The effects of the neurotoxin DSP4 on spatial learning and memory in Wistar rats

The aim of the present study was to investigate the effect of DSP4-induced noradrenaline depletion on learning and memory in a spatial memory paradigm (holeboard). Since Harro et al. Brain Res 976:209–216 (2003) have demonstrated that short-term effects of DSP4 administration include both noradrenaline depletion and changes in dopamine and its metabolites—with the latter vanishing within 4 weeks after the neurotoxic lesion—the behavioural effects observed immediately after DSP4 administration cannot solely be related to noradrenaline. In the present study, spatial learning, reference memory and working memory were therefore assessed 5–10 weeks after DSP4 administration. Our results suggest that the administration of DSP4 did not lead to changes in spatial learning and memory when behavioural assessment was performed after a minimum of 5 weeks following DSP4. This lack of changes in spatial behaviour suggests that the role of noradrenaline regarding these functions may be limited. Future studies will therefore have to take into account the time-course of neurotransmitter alterations and behavioural changes following DSP4 administration

From sleep spindles of natural sleep to spike and wave discharges of typical absence seizures: is the hypothesis still valid?

The temporal coincidence of sleep spindles and spike-and-wave discharges (SWDs) in patients with idiopathic generalized epilepsies, together with the transformation of spindles into SWDs following intramuscular injection of the weak GABAA receptor (GABAAR) antagonist, penicillin, in an experimental model, brought about the view that SWDs may represent ‘perverted’ sleep spindles. Over the last 20 years, this hypothesis has received considerable support, in particular by in vitro studies of thalamic oscillations following pharmacological/genetic manipulations of GABAARs. However, from a critical appraisal of the evidence in absence epilepsy patients and well-established models of absence epilepsy it emerges that SWDs can occur as frequently during wakefulness as during sleep, with their preferential occurrence in either one of these behavioural states often being patient dependent. Moreover, whereas the EEG expression of both SWDs and sleep spindles requires the integrity of the entire cortico-thalamo-cortical network, SWDs initiates in cortex while sleep spindles in thalamus. Furthermore, the hypothesis of a reduction in GABAAR function across the entire cortico-thalamo-cortical network as the basis for the transformation of sleep spindles into SWDs is no longer tenable. In fact, while a decreased GABAAR function may be present in some cortical layers and in the reticular thalamic nucleus, both phasic and tonic GABAAR inhibitions of thalamo-cortical neurons are either unchanged or increased in this epileptic phenotype. In summary, these differences between SWDs and sleep spindles question the view that the EEG hallmark of absence seizures results from a transformation of this EEG oscillation of natural sleep

Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods

Sleep spindles are discrete, intermittent patterns of brain activity observed in human electroencephalographic data. Increasingly, these oscillations are of biological and clinical interest because of their role in development, learning and neurological disorders. We used an Internet interface to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects