scholarly journals Shining Light On The Brain to Understand How It Works

2021 ◽  
Vol 9 ◽  
Author(s):  
Laura Bell ◽  
Vanessa Reindl ◽  
Jana A. Kruppa ◽  
Alexandra Niephaus ◽  
Simon H. Kohl ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared ◽  
Brain Activity ◽  
Infrared Light ◽  
Functional Near Infrared Spectroscopy ◽  
Near Infrared Light ◽  
Daily Lives ◽  
Long Run ◽  
Total Light ◽  
The Brain

Have you ever thought that light could tell you something about your brain? Light is a powerful tool that helps brain researchers understand the brain. Our eyes can only see <1% of the total light around us. Some of the light is red, so-called near-infrared light. This type of light can travel through the head and the top layers of the brain, and thereby gives researchers important information about brain activity. The technique that uses near-infrared light has a long name: functional near-infrared spectroscopy (fNIRS). In this article, we will show you what a fNIRS machine looks like and what it is like to take part in a fNIRS experiment. We will explain how we can use near-infrared light to better understand the brain. Finally, we will give you some examples of what we use fNIRS for and how it might help children who face difficulties in their daily lives in the long run.

scholarly journals Shining light on the brain to understand how it works and to help children who face difficulties

2020 ◽  
Author(s):  
Laura Bell ◽  
Vanessa Reindl ◽  
Jana Kruppa ◽  
Alexandra Niephaus ◽  
Simon Huldreich Kohl ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Brain Activation ◽  
Infrared Light ◽  
Functional Near Infrared Spectroscopy ◽  
Near Infrared Light ◽  
Daily Lives ◽  
Total Light ◽  
The Brain

Have you ever thought that light could tell you something about your brain? Light is a powerful tool that helps brain researchers understand the brain. Our eyes can only see less than 1 % of the total light around us. Some of the light is red, so-called near-infrared light. It can run through your head and the top layers of your brain and thereby gains important information about your brain activation. The technique that uses near-infrared light is called functional near-infrared spectroscopy. This term is very long, so we will call it “fNIRS” from now on. In this article, we will first show you how a fNIRS machine looks like and what it is like to take part in a fNIRS experiment. Next, we will explain how we can use near-infrared light to better understand the brain. Finally, we will give you some examples of what fNIRS can be used for and how we can use it to help children who face difficulties in their daily lives.

scholarly journals Caffeine Effect on Cognitive Function during a Stroop Task: fNIRS Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yafei Yuan ◽  
Guanghao Li ◽  
Haoran Ren ◽  
Wei Chen
Keyword(s):  
Cognitive Function ◽  
Task Performance ◽  
Stroop Task ◽  
Near Infrared ◽  
Brain Activity ◽  
Brain Activation ◽  
Infrared Light ◽  
Functional Near Infrared Spectroscopy ◽  
Feedback Information ◽  
The Brain

Acting as a brain stimulant, coffee resulted in heightening alertness, keeping arousal, improving executive speed, maintaining vigilance, and promoting memory, which are associated with attention, mood, and cognitive function. Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical method to monitor brain activity by measuring the absorption of the near-infrared light through the intact skull. This study is aimed at acquiring brain activation during executing task performance. The aim is to explore the effect of coffee on cognitive function by the fNIRS neuroimaging method, particularly on the prefrontal cortex regions. The behavioral experimental results on 31 healthy subjects with a Stroop task indicate that coffee can easily and effectively modulate the execute task performance by feedback information of the response time and accuracy rate. The findings of fNIRS showed that apparent hemodynamic changes were detected in the bilateral VLPFC regions and the brain activation regions varied with different coffee conditions.

scholarly journals Application of functional near-infrared spectroscopy in the healthcare industry: A review

2019 ◽  
Vol 12 (06) ◽  
pp. 1930012 ◽  
Author(s):  
Keum-Shik Hong ◽  
M. Atif Yaqub
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Depressive Disorders ◽  
Near Infrared ◽  
Brain Activity ◽  
Autism Spectrum ◽  
Future Research ◽  
Functional Near Infrared Spectroscopy ◽  
Brain Hemodynamics ◽  
The Brain

Functional near-infrared spectroscopy (fNIRS), a growing neuroimaging modality, has been utilized over the past few decades to understand the neuronal behavior in the brain. The technique has been used to assess the brain hemodynamics of impaired cohorts as well as able-bodied. Neuroimaging is a critical technique for patients with impaired cognitive or motor behaviors. The portable nature of the fNIRS system is suitable for frequent monitoring of the patients who exhibit impaired brain activity. This study comprehensively reviews brain-impaired patients: The studies involving patient populations and the diseases discussed in more than 10 works are included. Eleven diseases examined in this paper include autism spectrum disorder, attention-deficit hyperactivity disorder, epilepsy, depressive disorders, anxiety and panic disorder, schizophrenia, mild cognitive impairment, Alzheimer’s disease, Parkinson’s disease, stroke, and traumatic brain injury. For each disease, the tasks used for examination, fNIRS variables, and significant findings on the impairment are discussed. The channel configurations and the regions of interest are also outlined. Detecting the occurrence of symptoms at an earlier stage is vital for better rehabilitation and faster recovery. This paper illustrates the usability of fNIRS for early detection of impairment and the usefulness in monitoring the rehabilitation process. Finally, the limitations of the current fNIRS systems (i.e., nonexistence of a standard method and the lack of well-established features for classification) and future research directions are discussed. The authors hope that the findings in this paper would lead to advanced breakthrough discoveries in the fNIRS field in the future.

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