Causal connectivity from right DLPFC to IPL in schizophrenia patients: a pilot study

Functional near-infrared spectroscopy in non-invasive neuromodulation

ABSTRACT

Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks, which have been widely applied in the field of central neurological diseases, such as stroke, Parkinson's disease, and mental disorders. Although significant advances have been made in neuromodulation technologies, the identification of optimal neurostimulation parameters including the cortical target, duration, and inhibition or excitation pattern is still limited due to the lack of guidance for neural circuits. Moreover, the neural mechanism underlying neuromodulation for improved behavioral performance remains poorly understood. Recently, advancements in neuroimaging have provided insight into neuromodulation techniques. Functional near-infrared spectroscopy, as a novel non-invasive optical brain imaging method, can detect brain activity by measuring cerebral hemodynamics with the advantages of portability, high motion tolerance, and anti-electromagnetic interference. Coupling functional near-infrared spectroscopy with neuromodulation technologies offers an opportunity to monitor the cortical response, provide real-time feedback, and establish a closed-loop strategy integrating evaluation, feedback, and intervention for neurostimulation, which provides a theoretical basis for development of individualized precise neurorehabilitation. We aimed to summarize the advantages of functional near-infrared spectroscopy and provide an overview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation, transcranial electrical stimulation, neurofeedback, and brain-computer interfaces. Furthermore, the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are summarized. In conclusion, functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central neural reorganization to achieve better functional recovery from central nervous system diseases.

Instantaneous effects of prefrontal transcranial magnetic stimulation on brain oxygenation: A systematic review

This systematic review investigates how prefrontal transcranial magnetic stimulation (TMS) immediately influences neuronal excitability based on oxygenation changes measured by functional magnetic resonance imaging (fMRI) or functional near-infrared spectroscopy (fNIRS). A thorough understanding of TMS-induced excitability changes may enable clinicians to adjust TMS parameters and optimize treatment plans proactively. Five databases were searched for human studies evaluating brain excitability using concurrent TMS/fMRI or TMS/fNIRS. Thirty-seven studies (13 concurrent TMS/fNIRS studies, 24 concurrent TMS/fMRI studies) were included in a qualitative synthesis. Despite methodological inconsistencies, a distinct pattern of activated nodes in the frontoparietal central executive network, the cingulo-opercular salience network, and the default-mode network emerged. The activated nodes included the prefrontal cortex (particularly dorsolateral prefrontal cortex), insula cortex, striatal regions (especially caudate, putamen), anterior cingulate cortex, and thalamus. High-frequency repetitive TMS most consistently induced expected facilitatory effects in these brain regions. However, varied stimulation parameters (e.g., intensity, coil orientation, target sites) and the inter- and intra-individual variability of brain state contribute to the observed heterogeneity of target excitability and co-activated regions. Given the considerable methodological and individual variability across the limited evidence, conclusions should be drawn with caution.

Combining transcranial magnetic stimulation with training to improve social cognition impairment in schizophrenia: a pilot randomized controlled trial

Schizophrenia is a severe, chronic mental disorder that profoundly impacts patients' everyday lives. The illness's core features include positive and negative symptoms and cognitive impairments. In particular, deficits in the social cognition domain showed a tighter connection to patients' everyday functioning than the other symptoms. Social remediation interventions have been developed, providing heterogeneous results considering the possibility of generalizing the acquired improvements in patients' daily activities. In this pilot randomized controlled trial, we investigated the feasibility of combining fifteen daily cognitive and social training sessions with non-invasive brain stimulation to boost the effectiveness of the two interventions. We delivered intermittent theta burst stimulation (iTBS) over the left dorsolateral prefrontal cortex (DLPFC). Twenty-one patients were randomized into four groups, varying for the assigned stimulation condition (real vs. sham iTBS) and the type of cognitive intervention (training vs. no training). Clinical symptoms and social cognition tests were administered at five time points, i.e., before and after the treatment, and at three follow-ups at one, three, and six months after the treatments' end. Preliminary data show a trend in improving the competence in managing emotion in participants performing the training. Conversely, no differences were found in pre and post-treatment scores for emotion recognition, theory of mind, and attribution of intentions scores. The iTBS intervention did not induce additional effects on individuals' performance. The methodological approach's novelty and limitations of the present study are discussed.

Impacts of complex electromagnetic radiation and low-frequency noise exposure conditions on the cognitive function of operators

Background

Both electromagnetic radiation (EMR) and low-frequency noise (LFN) are widespread and influential environmental factors, and operators are inevitably exposed to both EMR and LFN within a complex exposure environment. The potential adverse effects of such exposure on human health must be considered seriously. This study aimed to investigate the effects of EMR and LFN on cognitive function as well as their interaction effect, which remain unclear.

Methods

Sixty young male college students were randomly grouped and experiments were conducted with a 2 × 2 factorial design in a shielded chamber. Mental workload (MWL) levels of the study subjects were measured and assessed using the NASA-task load index (TLX) subjective scale, an n-back task paradigm, and the functional near-infrared spectroscopy (fNIRS) imaging technique.

Results

For the 3-back task, the NASA-TLX subjective scale revealed a statistically significant main effect of LFN intensity, which enhanced the subjects' MWL level (F = 8.716, p < 0.01). Behavioral performance revealed that EMR intensity (430.1357 MHz, 10.75 W/m²) and LFN intensity (0-200 Hz, 72.9 dB) had a synergistic interaction effect, and the correct response time was statistically significantly prolonged by the combined exposure (F = 4.343, p < 0.05). The fNIRS imaging technique revealed a synergistic interaction effect between operational EMR intensity and operational LFN intensity, with statistically significant effects on the activation levels in the left and right dorsolateral prefrontal cortex (DLPFC). The mean β values of DLPFC were significantly increased (L-DLPFC F = 5.391, p < 0.05, R-DLPFC F = 4.222, p < 0.05), and the relative concentrations of oxyhemoglobin in the DLPFC were also significantly increased (L-DLPFC F = 4.925, p < 0.05, R-DLPFC F = 9.715, p < 0.01).

Conclusion

We found a statistically significant interaction effect between EMR (430.1357 MHz, 10.75 W/m²) and LFN (0-200 Hz, 72.9 dB) when simultaneously exposing subjects to both for 30 min. We conclude that exposure to this complex environment can cause a statistically significant increase in the MWL level of operators, and even alterations in their cognitive function.

Altered nonlinear Granger causality interactions in the large-scale brain networks of patients with schizophrenia

Objective.It has been demonstrated that schizophrenia (SZ) is characterized by functional dysconnectivity involving extensive brain networks. However, the majority of previous studies utilizing resting-state functional magnetic resonance imaging (fMRI) to infer abnormal functional connectivity (FC) in patients with SZ have focused on the linear correlation that one brain region may influence another, ignoring the inherently nonlinear properties of fMRI signals.Approach. In this paper, we present a neural Granger causality (NGC) technique for examining the changes in SZ's nonlinear causal couplings. We develop static and dynamic NGC-based analyses of large-scale brain networks at several network levels, estimating complicated temporal and causal relationships in SZ patients.Main results. We find that the NGC-based FC matrices can detect large and significant differences between the SZ and healthy control groups at both the regional and subnetwork scales. These differences are persistent and significantly overlapped at various network sparsities regardless of whether the brain networks were built using static or dynamic techniques. In addition, compared to controls, patients with SZ exhibited extensive NGC confusion patterns throughout the entire brain.Significance. These findings imply that the NGC-based FCs may be a useful method for quantifying the abnormalities in the causal influences of patients with SZ, hence shedding fresh light on the pathophysiology of this disorder.