Measured Brain Activity Research Articles

Population-level task-evoked functional connectivity via Fourier analysis.

Functional magnetic resonance imaging (fMRI) is a noninvasive and in-vivo imaging technique essential for measuring brain activity. Functional connectivity is used to study associations between brain regions, either while study subjects perform tasks or during periods of rest. In this paper, we propose a rigorous definition of task-evoked functional connectivity at the population level (ptFC). Importantly, our proposed ptFC is interpretable in the context of task-fMRI studies. An algorithm for estimating the ptFC is provided. We present the performance of the proposed algorithm compared to existing functional connectivity frameworks using simulations. Lastly, we apply the proposed algorithm to estimate the ptFC in a motor-task study from the Human Connectome Project.

FNIRS is capable of distinguishing laterality of lower body contractions.

The use of functional near-infrared spectroscopy (fNIRS) for brain imaging during human movement continues to increase. This technology measures brain activity non-invasively using near-infrared light, is highly portable, and robust to motion artifact. However, the spatial resolution of fNIRS is lower than that of other imaging modalities. It is unclear whether fNIRS has sufficient spatial resolution to differentiate nearby areas of the cortex, such as the leg areas of the motor cortex. Therefore, the purpose of this study was to determine fNIRS' ability to discern laterality of lower body contractions. Activity in the primary motor cortex was recorded in forty participants (mean = 23.4years, SD = 4.5, female = 23, male = 17) while performing unilateral lower body contractions. Contractions were performed at 30% of maximal force against a handheld dynamometer. These contractions included knee extension, knee flexion, dorsiflexion, and plantar flexion of the left and right legs. fNIRS signals were recorded and stored for offline processing and analysis. Channels of fNIRS data were grouped into regions of interest, with five tolerance conditions ranging from strict to lenient. Four of five tolerance conditions resulted in significant differences in cortical activation between hemispheres. During right leg contractions, the left hemisphere was more active than the right hemisphere. Similarly, during left leg contractions, the right hemisphere was more active than the left hemisphere. These results suggest that fNIRS has sufficient spatial resolution to distinguish laterality of lower body contractions. This makes fNIRS an attractive technology in research and clinical applications in which laterality of brain activity is required during lower body activity.

Robustness of the self-referential process under normobaric hypoxia: an fNIRS study using the GLM and homologous cortical functional connectivity analyses.

Hypoxia has been reported to impair psychological functions, such as working memory and decision-making. However, few studies have examined hypoxia's effect on social cognition. Using a self-referential task, the present study investigated normobaric hypoxia's effect on the self-referential process. Additionally, we measured brain activity during the task with fNIRS and performed conventional univariate analysis with the general linear model (GLM) as well as homologous cortical functional connectivity analysis. The results revealed that normobaric hypoxia impaired recognition of adjectives in the other-reference condition but not in the self-reference. The GLM analysis did not detect differences in brain activity between the self- and other-reference conditions, suggesting that GLM analysis may not be suitable for examining self- and other-reference conditions' neural correlates. The homologous cortical connectivity analysis revealed that the connectivity's magnitude was greater in the self-reference than in the other-reference conditions in the normoxic group. However, such a decrease in connectivity in the other-reference conditions was not observed in the hypoxic group, possibly to compensate for cognitive decline induced by the hypoxia. Considering that homologous connectivity reflects the default mode network, which is supposedly linked to continuous self-reference, stable strength of the connectivity in the self-reference condition under the hypoxia may suggest robust nature of the self-reference process under normobaric hypoxia.

Mental workload assessment by monitoring brain, heart, and eye with six biomedical modalities during six cognitive tasks.

The efficiency and safety of complex high precision human-machine systems such as in aerospace and robotic surgery are closely related to the cognitive readiness, ability to manage workload, and situational awareness of their operators. Accurate assessment of mental workload could help in preventing operator error and allow for pertinent intervention by predicting performance declines that can arise from either work overload or under stimulation. Neuroergonomic approaches based on measures of human body and brain activity collectively can provide sensitive and reliable assessment of human mental workload in complex training and work environments. In this study, we developed a new six-cognitive-domain task protocol, coupling it with six biomedical monitoring modalities to concurrently capture performance and cognitive workload correlates across a longitudinal multi-day investigation. Utilizing two distinct modalities for each aspect of cardiac activity (ECG and PPG), ocular activity (EOG and eye-tracking), and brain activity (EEG and fNIRS), 23 participants engaged in four sessions over 4 weeks, performing tasks associated with working memory, vigilance, risk assessment, shifting attention, situation awareness, and inhibitory control. The results revealed varying levels of sensitivity to workload within each modality. While certain measures exhibited consistency across tasks, neuroimaging modalities, in particular, unveiled meaningful differences between task conditions and cognitive domains. This is the first comprehensive comparison of these six brain-body measures across multiple days and cognitive domains. The findings underscore the potential of wearable brain and body sensing methods for evaluating mental workload. Such comprehensive neuroergonomic assessment can inform development of next generation neuroadaptive interfaces and training approaches for more efficient human-machine interaction and operator skill acquisition.

Jointly constrained group sparse connectivity representation improves early diagnosis of Alzheimer's disease on routinely acquired T1-weighted imaging-based brain network.

Radiomics-based morphological brain networks (radMBN) constructed from routinely acquired structural MRI (sMRI) data have gained attention in Alzheimer's disease (AD). However, the radMBN suffers from limited characterization of AD because sMRI only characterizes anatomical changes and is not a direct measure of neuronal pathology or brain activity. To establish a group sparse representation of the radMBN under a joint constraint of group-level white matter fiber connectivity and individual-level sMRI regional similarity (JCGS-radMBN). Two publicly available datasets were adopted, including 120 subjects from ADNI with both T1-weighted image (T1WI) and diffusion MRI (dMRI) for JCGS-radMBN construction, 818 subjects from ADNI and 200 subjects solely with T1WI from AIBL for validation in early AD diagnosis. Specifically, the JCGS-radMBN was conducted by jointly estimating non-zero connections among subjects, with the regularization term constrained by group-level white matter fiber connectivity and individual-level sMRI regional similarity. Then, a triplet graph convolutional network was adopted for early AD diagnosis. The discriminative brain connections were identified using a two-sample t-test, and the neurobiological interpretation was validated by correlating the discriminative brain connections with cognitive scores. The JCGS-radMBN exhibited superior classification performance over five brain network construction methods. For the typical NC vs. AD classification, the JCGS-radMBN increased by 1-30% in accuracy over the alternatives on ADNI and AIBL. The discriminative brain connections exhibited a strong connectivity to hippocampus, parahippocampal gyrus, and basal ganglia, and had significant correlation with MMSE scores. The proposed JCGS-radMBN facilitated the AD characterization of brain network established on routinely acquired imaging modality of sMRI. The online version of this article (10.1007/s13755-023-00269-0) contains supplementary material, which is available to authorized users.

A CONSUMER SENTIMENT ANALYSIS METHOD BASED ON EEG SIGNALS AND A RESNEXT MODEL

E-commerce is becoming increasingly dependent on technologies such as consumer sentiment research at an ever-increasing rate. Its purpose is to recognize and comprehend the feelings and dispositions of customers by analyzing customer language and behavior as expressed in social media, online reviews, and other forms of digital communication. The proliferation of digital technology has resulted in an increase in the number and variety of channels through which customers can communicate their feelings. Gaining a comprehensive understanding of consumer sentiment may be of great use to businesses, as it enables them to better satisfy customer demands, enhance their products and services, improve their brand reputation, and ultimately increase their level of competitiveness. As a result, consumer sentiment research has evolved into a tool that is essential for the decision-making process in e-commerce as well as the management of customer relationships. Within the scope of this discussion, this study uses deep learning models to improve consumer sentiment research precision. The following is the list of the primary contributions that this paper makes. (1) Advancing the use of EEG signals as a basis for a method for analyzing customer feelings. This technique measures brain activity directly, thus avoiding the restrictions and ambiguities that come with relying on verbal expression. (2) The purpose of this study is to improve the overall performance of the model for analyzing sentiment by incorporating an attention mechanism into the ResNeXt model. This attention mechanism is intended to augment the model’s capacity to extract subtle characteristics. (3) The results of the experiments show that the strategy described in this study is effective in improving EEG-based sentiment analysis performance. When compared to standard text-based sentiment analysis approaches, this sentiment analysis model demonstrates greater objectivity, real-time capabilities, and multidimensionality when applied to consumer sentiment analysis in e-commerce.

Motor priming to enhance the effect of physical therapy in people with spinal cord injury

Context Brain–Computer Interface (BCI) is an emerging neurorehabilitation therapy for people with spinal cord injury (SCI). Objective The study aimed to test whether priming the sensorimotor system using BCI-controlled functional electrical stimulation (FES) before physical practice is more beneficial than physical practice alone. Methods Ten people with subacute SCI participated in a randomized control trial where the experimental (N = 5) group underwent BCI-FES priming (∼15 min) before physical practice (30 min), while the control (N = 5) group performed physical practice (40 min) of the dominant hand. The primary outcome measures were BCI accuracy, adherence, and perceived workload. The secondary outcome measures were manual muscle test, grip strength, the range of motion, and Electroencephalography (EEG) measured brain activity. Results The average BCI accuracy was 85%. The experimental group found BCI-FES priming mentally demanding but not frustrating. Two participants in the experimental group did not complete all sessions due to early discharge. There were no significant differences in physical outcomes between the groups. The ratio between eyes closed to eyes opened EEG activity increased more in the experimental group (theta Pθ = 0.008, low beta Plβ = 0.009, and high beta Phβ = 1.48e-04) indicating better neurological outcomes. There were no measurable immediate effects of BCI-FES priming. Conclusion Priming the brain before physical therapy is feasible but may require more than 15 min. This warrants further investigation with an increased sample size.

Electrical brain activity during human walking with parametric variations in terrain unevenness and walking speed

AbstractMobile brain imaging with high-density electroencephalography (EEG) can provide insight into the cortical processes involved in complex human walking tasks. While uneven terrain is common in the natural environment and poses challenges to human balance control, there is limited understanding of the supraspinal processes involved with traversing uneven terrain. The primary objective of this study was to quantify electrocortical activity related to parametric variations in terrain unevenness for neurotypical young adults. We used high-density EEG to measure brain activity when 32 young adults walked on a novel custom-made uneven terrain treadmill surface with four levels of difficulty at a walking speed tailored to each participant. We identified multiple brain regions associated with uneven terrain walking. Alpha (8 - 13 Hz) and beta (13 - 30 Hz) spectral power decreased in the sensorimotor and posterior parietal areas with increasing terrain unevenness while theta (4 - 8 Hz) power increased in the mid/posterior cingulate area with terrain unevenness. We also found that within stride spectral power fluctuations increased with terrain unevenness. Our secondary goal was to investigate the effect of parametric changes in walking speed (0.25 m/s, 0.5 m/s, 0.75 m/s, 1.0 m/s) to differentiate the effects of walking speed from uneven terrain. Our results revealed that electrocortical activities only changed substantially with speed within the sensorimotor area but not in other brain areas. Together, these results indicate there are distinct cortical processes contributing to the control of walking over uneven terrain versus modulation of walking speed on smooth, flat terrain. Our findings increase our understanding of cortical involvement in an ecologically valid walking task and could serve as a benchmark for identifying deficits in cortical dynamics that occur in people with mobility deficits.

Improving informational-attentional masking of water sound on traffic noise by spatial variation settings: An in situ study with brain activity measurements

According with soundscape strategies to improve the perception of the sound environment, laboratory studies have proven that introducing water sounds into urban spaces can be both an effective strategy for the informational-attentional masking of road traffic noise, and restorativeness creation. To extend previous laboratory findings and test the effectiveness and applicability of different spatial variations of water sounds in urban parks, a sound installation was prepared, and an experiment was conducted. Three different position-varied water-sound sequences were augmented into an existing University campus green park through surround sound design method with four Bluetooth loudspeakers. The mental effects and attention process were assessed by analyzing the EEG signals including aperiodic, oscillatory components and sensor-level functional connectivity, along with psychological scales. The water sounds played in-situ, brought more visual processing related to spatial attention and stimulus-driven salience. And the changes in the alpha band and the related theta/alpha ratio among four conditions showed more relaxation state induced by the introduction of water sounds, consistent with the positive effects on emotion saliency and perceived restorativeness. Moreover, different spatial variations of water sounds, especially for the two-position switching setting, modulated the activity of the attentional network related to the restoration process via the alpha-theta synchronization.

Having a chat and then watching a movie: how social interaction synchronises our brains during co-watching.

How does co-presence change our neural experience of the world? Can a conversation change how we synchronise with our partner during later events? Using fNIRS hyperscanning, we measured brain activity from 27 pairs of familiar adults simultaneously over frontal, temporal and parietal regions bilaterally, as they co-watched two different episodes of a short cartoon. In-between the two episodes, each pair engaged in a face-to-face conversation on topics unrelated to the cartoon episodes. Brain synchrony was calculated using wavelet transform coherence and computed separately for real pairs and shuffled pseudo) pairs. Findings reveal that real pairs showed increased brain synchrony over right Dorso-Lateral Pre-Frontal cortex (DLPFC) and right Superior Parietal Lobe (SPL), compared to pseudo pairs (who had never seen each other and watched the same movie at different times; uncorrected for multiple comparisons). In addition, co-watching after a conversation was associated with greater synchrony over right TPJ compared to co-watching before a conversation, and this effect was significantly higher in real pairs (who engaged in conversation with each other) compared to pseudo pairs (who had a conversation with someone else; uncorrected for multiple comparisons). The present study has shed the light on the role of social interaction in modulating brain synchrony across people not just during social interaction, but even for subsequent non-social activities. These results have implications in the growing domain of naturalistic neuroimaging and interactive neuroscience.

Health Behavior Assessment and Rehabilitation of Vestibular Migraine Patients: Interventions through Magnetic Resonance Imaging (MRI)

Objectives: Vestibular Migraine (VM) is a common neurological syndrome where the patient gets recurrent episodes of severe migraine along with vertigo, dizziness and nausea, often diagnosed through magnetic resonance imaging (MRI). This study examines efficiency of an MRI induced vestibular rehabilitation (VR) program in treating patients with VM. Methods: A total of 14 VM patients, including 8 females and 6 males, with an average age of 43.85 years, participated in this study. Clinical evaluations scales such as the Dizziness Handicap Inventory (DHI), Hamilton Anxiety Scale (HAMA), SF36 domains and Hamilton Depression Scale (HAMD) were carried out both at the beginning and end of VR programmes. Results:DHI and HAMA ratings post-VR was significantly decreased (p=0.031 and p=0.021 respectively). In the SF36 domains, role-emotional and role-physical scores increased (p= 0.05). After VR, the left posterior cerebellum's amplitude of low frequency fluctuation (ALFF) values—which measured brain activity— increased (p <0.001), suggesting enhanced neural function. Between DHI scores and ALFF values, there was a significant negative association (r=-0.612, p<0.05). Conclusions: The study stresses the value of VR therapy in treating VM symptoms and improving patient outcomes through improved health behavior.

Eye Tracking in MEG.

Magnetoencephalography (MEG) can measure brain activity in ms-level temporal resolution. MEG sensors are super sensitive devices for magnetic signals of the brain but are also prone to electromagnetic interferences. The MEG device is located inside the magnetically shielded room (MSR), and any monitoring device used inside the MSR requires special shielding and its location must be carefully selected to suppress electromagnetic interference. Eye-tracker measures eye movements, providing spatial location of the gaze, pupil diameters, and eye blinks. Eye tracking in MEG enables, for example, categorization of the MEG data based on gaze position and interactive stimulus using gaze position. Combining the methods together will require considering the electromagnetic interference for the MEG-that is, additional shielding, positioning of the eye tracker, and subject-specific issues related to make-up and eye-corrective lenses.

Predicting the subjective intensity of imagined experiences from electrophysiological measures of oscillatory brain activity

Most people can conjure images and sounds that they experience in their minds. There are, however, marked individual differences. Some people report that they cannot generate imagined sensory experiences at all (aphantasics) and others report that they have unusually intense imagined experiences (hyper-phantasics). These individual differences have been linked to activity in sensory brain regions, driven by feedback. We would therefore expect imagined experiences to be associated with specific frequencies of oscillatory brain activity, as these can be a hallmark of neural interactions within and across regions of the brain. Replicating a number of other studies, relative to a Resting-State we find that the act of engaging in auditory or in visual imagery is linked to reductions in the power of oscillatory brain activity across a broad range of frequencies, with prominent peaks in the alpha band (8–12 Hz). This oscillatory activity, however, did not predict individual differences in the subjective intensity of imagined experiences. For audio imagery, these were rather predicted by reductions within the theta (6–9 Hz) and gamma (33–38 Hz) bands, and by increases in beta (15–17 Hz) band activity. For visual imagery these were predicted by reductions in lower (14–16 Hz) and upper (29–32 Hz) beta band activity, and by an increase in mid-beta band (24–26 Hz) activity. Our data suggest that there is sufficient ground truth in the subjective reports people use to describe the intensity of their imagined sensory experiences to allow these to be linked to the power of distinct rhythms of brain activity. In future, we hope to combine this approach with better measures of the subjective intensity of imagined sensory experiences to provide a clearer picture of individual differences in the subjective intensity of imagined experiences, and of why these eventuate.

Neural substrates of cough control during coughing

Cough is known as a protective reflex to keep the airway free from harmful substances. Although brain activity during cough was previously examined mainly by functional magnetic resonance imaging (fMRI) with model analysis, this method does not capture real brain activity during cough. To obtain accurate measurements of brain activity during cough, we conducted whole-brain scans during different coughing tasks while correcting for head motion using a restraint-free positron emission tomography (PET) system. Twenty-four healthy right-handed males underwent multiple PET scans with [15O]H2O. Four tasks were performed during scans: “resting”; “voluntary cough (VC)”, which simply repeated spontaneous coughing; “induced cough (IC)”, where participants coughed in response to an acid stimulus in the cough‐inducing method with tartaric acid (CiTA); and “suppressed cough (SC)”, where coughing was suppressed against CiTA. The whole brain analyses of motion-corrected data revealed that VC chiefly activated the cerebellum extending to pons. In contrast, CiTA-related tasks (IC and SC) activated the higher sensory regions of the cerebral cortex and associated brain regions. The present results suggest that brain activity during simple cough is controlled chiefly by infratentorial areas, whereas manipulating cough predominantly requires the higher sensory brain regions to allow top-down control of information from the periphery.

Analysis of Multimodal Biosignals during Surprise Conditions Correlates with Psychological Traits

Surprise can simultaneously represent bad or good, pleasant or unpleasant, with the same experiences since understanding how humans' physiological qualities link with their emotional or mental health is required. We conducted quantitative research to concisely correlate mental stress and emotional issues by measuring brain activity, breathing, and heart rate in real time while executing specialized audio-visual stimulation to elicit a surprise event. We evaluated the frequency and temporal domain characteristics to determine if physiological measurements matched biochemical metrics and subjective stress assessments during the elicit surprise condition experiment. We discovered that the brain is still preferable to most in recognizing a human's psychological changes over a short period of time. The temporal (T3) (r = 0.544, p = 0.005) and frontal (Fz) (r = 0.519, p = 0.008) regions were shown to correlate with salivary amylase activity. In comparison to other channels, there was a negative association between stress perception and the occipital site (O1, r = -0.618, p = 0.001). We also found that heart rate variability activity correlates with arousal perception. By looking at specific multimodal biosignals, it is possible to understand human psychological traits by recording specific physiological signals for daily mental health monitoring.

Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization

Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employ wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determine cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks exhibit overlapping organization. We find that there is considerable network overlap (both modalities) in addition to disjoint organization. Our results show that multiple BOLD networks are detected via Ca2+ signals, and networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks. In addition, the principal gradient of functional connectivity is nearly identical for BOLD and Ca2+ signals. Despite similarities, important differences are also detected across modalities, such as in measures of functional connectivity strength and diversity. In conclusion, Ca2+ imaging uncovers overlapping functional cortical organization in the mouse that reflects several, but not all, properties observed with fMRI-BOLD signals.

Midfrontal conflict theta and parietal P300 are linked to a latent factor of DSM externalising disorders.

Psychiatric illnesses form spectra rather than categories, with symptoms varying continuously across individuals, i.e., there is no clear break between health and disorder. Dimensional measures of behaviour and brain activity are promising targets for studying biological mechanisms that are common across disorders. Here, we assessed the extent to which neural measures of the sensitivity of the three biological systems in the reinforcement sensitivity theory (RST) could account for individual differences in a latent general factor estimated from symptom counts across externalising disorders (EXTs). RST explanatory power was pitted against reduced P300, a reliable indicator of externalising per previous research. We assessed 206 participants for DSM-5 EXTs (antisocial personality disorder, conduct disorder, attention-deficit/hyperactivity disorder, intermittent explosive disorder symptoms, alcohol use disorder, and cannabis use disorder). Of the final sample, 49% met diagnostic criteria for at least one of the EXTs. Electroencephalographic measures of the sensitivities of the behavioural activation system (BAS), the fight/flight/freeze system, and the behavioural inhibition system (BIS), as well as P300 were extracted from the gold bar-lemon and stop-signal tasks. As predicted, we found that low neural BIS sensitivity and low P300 were uniquely and negatively associated with our latent factor of externalising. Contrary to prediction, neural BAS/"dopamine" sensitivity was not associated with externalising. Our results provide empirical support for low BIS sensitivity and P300 as neural mechanisms common to disorders within the externalising spectrum; but, given the low N involved, future studies should seek to assess the replicability of our findings and, in particular, the differential involvement of the three RST systems.

Multiscale effective connectivity analysis of brain activity using neural ordinary differential equations.

Neural mechanisms and underlying directionality of signaling among brain regions depend on neural dynamics spanning multiple spatiotemporal scales of population activity. Despite recent advances in multimodal measurements of brain activity, there is no broadly accepted multiscale dynamical models for the collective activity represented in neural signals. Here we introduce a neurobiological-driven deep learning model, termed multiscale neural dynamics neural ordinary differential equation (msDyNODE), to describe multiscale brain communications governing cognition and behavior. We demonstrate that msDyNODE successfully captures multiscale activity using both simulations and electrophysiological experiments. The msDyNODE-derived causal interactions between recording locations and scales not only aligned well with the abstraction of the hierarchical neuroanatomy of the mammalian central nervous system but also exhibited behavioral dependences. This work offers a new approach for mechanistic multiscale studies of neural processes.

Evaluation of Acupuncture Efficacy in Modulating Brain Activity with Periodic-aperiodic EEG Measurements.

Acupuncture is an important therapeutic method of traditional Chinese medicine and can effectively modulate brain disorders. The therapeutic efficacy of acupuncture is hard to evaluate due to lacking of effective measurements of brain activity. In this work, we design an EEG-based monitoring system to evaluate therapeutic effect of acupuncture on human brain by extracting periodic-aperiodic features. Power spectral density is estimated to compute the adjusted power of periodic oscillatory rhythm in EEG under acupuncture stimulation. It is exhibited that the brain activity in alpha band (8-12 Hz) is significantly enhanced during acupuncture, especially in parietal and occipital lobe regions. To probe the modulatory effect of acupuncture on aperiodic brain activity, we calculate the aperiodic exponent based on the parameterization of EEG power spectra. The aperiodic exponent decreases along with acupuncture process, which is more significant in central and frontal lobe regions. Furthermore, sensitivity of different brain regions to acupuncture is assessed by the integration of adjusted power and aperiodic exponent. Experimental results demonstrate the effectiveness of proposed periodic-aperiodic measurements of EEG signals, by which different effects of four acupuncture manipulations are precisely evaluated and a knowledge graph is established. The monitoring system provides a new perspective to quantitatively evaluate acupuncture effect on human brain and improve its therapeutic efficacy in clinical applications for neural disorders.

Differences in Brain Activity During Real and Virtual Reality Motor Tasks in Normal Healthy Individuals.

This study aimed to clarify the differences between brain activity during virtual reality and real motor tasks. Twelve healthy adults participated in this study. Near-infrared spectroscopy (NIRS) was used to measure brain activity, and a total of 34 channels, 17 channels each, centred on the bilateral motor cortex, were used as measurement sites. Two types of motor tasks were used: a real Box and Block test (R-BBT) and a virtual reality Box and Block test (VR-BBT). In both motor tasks, an increase in oxy-haemoglobin (O2Hb) and a slight decrease in deoxy-haemoglobin (HHb) levels were observed in the central region of the participant's motor cortex. The O2Hb in the motor cortex during R-BBT increased at the beginning of the task, rapidly decreased, and remained at a low value. Conversely, the amount of O2Hb in the motor cortex during the VR-BBT remained high throughout the task. In addition, O2Hb in the dorsal prefrontal cortex during the VR-BBT was significantly higher than during the R-BBT. This study indicates that brain activity differs significantly between real and virtual reality motor tasks, even for similar tasks.