified HRF trough amplitude in the frontal part of the FPCN, default mode network (DMN) and in the frontal white matter. The frequent-related ß 1 patterns visualized less significant and distinct suprathreshold spatial associations. Each θ 1 model showed strong involvement of lateralized left-sided sensory-motor and motor networks with simultaneous basal ganglia co-activations and reduced HRF peak and amplified HRF trough in the frontal part of the FPCN and DMN. The ASM θ 1 model preserved target-related EEG-fMRI associations in the dorsal part of the FPCN. For δ 4, ß 1, and θ 1 bands, all models provided high local F-statistics in expected regions. The most robust EEG-fMRI associations were observed for ASM and RSSM.

Blind Source Separation of Retinal Pulsatile Patterns in Optic Nerve Head Video-Recordings.

Dynamic optical imaging of retinal hemodynamics is a rapidly evolving technique in vision and eye-disease research. Video-recording, which may be readily accessible and affordable, captures several distinct functional phenomena such as the spontaneous venous pulsations (SVP) of central vein or local arterial blood supply etc. These phenomena display specific dynamic patterns that have been detected using manual or semi-automated methods. We propose a pioneering concept in retina video-imaging using blind source separation (BSS) serving as an automated localizer of distinct areas with temporally synchronized hemodynamics. The feasibility of BSS techniques (such as spatial principal component analysis and spatial independent component analysis) and K-means based post-processing method were successfully tested on the monocular and binocular video-ophthalmoscopic (VO) recordings of optic nerve head (ONH) in healthy subjects. BSSs automatically detected three spatially distinct reproducible areas, i.e. SVP, optic cup pulsations (OCP) that included areas of larger vessels in the nasal part of ONH, and "other" pulsations (OP). The K-means post-processing reduced a spike noise from the patterns' dynamics while high linear dependence between the non-filtered and post-processed signals was preserved. Although the dynamics of all patterns were heart rate related, the morphology analysis demonstrated significant phase shifts between SVP and OCP, and between SVP and OP. In addition, we detected low frequency oscillations that may represent respiratory-induced effects in time-courses of the VO recordings.

HARDI-ZOOMit protocol improves specificity to microstructural changes in presymptomatic myelopathy.

Diffusion magnetic resonance imaging (dMRI) proved promising in patients with non-myelopathic degenerative cervical cord compression (NMDCCC), i.e., without clinically manifested myelopathy. Aim of the study is to present a fast multi-shell HARDI-ZOOMit dMRI protocol and validate its usability to detect microstructural myelopathy in NMDCCC patients. In 7 young healthy volunteers, 13 age-comparable healthy controls, 18 patients with mild NMDCCC and 15 patients with severe NMDCCC, the protocol provided higher signal-to-noise ratio, enhanced visualization of white/gray matter structures in microstructural maps, improved dMRI metric reproducibility, preserved sensitivity (SE = 87.88%) and increased specificity (SP = 92.31%) of control-patient group differences when compared to DTI-RESOLVE protocol (SE = 87.88%, SP = 76.92%). Of the 56 tested microstructural parameters, HARDI-ZOOMit yielded significant patient-control differences in 19 parameters, whereas in DTI-RESOLVE data, differences were observed in 10 parameters, with mostly lower robustness. Novel marker the white-gray matter diffusivity gradient demonstrated the highest separation. HARDI-ZOOMit protocol detected larger number of crossing fibers (5-15% of voxels) with physiologically plausible orientations than DTI-RESOLVE protocol (0-8% of voxels). Crossings were detected in areas of dorsal horns and anterior white commissure. HARDI-ZOOMit protocol proved to be a sensitive and practical tool for clinical quantitative spinal cord imaging.

Spinal cord atrophy as a measure of severity of myelopathy in adrenoleukodystrophy.

All men and most women with X-linked adrenoleukodystrophy (ALD) develop myelopathy in adulthood. As clinical trials with new potential disease-modifying therapies are emerging, sensitive outcome measures for quantifying myelopathy are needed. This prospective cohort study evaluated spinal cord size (cross-sectional area - CSA) and shape (eccentricity) as potential new quantitative outcome measures for myelopathy in ALD. Seventy-four baseline magnetic resonance imaging (MRI) scans, acquired in 42 male ALD patients and 32 age-matched healthy controls, and 26 follow-up scans of ALD patients were included in the study. We used routine T1 -weighted MRI sequences to measure mean CSA, eccentricity, right-left and anteroposterior diameters in the cervical spinal cord. We compared MRI measurements between groups and correlated CSA with clinical outcome measures of disease severity. Longitudinally, we compared MRI measurements between baseline and 1-year follow-up. CSA was significantly smaller in patients compared to controls on all measured spinal cord levels (P < .001). The difference was completely explained by the effect of the symptomatic subgroup. Furthermore, the spinal cord showed flattening (higher eccentricity and smaller anteroposterior diameters) in patients. CSA correlated strongly with all clinical measures of severity of myelopathy. There was no detectable change in CSA after 1-year follow-up. The cervical spinal cord in symptomatic ALD patients is smaller and flattened compared to controls, possibly due to atrophy of the dorsal columns. CSA is a reliable marker of disease severity and can be a valuable outcome measure in long-term follow-up studies in ALD. SYNOPSIS: A prospective cohort study in 42 adrenoleukodystrophy (ALD) patients and 32 controls demonstrated that the spinal cord cross-sectional area of patients is smaller compared to healthy controls and correlates with severity of myelopathy in patients, hence it could be valuable as a much needed surrogate outcome measure.

Differential Effects of Sustained Manual Pressure Stimulation According to Site of Action.

Sustained pressure stimulation of the body surface has been used in several physiotherapeutic techniques, such as reflex locomotion therapy. Clinical observations of global motor responses and subsequent motor behavioral changes after stimulation in certain sites suggest modulation of central sensorimotor control, however, the neuroanatomical correlates remain undescribed. We hypothesized that different body sites would specifically influence the sensorimotor system during the stimulation. We tested the hypothesis using functional magnetic resonance imaging (fMRI) in thirty healthy volunteers (mean age 24.2) scanned twice during intermittent manual pressure stimulation, once at the right lateral heel according to reflex locomotion therapy, and once at the right lateral ankle (control site). A flexible modeling approach with finite impulse response basis functions was employed since non-canonical hemodynamic response was expected. Subsequently, a clustering algorithm was used to separate areas with differential timecourses. Stimulation at both sites induced responses throughout the sensorimotor system that could be mostly separated into two anti-correlated subsystems with transient positive or negative signal change and rapid adaptation, although in heel stimulation, insulo-opercular cortices and pons showed sustained activation. In direct voxel-wise comparison, heel stimulation was associated with significantly higher activation levels in the contralateral primary motor cortex and decreased activation in the posterior parietal cortex. Thus, we demonstrate that the manual pressure stimulation affects multiple brain structures involved in motor control and the choice of stimulation site impacts the shape and amplitude of the blood oxygenation level-dependent response. We further discuss the relationship between the affected structures and behavioral changes after reflex locomotion therapy.

EEG spatiospectral patterns and their link to fMRI BOLD signal via variable hemodynamic response functions.

BACKGROUND: Spatial and temporal resolution of brain network activity can be improved by combining different modalities. Functional Magnetic Resonance Imaging (fMRI) provides full brain coverage with limited temporal resolution, while electroencephalography (EEG), estimates cortical activity with high temporal resolution. Combining them may provide improved network characterization. NEW METHOD: We examined relationships between EEG spatiospectral pattern timecourses and concurrent fMRI BOLD signals using canonical hemodynamic response function (HRF) with its 1st and 2nd temporal derivatives in voxel-wise general linear models (GLM). HRF shapes were derived from EEG-fMRI time courses during "resting-state", visual oddball and semantic decision paradigms. RESULTS: The resulting GLM F-maps self-organized into several different large-scale brain networks (LSBNs) often with different timing between EEG and fMRI revealed through differences in GLM-derived HRF shapes (e.g., with a lower time to peak than the canonical HRF). We demonstrate that some EEG spatiospectral patterns (related to concurrent fMRI) are weakly task-modulated. COMPARISON WITH EXISTING METHOD(S): Previously, we demonstrated 14 independent EEG spatiospectral patterns within this EEG dataset, stable across the resting-state, visual oddball and semantic decision paradigms. Here, we demonstrate that their time courses are significantly correlated with fMRI dynamics organized into LSBN structures. EEG-fMRI derived HRF peak appears earlier than the canonical HRF peak, which suggests limitations when assuming a canonical HRF shape in EEG-fMRI. CONCLUSIONS: This is the first study examining EEG-fMRI relationships among independent EEG spatiospectral patterns over different paradigms. The findings highlight the importance of considering different HRF shapes when spatiotemporally characterizing brain networks using EEG and fMRI.

In-vivo cortical thickness estimation from high-resolution T1w MRI scans in healthy and mucopolysaccharidosis affected dogs.

Cortical thickness measurement estimated from high-resolution anatomical MRI scans may serve as a marker of cortical atrophy in clinical research applications. Most of the working algorithms and pipelines are optimized for human in-vivo data analyses that offer robust and reproducible measures. As animal-models are widely utilized in many preclinical phases of clinical trials the need for an optimized automated MRI data analysis to yield reliable data is warranted. We present a processing pipeline optimized for cortical thickness estimation of canine brains in native and template spaces. Preliminary results of 5 healthy and 5 mucopolysaccharidosis (MPS) dogs demonstrate single-canine mean/median cortical thickness in range of 2.69-3.58mm in native space and 3.26-4.15mm in template space. Our MRI generated values exceed previous histological measurements (observed mean about 2mm) in limited literature reports. Randomly selected manual measures corroborated the ranges defined by estimated cortical thickness probability density functions. Geometric transformations between native and template spaces change absolute mean/median cortical thickness values, but do not change the data nature and properties since the Pearson correlation coefficients between different space estimates were 0.84 for mean values and 0.89 for median values. No significant difference in total cortical thickness between MPS and age-and gender-matched dogs was observed.

Blind Source Separation of Different Retinal Pulsatile Patterns from Simultaneous Long-term Binocular Ophthalmoscopic Video-records.

Optical imaging of retinal hemodynamic function is an important part of ophthalmologic research. Development and inventing of imaging devices and data analysis methods are both just in progress. The current study innovatively implements two blind source separation (BSS) techniques (i.e. spatial Principal Component Analysis - sPCA; and spatial Independent Component Analysis - sICA) in application of an automatic detection and segmentation of a distinct Optic Disc (OD) areas with different hemodynamic properties from a simultaneous binocular video-ophthalmoscopic records. Both methods detected 3 different spatial patterns mostly symmetric over both eyes stable and reproducible over investigated participants, i.e. central Spontaneous Vessel Pulsations (SVPs), inner OD intensity pulsations and other OD pulsations. Dynamics of all mentioned patterns has a periodic character with similar main frequency (possibly corresponding to subject-specific heart rate) but shifted phase decreasing patterns' mutual high cross-correlations. The sICA estimates a higher rate of phase shifts than sPCA.

Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.

Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

Multiway Array Decomposition of EEG Spectrum: Implications of Its Stability for the Exploration of Large-Scale Brain Networks.

Multiway array decomposition methods have been shown to be promising statistical tools for identifying neural activity in the EEG spectrum. They blindly decompose the EEG spectrum into spatial-temporal-spectral patterns by taking into account inherent relationships among signals acquired at different frequencies and sensors. Our study evaluates the stability of spatial-temporal-spectral patterns derived by one particular method, parallel factor analysis (PARAFAC). We focused on patterns' stability over time and in population and divided the complete data set containing data from 50 healthy subjects into several subsets. Our results suggest that the patterns are highly stable in time, as well as among different subgroups of subjects. Further, we show with simultaneously acquired fMRI data that power fluctuations of some patterns have stable correspondence to hemodynamic fluctuations in large-scale brain networks. We did not find such correspondence for power fluctuations in standard frequency bands, the common way of dealing with EEG data. Altogether, our results suggest that PARAFAC is a suitable method for research in the field of large-scale brain networks and their manifestation in EEG signal.

Exploring task-related variability in fMRI data using fluctuations in power spectrum of simultaneously acquired EEG.

BACKGROUND: The paper deals with joint analysis of fMRI and scalp EEG data, simultaneously acquired during event-related oddball experiment. The analysis is based on deriving temporal sequences of EEG powers in individual frequency bands for the selected EEG electrodes and using them as regressors in the general linear model (GLM). NEW METHOD: Given the infrequent use of EEG spectral changes to explore task-related variability, we focused on the aspects of parameter setting during EEG regressor calculation and searched for such parameters that can detect task-related variability in EEG-fMRI data. We proposed a novel method that uses relative EEG power in GLM. RESULTS: Parameter, the type of power value, has a direct impact as to whether task-related variability is detected or not. For relative power, the final results are sensitive to the choice of frequency band of interest. The electrode selection also has certain impact; however, the impact is not crucial. It is insensitive to the choice of EEG power series temporal weighting step. Relative EEG power characterizes the experimental task activity better than the absolute power. Absolute EEG power contains broad spectrum component. Task-related relative power spectral formulas were derived. COMPARISON WITH EXISTING METHODS: For particular set of parameters, our results are consistent with previously published papers. Our work expands current knowledge by new findings in spectral patterns of different brain processes related to the experimental task. CONCLUSIONS: To make analysis to be sensitive to task-related variability, the parameters type of power value and frequency band should be set properly.