The integration of emotional intelligence in machines is an important step in advancing human-computer interaction. This demands the development of reliable end-to-end emotion recognition systems. However, the scarcity of public affective datasets presents a challenge. In this literature review, we emphasize the use of generative models to address this issue in neurophysiological signals, particularly Electroencephalogram (EEG) and Functional Near-Infrared Spectroscopy (fNIRS). We provide a comprehensive analysis of different generative models used in the field, examining their input formulation, deployment strategies, and methodologies for evaluating the quality of synthesized data. This review serves as a comprehensive overview, offering insights into the advantages, challenges, and promising future directions in the application of generative models in emotion recognition systems. Through this review, we aim to facilitate the progression of neurophysiological data augmentation, thereby supporting the development of more efficient and reliable emotion recognition systems.

UNASSIGNED: The purpose of this study was to examine the extent of the literature on the neurophysiological lesion as referenced in functional neurology.
UNASSIGNED: A literature search was performed within the period from 2010 to March 2021. Search terms included central sensitization, central sensitivity syndrome, nociplastic pain, cold hyperalgesia, heat hyperalgesia, mechanical hyperalgesia, dynamic mechanical allodynia, temporal summation, spatial summation, and descending inhibition. A qualitative synthesis summarized the research findings, including clinical conditions and effect of spinal manipulation.
UNASSIGNED: There were 30 studies, which included 7 high-level studies (meta-analysis or systematic reviews), 22 randomized controlled studies, and 1 scoping review. The findings suggest the existence of the changes in the central integrated state of a population of neurons with various disorders, experimentally induced stimulation, and treatment. The current literature suggests plasticity of the central integrative state (CIS) with the onset of pathologies and the changes in the CIS with different conservative nonpharmacologic treatments.
UNASSIGNED: This review suggests changes in the resting state of the CIS of a population of neurons that exist in the physiologic lesion may change in response to various therapies, including manipulative therapy. The findings from this review provide support of the hypothesis that nonpharmacologic conservative care may affect the neurophysiological lesion. However, studies were heterogeneous and evidence was lacking in the translation of targeting the therapies to distinct neuronal areas for clinical outcomes to treat specific disease states.

Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural mechanisms of sustained attention with computational models to facilitate research and application. Although many studies have assessed attention, the evaluation of humans\' sustained attention is not sufficiently comprehensive. Hence, this study provides a current review on both neural mechanisms and computational models of visual sustained attention. We first review models, measurements, and neural mechanisms of sustained attention and propose plausible neural pathways for visual sustained attention. Next, we analyze and compare the different computational models of sustained attention that the previous reviews have not systematically summarized. We then provide computational models for automatically detecting vigilance states and evaluation of sustained attention. Finally, we outline possible future trends in the research field of sustained attention.

The classical Hodgkin-Huxley (HH) point-neuron model of action potential generation is four-dimensional. It consists of four ordinary differential equations describing the dynamics of the membrane potential and three gating variables associated to a transient sodium and a delayed-rectifier potassium ionic currents. Conductance-based models of HH type are higher-dimensional extensions of the classical HH model. They include a number of supplementary state variables associated with other ionic current types, and are able to describe additional phenomena such as subthreshold oscillations, mixed-mode oscillations (subthreshold oscillations interspersed with spikes), clustering and bursting. In this manuscript we discuss biophysically plausible and phenomenological reduced models that preserve the biophysical and/or dynamic description of models of HH type and the ability to produce complex phenomena, but the number of effective dimensions (state variables) is lower. We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.

The superconducting Josephson junction shows spiking and bursting behaviors, which have similarities with neuronal spiking and bursting. This phenomenon had been observed long ago by some researchers; however, they overlooked the biological similarity of this particular dynamical feature and never attempted to interpret it from the perspective of neuronal dynamics. In recent times, the origin of such a strange property of the superconducting junction has been explained and such neuronal functional behavior has also been observed in superconducting nanowires. The history of this research is briefly reviewed here with illustrations from studies of two junction models and their dynamical interpretation in the sense of biological bursting.

Coronavirus disease 2019 (COVID-19) is a devastating viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The incidence and mortality of COVID-19 patients have been increasing at an alarming rate. The mortality is much higher in older individuals, especially the ones suffering from respiratory distress, cardiac abnormalities, renal diseases, diabetes, and hypertension. Existing evidence demonstrated that SARS-CoV-2 makes its entry into human cells through angiotensin-converting enzyme 2 (ACE-2) followed by the uptake of virions through cathepsin L or transmembrane protease serine 2 (TMPRSS2). SARS-CoV-2-mediated abnormalities in particular cardiovascular and neurological ones and the damaged coagulation systems require extensive research to develop better therapeutic modalities. As SARS-CoV-2 uses its S-protein to enter into the host cells of several organs, the S-protein of the virus is considered as the ideal target to develop a potential vaccine. In this review, we have attempted to highlight the landmark discoveries that lead to the development of various vaccines that are currently under different stages of clinical progression. Besides, a brief account of various drug candidates that are being tested to mitigate the burden of COVID-19 was also covered. Further, in a dedicated section, the impact of SARS-CoV-2 infection on neuronal inflammation and neuronal disorders was discussed. In summary, it is expected that the content covered in this article help to understand the pathophysiology of COVID-19 and the impact on neuronal complications induced by SARS-CoV-2 infection while providing an update on the vaccine development.

Electrical nerve fiber stimulation is a technique widely used in prosthetics and rehabilitation, and its study from a computational point of view can be a useful instrument to support experimental tests. In the last years, there was an increasing interest in computational modeling of neural cells and numerical simulations on nerve fibers stimulation because of its usefulness in forecasting the effect of electrical current stimuli delivered to tissues through implanted electrodes, in the design of optimal stimulus waveforms based on the specific application (i.e., inducing limb movements, sensory feedback or physiological function restoring), and in the evaluation of the current stimuli properties according to the characteristics of the nerves surrounding tissue. Therefore, a review study on the main modeling and computational frameworks adopted to investigate peripheral nerve stimulation is an important instrument to support and drive future research works. To this aim, this paper deals with mathematical models of neural cells with a detailed description of ion channels and numerical simulations using finite element methods to describe the dynamics of electrical stimulation by implanted electrodes in peripheral nerve fibers. In particular, we evaluate different nerve cell models considering different ion channels present in neurons and provide a guideline on multiscale numerical simulations of electrical nerve fibers stimulation.

Burn survivors experience myriad associated symptoms such as pain, pruritus, fatigue, impaired motor strength, post-traumatic stress, depression, anxiety, and sleep disturbance. Many of these symptoms are common and remain chronic, despite current standard of care. One potential novel intervention to target these post burn symptoms is transcranial direct current stimulation (tDCS). tDCS is a non-invasive brain stimulation (NIBS) technique that modulates neural excitability of a specific target or neural network. The aim of this work is to review the neural circuits of the aforementioned clinical sequelae associated with burn injuries and to provide a scientific rationale for specific NIBS targets that can potentially treat these conditions. We ran a systematic review, following the PRISMA statement, of tDCS effects on burn symptoms. Only three studies matched our criteria. One was a feasibility study assessing cortical plasticity in chronic neuropathic pain following burn injury, one looked at the effects of tDCS to reduce pain anxiety during burn wound care, and one assessed the effects of tDCS to manage pain and pruritus in burn survivors. Current literature on NIBS in burn remains limited, only a few trials have been conducted. Based on our review and results in other populations suffering from similar symptoms as patients with burn injuries, three main areas were selected: the prefrontal region, the parietal area and the motor cortex. Based on the importance of the prefrontal cortex in the emotional component of pain and its implication in various psychosocial symptoms, targeting this region may represent the most promising target. Our review of the neural circuitry involved in post burn symptoms and suggested targeted areas for stimulation provide a spring board for future study initiatives.

The past 25 years have seen a strong increase in the number of publications related to criticality in different areas of neuroscience. The potential of criticality to explain various brain properties, including optimal information processing, has made it an increasingly exciting area of investigation for neuroscientists. Recent reviews on this topic, sometimes termed brain criticality, make brief mention of clinical applications of these findings to several neurological disorders such as epilepsy, neurodegenerative disease, and neonatal hypoxia. Other clinicallyrelevant domains - including anesthesia, sleep medicine, developmental-behavioral pediatrics, and psychiatry - are seldom discussed in review papers of brain criticality. Thorough assessments of these application areas and their relevance for clinicians have also yet to be published. In this scoping review, studies of brain criticality involving human data of all ages are evaluated for their current and future clinical relevance. To make the results of these studies understandable to a more clinical audience, a review of the key concepts behind criticality (e.g., phase transitions, long-range temporal correlation, self-organized criticality, power laws, branching processes) precedes the discussion of human clinical studies. Open questions and forthcoming areas of investigation are also considered.

The global pandemic of novel coronavirus disease 2019 (COVID-19) has taken the entire human race by surprise and led to an unprecedented number of mortalities worldwide so far. Current clinical studies have interpreted that angiotensin-converting enzyme 2 (ACE2) is the host receptor for severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). In addition, ACE2 is the major component of the renin-angiotensin system. ACE2 deteriorates angiotensin II, a peptide that is responsible for the promotion of stroke. The downregulation of ACE2 further activates an immunological cascade. Thus, researchers need to explore and examine the possible links between COVID-19 and ischemic stroke (IS). Human ACE2 expression level and pattern in various tissues might be decisive for the vulnerability, symptoms, and treatment outcomes of the SARS-CoV-2 infection. The swift increase in the knowledge of SARS-CoV-2 has given creditable evidence that SARS-CoV-2 infected patients also encounter neurological deficits. As the SARS-CoV-2 binds to ACE2, it will hamper the activity of ACE2 in providing neuroprotection, especially in the case of stroke patients. Due to the downregulation of ACE2, the inflammatory response is activated in the ischemic penumbra. The COVID-19 pandemic has affected people with various pre-existing diseases, including IS, in such a way that these patients need special care and attention for their survival. Several clinical trials are currently ongoing worldwide as well as many other projects are in different stages of conceptualization and planning to facilitate the effective management of stroke patients with COVID-19 infection.