neurophysiological assessment
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2021 ◽  
Vol 429 ◽  
pp. 119813
Author(s):  
Tommaso Bocci ◽  
Federica Cencini ◽  
Amedeo De Grado ◽  
Chiara Manfredi ◽  
Elisabetta Groppo ◽  
...  

Author(s):  
Ewa Wiwatowska ◽  
Dominik Czajeczny ◽  
Jarosław M. Michałowski

AbstractProcrastination is a voluntary delay in completing an important task while being aware that this behavior may lead to negative outcomes. It has been shown that an increased tendency to procrastinate is associated with deficits in some aspects of cognitive control. However, none of the previous studies investigated these dysfunctions through the lenses of the Dual Mechanisms Framework, which differentiates proactive and reactive modes of control. The present study was designed to fill this gap, using behavioral and neurophysiological assessment during the completion of the AX-Continuous Performance Task (AX-CPT) by high (HP) and low (LP) procrastinating students (N = 139). Behavioral results indicated that HP (vs. LP) were characterized by increased attentional fluctuations (higher reaction time variability) and reduction in some indices of proactive cognitive control (lower d’-context and A-cue bias, but similar PBIs). Furthermore, the neurophysiological data showed that HP, compared with LP, allocated less attentional resources (lower P3b) to cues that help to predict the correct responses to upcoming probes. They also responded with reduced preparatory activity (smaller CNV) after cues presentation. The two groups did not differ in neural responses linked to conflict detection and inhibition (similar N2 and P3a). Obtained findings indicate that HP might present deficits in some cognitive functions that are essential for effective proactive control engagement, along with preserved levels of reactive cognitive control. In the present paper, we discuss the potential neural and cognitive mechanisms responsible for the observed effects.


Author(s):  
John Harvey Kindred ◽  
Christian Finetto ◽  
Jasmine Jamilah Cash ◽  
Mark Goodman Bowden

Author(s):  
Gustavo Balbinot ◽  
Guijin Li ◽  
Matheus Joner Wiest ◽  
Maureen Pakosh ◽  
Julio Cesar Furlan ◽  
...  

AbstractTraumatic spinal cord injury (SCI) disrupts spinal and supraspinal pathways, and this process is reflected in changes in surface electromyography (sEMG). sEMG is an informative complement to current clinical testing and can capture the residual motor command in great detail—including in muscles below the level of injury with seemingly absent motor activities. In this comprehensive review, we sought to describe how the sEMG properties are changed after SCI. We conducted a systematic literature search followed by a narrative review focusing on sEMG analysis techniques and signal properties post-SCI. We found that early reports were mostly focused on the qualitative analysis of sEMG patterns and evolved to semi-quantitative scores and a more detailed amplitude-based quantification. Nonetheless, recent studies are still constrained to an amplitude-based analysis of the sEMG, and there are opportunities to more broadly characterize the time- and frequency-domain properties of the signal as well as to take fuller advantage of high-density EMG techniques. We recommend the incorporation of a broader range of signal properties into the neurophysiological assessment post-SCI and the development of a greater understanding of the relation between these sEMG properties and underlying physiology. Enhanced sEMG analysis could contribute to a more complete description of the effects of SCI on upper and lower motor neuron function and their interactions, and also assist in understanding the mechanisms of change following neuromodulation or exercise therapy.


2021 ◽  
Vol 11 (6) ◽  
pp. 729
Author(s):  
Diana Sipos-Lascu ◽  
Ștefan-Cristian Vesa ◽  
Lăcrămioara Perju-Dumbravă

Background: Patients with Parkinson’s disease (PD) often have, besides the characteristic motor manifestations, a wide variety of non-motor symptoms. These include apathy and anhedonia, common issues in PD, which can be quantified with the help of evaluation scales recommended by the literature. There are sensory non-motor manifestations of PD, some of which are easy to detect through electrophysiological studies. Our aim was to investigate the possible association of apathy and anhedonia with the severity of the motor status in a sample of PD patients in Romania. We also examined the prevalence of latency changes in the P100 wave of visual evoked potentials (VEPs) and how they correlated with motor status, apathy, and anhedonia in PD patients. Methods: Thirty-four patients with PD participated in this study. All were assessed for motor status using the Unified Parkinson’s Disease Rating Scale (UPDRS) and were rated on the Hoehn and Yahr scales. The presence and severity of apathy and anhedonia were assessed using the Apathy Evaluation Scale (AES), the Dimensional Apathy Scale (DAS), the Lille Apathy Rating Scale (LARS), and the Snaith–Hamilton Pleasure Scale (SHAPS). The latency of the P100 wave of the VEP was measured in all the patients. Results: Apathy and anhedonia were common among the patients with PD (35% and 58.8%, respectively). The presence of apathy/anhedonia was correlated with the severity of motor symptoms, as assessed using the UPDRS scale (p < 0.001), and with the stage of the disease according to the Hoehn and Yahr scale (p < 0.001). A prolonged latency of the P100 wave of the VEP was observed among apathetic (p < 0.001)/anhedonic (p < 0.01) patients and those with increased disease severity (p < 0.001). Conclusion: Apathy and anhedonia are common in PD and may correlate with the severity of motor symptoms. There may be visual impairment in these patients, evidenced by a prolonged P100 latency, which correlates with the severity of disease. Significance: Scales for assessing apathy and anhedonia, as well as measuring VEP latency, could be useful in assessing the severity of disease.


2021 ◽  
Vol 132 (1) ◽  
pp. 165-166
Author(s):  
Lorenzo Stanzani ◽  
Elisa Visani ◽  
Luisa Chiapparini ◽  
Ferruccio Panzica ◽  
Andrea Salmaggi ◽  
...  

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