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Background and aims : Epidemiological studies have examined the association between the use of non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of Alzheimer’s disease (AD). Recently, a variety of experimental studies indicates that a subset of NSAIDs, such as ibuprofen or flurbiprofen, also have Aβ-lowering properties in both AD transgenic mice and cell cultures of peripheral, glial and neuronal origin. In this trial, we evaluated whether the non-selective NSAID ibuprofen slows disease progression in patients with mild to moderate AD. Methods : This was a 12-month multicenter, randomized, double-blind, placebo-controlled, parallel group trial. Participants with mild-moderate AD (Mini-Mental State Examination score >15, <26; Clinical Dementia Rating= 0.5–1), 65 years or older, with reliable caregivers, were recruited between April 2003 and September 2004. Seven AD Outpatient Treatment Centers screened 530 patients, 132 of whom were enrolled. Interventionconsisted of 400 mg ibuprofen twice a day or placebo, together with 20 mg once a day of esomeprazol, or placebo. The primary measure was any one-year change in the Alzheimer Disease Assessment Scale-Cognitive (ADAS-Cog) subscale score. Secondary measures included changes in MMSE, CDR, Basic and Instrumental Activities of Daily Living scales, and Neuropsychiatry Inventory (NPI). Results : Fifty-one patients (77%) in the ibuprofen vs 46 (70%) in the placebo group completed the protocol (p>0.20). In intention-to-treat analysis, ADAS-Cog score worsening was similar in the two groups (p=0.951, treatment difference= 0.1, CI-2.7; 2.9). No differences were found for any secondary outcomes. In a subsample of genotyped patients, ApoE ε4 carriers treated with ibuprofen (n=27) were the only group without significant cognitive decline. Conclusions : Ibuprofen, if used for relatively short periods of time and although well tolerated thanks to gastroprotection, does not seem to be effective in tertiary prevention of mild-moderate AD. Our results suggest the need to examine whether differences in the response to NSAIDs exist, based on ApoE ε4 carrier status.

The growing interest in the preclinical stage of Alzheimer's disease (AD) led investigators to identify modifiable risk and predictive factors useful to design early intervention strategies. The preclinical stage of AD is characterized by β-amyloid (Aβ) aggregation into amyloid plaques and tau phosphorylation and aggregation into neurofibrillary tangles. There is a consensus on the importance of sleep within this context: the bidirectional relationship between sleep and AD pathology is supported by growing evidence that proved that the occurrence of sleep changes starting from the preclinical stage of AD, many years before the onset of cognitive decline. Hence, we review the most recent studies on sleep disturbances related to Aβ and the effects of sleep deprivation on Aβ accumulation in animal and human models. We also discuss evidence on the role of sleep in clearing the brain of toxic metabolic by-products, with original findings of the clearance activity of the glymphatic system stimulated by sleep. Furthermore, starting from new recent advances about the relationship between slow-wave sleep (SWS) and Aβ burden, we review the results of recent electroencephalographic (EEG) studies in order to clarify the possible role of SWS component disruption as a novel mechanistic pathway through which Aβ pathology may contribute to cognitive decline and, conversely, the eventual useful role of SWS in facilitating Aβ clearance. Finally, we discuss some promising innovative, effective, low-risk, non-invasive interventions, although empirical evidence on the efficacy of sleep interventions in improving the course of AD is at the very beginning.

Brain activity is complex; a reflection of its structural and functional organization. Among other measures of complexity, the fractal dimension is emerging as being sensitive to neuronal damage secondary to neurological and psychiatric diseases. Here, we calculated Higuchi's fractal dimension (HFD) in resting-state eyes-closed electroencephalography (EEG) recordings from 41 healthy controls (age: 20-89 years) and 67 Alzheimer's Disease (AD) patients (age: 50-88 years), to investigate whether HFD is sensitive to brain activity changes typical in healthy aging and in AD. Additionally, we considered whether AD-accelerating effects of the copper fraction not bound to ceruloplasmin (also called \"free\" copper) are reflected in HFD fluctuations. The HFD measure showed an inverted U-shaped relationship with age in healthy people (R2 = .575, p < .001). Onset of HFD decline appeared around the age of 60, and was most evident in central-parietal regions. In this region, HFD decreased with aging stronger in the right than in the left hemisphere (p = .006). AD patients demonstrated reduced HFD compared to age- and education-matched healthy controls, especially in temporal-occipital regions. This was associated with decreasing cognitive status as assessed by mini-mental state examination, and with higher levels of non-ceruloplasmin copper. Taken together, our findings show that resting-state EEG complexity increases from youth to maturity and declines in healthy, aging individuals. In AD, brain activity complexity is further reduced in correlation with cognitive impairment. In addition, elevated levels of non-ceruloplasmin copper appear to accelerate the reduction of neural activity complexity. Overall, HDF appears to be a proper indicator for monitoring EEG-derived brain activity complexity in healthy and pathological aging.

Increasing evidence supports the notion that brain plasticity involves distinct functional and structural components, each entailing a number of cellular mechanisms operating at different time scales, synaptic loci, and developmental phases within an extremely complex framework. However, the exact relationship between functional and structural components of brain plasticity/connectivity phenomena is still unclear and its explanation is a major challenge within modern neuroscience. Transcranial magnetic stimulation (TMS), with or without electroencephalography (EEG), is a sensitive and objective measure of the effect of different kinds of noninvasive manipulation of the brain's activity, particularly of the motor cortex. Moreover, the key feature of TMS and TMS-EEG coregistration is their crucial role in tracking temporal dynamics and inner hierarchies of brain functional and effective connectivities, possibly clarifying some essential issues underlying brain plasticity. All together, the findings presented here are significant for the adoption of the TMS and TMS-EEG coregistration techniques as a tool for basic neurophysiologic research and, in the future, even for clinical diagnostics purposes.

The aim of this study is to validate the Italian version of the Pittsburgh Sleep Quality Index (PSQI), comparing five different groups of individuals (healthy young and elderly, sleep apnoea syndrome patients, depressed patients, individuals with dementia) by both questionnaire scores and polysomnographic measures. Fifty individuals (10 for each group) participated in the study. Each of them filled in the PSQI and slept for two consecutive nights in the sleep laboratory. The PSQI showed an overall reliability coefficient (Cronbach’s α) of 0.835, indicating a high degree of internal consistency. The mean PSQI global score showed significant differences between groups, with an impaired overall quality of sleep in patients’ groups with respect to both the healthy groups. Results also indicated that the best cut-off score (differentiating “good” from “bad” sleepers) is 5. Pittsburgh Sleep Quality Index is a useful, valid and reliable tool for the assessment of sleep quality, with an overall efficiency comparable to the mother language version and differentiate “good” from “bad” sleepers. The Italian version of the questionnaire provides a good and reliable differentiation between normal and pathological groups, with higher scores reported by people characterized by impaired objectively evaluated sleep quality.

Over the last four decades, non-invasive brain stimulation techniques (NIBS) have significantly gained interest in the fields of cognitive sciences and dementia care, including neurorehabilitation, for its emerging potential in increasing the insights over brain functions and in boosting residual cognitive functions. In the present paper, basic physiological and technical mechanisms and different applications of NIBS were reviewed and discussed to highlight the importance of NIBS in multidisciplinary and translational approaches in clinical and research settings of cognitive sciences and neurodegenerative diseases, especially in Alzheimer's disease. Indeed, NIBS strategies may represent a promising opportunity to increase the potential of neuromodulation as efficacious interventions for individualized patients care.

Sensory feedback in motor control is widely recognized to be the key link between the activity of the primary motor cortex to the motor behavior. Through an ad-hoc developed procedure for source extraction (functional source separation), the primary sensory and motor cortex activities (FS S1 and FS M1) were obtained from magnetoencephalographic recordings during a sensorimotor task sequence, and sensorimotor interaction was assessed. Source activity spectral powers were evaluated in the alpha (8–13 Hz), beta (14–32 Hz), gamma1 (33–60 Hz) and gamma2 (61–90 Hz) frequency bands. FS S1 and FS M1had different spectral properties, with FS S1 prevailing in alpha and FS M1 in gamma band. Both FS S1 and FS M1 were reactive in the different sensorimotor tasks with respect to rest in all frequency bands, except for gamma2. During an isometric contraction, we searched for an index dependent on the performance level and with low variability in the healthy population. We found these properties satisfied within a relationship between FS S1 and FS M1 in the gamma2 band. This sensorimotor feedback efficiency index quantitatively estimates the continuous functional balance between primary sensory and motor areas devoted to hand control and seems promising for future developments, as it is easily assessable in patients.

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands. Our hands provide us with a wide variety of information about our surroundings, enabling us to detect pain, temperature and pressure. Our sense of touch also allows us to interact with objects by feeling their texture and solidity. However, completely reproducing a sense of touch in artificial or prosthetic hands has proven challenging. While commercial prostheses can mimic the range of movements of natural limbs, even the latest experimental prostheses have only a limited ability to ‘feel’ the objects being manipulated. Oddo, Raspopovic et al. have now brought this ability a step closer by exploiting an artificial fingertip and appropriate neural interfaces through which different textures can be identified. The initial experiments were performed in four healthy volunteers with intact limbs. Oddo, Raspopovic et al. connected the artificial fingertip to the volunteers via an electrode inserted into a nerve in the arm. When moved over a rough surface, sensors in the fingertip produced patterns of electrical pulses that stimulated the nerve, causing the volunteers to feel like they were touching the surface. The volunteers were even able to tell the difference between the different surface textures the artificial fingertip moved across. The temporary electrodes used in this group of volunteers are unsuitable for use with prosthetic limbs because they can easily be knocked out of position. Therefore, in a further experiment involving a volunteer who had undergone an arm amputation a number of years previously, Oddo, Raspopovic et al. tested an implanted electrode array that could, in principle, remain in place long-term. This volunteer could also identify the different textures the artificial fingertip touched, with a slightly higher degree of accuracy than the previous group of intact volunteers. Further studies are now required to explore the potential of this approach in larger groups of volunteers.

Parkinson’s disease (PD) is the second most common neurodegenerative disease in the elderly population. Similarly to other neurodegenerative diseases, the early diagnosis of PD is quite difficult. The current pilot study aimed to explore the differences in brain connectivity between PD and NOrmal eLDerly (Nold) subjects to evaluate whether connectivity analysis may speed up and support early diagnosis. A total of 26 resting state EEGs were analyzed from 13 PD patients and 13 age-matched Nold subjects, applying to cortical reconstructions the graph theory analyses, a mathematical representation of brain architecture. Results showed that PD patients presented a more ordered structure at slow-frequency EEG rhythms (lower value of SW) than Nold subjects, particularly in the theta band, whereas in the high-frequency alpha, PD patients presented more random organization (higher SW) than Nold subjects. The current results suggest that PD could globally modulate the cortical connectivity of the brain, modifying the functional network organization and resulting in motor and non-motor signs. Future studies could validate whether such an approach, based on a low-cost and non-invasive technique, could be useful for early diagnosis, for the follow-up of PD progression, as well as for evaluating pharmacological and neurorehabilitation treatments.

Intracortical inhibition (SICI) and facilitation (ICF) in the human motor cortex can be measured using a paired pulse transcranial magnetic stimulation (ppTMS) protocol. Recently, a technical device has been introduced, which allows recording electroencephalographic (EEG) responses to TMS of a given scalp site. The latency, amplitude and scalp topography of such responses are considered a reflection of cortico-cortical connectivity and functional state. The aim of the present study is to better characterize the neuronal circuits underlying motor cortex connectivity as well as the mechanisms regulating its balance between inhibition and facilitation by means of EEG navigated-ppTMS coregistration. Sub-threshold and supra-threshold single and ppTMS of the left primary motor cortex were carried out during a multi-channel EEG recording on 8 healthy volunteers; the between-pulse intervals used in the paired pulse trials were 3 (for SICI) and 11ms (for ICF). Motor evoked potentials (MEPs) from the opposite hand were simultaneously recorded. Single and ppTMS induced EEG responses characterized by a sequence of negative deflections peaking at approximately 7, 18, 44, 100 and 280ms alternated with positive peaks at approximately 13, 30, 60 and 190ms post-TMS. Moreover, ppTMS modulated both EEG evoked activity and MEPs. Amplitude variability of EEG responses was correlated with – and therefore might partially explain – amplitude variability of MEPs. EEG-ppTMS is a promising tool to better characterize the neuronal circuits underlying cortical effective connectivity as well as the mechanisms regulating the balance between inhibition and facilitation within the human cortices and the corticospinal pathway.