• Introduction: The differentiation of voluntary and involuntary movements represents a crucial challenge for observers, particularly providers who face the behaviors in an emergency.
• Methods: An algorithm is developed to classify movements as voluntary or involuntary are identified. Red flags to identify movements that require treatment or restraint are presented.

• Results and Discussion:

Involuntary movements include the broad class of movement disorders, including (A) movement disorders with identified pathophysiology and (B) functional movement disorders, a wide variety of movements that may or may not resemble movement disorders with identified pathophysiology.

Voluntary movements include (A) motions deliberately performed by persons to express exuberance such as applause and zaghrouta and (B) motions deliberately performed by persons to deceive others, such as (A) malingering, the fabrication of actions in order to avoid jail, work, school, and to obtain financial and other rewards, and (B) Münchausen syndrome, the fabrication of symptoms and signs to seek medical attention and treatment. Identification of functional movement disorders and fabricated voluntary movements is crucial to avoid providing inappropriate interventions, such as medications and surgeries with significant risks and no beneficial effects.

Electrophysiological and motion measurements may facilitate the identification of voluntary movements. For example, a Bereitschaftspotential, a surface-negative electrical brain potential identified on electroencephalograph (EGG), can identify self-initiated voluntary acts.

• Conclusions

Neuroscientists can benefit from the proposed algorithm to differentiate voluntary and involuntary movements particularly in emergent situations to determine when interventions are required and contraindicated.

The imbalance between the speed and accuracy of cognitive-motor operations can lead to the formation of abnormal behavioral programs fraught with serious negative consequences for the individual. For successful correction and prevention of social disadaptation in adolescents with nervous and mental diseases and functional disorders in mental sphere in general education schools, the peculiarities of their psychomotor activity should be taken into account.

We measured some parameters of psychomotor coordination in adolescents, students of a specialized school for psychiatric patients in remission. Based on their medical records, these students were divided into two groups: adolescents with neuropsychiatric diagnoses and sequelae of organic brain damage (n = 37) and adolescents with mental disorders without organic brain damage (n = 28). The control group consisted of healthy adolescents from a secondary school (n = 70). During simple motor tests, the trajectory of horizontal movement of the arm "from elbow to fingers" was recorded. During cyclic (right – left) movements of the lever within the range marked by external light markers, adolescents with mental disorders from both groups showed higher speed, but poorer accuracy and smoothness of movements than healthy participants. The latencies of the sensorimotor response to light and acoustic stimuli in adolescents with mental disorders without organic brain damage were longer than in the control group. These results are included in a comprehensive database for large-scale health monitoring in schoolchildren.

Background

Intraoperative ultrasound (ioUS) images of brain tumors contain information that has not yet been exploited. The present work aims to analyze images in both B-mode and strain-elastography using techniques based on artificial intelligence and radiomics. We pretend to assess the capacity for differentiating glioblastomas (GBM) from solitary brain metastases (SBM) and also to assess the ability to predict the overall survival (OS) in GBM.

Methods

We performed a retrospective analysis of patients who underwent craniotomy between March 2018 to June 2020 with GBM and SBM diagnoses. Cases with an ioUS study were included. In the first group of patients, an analysis based on deep learning was performed. An existing neural network (Inception V3) was used to classify tumors into GBM and SBM. The models were evaluated using the area under the curve (AUC), classification accuracy, and precision. In the second group, radiomic features from the tumor region were extracted. Radiomic features associated with OS were selected employing univariate correlations. Then, a survival analysis was conducted using Cox regression.

Results

For the classification task, a total of 36 patients were included. 26 GBM and 10 SBM. Models were built using a total of 812 ultrasound images. For B-mode, AUC and accuracy values of the classification algorithms ranged from 0.790 to 0.943 and from 72 to 89 % respectively. For elastography, AUC and accuracy values ranged from 0.847 to 0.985 and from 79 to 95 % respectively. Sixteen patients were available for the survival analysis. A total of 52 radiomic features were extracted. Two texture features from B-mode (Conventional mean and GLZLM_SZLGE) and one texture feature from strain-elastography (GLZLM_LZHGE) were significantly associated with OS.

Conclusion

Automated processing of ioUS images through deep learning can generate high-precision classification algorithms. Radiomic tumor region features in B-mode and elastography appear to be significantly associated with OS in GBM.

In Arabic, two-digit numbers are read from right to left, i.e. the unit digit precedes the decade digit (24 = four and twenty) in accordance to the text reading and writing direction but opposite to the math direction (left-to-right).

The current study investigated the effect of the syntactic representation of numbers in Arabic on the task of transcoding two-digit numbers from dictation. The study participants were primary, junior-high and high school pupils in addition to higher education students with Arabic as their first language. They performed transcoding task, namely writing two-digit numbers from dictation. Units first\decades first writing patterns were collected depending on the differential syntactics structure evident in the two-digit number dictated (Teens numbers-units first, Identical units and decades- units first, Whole tens- decades firs, the rest remaining two-digit numbers-units first).

The findings reveal that in general Arabic speakers adopt decades first writing pattern of two-digit numbers especially when it is consistent with syntactic structure of two-digit numbers as in whole tens. This first decade writing pattern becomes more evident in junior-high school, high school and higher education since the proficiency and skills in math, second and third languages improves. However, this pattern is modulated depending on a complexity of the units and decades structure that requires more working memory capacity. This complexity is more pronounced in two-digit numbers, where the numerical syntactic structure is more evident than in numbers with a less prominent numerical syntactic structure (numbers 19-12) or in identical units and decades numbers compared to the remaining two-digit numbers category (with an evident syntactic structure of units and decades). Additionally, influences were claimed because of the consistency or inconsistency between the reading direction of text (Right-to-Left), two-digit numbers reading (Right-to-Left) in Arabic and math writing direction taught (Left-to-Right) placing less or more load on working memory.

The basement of the vertebrate motor system is flexor reflex whilst the extensor thrust supposed to be an optional factor for the stepping. But different forms of stepping (in opposite directions) could be differently depending upon it, since the sensory input is crucial for the stepping. The most investigated is forward stepping (FW) being the most “learned” in both phylogeny and ontogeny. In opposite, the backward (BW) stepping is associated with mostly the specific forms of behavioral activity. We compared an EMG activity of several hindlimb muscles moved the hip (iliopsoas, IP, sartorius (SR), adductor magnus (AM), biceps femoris posterior (BFP)), knee (rectus femoris (RF), vastus medialis (VM)), and ankle (tibialis anterior (TA), gastrocnemius medialis (GM), soleus (SL)) joints, in decerebrate cats stepped under epidural electrical stimulation. For most cats, an activity of hip flexors (IP, SR) was lower, hip extensors (AM, BFP) – higher, knee extensors (RF and VM) – lower, ankle flexor (TA) – lower, ankle extensor (GM) – higher for BW stepping than for FW stepping. For all muscles but SR (with minimal sample size) differences were statistically significant (Wilcoxon test). Only in SL, no clear predominance for any stepping mode was obtained. These data point out to different balance in flexion and extension during stepping in opposite directions.