Attention Supports Verbal Short-Term Memory via Competition between Dorsal and Ventral Attention Networks

Interactions between the neural correlates of short-term memory (STM) and attention have been actively studied in the visual STM domain but much less in the verbal STM domain. Here we show that the same attention mechanisms that have been shown to shape the neural networks of visual STM also shape those of verbal STM. Based on previous research in visual STM, we contrasted the involvement of a dorsal attention network centered on the intraparietal sulcus supporting task-related attention and a ventral attention network centered on the temporoparietal junction supporting stimulus-related attention. We observed that, with increasing STM load, the dorsal attention network was activated while the ventral attention network was deactivated, especially during early maintenance. Importantly, activation in the ventral attention network increased in response to task-irrelevant stimuli briefly presented during the maintenance phase of the STM trials but only during low-load STM conditions, which were associated with the lowest levels of activity in the dorsal attention network during encoding and early maintenance. By demonstrating a trade-off between task-related and stimulus-related attention networks during verbal STM, this study highlights the dynamics of attentional processes involved in verbal ST

Gemvid, an open source, modular, automated activity recording system for rats using digital video

BACKGROUND: Measurement of locomotor activity is a valuable tool for analysing factors influencing behaviour and for investigating brain function. Several methods have been described in the literature for measuring the amount of animal movement but most are flawed or expensive. Here, we describe an open source, modular, low-cost, user-friendly, highly sensitive, non-invasive system that records all the movements of a rat in its cage. METHODS: Our activity monitoring system quantifies overall free movements of rodents without any markers, using a commercially available CCTV and a newly designed motion detection software developed on a GNU/Linux-operating computer. The operating principle is that the amount of overall movement of an object can be expressed by the difference in total area occupied by the object in two consecutive picture frames. The application is based on software modules that allow the system to be used in a high-throughput workflow. Documentation, example files, source code and binary files can be freely downloaded from the project website at . RESULTS: In a series of experiments with objects of pre-defined oscillation frequencies and movements, we documented the sensitivity, reproducibility and stability of our system. We also compared data obtained with our system and data obtained with an Actiwatch device. Finally, to validate the system, results obtained from the automated observation of 6 rats during 7 days in a regular light cycle are presented and are accompanied by a stability test. The validity of this system is further demonstrated through the observation of 2 rats in constant dark conditions that displayed the expected free running of their circadian rhythm. CONCLUSION: The present study describes a system that relies on video frame differences to automatically quantify overall free movements of a rodent without any markers. It allows the monitoring of rats in their own environment for an extended period of time. By using a low-cost, open source hardware/software solution, laboratories can greatly simplify their data acquisition and analysis pipelines and improve their workload

Decoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets

Proteomic changes in rat hippocampus and adrenals following short-term sleep deprivation

ABSTRACT: BACKGROUND: To identify the biochemical changes induced by sleep deprivation at a proteomic level, we compared the hippocampal proteome of rats either after 4 hours of sleep or sleep deprivation obtained by gentle handling. Because sleep deprivation might induce some stress, we also analyzed proteomic changes in rat adrenals in the same conditions. After sleep deprivation, proteins from both tissues were extracted and subjected to 2D-DIGE analysis followed by protein identification through mass spectrometry and database search. RESULTS: In the hippocampus, 87 spots showed significant variation between sleep and sleep deprivation, with more proteins showing higher abundance in the latter case. Of these, 16 proteins were present in sufficient amount for a sequencing attempt and among the 12 identified proteins, inferred affected cellular functions include cell metabolism, energy pathways, transport and vesicle trafficking, cytoskeleton and protein processing. Although we did not observe classical, macroscopic effect of stress in sleep-deprived rats, 47 protein spots showed significant variation in adrenal tissue between sleep and sleep deprivation, with more proteins showing higher abundance following sleep. Of these, 16 proteins were also present in sufficient amount for a sequencing attempt and among the 13 identified proteins, the most relevant cellular function that was affected was cell metabolism. CONCLUSION: At a proteomic level, short term sleep deprivation is characterized by a higher expression of some proteins in the hippocampus and a lower abundance of other proteins in the adrenals (compared to normal sleep control). Altogether, this could indicate a general activation of a number of cellular mechanisms involved in the maintenance of wakefulness and in increased energy expenditure during sleep deprivation. These findings are relevant to suggested functions of sleep like energy repletion and the restoration of molecular stocks or a more global homeostasis of synaptic processes

Recurrent boosting effects of short inactivity delays on performance: an ERPs study

<p>Abstract</p> <p>Background</p> <p>Recent studies investigating off-line processes of consolidation in motor learning have demonstrated a sudden, short-lived improvement in performance after 5–30 minutes of post-training inactivity. Here, we investigated further this behavioral boost in the context of the probabilistic serial reaction time task, a paradigm of implicit sequence learning. We looked both at the electrophysiological correlates of the boost effect and whether this phenomenon occurs at the initial training session only.</p> <p>Findings</p> <p>Reaction times consistently improved after a 30-minute break within two sessions spaced four days apart, revealing the reproducibility of the boost effect. Importantly, this improvement was unrelated to the acquisition of the sequential regularities in the material. At both sessions, event-related potentials (ERPs) analyses disclosed a boost-associated increased amplitude of a first negative component, and shorter latencies for a second positive component.</p> <p>Conclusion</p> <p>Behavioral and ERP data suggest increased processing fluency after short delays, which may support transitory improvements in attentional and/or motor performance and participate in the final setting up of the neural networks involved in the acquisition of novel skills.</p

Multimodal evoked potentials for functional quantification and prognosis in multiple sclerosis

peer reviewedFunctional biomarkers able to identify multiple sclerosis (MS) patients at high risk of fast disability progression are lacking. The aim of this study was to evaluate the ability of multimodal (upper and lower limbs motor, visual, lower limbs somatosensory) evoked potentials (EP) to monitor disease course and identify patients exposed to unfavourable evolution. One hundred MS patients were assessed with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) at baseline (T0) and about 6 years later (T1). The Spearman correlation (rS) was used to evaluate the relationship between conventional EP scores and clinical findings. Multiple (logistic) regression analysis estimated the predictive value of baseline electrophysiological data for three clinical outcomes: EDSS, annual EDSS progression, and the risk of EDSS worsening. In contrast to longitudinal correlations, cross-sectional correlations between the different EP scores and EDSS were all significant (0.33 ≤ rS < 0.67, p < 0.001). Baseline global EP score and EDSS were highly significant predictors (p < 0.0001) of EDSS progression 6 years later. The aseline global EP score was found to be an independent predictor of the EDSS annual progression rate (p < 0.001), and of the risk of disability progression over time (p < 0.005). Based on a ROC curve determination, we defined a Global EP Score cut off point (17/30) to identify patients at high risk of disability progression illustrated by a positive predictive value of 70 %. This study provides a proof of the concept that electrophysiology could be added to MRI and used as another complementary prognostic tool in MS patients

Period 2 regulates neural stem/progenitor cell proliferation in the adult hippocampus

BACKGROUND: Newborn granule neurons are generated from proliferating neural stem/progenitor cells and integrated into mature synaptic networks in the adult dentate gyrus of the hippocampus. Since light/dark variations of the mitotic index and DNA synthesis occur in many tissues, we wanted to unravel the role of the clock-controlled Period2 gene (mPer2) in timing cell cycle kinetics and neurogenesis in the adult DG. RESULTS: In contrast to the suprachiasmatic nucleus, we observed a non-rhythmic constitutive expression of mPER2 in the dentate gyrus. We provide evidence that mPER2 is expressed in proliferating neural stem/progenitor cells (NPCs) and persists in early post-mitotic and mature newborn neurons from the adult DG. In vitro and in vivo analysis of a mouse line mutant in the mPer2 gene (Per2Brdm1), revealed a higher density of dividing NPCs together with an increased number of immature newborn neurons populating the DG. However, we showed that the lack of mPer2 does not change the total amount of mature adult-generated hippocampal neurons, because of a compensatory increase in neuronal cell death. CONCLUSION: Taken together, these data demonstrated a functional link between the constitutive expression of mPER2 and the intrinsic control of neural stem/progenitor cells proliferation, cell death and neurogenesis in the dentate gyrus of adult mice

Be caught napping : you're doing more than resting your eyes

peer reviewedSleep is suggested to repair fatigue or to enhance memory consolidation. A new paper shows that the beneficial effect of sleep is specific to the task and the brain regions engaged by it

Sleep and motor skill learning

peer reviewedThe improvement of a perceptual or motor skill continues after training has ended. The central question is whether this improvement is just a function of time or whether sleep, a certain circadian phase, or their interaction (sleep occurring in a particular circadian phase) is favorable to the reprocessing of recent memory traces. In this issue of Neuron, Walker et al. (2002) provide behavioral evidence that most of the improvement of a motor skill depends on nocturnal sleep