Overview
You can find information on our upcoming webinars here. We do try to record all of these events and make all recorded content available to our customers via the NIRx Help Center.
Please note: Some NIRx webinars are open to the public, others only to customers.
Upcoming Webinars
Photogrammetric fNIRS optode registration on the head with the Cedalion toolbox: A tutorial
Date & time: November 18th, 4pm Berlin time (1 hour)
Speakers: Dr. Alexander von Lühmann and Dr. Eike Middell, members of the independent research group “Intelligent Biomedical Sensing (IBS)” at BIFOLD, Machine Learning Dept, TU Berlin.
In contrast to EEG, thanks to the good spatial resolution of fNIRS, precise localization of optodes on the head can make a major difference in the outcome and repeatability of fNIRS studies. In recent years, several publications have shown the viability and benefit of using photogrammetry to determine optode placement quickly and precisely relative to landmarks on the head. At the Intelligent Biomedical Sensing (IBS) Lab we have implemented such a solution into our novel python-based toolbox “Cedalion”, which is available open source to the research community. In this workshop we will demonstrate the typical workflow to help users to adopt or reproduce our method.
Register now and don't miss the opportunity to attend this webinar!
Personalized EEG/fNIRS promoting fNIRS optimal probe design and advanced diffused optical tomography within NIRSTORM package: applications in sleep and epilepsy studies.
Date & time: November 27th, 4pm Berlin time (1h)
Speaker: Christophe Grova PhD, Professor in the Department of Physics of Concordia University and a research member of Concordia School of Health (PERFORM center)
This webinar introduces new fNIRS methods implemented in NIRSTORM, a Brainstorm plugin for fNIRS data analysis, enabling 3D visualizations and interactions with multi-channel signals. We will discuss our algorithm for optimal fNIRS montage, enhancing sensitivity to targeted brain regions, allowing dense montage for local 3D reconstructions. Examples include freely placed optodes or high-density cap positions. Additionally, we will cover advanced 3D reconstructions of hemoglobin changes on the cortical surface using Maximum Entropy on the Mean (MEM) to solve inverse problems, applied to EEG/fNIRS recordings in sleep and epilepsy studies.
Uncovering Hidden Consciousness in the ICU: The Role of fNIRS in Brain Injury Care
Date & time: December 3rd, 5pm Berlin time (45’)
Speaker: Dr. Karnig Kazazian completed his PhD at Western University under the supervision of Dr. Adrian Owen and Dr. Teneille Gofton. His research focuses on using advanced brain imaging techniques, such as functional MRI and fNIRS to improve the detection of consciousness and prediction of recovery for critically ill patients who are unresponsive after severe brain injury.
In the ICU, many patients with severe brain injury appear unresponsive, yet some may retain a level of consciousness that is challenging to assess through traditional bedside evaluations. fNIRS offers a transformative approach for detecting consciousness by identifying brain activity in unresponsive patients.
In this talk, I will discuss how recent advancements in fNIRS research demonstrate its ability to detect different levels of consciousness by examining key brain networks, sensorimotor and auditory processing, as well as responses to specific commands. We have observed that fNIRS can reveal preserved awareness, even in patients who lack visible behavioral signs of consciousness, which has profound clinical implications for diagnosis and patient management in critical care.
This session will also cover:
The practical applications of fNIRS in the ICU for consciousness assessment.
Clinical and ethical considerations in implementing fNIRS for patient care, especially in cases where hidden awareness may alter treatment decisions.
The potential for fNIRS to enhance our understanding of consciousness, offering a more individualized approach to care and a pathway for improving outcomes in patients with brain injuries.
By the end, we’ll explore how fNIRS can redefine our approach to diagnosing and supporting patients with severe brain injuries, ultimately transforming ICU care.
Don’t miss this opportunity. Register here!
Past Webinars
Spatio-temporal tomography of the brain: the DOT-EEG fusion algorithm and the new NIRFASTer
Speaker: Dr. Jiaming Cao, Research Fellow at University of Birmingham. His research mainly focuses on advancing algorithms for high-speed, high-accuracy diffuse optical tomography.
In the first part of the webinar, Dr. Cao talks about a novel algorithm that synthesizes simultaneously recorded DOT and EEG signals for high spatio-temporal resolution neuronal source reconstruction. He will discuss how the algorithm was designed, and how it was validated through a retinotopy experiment which evolved around a NIRx NIRSports2.
In the second part, he briefly introduce his current work in progress: an updated version of NIRFASTer, the commonly used photon forward modeling software, which is now Python-based, and even faster. A compact version is already available, and has been integrated into the Cedalion toolbox.
References: J. Cao, E. Bulger, B. Shinn-Cunningham, P. Grover, and J. M. Kainerstorfer. “Diffuse Optical Tomography Spatial Prior for EEG Source Localization in Human Visual Cortex”. In: NeuroImage (2023), p. 120210. DOI: 10. 1016/j.neuroimage.2023.120210.
Towards more inclusive fNIRS research: Developing best practices for scanning participants with afro-textured hair
Speakers: Abria Simmons, senior at the University of Maryland College Park, majoring in Psychology and minoring in Human Development and Gavkhar Abdurokhmonova, 3rd year PhD student in the Human Development program at the University of Maryland, College of Education.
For decades, Black individuals have been systematically excluded from neuroimaging research due to individual characteristics that can make scanning challenging, combined with lack of researcher knowledge of inclusive practices. Although fNIRS is well-suited for data collection in naturalistic contexts with movement-prone populations, it is, unfortunately, often less suitable when working with participants with afro-textured hair (i.e., coarse, coily) in an inclusive and respectful way. As an optical technology, fNIRS, requires an unobstructed path to the scalp which may be difficult with coarser, denser hair types and textures.
On this webinar, Abria Simmons and Gavkhar Abdurokhmonova from the University of Maryland are sharing with us some of the work they have been conducting at the Language, Experience, and Development (LEAD) lab to develop best practices for scanning Black participants with different types of hair and hairstyles. They are presenting their workflow to maximize the comfort of Black participants, demonstrate a variety of procedures (such as hair braiding) to optimize fNIRS sensor-scalp connection, and discuss future directions to increase representation in neuroscience on both methodological and relational sides.
E-Prime Extension for NIRx - Optimize E-Prime for NIRx fNIRS systems
Speakers: Franziska Keller, NIRx Scientific Consultant and Kimberly Barone & Gretchen Brauch from PST
In this webinar we’re showcasing the innovative "E-Prime Extension for NIRx," developed through a collaboration between PST and NIRx. This extension enhances the capabilities of E-Prime, integrating E-Prime experiment communication seamlessly with NIRx fNIRS systems.
You will discover the features and benefits of the E-Prime extension tailored for NIRx systems and watch a live demonstration of the extension in action, highlighting its practical applications.
Beyond the Lab: fNIRS Imaging from Classrooms to Rainforests
Invited speaker: Prof. Dan Dewey, serves as the Department Chair of Linguistics and directs the fNIRS Applied Linguistics Lab at Brigham Young University
In this presentation, we emphasize the expansive potential of fNIRS beyond the confines of the lab, sharing our experiences using fNIRS in naturalistic, relatively stable environments like classrooms and unpredictable settings like rainforests. Through examples, we highlight the strengths of fNIRS, including its portability, movement tolerance, non-invasiveness, relative ease of learning, and usability for hyperscanning well beyond dyads. We also explain how we have navigated challenges such as Wi-Fi interference, limited access to electricity, high temperatures, humidity, and the unfamiliarity of indigenous communities with scientific equipment and methods. We also discuss the unique strengths of fNIRS that make it especially suitable for our own on-site, ecologically valid, real-time data collection.
Simplifying machine learning for fNIRS: implementation and benchmarking with BenchNIRS
Invited speaker: Johann Benerradi, a researcher in neuroinformatics at the University of Cambridge, currently working on the Brain Imaging for Global Health (BRIGHT) Project. He obtained his PhD in Computer Science from the University of Nottingham. His research focuses on neuroimaging data analysis and machine learning for fNIRS, with applications ranging from the study of neurodevelopment to brain-computer interfaces.
While machine learning has become very popular for neuroimaging data, it remains non-trivial to use this set of techniques properly. It can indeed be challenging and time-consuming not only to implement machine learning models for fNIRS data classification, but also to evaluate such models in a way that reflects the performance on unseen data (generalisation capabilities). This is key however in order to estimate realistically the capabilities of real-world brain-computer interfaces for example.
In this webinar, our speaker introduces some of the challenges of machine learning with fNIRS data, and shows how the BenchNIRS Python framework can be used to simplify the implementation, fine-tuning and rigorous evaluation of machine learning models for fNIRS data classification. Furthermore, Johann presents a case study of how BenchNIRS was used to initiate the largest benchmarking of machine learning on existing open-access fNIRS datasets, comparing popular models on various tasks and paradigms.
Full paper: Benerradi, J., Clos, J., Landowska, A., Valstar, M. F., & Wilson, M. L. (2023). Benchmarking framework for machine learning classification from fNIRS data. Frontiers in Neuroergonomics, 4, 994969.
Demo link: https://colab.research.google.com/drive/1nRyrSipkDpkor-7qh8kCv8vCbpHLp6IN
Homepage of the project: https://hanbnrd.gitlab.io/benchnirs/
An assessment of baseline-corrected averaging, general linear model (GLM) and multivariate pattern analysis (MVPA) based approaches to analyse fNIRS infant data
Invited speaker: Dr. Maria Laura Filippetti, a developmental cognitive neuroscientist investigating the development of body representations. Her research combines behavioural and psychophysiological methods to study the role of multisensory integration in how infants learn about their bodies.
Dr. Filippetti is currently a Senior Lecturer (Associate Professor) in the Department of Psychology at the University of Essex, where she is also part of the Essex Babylab.
In this webinar, Dr Maria Laura Filippetti presented a registered report that employed both standard approaches and recent machine learning techniques to infant fNIRS data. Specifically, the webinar discussed the use of baseline-corrected averaging, General Linear Model (GLM)-based univariate, and Multivariate Pattern Analysis (MVPA) approaches to show how the conclusions one would draw based on these different analysis approaches converge or differ. The webinar presented fNIRS data from 30 4-to-6-month-old infants who were presented with a standard face inversion paradigm where changes in brain activation in response to upright and inverted face stimuli were measured. By including more standard approaches together with recent machine learning techniques, the webinar aimed to inform the fNIRS community on ways to analyse infant fNIRS datasets.
Link to the registered report: Filippetti, M. L., Andreu-Perez, J., de Klerk, C., Richmond, C., & Rigato, S. (2023). Are advanced methods necessary to improve infant fNIRS data analysis? An assessment of baseline-corrected averaging, general linear model (GLM) and multivariate pattern analysis (MVPA) based approaches. NeuroImage, 265, 119756.
Multi-modal Integration of Simultaneous fMRI and fNIRS Signals: From Protocol Development to Data Preprocessing
Invited speaker: Sara Sanchez-Alonso, Associate Research Scientist at the Child Study Center at Yale School of Medicine, US.
This webinar is providing an overview of the challenges and considerations when collecting fMRI and fNIRS data simultaneously including protocol development, experimental set up and implementation, data collection and analysis. Specifically, Dr. Sanchez-Alonso describes a protocol that allows for simultaneous data collection of fMRI and fNIRS signals and that: i) provides whole-head fNIRS coverage; ii) includes short-distance measurements for regression of the non-cortical, systemic physiological signal; and iii) implements two different methods for optode-to-scalp co-registration of fNIRS measurements. The webinar also considers how to adapt the fNIRS equipment for use in the magnetic resonance (MR) environment and provide recommendations for both data recording and optode-to-scalp co-registration. In turn, we discuss potential modifications of the protocol to fit the specifics of the available MR-safe fNIRS system. Finally, the webinar describes key steps in the analysis of fMRI and fNIRS data that have been simultaneously collected.
Modality Fusion: EEG-fNIRS Convergence for a Deeper Dive into Auditory Processing
Invited speaker: Dr. Yalda Shahriari, Associate Professor of Biomedical Engineering and the director of NeuralPC Lab at the University of Rhode Island, US.
Multimodal neuroimaging has demonstrated considerable promise in facilitating a more complete understanding of neural processes associated with many different motor, cognitive, and perceptual processes. In particular, EEG and fNIRS have proven to be particularly synergistic neuroimaging modalities due to their low cost, portability, and compatibility, allowing for the simultaneous recording of electro-cortical and hemodynamic responses to experimental tasks. One particular domain that has benefitted from simultaneous EEG-fNIRS recordings is the exploration of auditory processing, especially when considering the challenges involved in conducting such experiments using other systems intended to measure functional hemodynamic activity, namely fMRI, which is loud and often cost-prohibitive.
The results of the study shed light on the benefits of nonlinear interaction exploration between EEG and fNIRS in multimodal neuroimaging. Additionally, the research extends into the realm of multi-view methodologies for EEG signal categorization, with a focus on the potential of fNIRS for providing robust discriminatory features.
The study highlights the promise of integrating EEG and fNIRS to enhance the classification of neural responses during auditory tasks.
Two-Part Webinar with Dr. Pascal Vrticka
Dr. Pascal Vrticka is a social neuroscientist and Associate Professor in Psychology at the University of Essex (Colchester, UK), where he also is the PI of the Social Neuroscience of Human Attachment (SoNeAt) Lab. The SoNeAt Lab is pioneering a new area of research investigating the neurobiological basis of human attachment - the social neuroscience of human attachment (SoNeAt). This includes the description of the first functional neuroanatomical models of human attachment, both organised (i.e., secure, insecure-avoidant and insecure-anxious; NAMA) and disorganised (NAMDA). One current focus of SoNeAt Lab's research is devoted to bio-behavioural and particularly interpersonal neural synchrony (INS) acquired by means of functional near-infrared spectroscopy (fNIRS) hyperscanning. Together with many international collaborators and as part of the CARE studies, Dr. Vrticka has published several high-impact peer-reviewed papers on parent-child INS including both fathers and mothers, in addition to providing A Guide to Parent-Child fNIRS Hyperscanning Data Processing and Analysis comprising free sample data and code. A freely available introduction to fNIRS hyperscanning can furthermore be found on Dr Vrticka's website.
Part I - fNIRS Hyperscanning: Underlying Theory and Experimental Design
Part II - fNIRS Hyperscanning – Practical Considerations for Data Analysis
devfOLD: A Toolbox for Designing Age-Specific fNIRS Channel Placement
Invited speaker: Dr. Xiaoxue Fu, Assistant Professor in the Department of Psychology at the University of South Carolina (USC). She shared with us her study conducted together with John E. Richards on devfOLD toolbox.
NIRS enables researchers to track neurodevelopment from infancy to adulthood. Commercial NIRS instruments do not allow for whole-head coverage and do not intrinsically indicate which brain areas generate the NIRS signal. Hence, the challenge is to design source-detector channel arrangement that maximizes sensitivity to a given brain region of interest (ROI). Existing methods for optimizing channel placement design have been developed using adult head models. Thus, they have limited utility for developmental research. We aimed to build an application from an existing toolbox (“fOLD”) that guides NIRS channel configuration based on age group, stereotaxic atlas, and ROI (“devfOLD”). The talk will introduce devfOLD, a toolbox that provides NIRS channel-to-ROI specificity computed using photon propagation simulation with realistic head models from age 2 weeks to 30-34 years with narrow age intervals. The devfOLD toolbox is publicly shared (https://github.com/nirx/devfOLD). We found that there are between-age consistency as well as differences in the channel-to-ROI correspondence among the example infant and adult age groups. The toolbox provides data for probabilistic channel-to-ROI mapping across infant, child, and adult ages. Our study also highlights the importance of incorporating age-specific head models for optimizing NIRS channel configurations. The talk will also discuss considerations and methods for enhancing cortical localization of NIRS data in data collection.
Full paper: Fu, X., & Richards, J.E. (2021). devfOLD: A Toolbox for Designing Age-Specific fNIRS Channel Placement. Neurophotonics. 8(4) 045003.
Disrupted inter-brain synchronization between alcohol use disorders and its neural mechanism
Invited speaker: Mr. Lei Guo, Ph.D. candidate and member of the addiction study group at the Jiao Tong University, School of Medicine in Shanghai, China.
During his talk, he presented us the results obtained by the study group on the neural mechanisms behind social dysfunction in alcohol use disorder. Within the conducted research, the study group compared the brain activity synchronization between 28 subjects with AUD and 36 healthy controls using hyper scanning with fNIRS. They found that inter-brain synchronization was reduced in the right middle frontal cortex in the AUD group, suggesting impaired social cognition. This inter-brain synchronization reduction correlated with higher impulsivity. This study may shed light on the neural basis of social deficits in AUD and may inform future interventions.
Aurora Release Webinar
Continuing our tradition of providing researchers with cutting-edge and easy-to-use solutions, NIRx is proud to announce a new release of Aurora!
This release comes with two major new features to further enable researchers to perform high-density (HD-DOT) fNIRS recordings using the NIRSport2, plus a few small bug fixes and interface changes.
In this webinar, our crew of experts will walk you through what’s new and how it is implemented in the software.
Satori 2.0 Webinar - Discover the new features of the innovative fNIRS analysis software
Since the first launch of Satori, Brain Innovation and NIRx have been collecting feedback from fNIRS scientists about the features important in making their data analysis more straightforward. With Satori 2.0, we are happy to introduce these new and updated features that will enhance your data preprocessing and analysis capabilities.
Th four key additions: Python Integration, Data Plotter, integrated User Guides, and GUI Updates.
The webinar was conducted by our Scientific Consultant Team Lead, Jeremy Burnison and Dr. Michael Lührs from Brain Innovation.
NIRx Journal Club webinar: The use of Heart Rate Responses Extracted From Functional Near-Infrared Spectroscopy Data as a Measure of Speech Discrimination Ability in Sleeping Infants
In this Journal Club webinar, Onn Wah Lee presents his recent publication on the use of heart rate information extracted from functional near-infrared spectroscopy (fNIRS) data to measure speech discrimination ability in sleeping infants.
Onn Wah Lee is a PhD student who conducted his study at the Bionics Institute and the University of Melbourne in Australia under the supervision of Prof. Colette McKay and Dr. Julia Wunderlich.
The study recorded fNIRS data from a sample of 23 infants aged between 2 and 10 months old and introduced a novel technique for extracting heart rate information from fNIRS data.
The key findings of this research suggest that the heart rate response is modulated by the habituation/dishabituation test paradigm, and it adapts significantly over the session duration.
NIRx Journal club with Franziska Klein: Performance comparison of systemic activity correction in functional near-infrared spectroscopy for methods with and without short-distance channels
One major challenge with fNIRS is to clean the signals from the contamination of various systemic artifacts. While it is relatively straightforward to reduce physiological confounds such as heartbeat and respiration, systemic artifacts resulting from the extracerebral layers are much more difficult to handle. Since the introduction of short-distance channels, this hardware-based solution has become a leading technique to correct for this type of artifact.
In this webinar, Dr. Franziska Klein presents her and her collaborators' work on the performance comparison of extracerebral systemic activity correction methods including three approaches with and two without short-distance channels based on a semi-simulated and a real motor data set. Based on this work, this journal club will discuss the importance of extracerebral systemic activity correction and the relevance of short-distance channels.
Franziska Klein received her Ph.D. in 2022 at the University of Oldenburg. Her research focus lies in the development and validation of fNIRS-based real-time applications such as neurofeedback and BCI as well as in the improvement and further development of signal processing techniques. Since 2022 she has also worked at the University Hospital RWTH Aachen where she transfers her experience and knowledge to clinical applications.
NIRx Webinar with Julie Tremblay: Introduction to the LIONirs toolbox: a freely accessible fNIRS data analysis tool
Design for fNIRS data analysis, LIONirs toolbox includes several functions to read, preprocess, and analyze fNIRS data, including task-based and functional connectivity measures. In this webinar, we introduce the basics of how to start with a data set and create a pipeline of data analysis. Several examples of data analysis and a short hands-on will be presented to show how to use data decompositions methods PCA and PARAFAC to reduce data artifacts.
Watch the webinar here.
Satori - New Advancements and Features by Brain Innovation and NIRx
The concept of Satori is to make fNIRS analysis straightforward to all our users. The software includes the most popular processing and statistical tools, with the aim of looking at your data at every step. You will have total control over your analysis without having to program a single line.
We have been continuously developing and improving Satori since its launch last year. In this live webinar, NIRx and Brain Innovation share new features available in the latest version of Satori.
NIRx Journal Club with Anneke Hamann: Investigating mental workload-induced changes in cortical oxygenation and frontal theta activity during simulated flights.
In aviation research, valid and reliable physiological assessment of human performance is of interest for aspects of training and adaptive assistance systems. In their study, they used concurrent fNIRS-EEG measurement to analyze the effects of stepwise increased mental workload on cortical activation in a simulated flight task while controlling for mental fatigue. Their findings suggest higher cortical activation with higher task demands and different sensitivity of fNIRS and EEG to different demand levels, thus illustrating the benefit of combined measurement for mental workload assessment.
Satori, innovative fNIRS analysis software - new features with Dr. Michael Lührs
Since the release of Satori in October last year many exciting new developments were made. In this webinar, we will provide you with an overview of these new features and give an outlook on upcoming highlights. In addition, we will show you how you can use Satori to analyze your data and get many important insights from quality assurance over preprocessing to the final analysis.
Cortical correlates of pain relief: A NIRx Journal Club with Dr. Benedict Alter
Dr. Alter discusses his recent study examining fNIRS-measured brain activity during top-down inhibition of pain, a model of pain relief (https://journals.sagepub.com/doi/full/10.1177/17448069221074991). In volunteers, pain inhibition is associated with right dorsolateral prefrontal cortex activation and relative deactivations of bilateral medial prefrontal cortex and somatosensory cortex. This and work from others highlight a promising role for fNIRS in pain research.
Optimizing fNIRS Signal Quality with NIRx Support
How do you check, troubleshoot and optimize fNIRS signal quality to ensure the best signal for your research? In this webinar, we go through just that! This is the release of our latest video, available on our Support Site, plus a live Q&A with our expert support staff.
In Part 1, Demetris takes us through how to assess signal quality. Part 2 shows how to troubleshoot the challenges when things are less than perfect. These two sections follow the Signal Quality Guidelines, available as a PDF on our Support Site. In Part 3, with the help of our colleagues, we show a real-time example of set up, checks, and troubleshooting.
Effect of Physiology on Mapping Resting State Networks Using fNIRS - Challenges and Considerations with Sergio Novi and Androu Abdalmalak
In this webinar, Androu Abdalmalak and Sergio Novi discussed their recent publication titled " Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy". This work investigates the effects of systemic physiological noise on extracting resting-state networks with fNIRS. In the first part of this webinar, Androu explained the importance of extracting meaningful resting-state networks at the single-subject level, particularly as it pertains to their ongoing research aimed at using fNIRS to predict outcomes in patients with acute brain injuries.
In the second part, Sergio focused on the methodological challenges when incorporating additional physiological measurements in the fNIRS analysis pipeline.
The Neuroergonomics of Exercise and Neuromuscular Fatigue in Older Adults: lessons from fNIRS - with Oshin Tyagi
The cortex and motor areas of the brain are responsible for voluntary muscle control, and determination of the “safe limit” of exercise performance. Moreover, neuromuscular performance in older adults is exacerbated under stress and is characterized by shorter endurance time, greater perceived effort, lower force steadiness, and higher electromyographic activity. But the neural mechanisms of exercise under stress are not well understood.
In this talk, Oshin explored the neural correlates of exercise and how stress influences these correlates. For this, they used effective connectivity, which quantifies the influence of one brain region over the other, to understand how the prefrontal and motor areas of the brain influence each other during exercise performance under stress.
NIRx Journal Club: fNIRS and Heart Rate Variability During Self-Compassionate Thinking Related to Stressful Memories with Paulo Bazán
He discussed his fNIRS research into self-compassionate thinking related to stressful memories and the recent paper he is co-author of.
dos Santos, F. R., Bazán, P. R., Balardin, J. B., de Aratanha, M. A., Rodrigues, M., Lacerda, S., ... & Kozasa, E. H. (2021). Changes in Prefrontal fNIRS Activation and Heart Rate Variability During Self-Compassionate Thinking Related to Stressful Memories. Mindfulness, 1-13. https://link.springer.com/article/10.1007/s12671-021-01789-0
Image Reconstruction in fNIRS with Dr. Ted Huppert
In this webinar, Dr. Ted Huppert talked about how to perform image reconstruction and use digitization information in the Brain AnalzyIR toolbox.
Image reconstruction is one of the most important topics in neuroimaging. It gives more information about where the measured signal is coming from and helps with the correct interpretation of the dataset.
Physiological Considerations of Employing a Multimodal Imaging Protocol: Pitfalls, Methodological Advancements, and Future Directions for fNIRS research - Joel Burma
In this talk, Joel Burma of the Cerebrovascular Concussion Laboratory/Experimental Imaging Centre at the University of Calgary, talks about using fNIRS multimodal imaging. The concurrent use of physiological sensors in fNIRS experiments has grown in recent years. In this open webinar Joel discusses pitfalls, methodological advancements, and future directions for multimodal research using fNIRS + physiological measurements.
High Density fNIRS - A two part Webinar Series with Dr. David Boas
Dr. David Boas shared with us his expert knowledge on the topic of High-Density fNIRS (HD-fNIRS / DOT). HD-fNIRS is a methodology that employs high-density arrays with short, medium and long channels. Overlapping measurements with multiple source-detector distances can improve spatial resolution, depth and lateral specificity, and can enable the tomographic (image) reconstruction of cerebral activation.
In this two part webinar series, we went full circle of HD fNIRS: From practically setting up, conducting, and analyzing HD-fNIRS experiments using Dr. Boas' open source fNIRS analysis toolboxes AtlasViewer and Homer3 together with NIRx' NIRSport2 systems and Aurora/NIRSite software.
Part 1 covered experimental set up and data collection. Dr. Boas explained how to design a HD optode array using AtlasViewer. Then we addressed how to take those probes (.snirf) into NIRSITE and how to perform a straight-forward HD fNIRS measurement with the NIRSport2 system and Aurora.
Part 2 Dr. Boas described the analysis of the HD fNIRS data acquired with the NIRSport2 in Part 1. He showed how to do tomographic image reconstruction in AtlasViewer and trial-based signal analysis in Homer3.
You can download the data set used in Part 2 of the webinar here. Note that this is a large zip file as it also includes all of the results from the Monte Carlo run in AtlasViewer preparing for the image reconstruction. Thus, you will not need to run the Monte Carlo yourself to do the brain and scalp image reconstruction.
Part 1 - Watch the recording here.
Part 2 - Watch the recording here.
fNIRS in Infants - from Data Collection to Preprocessing with Dr. Jessica Gemignani
The talk covered different aspects related to infant studies. It started with an overview of approaches for the design of the optode array, with examples from literature as well as a couple practical examples of tools that can be used to this end. Relatedly, she discussed strategies for anatomical localization of the designed array. Following, the talk, Dr. Gemignani focused on the data pre-processing stage, including the assessment of raw data quality as well as best approaches to design a routine that optimally suits the study characteristics (e.g., number of trials) while accurately recovering the HRF (Gemignani and Gervain 2021).
Group Level Analysis with Dr. Ted Huppert
Dr. Ted Huppert is an Associate Professor from the University of Pittsburgh with more than 65 peer-reviewed publications on brain imaging methodologies. He will be joining us to give a detailed look at Group Level Analysis with fNIRS and practical demonstration in the BrainAnalyzIR, his Matlab based analysis platform. This toolbox is one of the most used fNIRS analysis platforms and was developed by Dr. Huppert and his team.
Satori, a look at the new fNIRS analysis software with Dr. Michael Lührs from Brain Innovation
We are very excited to announce the launch of our new easy-to-use, GUI-based analysis software made in collaboration with Brain Innovation. Brain Innovation have been our partners in the established real-time analysis software Turbo-Satori. The webinar will give you an overview of the main features of Satori, from standard fNIRS processing methods to statistical tools and data visualization.
Objective Measurements of Tinnitus using fNIRS with Dr. Mehrnaz Shoushtarian
For this webinar we were pleased to welcome Dr. Mehrnaz Shoushtarian of the Bionics Institute, Melbourne to talk about objective measurements of tinnitus. Chronic tinnitus, hearing sounds that are not present externally, affects around 1 in 8 individuals and can severely impact their quality of life. Rates of tinnitus increase with age and are expected to further rise in the future due to increasing noise exposure among young people.
Despite its wide prevalence, there is currently no objective way to determine the presence or severity of tinnitus or assess whether treatments are effective. Lack of an objective measure remains a significant hurdle to the development of treatments for this condition. They are working to develop an objective measure of tinnitus using functional near-infrared spectroscopy. This talk will present some of their work to date.
An introduction to fNIRS analysis using MNE with Dr. Robert Luke: Part 1 and 2
Dr. Robert Luke spoke in a 2 part series about fNIRS analysis using MNE. MNE is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. The first webinar held 30th June 2021 included an introduction to MNE, the ecosystem of packages, installation, and an overview of basic analysis. You can watch it here. In the second webinar, Dr. Luke will dove deeper into fNIRS analysis with MNE including GLM and group-level analysis. You can watch part 2 here.
NIRx Journal Club: Best Practices in fNIRS with Dr. Meryem Yücel
For the first of the open webinars in Journal Club format, we were pleased to welcome Dr. Meryem Yücel to talk about the recently released paper on best practices in fNIRS. With the rapid growth and the diversification of research methods in fNIRS studies, some inconsistencies are appearing in the way in which methods are presented, which can make the interpretation and replication of studies unnecessarily challenging.
A representative group of leaders in the field of fNIRS (including Dr. Yücel) was assembled by the Society for Functional Near-Infrared Spectroscopy to build a consensus on the best practices for describing the methods utilized in fNIRS studies. Their "paper has been designed to provide guidelines to help enhance the reliability, repeatability, and traceability of reported fNIRS studies and encourage best practices throughout the community."
Hyperscan: The hyperscanning feature for NIRSport2 + Aurora
Hosted by NIRx support staff Blanca Pérez-Sempere and Dr. Mahipal Choudhary
To efficiently collect fNIRS data from multiple subjects simultaneously with the NIRSport2 platform, NIRx is proud to offer Hyperscan, a standalone application that can control the functionality of multiple instances of Aurora from a single interface. The purpose of this webinar is to get users acquainted with the use of this application.
Hyperscan offers great flexibility in terms of recording connection, number of NIRSport2 devices and the optode count and montage layout for individual subjects. After the theoretical introduction to these features, we show an example experiment to give a demonstration of Hyperscan in action. This webinar was hosted by our expert support team.
Optimal Probe Placement in fNIRS Research
Guest Lecturer: Prof. Dr. Rickson Mesquita
Reproducibility of results is one of the keystones in science and, in fact, is what makes science advanced over the centuries. The search for high reproducibility of the same experimental protocol across different sessions is particularly critical for longitudinal studies in functional neuroscience and in different clinical applications, so that one can unentangle the variability caused by systematic errors due to instrumentation/protocol from the intrinsic variability due to the research question. Specifically for fNIRS studies, we have found several contributors to systematic errors over the past ten years, such as motion artifacts, extra cortical contamination and global systemic physiology. More recently, we have found that the lack of spatial information of the optodes on the head can also introduce a major confounding source to the results and lead to misinterpretation of data. In this talk we will discuss the major problems that contributes to systematic errors in fNIRS, and present recent solutions we implemented to reduce variability in fNIRS protocols - including the integration of a real time neuronavigator system to guide probe placement of optodes in fNIRS.
fNIRS In Epilepsy: From Research To Clinic
Guest Lecturers: Dr. Anne Gallagher, Phetsamone Vannasing, and Alejandra M. Hüsser
In this webinar, a team of three scientists of the LIONlab, Université de Montréal, Dr. Anne Gallagher, Phetsamone Vannasing and Alejandra Hüsser, will discuss the value of simultaneous fNIRS and EEG acquisition in patients with epilepsy. They will describe different applications of combined fNIRS-EEG evaluations in research as well as the integration of fNIRS-EEG into the pre-surgical assessment protocol of patients with severe epilepsy. The particularities, challenges and solutions for the installation and data acquisition of a multimodal fNIRS set-up in young patients will be discussed. We will conclude with a preview of potential pathways for multimodal data analysis using LIONirs toolbox.
fNIRS in a different light: a webinar
Guest Lecturer: Dr. Felipe Orihuela-Espina
Part narrative, part mathematics, this webinar is about uniqueness of Dr. Orihuela-Espina’s research in fNIRS. He will review some of his research in fNIRS analysis and interpretation, with computational approaches unorthodox to the field. This will be in the context of three peculiarities; a computer science background, research in a developing country, and unconventional research interests. We shall visit the beauty of manifolds, explore different theories of causal analysis, and envision the automation of our research analysis pipelines by means of knowledge representation.
Short channels analysis in the AnalyzIR toolbox
Guest Lecturer: Dr. Hendrik Santosa
In this webinar, Dr. Santosa will quantitatively compare the performance of several techniques in fNIRS analysis including spatial and temporal filtering, regression, component analysis, and the use of short-separation measurements as the part of the AnalyzIR toolbox. Dr. Santosa is a research instructor in the Department of Radiology at the University of Pittsburgh. His research interest includes statistical method, brain-computer interface, hyperscanning, advance brain signal processing, and multimodal neuroimaging techniques.
Cognitive load assessment in surgeons brain and skill acquisition in surgical training
Guest lecturers: Dr Daniel Richard Leff and Dr. Harsimrat Singh
Technical skills are a critical component of every surgeon. The early assessment of the learning curve of surgical skills can help assess the efficacy of training and adapt it to individual needs. How do we consistently assess the cognitive strain on surgeons during surgeries? Can strategies be developed to help trainees and surgeons cope with excessive cognitive load in the operating theatre? These topics and much more were discussed in this webinar.
Q&A Session on LSL
Guest lecturers: Dr. David Medine
In August, Dr. Medine held a webinar on integrated NIRS-EEG, with particular focus on LSL integration. To give an opportunity to all users in North and South America to reach out to Dr. Medine for questions, we organized a second Q&A portion. Watch the webinar and access the presentation slides.
Mobile brain imaging with fNIRS
Guest lecturers: Dr. Alexander von Lühmann, Dr. Robert Franke
Dr. Alexander von Lühmann joins us for a webinar focussed on the challenges of mobile brain imaging and the application of fNIRS. Dr. Robert Franke gives an overview of NIRx' accelerometer specifications and the team performs a NIRSport2 32x32 live demo with 2 accelerometers. If you are interested in mobile brain imaging using fNIRS, this webinar is for you.
Infant & Child Imaging with fNIRS
Guest lecturers: Dr. Judit Gervain, Dr. Susan Perlman
Part I: Hemodynamic response in infants with Dr. Judit Gervain. Learn more about infant imaging with fNIRS. In this webinar, Dr. Gervain discusses advantages and possible limitations and also use cases and applications. Practical considerations of imaging infants are also discussed. Watch the webinar.
PartII: Infant & Child Imaging with fNIRS with Dr. Susan Perlman. The following key considerations were discussed: advantages and tradeoffs of using fNIRS for developmental research; specific use cases, such as looking at simultaneous parent-child measurements; and data collection tips. Watch the webinar and access the presentation slides.
Multi-Modal Integration: EEG & fNIRS
Guest Lecturers: Dr. David Medine, Dr. Ted Huppert, Dr. Alexander von Lühmann, Maria Adelia de Aratanha
Part I: Integrating EEG and fNIRS, how is it done? Joining our team of consultants are Dr. David Medine, Dr. Alexander von Lühmann and Maria Adelia de Aratanha to explore the integration of combined fNIRS-EEG. A portion of the webinar focussed on triggering, synchronization and LSL. Practical hints on how to setup the integrated cap for good signal quality were also discussed. Watch the webinar and access the presentation slides.
Part II: Approaches to analysis of fNIRS and EEG data. Dr. Ted Huppert (University of Pittsburgh) is a leader in multi-modal neuroimaging methods. He begins this talk with an in-depth discussion of cross validation of multi-modal methods. He then discusses physiological modelling of neural signals, and combined EEG-fNIRS analysis methods. He rounds out the talk with a practical demonstration in the NIRS Toolbox, his Matlab based analysis platform. Watch the webinar and access the presentation slides.
Turbo Satori Webinars I: Getting Started
Guest Lecturer: Dr. Michael Lührs
Part I: This webinar covered how to download, install and get familiar with Turbo-Satori, a comprehensive real-time fNIRS analysis and neurofeedback solution from our partners at Brain Innovation. Download the slides here and watch the webinar here.
Part II: Overview: This advanced webinar on Turbo-Satori was done in collaboration with our partner, Brain Innovation. Dr. Michael Lührs gave us a deeper look into the new Turbo-Satori release and showed some advanced analysis features. Download the slides here and watch the webinar here.
2nd Level fNIRS Analysis with Covariates (Examples in the Brain AnalyzIR/NIRS Toolbox)
Guest Lecturer: Dr. Jessica Gemignani
Overview: This webinar explored 2nd level analysis, focusing in particular on the use of covariates and how they can be tested for correlations with the signal change in contrasts across subjects. Tools: NIRS Toolbox / AnalyzIR. Download the slides here and watch the webinar here.
Motion Analysis in the Brain AnalyzIR/NIRS Toolbox
Guest Lecturer: Dr. Ted Huppert
Overview: Dr. Huppert reviewed fNIRS data analysis with short channels and an accelerometer within NIRS Toolbox, an fNIRS analysis program. Download the data set here. Watch the first part of the presentation about motion artifact correction here and the second part where Dr. Huppert gives a walkthrough of motion and artifact corrections in NIRS Toolbox here. Download the code from Dr. Huppert here. To find answers to questions that weren’t covered during the webinar, click here.
The New Homer3 and Motion Analysis
Guest Lecturer: Dr. Meryem Yücel
Overview: Dr. Yucel reviewed fNIRS analysis with short channels and an accelerometer within the Homer3 fNIRS analysis program. Download presentation slides and download the data set. Watch the first part of the presentation about motion artifact correction here and the second part about Homer3, demonstration of motion correction and a new artifact correction model with the GLM here. To find answers to questions that weren’t covered during the webinar, click here.
Introduction to NIRS Toolbox: Installation & Getting Started
Guest Lecturer: Dr. Ted Huppert
Overview: Covers installation and basic use of the NIRS Toolbox (Brain AnalyzIR), followed by a Q&A session with its creator, Dr. Huppert. Download presentation slides here, download data set here and watch the video here. To find answers to questions that weren’t covered during the webinar, click here.
Introduction to Homer3: Installation & Getting Started
Guest Lecturer: Dr. Ted Huppert
Overview: Description: Covers installation and basic use of the Homer3 fNIRS analysis software. Download presentation slides here, download data set here and watch the video here. To find answers to questions that weren’t covered during the webinar, click here.
Hyperscanning with the NIRSport2 and Aurora 1.4
Overview: This webinar shows how to use the NIRSport2 and Aurora platform to perform an acquisition on multiple participants at the same time. Watch the webinar here.
NIRS Montage Design
Overview: NIRx FOLD (fNIRS Optode-Location Decider) toolbox; NIRSite; NIRS cap preparation. Watch the video here.
fNIRS Experimental design
Overview: Designing your NIRS experiment, TTL pulse basics with NIRS, using Lab-Streaming Layer with NIRStar, etc. Watch the video here.
fNIRS Studies with Infants & Toddlers
Overview: Dr. Afrouz Anderson and Dr. Jessica Gemignani share their expertise on infant studies. They discussed the impact of short distance channels in different ages, point out some montages and brain atlases that are frequently used for infants, among other considerations. The talk focused on children, aged prenatal through 4 years old. Watch the video here.
Overview of NIRStar 15-2
Overview: An introduction and online training of the new NIRStar 15-2 software. Watch the video here.
Overview of Aurora 1.4
Overview: A walk through and basic training of Aurora, the NIRSport2 data acquisition software. Emphasis is placed on the new features with the Aurora 1.4 release, including a new block average view and improved Wi-Fi connection with an access point router. Watch the video here.
High Density Measurements - Multi-Device Mode with NIRSport2
Overview: This second webinar of the Aurora 1.4 series details the hardware and software considerations for cascading multiple NIRSport2 devices together. Watch the video here.
Using Short Channels with NIRx Platform
Overview: Creating montages in NIRSite, enabling short channel setup in NIRStar and cap setup. Watch the video here.
PsychoPy Presentation Software with NIRx Systems
Overview: This webinar goes through using the PsychoPy Presentation software (a free python-based program: http://www.psychopy.org/) with NIRx NIRS recording systems and software. Watch the video here.
fNIRS Analysis Options For Data Including Short Channels
Overview: This short webinar covers the basics of short channel analysis in Homer2 NIRS analysis software. Watch the video here.
Introduction to The NIRS Brain AnalyzIR Toolbox - a Possible Processing Workflow
Overview: This webinar gives a brief introduction of the NIRS Brain AnalyzIR Toolbox and presents a possible pipeline for the complete analysis of fNIRS data. Watch the video here.
Introduction to Turbo Satori, a real-time Analysis Program for fNIRS data
Overview: This webinar gives a an overview of Turbo Satori, the main features and benefits and integration with NIRx instruments and software. Watch the video here.
NIRSite 2.0
Overview: This webinar covers all new features of the recently released NIRSite 2.0 Software. Watch the video here.
Co-Registering fNIRS/MRI in NIRS Toolbox
Guest Lecturer: Dr. Ted Huppert
Overview: Importing of anatomical (MRI) information , probe registration to anatomical landmarks (including head size variations), optical forward model simulations, image reconstruction basics, and anatomically defined region-of-interest methods. Watch the video here.
Studying functional connectivity with fNIRS
Overview: A review of the concepts of functional connectivity analysis in fNIRS, plus a simple demonstration of how to a connectivity analysis in the Brain AnalyzIR Toolbox. Watch the video here.
Overview of Aurora fNIRS
Overview: An introduction and online training of the new Aurora fNIRS software for the NIRSport 2. Watch the video here.
fNIRS Based Brain Computer Interfaces
Guest Lecturer: Dr. Noman Naseer
Overview: Practical and analysis considerations for using fNIRS based Brain Computer Interfaces (BCI) by BCI expert, Dr. Noman Naseer. Watch the video here.
Click below to learn more on NIRS
About NIRS and NIRx
- fNIRS and NIRx Overview
- NIRx NIRS Publication Sample
- NIRx Newsletters
- NIRx Webinars
- fNIRS Analysis
Applications
- fMRI-concurrent fNIRS
- EEG-concurrent fNIRS
- TMS-concurrent fNIRS
- Customized Real-time Analysis in NIRS: BCI / Neurofeedback
- Combining eye-tracking with fNIRS
- Using NIRS to conduct child and infant measurements
Products
- NIRScout NIRS Imaging System for Multi-Modal Integration
- NIRSport Portable NIRS Imaging System for Multi-Modal Integration
- NIRS Caps & NIRS Optodes (Probes)
- NIRS software