52 research outputs found
Discharge correlates of hippocampal complex spike neurons in behaving rats passively displaced on a mobile robot
Dizziness and Convergence Insufficiency in Children: Screening and Management
International audienceObjective: In children screened for dizziness with vergence disorders, we tested short and long term efficacy of orthoptic vergence training (OVT) and instructions to reduce screen usage.Methods: Prospective study: Of the 179 children referred for vertigo or dizziness (over 3 years) with ophthalmological disorder as the only problem after complete oto-neuro-vestibular testing, 69 presented vergence insufficiency, and 49 accepted to participate in this study. 109 healthy children served as controls. All subjects had classic orthoptic evaluation and video binocular movement recordings during various oculomotor tasks. Patients were evaluated before OVT (M0), 3 months after the end of OVT (M3) and 9 months after the end of OVT (M9). Statistics compared orthoptic and oculomotor parameters between patients and controls over time with one-way ANCOVA, and mixed models, controlling for age and gender.Results: Patients reported vertigo that was usually rotatory, lasting <15 min, associated with or alternating with headache (50%). Their exposure to small video screens and TV was intensive (∼3.6 h per day). At M0, all orthoptic and oculomotor parameters were statistically different in patients relative to controls (p < 0.0001) except for divergence. At M3, vertigo symptoms had disappeared in all of the patients, and all eye movement parameters improved significantly (p < 0.0001). At M9, this improvement remained stable or continued.Conclusion: Vergence disorders (assessed by abnormal orthoptic and oculomotor parameters) can generate symptoms of dizziness in children. Orthoptic treatment and instruction to reduce screen usage has a significant and long term effect on vertigo symptoms as well as oculomotor performances. Dizzy children should be screened for vergence disorders
Coherent Theta Oscillations and Reorganization of Spike Timing in the Hippocampal- Prefrontal Network upon Learning
To study the interplay between hippocampus and medial prefrontal cortex (Pfc) and its importance for learning and memory consolidation, we measured the coherence in theta oscillations between these two structures in rats learning new rules on a Y maze. Coherence peaked at the choice point, most strongly after task rule acquisition. Simultaneously, Pfc pyramidal neurons reorganized their phase, concentrating at hippocampal theta trough, and synchronous cell assemblies emerged. This synchronous state may result from increased inhibition exerted by interneurons on pyramidal cells, as measured by cross-correlation, and could be modulated by dopamine: we found similar hippocampal-Pfc theta coherence increases and neuronal phase shifts following local administration of dopamine in Pfc of anesthetized rats. Pfc cell assemblies emerging during high coherence were preferentially replayed during subsequent sleep, concurrent with hippocampal sharp waves. Thus, hippocampal/prefrontal coherence could lead to synchronization of reward predicting activity in prefrontal networks, tagging it for subsequent memory consolidation.European Commission (Contract FP6-IST 027819)European Commission (Contract FP6-IST-027140)European Commission (Contract FP6-IST-027017
Sequential Reinstatement of Neocortical Activity during Slow Oscillations Depends on Cells’ Global Activity
During Slow Wave Sleep (SWS), cortical activity is dominated by endogenous processes modulated by slow oscillations (0.1–1 Hz): cell ensembles fluctuate between states of sustained activity (UP states) and silent epochs (DOWN states). We investigate here the temporal structure of ensemble activity during UP states by means of multiple single unit recordings in the prefrontal cortex of naturally sleeping rats. As previously shown, the firing rate of each PFC cell peaks at a distinct time lag after the DOWN/UP transition in a consistent order. We show here that, conversely, the latency of the first spike after the UP state onset depends primarily on the session-averaged firing rates of cells (which can be considered as an indirect measure of their intrinsic excitability). This latency can be explained by a simple homogeneous process (Poisson model) of cell firing, with sleep averaged firing rates employed as parameters. Thus, at DOWN/UP transitions, neurons are affected both by a slow process, possibly originating in the cortical network, modulating the time course of firing for each cell, and by a fast, relatively stereotyped reinstatement of activity, related mostly to global activity levels
Behavioral correlates of activity of optogenetically identified locus coeruleus noradrenergic neurons in rats performing T-maze tasks
Abstract The nucleusLocus Coeruleus (LC) is the major source of forebrain norepinephrine. LC is implicated in arousal, response to novelty, and cognitive functions, including decision-making and behavioral flexibility. One hypothesis is that LC activation promotes rapid shifts in cortical attentional networks following changes in environmental contingencies. Recent recordings further suggest LC is critical for mobilizing resources to deal with challenging situations. In the present study optogenetically identified LC neuronal activity was recorded in rats in a self-paced T-maze. Rats were trained on visual discrimination; then place-reward contingencies were instated. In the session where the animal shifted tasks the first time, the LC firing rate after visual cue onset increased significantly, even as the animal adhered to the previous rule. Firing rate also increased prior to crossing photodetectors that controlled stimulus onset and offset, and this was positively correlated with accelerations, consistent with a role in mobilizing effort. The results contribute to the growing evidence that the noradrenergic LC is essential for behavioral adaptation by promoting cognitive flexibility and mobilizing effort in face of changing environmental contingencies
Locus coeruleus noradrenergic neurons phase-lock to prefrontal and hippocampal infra-slow rhythms that synchronize to behavioral events
The locus coeruleus (LC) is the primary source of noradrenergic projections to the forebrain, and, in prefrontal cortex, is implicated in decision-making and executive function. LC neurons phase-lock to cortical infra-slow wave oscillations during sleep. Such infra-slow rhythms are rarely reported in awake states, despite their interest, since they correspond to the time scale of behavior. Thus, we investigated LC neuronal synchrony with infra-slow rhythms in awake rats performing an attentional set-shifting task. Local field potential (LFP) oscillation cycles in prefrontal cortex and hippocampus on the order of 0.4 Hz phase-locked to task events at crucial maze locations. Indeed, successive cycles of the infra-slow rhythms showed different wavelengths, as if they are periodic oscillations that can reset phase relative to salient events. Simultaneously recorded infra-slow rhythms in prefrontal cortex and hippocampus could show different cycle durations as well, suggesting independent control. Most LC neurons (including optogenetically identified noradrenergic neurons) recorded here were phase-locked to these infra-slow rhythms, as were hippocampal and prefrontal units recorded on the LFP probes. The infra-slow oscillations also phase-modulated gamma amplitude, linking these rhythms at the time scale of behavior to those coordinating neuronal synchrony. This would provide a potential mechanism where noradrenaline, released by LC neurons in concert with the infra-slow rhythm, would facilitate synchronization or reset of these brain networks, underlying behavioral adaptation
Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution
Simultaneous recordings of many single neurons reveals unique insights into network processing spanning the timescale from single spikes to global oscillations. Neurons dynamically self-organize in subgroups of coactivated elements referred to as cell assemblies. Furthermore, these cell assemblies are reactivated, or replayed, preferentially during subsequent rest or sleep episodes, a proposed mechanism for memory trace consolidation. Here we employ Principal Component Analysis to isolate such patterns of neural activity. In addition, a measure is developed to quantify the similarity of instantaneous activity with a template pattern, and we derive theoretical distributions for the null hypothesis of no correlation between spike trains, allowing one to evaluate the statistical significance of instantaneous coactivations. Hence, when applied in an epoch different from the one where the patterns were identified, (e.g. subsequent sleep) this measure allows to identify times and intensities of reactivation. The distribution of this measure provides information on the dynamics of reactivation events: in sleep these occur as transients rather than as a continuous process
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses
Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions
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