Neurophysiologie Clinique/Clinical Neurophysiology最新文献

Objectives

Corneal confocal microscopy (CCM) is a non-invasive technique that examines the corneal cellular structure. Its use in the detection of small fiber neuropathy is being researched. In our study, we examined the role of CCM in the detection of small fiber neuropathy in diabetic patients, as well as the differences between CCM findings in diabetic patients with and without overt polyneuropathy with neuropathic symptoms.

Methods

56 Diabetes Mellitus (DM) patients and 18 healthy controls were included in the study. The individuals included in the study were divided into three groups. Patients with diabetes who were found to have polyneuropathy according to electrophysiological diagnostic criteria were classified as Group 1, patients with diabetes and neuropathic symptoms without overt polyneuropathy according to electrophysiological diagnostic criteria were classified as Group 2, and healthy individuals were classified as Group 3. Electrophysiological examination and corneal imaging with CCM were performed in all groups.

Results

The CNFD and CNFL values of individuals in the diabetic group were discovered to be lower. CNFD values differ statistically between the groups (p = 0.047). Group 1-Group 3 differs from Group 2-Group 3 (respectively; p = 0.018, p = 0.048).

Conclusion

Our study demonstrates that CCM can be used in patients with neuropathic symptoms and no polyneuropathy detected in EMG and thought to have small fiber neuropathy. CCM provides an opportunity for early diagnosis in small fiber neuropathy.

Background

Parkinson's disease (PD), and other parkinsonian syndromes are known to cause striatonigral dopaminergic system dysfunction and autonomic disturbances, including the vasomotor and sudomotor nervous systems. The detection of ¹²³I-FP-CIT SPECT (DaT scan) imaging and autonomic dysfunction helps differentiate PD from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). The sympathetic skin response (SSR) is a simple, non-invasive electrophysiological test that assesses the sympathetic sudomotor nervous system. It is reported that the SSR is impaired in patients with PD, MSA, and PSP.

Objective

To study the relationship between SSR, ¹²³I-metaiodobenzylguanidine (MIBG) cardiac scintigraphy and DaT scan imaging parameters in patients with PD, MSA, and PSP.

Methods

The study included 62, 25, and 19 patients with PD, MSA, and PSP, respectively. The SSR, MIBG cardiac scintigraphy, and DaT scan imaging were examined. The amplitude and latency of the SSR were measured in all limbs and were compared with the results of MIBG cardiac scintigraphy and DAT scan imaging.

Results

The SSR amplitudes were lower than reported normal subjects' reference values in PD, MSA, and PSP. The SSR amplitude only correlated with MIBG cardiac scintigraphy and DaT scan imaging parameters in PD. Multiple regression analyses also showed a significant relationship between the amplitudes of SSR and DaT scan imaging in PD.

Conclusion

Unlike MSA, and PSP, the sudomotor nervous system is parallelly involved with cardiac sympathetic and central dopaminergic dysfunction from the early stage of PD.

Historically, the field of sleep medicine has revolved around electrophysiological tools. However, the use of these tools as a neurophysiological method of investigation seems to be underrepresented today, from both international recommendations and sleep centers, in contrast to behavioral and psychometric tools. The aim of this article is to combine a data-driven approach and neurophysiological and sleep medicine expertise to confirm or refute the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness, despite the use of electrophysiological tools. Using Natural Language Processing methods, we analyzed the abstracts of the 18,370 articles indexed by PubMed containing the terms ‘sleepiness’ or ‘sleepy’ in the title, abstract, or keywords. For this purpose, we examined these abstracts using two methods: a lexical network, enabling the identification of concepts (neurophysiological or clinical) related to sleepiness in these articles and their interconnections; furthermore, we analyzed the temporal evolution of these concepts to extract historical trends. These results confirm the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness. In order to bring sleepiness measurements closer to brain functioning and to reintroduce neurophysiology into sleep medicine, we discuss two strategies: the first is reanalyzing electrophysiological signals collected during the standard sleep electrophysiological test; the second takes advantage of the current trend towards dimensional models of sleepiness to situate clinical neurophysiology at the heart of the redefinition of sleepiness.

Excessive daytime sleepiness (EDS) is multifactorial. It combines, among other things, an excessive propensity to fall asleep (“physiological sleepiness”) and a continuous non-imperative sleepiness (or drowsiness/hypo-arousal) leading to difficulties remaining awake and maintaining sustained attention and vigilance over the long term (“manifest sleepiness”). There is no stand-alone biological measure of EDS. EDS measures can either capture the severity of physiological sleepiness, which corresponds to the propensity to fall asleep, or the severity of manifest sleepiness, which corresponds to behavioral consequences of sleepiness and reduced vigilance. Neuropsychological tests (The psychomotor vigilance task (PVT), Oxford Sleep Resistance Test (OSLeR), Sustained Attention to Response Task (SART)) explore manifest sleepiness through several sustained attention tests but the lack of normative values and standardized protocols make the results difficult to interpret and use in clinical practice. Neurophysiological tests explore the two main aspects of EDS, i.e. the propensity to fall asleep (Multiple sleep latency test, MSLT) and the capacity to remain awake (Maintenance of wakefulness test, MWT). The MSLT and the MWT are widely used in clinical practice. The MSLT is recognized as the “gold standard” test for measuring the severity of the propensity to fall asleep and it is a diagnostic criterion for narcolepsy. The MWT measures the ability to stay awake. The MWT is not a diagnostic test as it is recommended only to evaluate the evolution of EDS and efficacy of EDS treatment. Even if some efforts to standardize the protocols for administration of these tests have been ongoing, MSLT and MWT have numerous limitations: age effect, floor or ceiling effects, binding protocol, no normal or cutoff value (or determined in small samples), and no or low test-retest values in some pathologies. Moreover, the recommended electrophysiological set-up and the determination of sleep onset using the 30‑sec epochs scoring rule show some limitations. New, more precise neurophysiological techniques should aim to detect very brief periods of physiological sleepiness and, in the future, the brain local phenomenon of sleepiness likely to underpin drowsiness, which could be called “physiological drowsiness”.

Sleep inertia refers to the transient physiological state of hypoarousal upon awakening, associated with various degrees of impaired neurobehavioral performance, confusion, a desire to return to sleep and often a negative emotional state. Scalp and intracranial electro-encephalography as well as functional imaging studies have provided evidence that the sleep inertia phenomenon is underpinned by an heterogenous cerebral state mixing local sleep and local wake patterns of activity, at the neuronal and network levels. Sleep inertia is modulated by homeostasis and circadian processes, sleep stage upon awakening, and individual factors; this translates into a huge variability in its intensity even under physiological conditions. In sleep disorders, especially in hypersomnolence disorders such as idiopathic hypersomnia, sleep inertia may be a daily, serious and long-lasting symptom leading to severe impairment. To date, few tools have been developed to assess sleep inertia in clinical practice. They include mainly questionnaires and behavioral tests such as the psychomotor vigilance task. Only one neurophysiological protocol has been evaluated in hypersomnia, the forced awakening test which is based on an event-related potentials paradigm upon awakening. This contrasts with the major functional consequences of sleep inertia and its potentially dangerous consequences in subjects required to perform safety-critical tasks soon after awakening. There is a great need to identify reproducible biomarkers correlated with sleep inertia-associated cognitive and behavioral impairment. These biomarkers will aim at better understanding and measuring sleep inertia in physiological and pathological conditions, as well as objectively evaluating wake-promoting treatments or non-pharmacological countermeasures to reduce this phenomenon.

The mechanisms underlying the individual need for sleep are unclear. Sleep duration is indeed influenced by multiple factors, such as genetic background, circadian and homeostatic processes, environmental factors, and sometimes transient disturbances such as infections. In some cases, the need for sleep dramatically and chronically increases, inducing a daily-life disability. This “excessive need for sleep” (ENS) was recently proposed and defined in a European Position Paper as a dimension of the hypersomnolence spectrum, “hypersomnia” being the objectified complaint of ENS. The most severe form of ENS has been described in Idiopathic Hypersomnia, a rare neurological disorder, but this disabling symptom can be also found in other hypersomnolence conditions. Because ENS has been defined recently, it remains a symptom poorly investigated and understood. However, protocols of long-term polysomnography recordings have been reported by expert centers in the last decades and open the way to a better understanding of ENS through a neurophysiological approach. In this narrative review, we will 1) present data related to the physiological and pathological variability of sleep duration and their mechanisms, 2) describe the published long-term polysomnography recording protocols, and 3) describe current neurophysiological tools to study sleep microstructure and discuss perspectives for a better understanding of ENS.

Background

The mechanism of Short-Latency Afferent Inhibition (SAI) is relatively well understood. In contrast, Long-Latency Afferent Inhibition (LAI) has not been as extensively studied as SAI, and its underlying mechanism remains unclear.

Objective/Hypothesis

This study had two primary objectives: first, to determine the optimal ISIs for LAI measured by amplitude changes (A-LAI) using high-resolution ISI ranges; and second, to compare measurements of LAI by threshold-tracking (T-LAI).

Methods

Twenty-eight healthy volunteers (12 males aged 24- 45 years) participated in the study. Paired peripheral electrical and transcranial magnetic stimulation (TMS) stimuli (TS1mv) were applied at varying (ISIs)- 100, 200, 250, 300, 350, 400, 450, 500, 550, 600, 700, 800, 900, 1000 ms.

Results

Both A-LAI and T-LAI showed that LAI decreased progressively from a peak at 200 or 250 ms to 1000 ms. Using the A-LAI method, pronounced inhibition was observed at three specific ISIs: 100 ms, 250 ms and 450 ms. When A-LAI values were converted to equivalent threshold changes, they did not differ significantly from T-LAI. Reliability at distinguishing individuals, as indicated by intraclass correlation coefficient (ICC) was greater for A-LAI, with a peak value of 0.82 at 250 ms.

Conclusion(s)

The study demonstrates that ISIs of 100 ms and 250 ms can be reliably used in amplitude measurement LAI. The study demonstrates that both LAI measurements record a similar decline of inhibition with increasing ISI.

Objective

Changes in brain structure and neurotransmitter systems are involved in pain in Parkinson's disease (PD), and emotional factors are closely related to pain. Our study applied electroencephalography (EEG) to investigate the role of emotion in PD patients with chronic musculoskeletal pain.

Methods

Forty-two PD patients with chronic musculoskeletal pain and 38 without were enrolled. EEG data were recorded under resting conditions, and while viewing pictures with neutral, positive, and negative content. We compared spectrum power, functional connectivity, and late positive potential (LPP), an event-related potential (ERP), between the groups.

Results

PD patients with pain tended to have higher scores for the Hamilton Rating Scale for Depression (HRSD). In the resting EEG, mean β-band amplitude was significantly higher in patients with pain than in those without. Logistic regression analysis showed that higher HRSD scores and higher mean β-band amplitude were associated with pain. ERP analysis revealed that the amplitudes of LPP difference waves (the absolute difference between positive and negative condition LPP and neutral condition LPP) at the central–parietal region were significantly reduced in patients with pain (P = 0.029). Spearman correlation analysis showed that the amplitudes of late (700–1000 ms) negative versus neutral condition LPP difference waves were negatively correlated with pain intensity, assessed by visual analogue scale, (r = −0.393, P = 0.010) and HRSD scores (r = −0.366, P = 0.017).

Conclusion

Dopaminergic and non-dopaminergic systems may be involved in musculoskeletal pain in PD by increasing β-band activity and weakening the connection of the θ-band at the central–parietal region. PD patients with musculoskeletal pain have higher cortical excitability to negative emotions. The changes in pain-related EEG may be used as electrophysiological markers and therapeutic targets in PD patients with chronic pain.