Intan Technologies' integrated circuits (ICs) are valuable tools for neurophysiological data acquisition, providing signal amplification, filtering, and digitization from many channels (up to 64 channels/chip) at high sampling rates (up to 30 kSPS) within a compact package (⩽9× 7 mm). However, we found that the analog-to-digital converters (ADCs) in the Intan RHD2000 series ICs can produce artifacts in recorded signals. Here, we examine the effects of these ADC artifacts on neural signal quality and describe a method to detect them in recorded data.We identified two types of ADC artifacts produced by Intan ICs: 1) jumps, resulting from missing output codes, and 2) flatlines, resulting from overrepresented output codes. We identified ADC artifacts in neural recordings acquired with Intan RHD2000 ICs and tested the repeated performance of 17 ICs. With the on-chip digital-signal-processing disabled, we detected the ADC artifacts in each test recording by examining the distribution of unfiltered ADC output codes.We found larger ADC artifacts in recordings using the Intan RHX data acquisition software versions 3.0-3.2, which did not run the necessary ADC calibration command when the inputs to the Intan recording controller were rescanned. This has been corrected in the Intan RHX software version 3.3. We found that the ADC calibration routine significantly reduced, but did not fully eliminate, the occurrence and size of ADC artifacts as compared with recordings acquired when the calibration routine was not run (< 0.0001). When the ADC calibration routine was run, we found that the artifacts produced by each ADC were consistent over time, enabling us to sort ICs by performance.Our findings call attention to the importance of evaluating signal quality when acquiring electrophysiological data using Intan Technologies ICs and offer a method for detecting ADC artifacts in recorded data.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11316496PMC
http://dx.doi.org/10.1088/1741-2552/ad5762DOI Listing

Publication Analysis

Top Keywords

adc artifacts
28
adc
12
adc calibration
12
calibration routine
12
artifacts
10
intan
9
intan technologies
8
integrated circuits
8
neural signal
8
data acquisition
8

Similar Publications

Comparison of DWI techniques in patients with epidermoid cyst: TGSE-BLADE DWI vs. SS-EPI DWI.

Jpn J Radiol

December 2024

Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawaharacho, Kyoto, 6068507, Japan.

Purpose: To compare quantitative values and image quality between single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) and two-dimensional turbo gradient- and spin-echo DWI with non-Cartesian BLADE trajectory (TGSE-BLADE DWI) in patients with epidermoid cyst.

Methods: Patients with epidermoid cyst who underwent both SS-EPI DWI and TGSE-BLADE DWI were included in this study. Two raters placed ROIs encircling the entire epidermoid cyst on SS-EPI DWI, and then on TGSE-BLADE DWI.

View Article and Find Full Text PDF

Objectives: Implementation of diffusion-weighted imaging (DWI) for abdominal imaging in children has challenges due to motion artifacts exacerbated by long acquisition times. We aimed to compare acquisition time and image quality between conventional DWI and multi-band (MB) DWI of the liver in children and young adults.

Methods: Clinical MRI exams from May 2023 to January 2024 were reviewed, including four DWI sequences: respiratory-triggered (RTr, clinical standard), free-breathing (FB), MB-DWI with shift factor 1 (MBsf1), and MB-DWI with shift factor 2 (MBsf2).

View Article and Find Full Text PDF

Perfusion Showdown: Comparison of Multiple MRI Perfusion Techniques in the Grading of Pediatric Brain Tumors.

AJNR Am J Neuroradiol

December 2024

From the Department of Diagnostic Medicine, Dell Medical School at The University of Texas at Austin, Austin, TX, USA (C.Y.H.), Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA (N.S., G.A., Q.W., P.C., M.A., J.G.P., B.R.G., P.R.T., G.D.H.), Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA (E.C., P.R.T., S.A.P.), Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA (P.R.T., S.A.P.), and the Department of Radiology at Texas Children's Hospital, Houston, TX, USA (S.F.K.).

Background And Purpose: There are multiple MRI perfusion techniques, with limited available literature comparing these techniques in the grading of pediatric brain tumors. For efficiency and limiting scan time, ideally only one MRI perfusion technique can be used in initial imaging. We compared DSC, DCE, and IVIM along with ADC from DWI for differentiating high versus low grade pediatric brain tumors.

View Article and Find Full Text PDF
Article Synopsis
  • This study compares turbo spin echo with intravoxel incoherent motion (TSE-IVIM) to traditional echo-planar imaging (EPI-IVIM) in detecting nasopharyngeal carcinoma (NPC), aiming to identify optimal imaging strategies.
  • TSE-IVIM showed superior qualitative assessments, such as reduced susceptibility artifacts and better image quality in depicting anatomical structures related to NPC compared to EPI-IVIM.
  • Both subjective and quantitative measures highlighted TSE-IVIM's advantages, suggesting it could improve pre-treatment staging MR examinations for NPC patients.
View Article and Find Full Text PDF

Introduction: This study investigated the feasibility of single breath-hold (BH) diffusion-weighted MR imaging (DWI) using deep learning reconstruction (DLR) compared to navigator triggered (NT) DWI in patients with malignant liver tumors.

Methods: This study included 91 patients who underwent both BH-DWI and NT-DWI with 3T MR system. Abdominal MR images were subjectively analyzed to compare visualization of liver edges, presence of ghosting artifacts, conspicuity of malignant liver tumors, and overall image quality.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!