Dynamics of Sleep-Wake Transitions During Sleep

We study the dynamics of the awakening during the night for healthy subjects and find that the wake and the sleep periods exhibit completely different behavior: the durations of wake periods are characterized by a scale-free power-law distribution, while the durations of sleep periods have an exponential distribution with a characteristic time scale. We find that the characteristic time scale of sleep periods changes throughout the night. In contrast, there is no measurable variation in the power-law behavior for the durations of wake periods. We develop a stochastic model which agrees with the data and suggests that the difference in the dynamics of sleep and wake states arises from the constraints on the number of microstates in the sleep-wake system.Comment: Final form with some small corrections. To be published in Europhysics Letters, vol. 57, issue no. 5, 1 March 2002, pp. 625-63

Genetic manipulation of adult-born hippocampal neurons rescues memory in a mouse model of Alzheimer's disease.

In adult mammals, neural progenitors located in the dentate gyrus retain their ability to generate neurons and glia throughout lifetime. In rodents, increased production of new granule neurons is associated with improved memory capacities, while decreased hippocampal neurogenesis results in impaired memory performance in several memory tasks. In mouse models of Alzheimer's disease, neurogenesis is impaired and the granule neurons that are generated fail to integrate existing networks. Thus, enhancing neurogenesis should improve functional plasticity in the hippocampus and restore cognitive deficits in these mice. Here, we performed a screen of transcription factors that could potentially enhance adult hippocampal neurogenesis. We identified Neurod1 as a robust neuronal determinant with the capability to direct hippocampal progenitors towards an exclusive granule neuron fate. Importantly, Neurod1 also accelerated neuronal maturation and functional integration of new neurons during the period of their maturation when they contribute to memory processes. When tested in an APPxPS1 mouse model of Alzheimer's disease, directed expression of Neurod1 in cycling hippocampal progenitors conspicuously reduced dendritic spine density deficits on new hippocampal neurons, to the same level as that observed in healthy age-matched control animals. Remarkably, this population of highly connected new neurons was sufficient to restore spatial memory in these diseased mice. Collectively our findings demonstrate that endogenous neural stem cells of the diseased brain can be manipulated to become new neurons that could allow cognitive improvement

Transformational capacity and the influence of place and identity

Climate change is altering the productivity of natural resources with far-reaching implications for those who depend on them. Resource-dependent industries and communities need the capacity to adapt to a range of climate risks if they are to remain viable. In some instances, the scale and nature of the likely impacts means that transformations of function or structure will be required. Transformations represent a switch to a distinct new system where a different suite of factors become important in the design and implementation of response strategies. There is a critical gap in knowledge on understanding transformational capacity and its influences. On the basis of current knowledge on adaptive capacity we propose four foundations for measuring transformational capacity: (1)how risks and uncertainty are managed, (2)the extent of skills in planning, learning and reorganizing, (3)the level of financial and psychological flexibility to undertake change and (4)the willingness to undertake change. We test the influence of place attachment and occupational identity on transformational capacity using the Australian peanut industry, which is presently assessing significant structural change in response to predicted climatic changes. Survey data from 88% of peanut farmers in Queensland show a strong negative correlation between transformational capacity and both place attachment and occupational attachment, suggesting that whilst these factors may be important positive influences on the capacity to adapt to incremental change, they act as barriers to transformational change

Cortical fast-spiking parvalbumin interneurons enwrapped in the perineuronal net express the metallopeptidases Adamts8, Adamts15 and Neprilysin.

The in situ hybridization Allen Mouse Brain Atlas was mined for proteases expressed in the somatosensory cerebral cortex. Among the 480 genes coding for protease/peptidases, only four were found enriched in cortical interneurons: Reln coding for reelin; Adamts8 and Adamts15 belonging to the class of metzincin proteases involved in reshaping the perineuronal net (PNN) and Mme encoding for Neprilysin, the enzyme degrading amyloid β-peptides. The pattern of expression of metalloproteases (MPs) was analyzed by single-cell reverse transcriptase multiplex PCR after patch clamp and was compared with the expression of 10 canonical interneurons markers and 12 additional genes from the Allen Atlas. Clustering of these genes by K-means algorithm displays five distinct clusters. Among these five clusters, two fast-spiking interneuron clusters expressing the calcium-binding protein Pvalb were identified, one co-expressing Pvalb with Sst (PV-Sst) and another co-expressing Pvalb with three metallopeptidases Adamts8, Adamts15 and Mme (PV-MP). By using Wisteria floribunda agglutinin, a specific marker for PNN, PV-MP interneurons were found surrounded by PNN, whereas the ones expressing Sst, PV-Sst, were not

Circuit-based interrogation of sleep control.

Sleep is a fundamental biological process observed widely in the animal kingdom, but the neural circuits generating sleep remain poorly understood. Understanding the brain mechanisms controlling sleep requires the identification of key neurons in the control circuits and mapping of their synaptic connections. Technical innovations over the past decade have greatly facilitated dissection of the sleep circuits. This has set the stage for understanding how a variety of environmental and physiological factors influence sleep. The ability to initiate and terminate sleep on command will also help us to elucidate its functions within and beyond the brain

The Neuronal Transition Probability (NTP) Model for the Dynamic Progression of Non-REM Sleep EEG: The Role of the Suprachiasmatic Nucleus

Little attention has gone into linking to its neuronal substrates the dynamic structure of non-rapid-eye-movement (NREM) sleep, defined as the pattern of time-course power in all frequency bands across an entire episode. Using the spectral power time-courses in the sleep electroencephalogram (EEG), we showed in the typical first episode, several moves towards-and-away from deep sleep, each having an identical pattern linking the major frequency bands beta, sigma and delta. The neuronal transition probability model (NTP) – in fitting the data well – successfully explained the pattern as resulting from stochastic transitions of the firing-rates of the thalamically-projecting brainstem-activating neurons, alternating between two steady dynamic-states (towards-and-away from deep sleep) each initiated by a so-far unidentified flip-flop. The aims here are to identify this flip-flop and to demonstrate that the model fits well all NREM episodes, not just the first. Using published data on suprachiasmatic nucleus (SCN) activity we show that the SCN has the information required to provide a threshold-triggered flip-flop for timing the towards-and-away alternations, information provided by sleep-relevant feedback to the SCN. NTP then determines the pattern of spectral power within each dynamic-state. NTP was fitted to individual NREM episodes 1–4, using data from 30 healthy subjects aged 20–30 years, and the quality of fit for each NREM measured. We show that the model fits well all NREM episodes and the best-fit probability-set is found to be effectively the same in fitting all subject data. The significant model-data agreement, the constant probability parameter and the proposed role of the SCN add considerable strength to the model. With it we link for the first time findings at cellular level and detailed time-course data at EEG level, to give a coherent picture of NREM dynamics over the entire night and over hierarchic brain levels all the way from the SCN to the EEG

A Conserved Behavioral State Barrier Impedes Transitions between Anesthetic-Induced Unconsciousness and Wakefulness: Evidence for Neural Inertia

One major unanswered question in neuroscience is how the brain transitions between conscious and unconscious states. General anesthetics offer a controllable means to study these transitions. Induction of anesthesia is commonly attributed to drug-induced global modulation of neuronal function, while emergence from anesthesia has been thought to occur passively, paralleling elimination of the anesthetic from its sites in the central nervous system (CNS). If this were true, then CNS anesthetic concentrations on induction and emergence would be indistinguishable. By generating anesthetic dose-response data in both insects and mammals, we demonstrate that the forward and reverse paths through which anesthetic-induced unconsciousness arises and dissipates are not identical. Instead they exhibit hysteresis that is not fully explained by pharmacokinetics as previously thought. Single gene mutations that affect sleep-wake states are shown to collapse or widen anesthetic hysteresis without obvious confounding effects on volatile anesthetic uptake, distribution, or metabolism. We propose a fundamental and biologically conserved concept of neural inertia, a tendency of the CNS to resist behavioral state transitions between conscious and unconscious states. We demonstrate that such a barrier separates wakeful and anesthetized states for multiple anesthetics in both flies and mice, and argue that it contributes to the hysteresis observed when the brain transitions between conscious and unconscious states

Sustainability Science

Meeting fundamental human needs while preserving earth's life support systems will require an accelerated transition toward sustainability. A new field of sustainability science is emerging that seeks to understand the fundamental character of interactions between nature and society and to encourage the interactions along more sustainable trajectories. Such an integrated, place-based science will require new research strategies and institutional innovations to enable them especially in developing countries still separated by deepening divides from mainstream science. Sustainability science needs to be widely discussed in the scientific community, reconnected to the political agenda for sustainable development, and become a major focus for research

The waking brain: an update

Wakefulness and consciousness depend on perturbation of the cortical soliloquy. Ascending activation of the cerebral cortex is characteristic for both waking and paradoxical (REM) sleep. These evolutionary conserved activating systems build a network in the brainstem, midbrain, and diencephalon that contains the neurotransmitters and neuromodulators glutamate, histamine, acetylcholine, the catecholamines, serotonin, and some neuropeptides orchestrating the different behavioral states. Inhibition of these waking systems by GABAergic neurons allows sleep. Over the past decades, a prominent role became evident for the histaminergic and the orexinergic neurons as a hypothalamic waking center