The upshot of up states in the neocortex: From slow oscillations to memory formation

Contains fulltext : 201422.pdf (publisher's version ) (Open Access

Metabolomic profile of glycolysis and the pentose phosphate pathway identifies the central role of glucose-6-phosphate dehydrogenase in clear cell-renal cell carcinoma.

The analysis of cancer metabolome has shown that proliferating tumor cells require a large quantities of different nutrients in order to support their high rate of proliferation. In this study we analyzed the metabolic profile of glycolysis and the pentose phosphate pathway (PPP) in human clear cell-renal cell carcinoma (ccRCC) and evaluate the role of these pathways in sustaining cell proliferation, maintenance of NADPH levels, and production of reactive oxygen species (ROS). Metabolomic analysis showed a clear signature of increased glucose uptake and utilization in ccRCC tumor samples. Elevated levels of glucose-6-phosphate dehydrogenase (G6PDH) in association with higher levels of PPP-derived metabolites, suggested a prominent role of this pathway in RCC-associated metabolic alterations. G6PDH inhibition, caused a significant decrease in cancer cell survival, a decrease in NADPH levels, and an increased production of ROS, suggesting that the PPP plays an important role in the regulation of ccRCC redox homeostasis. Patients with high levels of glycolytic enzymes had reduced progression-free and cancer-specific survivals as compared to subjects with low levels. Our data suggest that oncogenic signaling pathways may promote ccRCC through rerouting the sugar metabolism. Blocking the flux through this pathway may serve as a novel therapeutic target

Multiplexed, High Density Electrophysiology with Nanofabricated Neural Probes

Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC) performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable

Continuous Attractors with Morphed/Correlated Maps

Continuous attractor networks are used to model the storage and representation of analog quantities, such as position of a visual stimulus. The storage of multiple continuous attractors in the same network has previously been studied in the context of self-position coding. Several uncorrelated maps of environments are stored in the synaptic connections, and a position in a given environment is represented by a localized pattern of neural activity in the corresponding map, driven by a spatially tuned input. Here we analyze networks storing a pair of correlated maps, or a morph sequence between two uncorrelated maps. We find a novel state in which the network activity is simultaneously localized in both maps. In this state, a fixed cue presented to the network does not determine uniquely the location of the bump, i.e. the response is unreliable, with neurons not always responding when their preferred input is present. When the tuned input varies smoothly in time, the neuronal responses become reliable and selective for the environment: the subset of neurons responsive to a moving input in one map changes almost completely in the other map. This form of remapping is a non-trivial transformation between the tuned input to the network and the resulting tuning curves of the neurons. The new state of the network could be related to the formation of direction selectivity in one-dimensional environments and hippocampal remapping. The applicability of the model is not confined to self-position representations; we show an instance of the network solving a simple delayed discrimination task

Prediction and Topological Models in Neuroscience

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone

Delayed Onset of a Daytime Nap Facilitates Retention of Declarative Memory

BACKGROUND: Learning followed by a period of sleep, even as little as a nap, promotes memory consolidation. It is now generally recognized that sleep facilitates the stabilization of information acquired prior to sleep. However, the temporal nature of the effect of sleep on retention of declarative memory is yet to be understood. We examined the impact of a delayed nap onset on the recognition of neutral pictorial stimuli with an added spatial component. METHODOLOGY/PRINCIPAL FINDINGS: Participants completed an initial study session involving 150 neutral pictures of people, places, and objects. Immediately following the picture presentation, participants were asked to make recognition judgments on a subset of "old", previously seen, pictures versus intermixed "new" pictures. Participants were then divided into one of four groups who either took a 90-minute nap immediately, 2 hours, or 4 hours after learning, or remained awake for the duration of the experiment. 6 hours after initial learning, participants were again tested on the remaining "old" pictures, with "new" pictures intermixed. CONCLUSIONS/SIGNIFICANCE: Interestingly, we found a stabilizing benefit of sleep on the memory trace reflected as a significant negative correlation between the average time elapsed before napping and decline in performance from test to retest (p = .001). We found a significant interaction between the groups and their performance from test to retest (p = .010), with the 4-hour delay group performing significantly better than both those who slept immediately and those who remained awake (p = .044, p = .010, respectively). Analysis of sleep data revealed a significant positive correlation between amount of slow wave sleep (SWS) achieved and length of the delay before sleep onset (p = .048). The findings add to the understanding of memory processing in humans, suggesting that factors such as waking processing and homeostatic increases in need for sleep over time modulate the importance of sleep to consolidation of neutral declarative memories

Customized birth weight for gestational age standards: Perinatal mortality patterns are consistent with separate standards for males and females but not for blacks and whites

BACKGROUND: Some currently available birth weight for gestational age standards are customized but others are not. We carried out a study to provide empirical justification for customizing such standards by sex and for whites and blacks in the United States. METHODS: We studied all male and female singleton live births and stillbirths (22 or more weeks of gestation; 500 g birth weight or over) in the United States in 1997 and 1998. White and black singleton live births and stillbirths were also examined. Qualitative congruence between gestational age-specific growth restriction and perinatal mortality rates was used as the criterion for identifying the preferred standard. RESULTS: The fetuses at risk approach showed that males had higher perinatal mortality rates at all gestational ages compared with females. Gestational age-specific growth restriction rates based on a sex-specific standard were qualitatively consistent with gestational age-specific perinatal mortality rates among males and females. However, growth restriction patterns among males and females based on a unisex standard could not be reconciled with perinatal mortality patterns. Use of a single standard for whites and blacks resulted in gestational age-specific growth restriction rates that were qualitatively congruent with patterns of perinatal mortality, while use of separate race-specific standards led to growth restriction patterns that were incompatible with patterns of perinatal mortality. CONCLUSION: Qualitative congruence between growth restriction and perinatal mortality patterns provides an outcome-based justification for sex-specific birth weight for gestational age standards but not for the available race-specific standards for blacks and whites in the United States

Explicit-Duration Hidden Markov Model Inference of UP-DOWN States from Continuous Signals

Neocortical neurons show UP-DOWN state (UDS) oscillations under a variety of conditions. These UDS have been extensively studied because of the insight they can yield into the functioning of cortical networks, and their proposed role in putative memory formation. A key element in these studies is determining the precise duration and timing of the UDS. These states are typically determined from the membrane potential of one or a small number of cells, which is often not sufficient to reliably estimate the state of an ensemble of neocortical neurons. The local field potential (LFP) provides an attractive method for determining the state of a patch of cortex with high spatio-temporal resolution; however current methods for inferring UDS from LFP signals lack the robustness and flexibility to be applicable when UDS properties may vary substantially within and across experiments. Here we present an explicit-duration hidden Markov model (EDHMM) framework that is sufficiently general to allow statistically principled inference of UDS from different types of signals (membrane potential, LFP, EEG), combinations of signals (e.g., multichannel LFP recordings) and signal features over long recordings where substantial non-stationarities are present. Using cortical LFPs recorded from urethane-anesthetized mice, we demonstrate that the proposed method allows robust inference of UDS. To illustrate the flexibility of the algorithm we show that it performs well on EEG recordings as well. We then validate these results using simultaneous recordings of the LFP and membrane potential (MP) of nearby cortical neurons, showing that our method offers significant improvements over standard methods. These results could be useful for determining functional connectivity of different brain regions, as well as understanding network dynamics

Duloxetine Inhibits Effects of MDMA (“Ecstasy") In Vitro and in Humans in a Randomized Placebo-Controlled Laboratory Study

This study assessed the effects of the serotonin (5-HT) and norepinephrine (NE) transporter inhibitor duloxetine on the effects of 3,4–methylenedioxy­methamphetamine (MDMA, ecstasy) in vitro and in 16 healthy subjects. The clinical study used a double-blind, randomized, placebo-controlled, four-session, crossover design. In vitro, duloxetine blocked the release of both 5-HT and NE by MDMA or by its metabolite 3,4-methylenedioxyamphetamine from transmitter-loaded human cells expressing the 5-HT or NE transporter. In humans, duloxetine inhibited the effects of MDMA including elevations in circulating NE, increases in blood pressure and heart rate, and the subjective drug effects. Duloxetine inhibited the pharmacodynamic response to MDMA despite an increase in duloxetine-associated elevations in plasma MDMA levels. The findings confirm the important role of MDMA-induced 5-HT and NE release in the psychotropic effects of MDMA. Duloxetine may be useful in the treatment of psychostimulant dependence