scholarly journals FPGA Implementation of RLSE Algorithm for Multichannel Brain Imaging

2021 ◽  
Vol 40 (1) ◽  
pp. 241-250
Author(s):  
Muhammad Shahid Nazir ◽  
Haroon-Ur-Rasheed Khan ◽  
Abubaker Akram ◽  
Bhagesh Maheshwari ◽  
Muhammad Aqil
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Resource Sharing ◽  
Near Infrared ◽  
Brain Activity ◽  
Computational Cost ◽  
Recursive Least Squares ◽  
Multiple Channels ◽  
Functional Near Infrared Spectroscopy ◽  
The Brain

This paper describes the implementation of a computationally efficient embedded system on an Field Programmable Gate Array (FPGA) platform for real-time brain activity estimation with multiple channels. The brain signals from multiple channels are considered as output of independent linear systems with unknown parameters representing the brain activity in corresponding channels. Multiple adaptive Recursive Least-Squares Estimation (RLSE) cores are implemented in FPGA to independently estimate the brain activity in each channel concurrently. The proposed RLSE-FPGA system provides dedicated (no time or resource sharing) and parallel processing environment. The universal asynchronous receiver transmitter core is also developed to communicate the measured and estimated parameters supported by storage facility programmed as shared memory. The computational precision is guaranteed by deploying a 32-bit floating point core for all the variables. The validation carried out by real Functional Near-Infrared Spectroscopy dataset and comparative analysis with the previously reported result, demonstrates the effectiveness of the proposed system. The computational cost endorses the effectiveness of concurrent processing of multiple channelsꞌ data in a sample before the arrival of the next sample. The proposed methodology has potential in real-time medical, military and industrial applications.

scholarly journals Interpersonal brain synchronization under bluffing in strategic games

2020 ◽  
Vol 15 (12) ◽  
pp. 1326-1335
Author(s):  
Zhihao Wang ◽  
Yiwen Wang ◽  
Xiaolin Zhou ◽  
Rongjun Yu
Keyword(s):  
Near Infrared ◽  
Brain Activity ◽  
Strategic Thinking ◽  
Human Condition ◽  
Angular Gyrus ◽  
Strategic Games ◽  
Functional Near Infrared Spectroscopy ◽  
High Penalty ◽  
The Right ◽  
The Brain

Abstract People commonly use bluffing as a strategy to manipulate other people’s beliefs about them for gain. Although bluffing is an important part of successful strategic thinking, the inter-brain mechanisms underlying bluffing remain unclear. Here, we employed a functional near-infrared spectroscopy hyperscanning technique to simultaneously record the brain activity in the right temporal-parietal junction in 32 pairs of participants when they played a bluffing game against each other or with computer opponents separately. We also manipulated the penalty for bluffing (high vs low). Under the condition of high relative to low penalty, results showed a higher bluffing rate and a higher calling rate in human-to-human as compared to human-to-computer pairing. At the neural level, high relative to low penalty condition increased the interpersonal brain synchronization (IBS) in the right angular gyrus (rAG) during human-to-human as compared to human-to-computer interaction. Importantly, bluffing relative to non-bluffing, under the high penalty and human-to-human condition, resulted in an increase in response time and enhanced IBS in the rAG. Participants who bluffed more frequently also elicited stronger IBS. Our findings support the view that regions associated with mentalizing become synchronized during bluffing games, especially under the high penalty and human-to-human condition.

scholarly journals Feasibility of a Real-Time Clinical Augmented Reality and Artificial Intelligence Framework for Pain Detection and Localization From the Brain (Preprint)

2019 ◽  
Author(s):  
Xiao-Su Hu ◽  
Thiago D. Nascimento ◽  
Mary C Bender ◽  
Theodore Hall ◽  
Sean Petty ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Augmented Reality ◽  
Real Time ◽  
Classification Accuracy ◽  
Near Infrared ◽  
Positive Likelihood Ratio ◽  
Cortical Activity ◽  
Functional Near Infrared Spectroscopy ◽  
Pain Detection ◽  
The Brain

BACKGROUND For many years, clinicians have been seeking for objective pain assessment solutions via neuroimaging techniques, focusing on the brain to detect human pain. Unfortunately, most of those techniques are not applicable in the clinical environment or lack accuracy. OBJECTIVE This study aimed to test the feasibility of a mobile neuroimaging-based clinical augmented reality (AR) and artificial intelligence (AI) framework, CLARAi, for objective pain detection and also localization direct from the patient’s brain in real time. METHODS Clinical dental pain was triggered in 21 patients by hypersensitive tooth stimulation with 20 consecutive descending cold stimulations (32°C-0°C). We used a portable optical neuroimaging technology, functional near-infrared spectroscopy, to gauge their cortical activity during evoked acute clinical pain. The data were decoded using a neural network (NN)–based AI algorithm to classify hemodynamic response data into pain and no-pain brain states in real time. We tested the performance of several networks (NN with 7 layers, 6 layers, 5 layers, 3 layers, recurrent NN, and long short-term memory network) upon reorganized data features on pain diction and localization in a simulated real-time environment. In addition, we also tested the feasibility of transmitting the neuroimaging data to an AR device, HoloLens, in the same simulated environment, allowing visualization of the ongoing cortical activity on a 3-dimensional brain template virtually plotted on the patients’ head during clinical consult. RESULTS The artificial neutral network (3-layer NN) achieved an optimal classification accuracy at 80.37% (126,000/156,680) for pain and no pain discrimination, with positive likelihood ratio (PLR) at 2.35. We further explored a 3-class localization task of left/right side pain and no-pain states, and convolutional NN-6 (6-layer NN) achieved highest classification accuracy at 74.23% (1040/1401) with PLR at 2.02. CONCLUSIONS Additional studies are needed to optimize and validate our prototype CLARAi framework for other pains and neurologic disorders. However, we presented an innovative and feasible neuroimaging-based AR/AI concept that can potentially transform the human brain into an objective target to visualize and precisely measure and localize pain in real time where it is most needed: in the doctor’s office. INTERNATIONAL REGISTERED REPOR RR1-10.2196/13594

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 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.

scholarly journals A Functional NIRS Study of Brain Functional Networks Induced by Social Time Coordination

2019 ◽  
Vol 9 (2) ◽  
pp. 43
Author(s):  
Megumi Mizuno ◽  
Tomoyuki Hiroyasu ◽  
Satoru Hiwa
Keyword(s):  
Brain Function ◽  
Data Clustering ◽  
Near Infrared ◽  
Brain Activity ◽  
Brain Regions ◽  
Functional Networks ◽  
Functional Near Infrared Spectroscopy ◽  
Social Time ◽  
The Relationship ◽  
The Brain

The ability to coordinate one’s behavior with the others’ behavior is essential to achieve a joint action in daily life. In this paper, the brain activity during synchronized tapping task was measured using functional near infrared spectroscopy (fNIRS) to investigate the relationship between time coordination and brain function. Furthermore, using brain functional network analysis based on graph theory, we examined important brain regions and network structures that serve as the hub when performing the synchronized tapping task. Using the data clustering method, two types of brain function networks were extracted and associated with time coordination, suggesting that they were involved in expectation and imitation behaviors.

scholarly journals Exploring the Brain Activity Related to Missing Penalty Kicks: An fNIRS Study

2021 ◽  
Vol 3 ◽  
Author(s):  
Max W. J. Slutter ◽  
Nattapong Thammasan ◽  
Mannes Poel
Keyword(s):  
Near Infrared ◽  
Brain Activity ◽  
Ecological Validity ◽  
Temporal Cortex ◽  
Lateral Asymmetry ◽  
Functional Near Infrared Spectroscopy ◽  
Professional Soccer ◽  
And Performance ◽  
Set Up ◽  
The Brain

At vital moments in professional soccer matches, penalties were often missed. Psychological factors, such as anxiety and pressure, are among the critical causes of the mistakes, commonly known as choking under pressure. Nevertheless, the factors have not been fully explored. In this study, we used functional near-infrared spectroscopy (fNIRS) to investigate the influence of the brain on this process. An in-situ study was set-up (N = 22), in which each participant took 15 penalties under three different pressure conditions: without a goalkeeper, with an amiable goalkeeper, and with a competitive goalkeeper. Both experienced and inexperienced soccer players were recruited, and the brain activation was compared across groups. Besides, fNIRS activation was compared between sessions that participants felt anxious against sessions without anxiety report, and between penalty-scoring and -missing sessions. The results show that the task-relevant brain region, the motor cortex, was more activated when players were not experiencing performance anxiety. The activation of task-irrelevant areas was shown to be related to players experiencing anxiety and missing penalties, especially the prefrontal cortex (PFC). More particularly, an overall higher activation of the PFC and an increase of PFC lateral asymmetry were related to anxious players and missed penalties, which can be caused by players' worries about the consequences of scoring or missing the penalty kicks. When experienced players were feeling anxious, their left temporal cortex activation increased, which could be an indication that experienced overthink the situation and neglect their automated skills. Besides, the left temporal cortex activation is higher when inexperienced players succeeded to score a penalty. Overall, the results of this study are in line with the neural efficiency theory and demonstrate the feasibility and ecological validity to detect neurological clues relevant to anxiety and performance from fNIRS recordings in the field.

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