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von Au S, Helmich I, Kieffer S, Lausberg H. Phasic and repetitive self-touch differ in hemodynamic response in the prefrontal cortex-An fNIRS study. FRONTIERS IN NEUROERGONOMICS 2023; 4:1266439. [PMID: 38234502 PMCID: PMC10790951 DOI: 10.3389/fnrgo.2023.1266439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/24/2023] [Indexed: 01/19/2024]
Abstract
Introduction Each individual touches the own body several 100 times a day. While some researchers propose a self-regulatory function of self-touch, others report that self-touching increases nervousness. This controversy appears to be caused by the fact that researchers did not define the kind of self-touch they examined and actually, referred to different types of self-touch. Thus, kinematically defining different types of self-touch, such as phasic (discrete), repetitive, and irregular, and exploring the neural correlates of the different types will provide insight into the neuropsychological function of self-touching behavior. Methods To this aim, we assessed hemodynamic responses in prefrontal brain areas using functional near-infrared spectroscopy (fNIRS) and behavioral responses with NEUROGES®. Fifty-two participants were recorded during three specific kinematically types of self-touch (phasic, irregular, repetitive) that were to be performed on command. The recently developed toolbox Satori was used for the visualization of neuronal processes. Results Behaviorally, the participants did not perform irregular self-touch reliably. Neurally, the comparison of phasic, irregular and repetitive self-touch revealed different activation patterns. Repetitive self-touch is associated with stronger hemodynamic responses in the left Orbitofrontal Cortex and the Dorsolateral Prefrontal Cortex than phasic self-touch. Discussion These brain areas have been reported to be associated with self-regulatory processes. Furthermore, irregular self-touch appears to be primarily generated by implicit neural control. Thus, by distinguishing kinematically different types of self-touch, our findings shed light on the controverse discussion on the neuropsychological function of self-touch.
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Affiliation(s)
- Sabrina von Au
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Cologne, Germany
| | - Ingo Helmich
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Cologne, Germany
- Department of Motor Behavior in Sports, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Cologne, Germany
| | - Simon Kieffer
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Cologne, Germany
| | - Hedda Lausberg
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Cologne, Germany
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Afzal Khan MN, Hong KS. Most favorable stimulation duration in the sensorimotor cortex for fNIRS-based BCI. BIOMEDICAL OPTICS EXPRESS 2021; 12:5939-5954. [PMID: 34745714 PMCID: PMC8547991 DOI: 10.1364/boe.434936] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 08/20/2021] [Accepted: 08/23/2021] [Indexed: 05/13/2023]
Abstract
One of the primary objectives of the brain-computer interface (BCI) is to obtain a command with higher classification accuracy within the shortest possible time duration. Therefore, this study evaluates several stimulation durations to propose a duration that can yield the highest classification accuracy. Furthermore, this study aims to address the inherent delay in the hemodynamic responses (HRs) for the command generation time. To this end, HRs in the sensorimotor cortex were evaluated for the functional near-infrared spectroscopy (fNIRS)-based BCI. To evoke brain activity, right-hand-index finger poking and tapping tasks were used. In this study, six different stimulation durations (i.e., 1, 3, 5, 7, 10, and 15 s) were tested on 10 healthy male subjects. Upon stimulation, different temporal features and multiple time windows were utilized to extract temporal features. The extracted features were then classified using linear discriminant analysis. The classification results using the main HR showed that a 5 s stimulation duration could yield the highest classification accuracy, i.e., 74%, with a combination of the mean and maximum value features. However, the results were not significantly different from the classification accuracy obtained using the 15 s stimulation. To further validate the results, a classification using the initial dip was performed. The results obtained endorsed the finding with an average classification accuracy of 73.5% using the features of minimum peak and skewness in the 5 s window. The results based on classification using the initial dip for 5 s were significantly different from all other tested stimulation durations (p < 0.05) for all feature combinations. Moreover, from the visual inspection of the HRs, it is observed that the initial dip occurred as soon as the task started, but the main HR had a delay of more than 2 s. Another interesting finding is that impulsive stimulation in the sensorimotor cortex can result in the generation of a clearer initial dip phenomenon. The results reveal that the command for the fNIRS-based BCI can be generated using the 5 s stimulation duration. In conclusion, the use of the initial dip can reduce the time taken for the generation of commands and can be used to achieve a higher classification accuracy for the fNIRS-BCI within a 5 s task duration rather than relying on longer durations.
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Affiliation(s)
- M. N. Afzal Khan
- School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea
- Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea
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Re R, Messenio D, Marano G, Spinelli L, Pirovano I, Contini D, Colombo R, Boracchi P, Biganzoli E, Cubeddu R, Torricelli A. Monitoring the haemodynamic response to visual stimulation in glaucoma patients. Sci Rep 2021; 11:13567. [PMID: 34193904 PMCID: PMC8245402 DOI: 10.1038/s41598-021-92857-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 06/16/2021] [Indexed: 11/23/2022] Open
Abstract
In this paper, we used time-domain functional near infrared spectroscopy (TD-fNIRS) to evaluate the haemodynamic response function (HRF) in the occipital cortex following visual stimulation in glaucomatous eyes as compared to healthy eyes. A total of 98 subjects were enrolled in the study and clinically classified as healthy subjects, glaucoma patients (primary open-angle glaucoma) and mixed subjects (i.e. with a different classification for the two eyes). After quality check data were used from HRF of 73 healthy and 62 glaucomatous eyes. The amplitudes of the oxygenated and deoxygenated haemoglobin concentrations, together with their latencies with respect to the stimulus onset, were estimated by fitting their time course with a canonical HRF. Statistical analysis showed that the amplitudes of both haemodynamic parameters show a significant association with the pathology and a significant discriminating ability, while no significant result was found for latencies. Overall, our findings together with the ease of use and noninvasiveness of TD-NIRS, make this technique a promising candidate as a supporting tool for a better evaluation of the glaucoma pathology.
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Affiliation(s)
- R Re
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy. .,Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.
| | - D Messenio
- Department of Clinical Sciences, Eye Clinic, ASST Fatebenefratelli Sacco Hospital, University of Milan, Milan, Italy
| | - G Marano
- Laboratorio di Statistica Medica, Biometria ed Epidemiologia "G.A. Maccacaro", Dipartimento di Scienze Cliniche e di Comunità, Università degli Studi di Milano, Via Vanzetti 5, Milan, Italy
| | - L Spinelli
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - I Pirovano
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.,Istituto di Tecnologie Biomediche, Consiglio Nazionale delle Ricerche, via Fratelli Cervi 93, 20090, Segrate, MI, Italy
| | - D Contini
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - R Colombo
- Department of Clinical Sciences, Eye Clinic, ASST Fatebenefratelli Sacco Hospital, University of Milan, Milan, Italy
| | - P Boracchi
- Laboratorio di Statistica Medica, Biometria ed Epidemiologia "G.A. Maccacaro", Dipartimento di Scienze Cliniche e di Comunità, Università degli Studi di Milano, Via Vanzetti 5, Milan, Italy
| | - E Biganzoli
- Laboratorio di Statistica Medica, Biometria ed Epidemiologia "G.A. Maccacaro", Dipartimento di Scienze Cliniche e di Comunità, Università degli Studi di Milano, Via Vanzetti 5, Milan, Italy.,Unità di Statistica Medica, Biometria e Bioinformatica, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Via Vanzetti 5, Milan, Italy
| | - R Cubeddu
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - A Torricelli
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.,Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
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Gabbard R, Fendley M, Dar IA, Warren R, Kashou NH. Utilizing functional near-infrared spectroscopy for prediction of cognitive workload in noisy work environments. NEUROPHOTONICS 2017; 4:041406. [PMID: 28840158 PMCID: PMC5562416 DOI: 10.1117/1.nph.4.4.041406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 07/17/2017] [Indexed: 06/07/2023]
Abstract
Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts' decision-making process. We investigated the effects of different noise stimuli on analysts' performance and workload in anomaly detection by simulating a noisy work environment. We utilized functional near-infrared spectroscopy (fNIRS) to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin concentration changes in the prefrontal cortex (PFC), as well as behavioral measures, which include eye tracking, reaction time, and accuracy rate. We hypothesized that noisy environments would have a negative effect on the participant in terms of anomaly detection performance due to the increase in workload, which would be reflected by an increase in PFC activity. We found that HbO for some of the channels analyzed were significantly different across noise types ([Formula: see text]). Our results also indicated that HbO activation for short-intermittent noise stimuli was greater in the PFC compared to long-intermittent noises. These approaches using fNIRS in conjunction with an understanding of the impact on human analysts in anomaly detection could potentially lead to better performance by optimizing work environments.
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Affiliation(s)
- Ryan Gabbard
- Wright State University, Biomedical, Industrial and Human Factors Engineering, Dayton, Ohio, United States
| | - Mary Fendley
- Wright State University, Biomedical, Industrial and Human Factors Engineering, Dayton, Ohio, United States
| | - Irfaan A. Dar
- Wright State University, Biomedical, Industrial and Human Factors Engineering, Dayton, Ohio, United States
| | - Rik Warren
- Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio, United States
| | - Nasser H. Kashou
- Wright State University, Biomedical, Industrial and Human Factors Engineering, Dayton, Ohio, United States
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