Functional near-infrared spectroscopy-based neurofeedback training regulates time-on-task effects and enhances sustained cognitive performance.

Time-on-task effect is a common consequence of long-term cognitive demand work, which reflects reduced behavioral performance and increases the risk of accidents. Neurofeedback is a neuromodulation method that can guide individuals to regulate their brain activity and manifest as changes in related symptoms and cognitive behaviors. This study aimed to examine the effects of functional near-infrared spectroscopy-based neurofeedback training on time-on-task effects and sustained cognitive performance. A randomized, single-blind, sham-controlled study was performed: 17 participants received feedback signals of their own dorsolateral prefrontal cortex activity (neurofeedback group), and 16 participants received feedback signals of dorsolateral prefrontal cortex activity from the neurofeedback group (sham-neurofeedback group). All participants received 5 neurofeedback training sessions and completed 2 sustained cognitive tasks, including a 2-back task and a psychomotor vigilance task, to evaluate behavioral performance changes following neurofeedback training. Results showed that neurofeedback relative to the sham-neurofeedback group exhibited increased dorsolateral prefrontal cortex activation, increased accuracy in the 2-back task, and decreased mean response time in the psychomotor vigilance task after neurofeedback training. In addition, the neurofeedback group showed slower decline performance during the sustained 2-back task after neurofeedback training compared with sham-neurofeedback group. These findings demonstrate that neurofeedback training could regulate time-on-task effects on difficult task and enhance performance on sustained cognitive tasks by increasing dorsolateral prefrontal cortex activity.

Anti-phasic oscillatory development for speech and noise processing in cochlear implanted toddlers.

Human brain demonstrates amazing readiness for speech and language learning at birth, but the auditory development preceding such readiness remains unknown. Cochlear implanted (CI) children (n = 67; mean age 2.77 year ± 1.31 SD; 28 females) with prelingual deafness provide a unique opportunity to study this stage. Using functional near-infrared spectroscopy, it was revealed that the brain of CI children was irresponsive to sounds at CI hearing onset. With increasing CI experiences up to 32 months, the brain demonstrated function, region and hemisphere specific development. Most strikingly, the left anterior temporal lobe showed an oscillatory trajectory, changing in opposite phases for speech and noise. The study provides the first longitudinal brain imaging evidence for early auditory development preceding speech acquisition.

Team-work, Team-brain: Exploring synchrony and team interdependence in a nine-person drumming task via multiparticipant hyperscanning and inter-brain network topology with fNIRS.

Teamwork is indispensable in human societies. However, due to the complexity of studying ecologically valid synchronous team actions, requiring multiple members and a range of subjective and objective measures, the mechanism underlying the impact of synchrony on team performance is still unclear. In this paper, we simultaneously measured groups of nine-participants' (total N = 180) fronto-temporal activations during a drum beating task using functional near infrared spectroscopy (fNIRS)-based hyperscanning and multi-brain network modeling, which can assess patterns of shared neural synchrony and attention/information sharing across entire teams. Participants (1) beat randomly without considering others' drumming (random condition), (2) actively coordinated their beats with the entire group without other external cue (team-focus condition), and (3) beat together based on a metronome (shared-focus condition). Behavioral data revealed higher subjective and objective measures of drum-beat synchronization in the team-focus condition, as well as higher felt interdependence. The fNIRS data revealed that participants in the team-focus condition also showed higher interpersonal neural synchronization (INS) and higher Global Network Efficiency in their left TPJ and mPFC. Higher left TPJ Global Network Efficiency also predicted higher actual synchrony in the team-focus condition, with an effect size roughly 1.5 times that of subjective measures, but not in the metronome-enabled shared-focus condition. This result suggests that shared mental representations with high efficiency of information exchange across the entire team may be a key component of synchrony, adding to the understanding of the actual relation to team work.

Transcranial brain atlas-based optimization for functional near-infrared spectroscopy optode arrangement: Theory, algorithm, and application.

The quality of optode arrangement is crucial for group imaging studies when using functional near-infrared spectroscopy (fNIRS). Previous studies have demonstrated the promising effectiveness of using transcranial brain atlases (TBAs), in a manual and intuition-based way, to guide optode arrangement when individual structural MRI data are unavailable. However, the theoretical basis of using TBA to optimize optode arrangement remains unclear, which leads to manual and subjective application. In this study, we first describe the theoretical basis of TBA-based optimization of optode arrangement using a mathematical framework. Second, based on the theoretical basis, an algorithm is proposed for automatically arranging optodes on a virtual scalp. The resultant montage is placed onto the head of each participant guided by a low-cost and portable navigation system. We compared our method with the widely used 10/20-system-assisted optode arrangement procedure, using finger-tapping and working memory tasks as examples of both low- and high-level cognitive systems. Performance, including optode montage designs, locations on each participant's scalp, brain activation, as well as ground truth indices derived from individual MRI data were evaluated. The results give convergent support for our method's ability to provide more accurate, consistent and efficient optode arrangements for fNIRS group imaging than the 10/20 method.

Functional near-infrared spectroscopy (fNIRS) as a tool to assist the diagnosis of major psychiatric disorders in a Chinese population.

Advances in neuroimaging have promised the development of specific and objective biomarkers for the diagnosis and treatment of psychiatric disorders. Recently, functional near-infrared spectroscopy (fNIRS) has been used during cognitive tasks to measure cortical dysfunction associated with mental illnesses such as Schizophrenia (SCH), Major-Depressive disorder (MD) and Bipolar Disorder (BD). We investigated the ability of fNIRS as a clinically viable tool to successfully distinguish healthy individuals from those with major psychiatric disorders. 316 patients with major psychiatric disorders (198 SCH/54 MD/64 BP) and 101 healthy controls were included in this study. Changes in oxygenated-hemoglobin during a Chinese language verbal fluency test were measured using a 52-channel fNIRS machine over the bilateral temporal and frontal lobe areas. We evaluated the ability of two task-evoked features selected from prior studies the Integral and Centroid values, to identify individuals with major diagnoses. Both the integral value of frontal and centroid value of temporal showed sensitivity in classifying individuals with mental disorders from healthy controls. However, using a combined index featuring both the integral value and centroid value to differentiate psychiatric disorders from healthy controls with an AUC of 0.913, differentiate individuals with mood disorders from healthy controls showed an AUC of 0.899, while for schizophrenia the AUC was 0.737. Our data suggest that fNIRS can be used as a candidate biomarker during differential diagnosis individuals with mood or psychosis disorders and offer a step towards individualization of treatment.

Targeting brain functions from the scalp: Transcranial brain atlas based on large-scale fMRI data synthesis.

Transcranial brain mapping techniques, such as functional near-infrared spectroscopy (fNIRS) and transcranial magnetic stimulation (TMS), have been playing an increasingly important role in studies of human brain functions. Given a brain function of interest, fNIRS probes and TMS coils should be properly placed on the scalp to ensure that the function is effectively measured or modulated. However, since brain activity is inside the skull and invisible to the researcher during placement, this blind targeting may cause the device to partially or completely miss the functional target, resulting in inconsistent experimental results and divergent clinical outcomes, especially when participants' structural MRI data are not available. To address this issue, we propose here a framework for targeting a designated function directly from the scalp. First, a functional brain atlas for the targeted brain function is constructed via a meta-analysis of large-scale functional magnetic resonance imaging datasets. Second, the functional brain atlas is presented on the scalp surface by using a transcranial mapping previously established from an structural MRI dataset (n â€‹= â€‹114), resulting in a novel functional transcranial brain atlas (fTBA). Finally, a low-cost, portable scalp-navigation system is used to localize the transcranial device on the individual's scalp with the guidance of the fTBA. To demonstrate the feasibility of the targeting framework, both fNIRS and TMS mapping experiments were conducted. The results show that fTBA-guided fNIRS positioning can detect functional activity with high sensitivity and specificity for working memory and motor systems; Moreover, compared with traditional TMS targeting approaches (e.g. the International 10-20 System and the conventional 5-cm rule), the fTBA suggested motor stimulation site is closesr to both the motor hotspot and the center of gravity of motor evoked potentials (MEP-COG). In summary, the proposed method unblinds the transcranial function targeting process using prior information, providing an effective and straightforward approach to transcranial brain mapping studies, especially those without participants' structural MRI data.

Assessing autism at its social and developmental roots: A review of Autism Spectrum Disorder studies using functional near-infrared spectroscopy.

We review a relatively new method for studying the developing brain in children and infants with Autism Spectrum Disorder (ASD). Despite advances in behavioral screening and brain imaging, due to paradigms that do not easily allow for testing of awake, very young, and socially-engaged children-i.e., the social and the baby brain-the biological underpinnings of this disorder remain a mystery. We introduce an approach based on functional near-infrared spectroscopy (fNIRS), which offers a noninvasive imaging technique for studying functional activations by measuring changes in the brain's hemodynamic properties. This further enables measurement of brain activation in upright, interactive settings, while maintaining general equivalence to fMRI findings. We review the existing studies that have used fNIRS for ASD, discussing their promise, limitations, and their technical aspects, gearing this study to the researcher who may be new to this technique and highlighting potential targets for future research.

Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility.

Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person's brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model's stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications.

Dielectric properties of urine in relation to bladder cancer.

Many studies have investigated the dielectric properties of human and animal tissues, particularly to differentiate between normal cells and tumors. However, these studies are invasive as tissue samples have to be excised to measure the properties. This study aims to investigate the dielectric properties of urine in relation to bladder cancer, which is safe and non-invasive to patients. 30 healthy subjects and 30 bladder cancer patients were recruited. Their urine samples were subjected to urinalysis and cytology assessment. A vector network analyzer was used to measure the dielectric constant (Ɛ') and loss factor (Ɛ″) at microwave frequencies of between 0.2 and 50 GHz at 25 °C, 30 °C and 37 °C. Significant differences in Ɛ' and Ɛ″ were observed between healthy subjects and patients, especially at frequencies of between 25 and 40 GHz at 25 °C. Bladder cancer patients had significant lower Ɛ' and higher Ɛ″ compared with healthy subjects. The Ɛ' was negatively correlated with urinary exfoliated urothelial cell number, and Ɛ″ was positively correlated. The study achieved a receiver operating characteristic area under curve (ROC-AUC) score of 0.69099 and an optimum accuracy of 75% with a sensitivity of 80% and a specificity of 70%. The number of exfoliated urothelial cell had significant effect on the dielectric properties, especially in bladder cancer patients. Urinary dielectric properties could potentially be used as a tool to detect bladder cancer.

Feasibility study of functional near-infrared spectroscopy in the ventral visual pathway for real-life applications.

Significance: fNIRS-based neuroenhancement depends on the feasible detection of hemodynamic responses in target brain regions. Using the lateral occipital complex (LOC) and the fusiform face area (FFA) in the ventral visual pathway as neurofeedback targets boosts performance in visual recognition. However, the feasibility of utilizing fNIRS to detect LOC and FFA activity in adults remains to be validated as the depth of these regions may exceed the detection limit of fNIRS. Aim: This study aims to investigate the feasibility of using fNIRS to measure hemodynamic responses in the ventral visual pathway, specifically in the LOC and FFA, in adults. Approach: We recorded the hemodynamic activities of the LOC and FFA regions in 35 subjects using a portable eight-channel fNIRS instrument. A standard one-back object and face recognition task was employed to elicit selective brain responses in the LOC and FFA regions. The placement of fNIRS optodes for LOC and FFA detection was guided by our group's transcranial brain atlas (TBA). Results: Our findings revealed selective activation of the LOC target channel (CH2) in response to objects, whereas the FFA target channel (CH7) did not exhibit selective activation in response to faces. Conclusions: Our findings indicate that, although fNIRS detection has limitations in capturing FFA activity, the LOC region emerges as a viable target for fNIRS-based detection. Furthermore, our results advocate for the adoption of the TBA-based method for setting the LOC target channel, offering a promising solution for optrode placement. This feasibility study stands as the inaugural validation of fNIRS for detecting cortical activity in the ventral visual pathway, underscoring its ecological validity. We suggest that our findings establish a pivotal technical groundwork for prospective real-life applications of fNIRS-based research.

A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge.

Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional near-infrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural self-regulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.

Neural synchronization during face-to-face communication.

Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-face dialog between partners but none during a back-to-back dialog, a face-to-face monologue, or a back-to-back monologue. Moreover, the neural synchronization between partners during the face-to-face dialog resulted primarily from the direct interactions between the partners, including multimodal sensory information integration and turn-taking behavior. The communicating behavior during the face-to-face dialog could be predicted accurately based on the neural synchronization level. These results suggest that face-to-face communication, particularly dialog, has special neural features that other types of communication do not have and that the neural synchronization between partners may underlie successful face-to-face communication.

Dynamic brain structural changes after left hemisphere subcortical stroke.

This study aimed to quantify dynamic structural changes in the brain after subcortical stroke and identify brain areas that contribute to motor recovery of affected limbs. High-resolution structural MRI and neurological examinations were conducted at five consecutive time points during the year following stroke in 10 patients with left hemisphere subcortical infarctions involving motor pathways. Gray matter volume (GMV) was calculated using an optimized voxel-based morphometry technique, and dynamic changes in GMV were evaluated using a mixed-effects model. After stroke, GMV was decreased bilaterally in brain areas that directly or indirectly connected with lesions, which suggests the presence of regional damage in these "healthy" brain tissues in stroke patients. Moreover, the GMVs of these brain areas were not correlated with the Motricity Index (MI) scores when controlling for time intervals after stroke, which indicates that these structural changes may reflect an independent process (such as axonal degeneration) but cannot affect the improvement of motor function. In contrast, the GMV was increased in several brain areas associated with motor and cognitive functions after stroke. When controlling for time intervals after stroke, only the GMVs in the cognitive-related brain areas (hippocampus and precuneus) were positively correlated with MI scores, which suggests that the structural reorganization in cognitive-related brain areas may facilitate the recovery of motor function. However, considering the small sample size of this study, further studies are needed to clarify the exact relationships between structural changes and recovery of motor function in stroke patients.

Transcranial magnetic stimulation mapping of the motor cortex: comparison of five estimation algorithms.

Background: There are currently five different kinds of transcranial magnetic stimulation (TMS) motor mapping algorithms available, from ordinary point-based algorithms to advanced field-based algorithms. However, there have been only a limited number of comparison studies conducted, and they have not yet examined all of the currently available algorithms. This deficiency impedes the judicious selection of algorithms for application in both clinical and basic neuroscience, and hinders the potential promotion of a potential superior algorithm. Considering the influence of algorithm complexity, further investigation is needed to examine the differences between fMRI peaks and TMS cortical hotspots that were identified previously. Methods: Twelve healthy participants underwent TMS motor mapping and a finger-tapping task during fMRI. The motor cortex TMS mapping results were estimated by five algorithms, and fMRI activation results were obtained. For each algorithm, the prediction error was defined as the distance between the measured scalp hotspot and optimized coil position, which was determined by the maximum electric field strength in the estimated motor cortex. Additionally, the study identified the minimum number of stimuli required for stable mapping. Finally, the location difference between the TMS mapping cortical hotspot and the fMRI activation peak was analyzed. Results: The projection yielded the lowest prediction error (5.27 ± 4.24 mm) among the point-based algorithms and the association algorithm yielded the lowest (6.66 ± 3.48 mm) among field-based estimation algorithms. The projection algorithm required fewer stimuli, possibly resulting from its suitability for the grid-based mapping data collection method. The TMS cortical hotspots from all algorithms consistently deviated from the fMRI activation peak (20.52 ± 8.46 mm for five algorithms). Conclusion: The association algorithm might be a superior choice for clinical applications and basic neuroscience research, due to its lower prediction error and higher estimation sensitivity in the deep cortical structure, especially for the sulcus. It also has potential applicability in various other TMS domains, including language area mapping and more. Otherwise, our results provide further evidence that TMS motor mapping intrinsically differs from fMRI motor mapping.

MNI2CPC: A probabilistic cortex-to-scalp mapping for non-invasive brain stimulation targeting.

BACKGROUND: Synthesis of neural imaging information from many studies is valuable for identifying stable cortical targets for non-invasive brain stimulation (NIBS). Typically, these targets are specified in Montreal Neurological Institute (MNI) standard brain space. However, in practical NIBS applications, localizing MNI cortical targets often relies on the International 10-20 system or heuristic scalp approaches, which often lacks precision or applies only to specific targets. OBJECTIVE/HYPOTHESIS: We aim to establish a probabilistic mapping from any cortical target in MNI space to continuous proportional coordinate (CPC) standard scalp space (MNI2CPC) and assess the performance of this mapping for NIBS targeting. METHODS: The MNI2CPC mapping was calculated based on a large MRI dataset (n = 114). Its targeting error was evaluated via cross-individual validation using a leave-one-out approach, as well as through independent validation across race (n = 27) and across patient (n = 58) cohorts. RESULTS: The cross-individual validation demonstrated targeting errors of 4.03 ± 0.69 mm on the scalp and 3.30 ± 0.59 mm in the cortex. For independent cohorts, targeting errors were 4.71 ± 0.81 mm (scalp) and 3.85 ± 0.64 mm (cortex) across race, and 4.66 ± 0.77 mm (scalp) and 3.77 ± 0.61 mm (cortex) across patient. We publish a free online tool to enable querying of the CPC coordinate for any given MNI cortical target. The resulting CPC coordinates enable rapid and accurate manual localization on the scalp in a user-friendly manner. CONCLUSIONS: The MNI2CPC mapping developed in this study allows for manual localization of any MNI cortical target, which improves the accessibility and ease of application of NIBS in diverse settings.

Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: a simultaneous recording study.

The feasibility of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (RSFC) has already been demonstrated. However the validity of fNIRS-based RSFC has rarely been studied. In the present study, fNIRS and fMRI data were simultaneously acquired from 21 subjects during the resting state. After the spatial correspondence was established between the two imaging modalities by transforming the fMRI data into fNIRS measurements space, the index of Between-Modality-Similarity (BMS) of RSFC was evaluated across multiple spatial scales. First, the RSFC between the bilateral primary motor ROI was quite similar between fNIRS and fMRI for all the subjects (BMS(ROI) = 0.95 ± 0.04 for HbO and BMS(ROI) = 0.86 ± 0.13 for HbR). Second, group-level sensorimotor RSFC maps (0.79 for HbO and 0.74 for HbR) showed higher between-modality similarity than individual-level RSFC maps (0.48 ± 0.16 for HbO and 0.41 ± 0.15 for HbR). Finally, for the first time, we combined fNIRS and graph theory to investigate topological properties of resting-state brain networks. The clustering coefficient (C(p)) and characteristic path length (L(p)) which are the most important network topological parameters, both showed high between-modality similarities (BMS(Cp) = 0.90 ± 0.03 for HbO and 0.90 ± 0.06 for HbR; BMS(Lp) = 0.92 ± 0.04 for HbO and 0.91 ± 0.05 for HbR). In summary, the converged results across all the spatial scales demonstrated that fNIRS is capable of providing comparable RSFC measures to fMRI, and thus provide direct evidence for the validity of the optical brain connectivity and the optical brain network approaches to functional brain integration during resting state.

Abnormal functional connectivity between the anterior cingulate and the default mode network in drug-naïve boys with attention deficit hyperactivity disorder.

A previous study indicated that adults with attention deficit hyperactivity disorder (ADHD) had a decreased anti-correlation between the dorsal anterior cingulate cortex (dACC) and the default mode network (DMN). In this study, we investigated whether children with ADHD also show a decreased anti-correlation between the dACC and the DMN. We also explored the developmental characteristics of the resting-state functional connectivity (RSFC) of the dACC with the DMN in children with ADHD. Resting-state functional magnetic resonance imaging scans were obtained from a 3T scanner in 19 drug-naïve boys with ADHD and 23 controls. Compared with normal controls, the dACC in boys with ADHD showed a significantly decreased negative RSFC with the DMN, including the dorsomedial prefrontal cortex and the posterior cingulate cortex. The RSFC strength between the dACC and the posterior cingulate cortex showed a significantly negative correlation with age in normal controls, but not in boys with ADHD. This decreased anti-correlation may suggest an abnormal balance or interaction between attentional and intrinsic thoughts. Our age-related analysis suggested an abnormal development pattern of the dACC-DMN interaction in ADHD.

Sex- and brain size-related small-world structural cortical networks in young adults: a DTI tractography study.

The anatomical connectivity of the human cerebral cortex resembles a "small-world" architecture, which is characterized by the coexistence of structurally segregated and integrative connectivity patterns. However, organizational differences in networks among individuals remain largely unknown. Here, we utilize diffusion tensor imaging tractography and graph-theoretical approaches to investigate the effects of sex and brain size on the topological organization of human cortical anatomical network. Weighted cortical networks were constructed from 72 young healthy participants by measuring anatomical connection densities between 78 cortical regions. As expected, all participants showed a small-world topology (high local clustering and short paths between nodes), which suggests a highly efficient topological organization. Furthermore, we found that females had greater local efficiencies than males. Moreover, smaller brains showed higher local efficiency in females but not in males, suggesting an interaction between sex and brain size. Specifically, we show that several brain regions (e.g., the precuneus, precentral gyrus, and lingual gyrus) had significant associations between nodal centrality and sex or brain size. Our findings suggest that anatomical network organization in the human brain is associated with sex and brain size and provide insights into the understanding of the structural substrates that underlie individual differences in behavior and cognition.

The Application of Sulfonyl Hydrazides in Electrosynthesis: A Review of Recent Studies.

Sulfonyl hydrazides are viewed as alternatives to sulfinic acids and their salts or sulfonyl halides, which are broadly used in organic synthesis or work as active pharmaceutical substances. Generally, sulfonyl hydrazides are considered good building blocks and show powerful value in a diverse range of reactions to construct C-S bonds or C-C bonds, and even C-N bonds as sulfur, carbon, or nitrogen sources, respectively. As a profound synthetic tool, the electrosynthesis method was recently used to achieve efficient and green applications of sulfonyl hydrazides. Interestingly, many unique and novel electrochemical syntheses using sulfonyl hydrazides as radical precursors have been developed, including cascade reactions, functionalization of heterocycles, as well as a continuous flow method combining with electrochemical synthesis since 2017. Accordingly, it is necessary to specifically summarize the recent developments of electrosynthesis with only sulfonyl hydrazides as radical precursors to more deeply understand and better design novel electrochemical synthesis reactions. Herein, electrosynthesis research using sulfonyl hydrazides as radical precursors since 2017 is reviewed in detail based on the chemical structures of products and reaction mechanisms.

Increased Inertia Triggers Linear Responses in Motor Cortices during Large-Extent Movements-A fNIRS Study.

Activities of daily living consist of accurate, coordinated movements, which require the upper limbs to constantly interact with environmental loads. The magnitude of the load was shown to affect kinematic outcomes in healthy subjects. Moreover, the increase in load facilitates the recovery of motor function in patients with neurological disorders. Although Brodmann Areas 4 and 6 were found to be active during loaded movements, it remains unclear whether stronger activation can be triggered simply by increasing the load magnitude. If such a linear relationship exists, it may provide a basis for the closed-loop adjustment of treatment plans in neurorehabilitation. Fourteen healthy participants were instructed to lift their hands to their armpits. The movements were grouped in blocks of 25 s. Each block was assigned a magnitude of inertial loads, either 0 pounds (bare hand), 3 pounds, or 15 pounds. Hemodynamic fNIRS signals were recorded throughout the experiment. Both channel-wise and ROI-wise analyses found significant activations against all three magnitudes of inertia. The generalized linear model revealed significant increases in the beta coefficient of 0.001673/pound in BA4 and 0.001338/pound in BA6. The linear trend was stronger in BA6 (conditional r2 = 0.9218) than in BA4 (conditional r2 = 0.8323).