Electroencephalography as a Biomarker for Functional Recovery in Spinal Cord Injury Patients

A neural signature for brain compensation in stroke with EEG and TMS: Insights from the DEFINE cohort study

OBJECTIVE

This study aimed to explore the relationships between potential neurophysiological biomarkers and upper limb motor function recovery in stroke patients, specifically focusing on combining two neurophysiological markers: electroencephalography (EEG) and transcranial magnetic stimulation (TMS).

METHODS

This cross-sectional study analyzed neurophysiological, clinical, and demographical data from 102 stroke patients from the DEFINE cohort. We searched for correlations of EEG and TMS measurements combined to build a prediction model for upper limb motor functionality, assessed by five outcomes, across five assessments: Fugl-Meyer Assessment (FMA), Handgrip Strength Test (HST), Finger Tapping Test (FTT), Nine-Hole Peg Test (9HPT), and Pinch Strength Test (PST).

RESULTS

Our multivariate models agreed on a specific neural signature: higher EEG Theta/Alpha ratio in the frontal region of the lesioned hemisphere is associated with poorer motor outcomes, while increased MEP amplitude in the non-lesioned hemisphere correlates with improved motor function. These relationships are held across all five motor assessments, suggesting the potential of these neurophysiological measures as recovery biomarkers.

CONCLUSION

Our findings indicate a potential neural signature of brain compensation in which lower frequencies of EEG power are increased in the lesioned hemisphere, and lower corticospinal excitability is also increased in the non-lesioned hemisphere. We discuss the meaning of these findings in the context of motor recovery in stroke.

Electrophysiology Methods for Assessing of Neurodegenerative and Post-Traumatic Processes as Applied to Translational Research

Electrophysiological studies have long established themselves as reliable methods for assessing the functional state of the brain and spinal cord, the degree of neurodegeneration, and evaluating the effectiveness of therapy. In addition, they can be used to diagnose, predict functional outcomes, and test the effectiveness of therapeutic and rehabilitation programs not only in clinical settings, but also at the preclinical level. Considering the urgent need to develop potential stimulators of neuroregeneration, it seems relevant to obtain objective data when modeling neurological diseases in animals. Thus, in the context of the application of electrophysiological methods, not only the comparison of the basic characteristics of bioelectrical activity of the brain and spinal cord in humans and animals, but also their changes against the background of neurodegenerative and post-traumatic processes are of particular importance. In light of the above, this review will contribute to a better understanding of the results of electrophysiological assessment in neurodegenerative and post-traumatic processes as well as the possibility of translating these methods from model animals to humans.

OPRM1 and BDNF polymorphisms associated with a compensatory neurophysiologic signature in knee osteoarthritis patients

OBJECTIVE

The present study investigated the relationship between three genetic polymorphisms of OPRM1 (rs1799971 - A118G and rs1799972 - C17T) and BDNF (rs6265 - C196T) and EEG-measured brain oscillations in Knee Osteoarthritis (KOA) patients.

MATERIALS AND METHODS

We performed a cross-sectional analysis of a cohort study (DEFINE cohort), KOA arm, with 66 patients, considering demographic (age, sex, and education), clinical (pain intensity and duration), OPRM1 (rs1799971 - A118G and rs1799972 - C17T) and BDNF (rs6265 - C196T) genotypes, and electrophysiological measures. Brain oscillations relative power from Delta, Theta, Alpha, Low Alpha, High Alpha, Beta, Low Beta and High Beta oscillations were measured during resting state EEG. Multivariate regression models were used to explore the main brain oscillation predictors of the three genetic polymorphisms.

RESULTS

Our findings demonstrate that Theta and Low Beta oscillations are associated with the variant allele of OPRM1-rs1799971 (A118G) on left frontal and left central regions, respectively, while Alpha brain oscillation is associated with variant genotypes (CT/TT) of BDNF-rs6265 on frontal (decrease of oscillation power) and left central (increase of oscillation power) regions. No significant model was found for OPRM1-rs1799972 (C17T) in addition to the inclusion of pain intensity as a significant predictor of this last model.

CONCLUSION

One potential interpretation for these findings is that polymorphisms of OPRM1 - that is involved with endogenous pain control - lead to increased compensatory oscillatory mechanisms, characterized by increased theta oscillations. Along the same line, polymorphisms of the BDNF lead to decreased alpha oscillations in the frontal area, likely also reflecting the disruption of resting states to also compensate for the increased injury associated with knee OA. It is possible that these polymorphisms require additional brain adaption to the knee OA related injury.

Aided diagnosis of cervical spondylotic myelopathy using deep learning methods based on electroencephalography

Cervical spondylotic myelopathy (CSM) is the most severe type of cervical spondylosis. It is challenging to achieve early diagnosis with current clinical diagnostic tools. In this paper, we propose an end-to-end deep learning approach for early diagnosis of CSM. Electroencephalography (EEG) experiments were conducted with patients having spinal cord cervical spondylosis and age-matched normal subjects. A Convolutional Neural Network with Long Short-Term Memory Networks (CNN-LSTM) model was employed for the classification of patients versus normal individuals. In contrast, a Convolutional Neural Network with Bidirectional Long Short-Term Memory Networks and attention mechanism (CNN-BiLSTM-attention) model was used to classify regular, mild, and severe patients. The models were trained using focal Loss instead of traditional cross-entropy Loss, and cross-validation was performed. Our method achieved a classification accuracy of 92.5 % for the two-class classification among 40 subjects and 72.2 % for the three-class classification among 36 subjects. Furthermore, we observed that the proposed model outperformed traditional EEG decoding models. This paper presents an effective computer-aided diagnosis method that eliminates the need for manual extraction of EEG features and holds potential for future auxiliary diagnosis of spinal cord-type cervical spondylosis.

From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems?

We examine the challenging "marriage" between computational efficiency and biological plausibility-A crucial node in the domain of spiking neural networks at the intersection of neuroscience, artificial intelligence, and robotics. Through a transdisciplinary review, we retrace the historical and most recent constraining influences that these parallel fields have exerted on descriptive analysis of the brain, construction of predictive brain models, and ultimately, the embodiment of neural networks in an enacted robotic agent. We study models of Spiking Neural Networks (SNN) as the central means enabling autonomous and intelligent behaviors in biological systems. We then provide a critical comparison of the available hardware and software to emulate SNNs for investigating biological entities and their application on artificial systems. Neuromorphics is identified as a promising tool to embody SNNs in real physical systems and different neuromorphic chips are compared. The concepts required for describing SNNs are dissected and contextualized in the new no man's land between cognitive neuroscience and artificial intelligence. Although there are recent reviews on the application of neuromorphic computing in various modules of the guidance, navigation, and control of robotic systems, the focus of this paper is more on closing the cognition loop in SNN-embodied robotics. We argue that biologically viable spiking neuronal models used for electroencephalogram signals are excellent candidates for furthering our knowledge of the explainability of SNNs. We complete our survey by reviewing different robotic modules that can benefit from neuromorphic hardware, e.g., perception (with a focus on vision), localization, and cognition. We conclude that the tradeoff between symbolic computational power and biological plausibility of hardware can be best addressed by neuromorphics, whose presence in neurorobotics provides an accountable empirical testbench for investigating synthetic and natural embodied cognition. We argue this is where both theoretical and empirical future work should converge in multidisciplinary efforts involving neuroscience, artificial intelligence, and robotics.

A Narrative Review on Multi-Domain Instrumental Approaches to Evaluate Neuromotor Function in Rehabilitation

In clinical scenarios, the use of biomedical sensors, devices and multi-parameter assessments is fundamental to provide a comprehensive portrait of patients' state, in order to adapt and personalize rehabilitation interventions and support clinical decision-making. However, there is a huge gap between the potential of the multidomain techniques available and the limited practical use that is made in the clinical scenario. This paper reviews the current state-of-the-art and provides insights into future directions of multi-domain instrumental approaches in the clinical assessment of patients involved in neuromotor rehabilitation. We also summarize the main achievements and challenges of using multi-domain approaches in the assessment of rehabilitation for various neurological disorders affecting motor functions. Our results showed that multi-domain approaches combine information and measurements from different tools and biological signals, such as kinematics, electromyography (EMG), electroencephalography (EEG), near-infrared spectroscopy (NIRS), and clinical scales, to provide a comprehensive and objective evaluation of patients' state and recovery. This multi-domain approach permits the progress of research in clinical and rehabilitative practice and the understanding of the pathophysiological changes occurring during and after rehabilitation. We discuss the potential benefits and limitations of multi-domain approaches for clinical decision-making, personalized therapy, and prognosis. We conclude by highlighting the need for more standardized methods, validation studies, and the integration of multi-domain approaches in clinical practice and research.

Analysis of temperaturepain sensitivity in patients with consequences of the cervical spinal cord injury

Background. The standard neurological assessment in patients with long-term consequences of spine-and-spinal cord injury and severe neurological deficit does not allow to accurately identify changes in sensitivity that determine the level, degree and nature of spinal cord injury, as well as to evaluate the minimal dynamics of these disorders with different treatment options. As a result, an objective instrumental assessment of the sensory sphere in the long-term period of spinal cord injury has not lost its relevance.The aim. To conduct an instrumental study of the temperature-pain sensitivity condition in patients with partial gross damage to the cervical spinal cord in the long-term period of the disease (type B on the ASIA scale).Methods. We examined 23 patients with consequences of vertebral fractures of the cervical spine in the late period of traumatic spinal cord disease, Grade B on the ASIA scale ASIA. The clinical analysis of sensitive disorders was performed according to ISNCSCI and ASIA scales. While studying the temperature-pain sensitivity the threshold of thermal sensitivity and the threshold of pain from hot were determined in СIV–SI dermatomes on the right and on the left using an electricesthesiometer.Results. The examined patients had hypesthesia of heat and pain sensitivity, hyperesthesia of pain sensitivity, thermoanesthesia and thermoanalgesia. The degree of changes in the temperature-pain sensitivity depended on the topographic localization of dermatomes. The more distally the study area was located from the level of damage, the more pronounced the disorders were. In 30.4 % of patients, the pain sensitivity from hot in the chain of dermatomes from CIV to SI was preserved on at least one side. The combination of thermoanesthesia with thermoanalgesia was observed in 69.6 % of cases in dermatomes with ThVII and distally.Conclusions. The instrumentally registered level of the temperature-pain sensitivity disorder did not correspond to clinically determined localization of sensory disorders. The range of discrepancy ranged from 2 to 12 dermatomes, with defining the sensitivity subclinical deficit over the area of clinical sensory disorders.