Notch/Delta signaling constrains reengineering of pro-T cells by PU.1

PU.1 is essential for early stages of mouse T cell development but antagonizes it if expressed constitutively. Two separable mechanisms are involved: attenuation and diversion. Dysregulated PU.1 expression inhibits pro-T cell survival, proliferation, and passage through β-selection by blocking essential T cell transcription factors, signaling molecules, and Rag gene expression, which expression of a rearranged T cell antigen receptor transgene cannot rescue. However, Bcl2 transgenic cells are protected from this attenuation and may even undergo β-selection, as shown by PU.1 transduction of defined subsets of Bcl2 transgenic fetal thymocytes with differentiation in OP9-DL1 and OP9 control cultures. The outcome of PU.1 expression in these cells depends on Notch/Delta signaling. PU.1 can efficiently divert thymocytes toward a myeloid-like state with multigene regulatory changes, but Notch/Delta signaling vetoes diversion. Gene expression analysis distinguishes sets of critical T lineage regulatory genes with different combinatorial responses to PU.1 and Notch/Delta signals, suggesting particular importance for inhibition of E proteins, Myb, and/or Gfi1 (growth factor independence 1) in diversion. However, Notch signaling only protects against diversion of cells that have undergone T lineage specification after Thy-1 and CD25 up-regulation. The results imply that in T cell precursors, Notch/Delta signaling normally acts to modulate and channel PU.1 transcriptional activities during the stages from T lineage specification until commitment

Hormonal basis of sex differences in anesthetic sensitivity

General anesthesia-a pharmacologically induced reversible state of unconsciousness-enables millions of life-saving procedures. Anesthetics induce unconsciousness in part by impinging upon sexually dimorphic and hormonally sensitive hypothalamic circuits regulating sleep and wakefulness. Thus, we hypothesized that anesthetic sensitivity should be sex-dependent and modulated by sex hormones. Using distinct behavioral measures, we show that at identical brain anesthetic concentrations, female mice are more resistant to volatile anesthetics than males. Anesthetic sensitivity is bidirectionally modulated by testosterone. Castration increases anesthetic resistance. Conversely, testosterone administration acutely increases anesthetic sensitivity. Conversion of testosterone to estradiol by aromatase is partially responsible for this effect. In contrast, oophorectomy has no effect. To identify the neuronal circuits underlying sex differences, we performed whole brain c-Fos activity mapping under anesthesia in male and female mice. Consistent with a key role of the hypothalamus, we found fewer active neurons in the ventral hypothalamic sleep-promoting regions in females than in males. In humans, we demonstrate that females regain consciousness and recover cognition faster than males after identical anesthetic exposures. Remarkably, while behavioral and neurocognitive measures in mice and humans point to increased anesthetic resistance in females, cortical activity fails to show sex differences under anesthesia in either species. Cumulatively, we demonstrate that sex differences in anesthetic sensitivity are evolutionarily conserved and not reflected in conventional electroencephalographic-based measures of anesthetic depth. This covert resistance to anesthesia may explain the higher incidence of unintended awareness under general anesthesia in females

History-Dependent Excitability as a Single-Cell Substrate of Transient Memory for Information Discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron “sees” through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types

A stochastic basis for neural inertia in emergence from general anaesthesia

BackgroundTransitions into and out of the anaesthetised state exhibit resistance to state transitions known as neural inertia. As a consequence, emergence from anaesthesia occurs at a consistently lower anaesthetic concentration than induction. Motivated by stochastic switching between discrete activity patterns observed at constant anaesthetic concentration, we investigated the consequences of such switching for neural inertia.MethodsWe simulated stochastic switching in MATLAB as Brownian motion on an energy landscape or equivalently as a discrete Markov process. Effects of anaesthetics were modelled as changing stability of the awake and the anaesthetised states. Simulation results were compared with re-analysed neural inertia data from mice and Drosophila.ResultsDiffusion on a two-well energy landscape gives rise to hysteresis. With additive noise, hysteresis collapses. This collapse occurs over a mixing time that is independent from pharmacokinetics. The two-well potential gives rise to the leftward shift for the emergence dose-response curve. Yet, from in vivo data, ΔEC50 and Δ Hill slope are strongly negatively correlated (R2=0.45, P<1.7×10-15). This correlation is not explained by a two-well potential. The extension of the diffusion model to a Markov process with 10 states (three awake, seven unconscious) reproduces both the left shift and the shallower Hill slope for emergence.ConclusionsStochastic state switching accounts for all known features of neural inertia. More than two states are required to explain the consistent increase observed in variability of recovery from general anaesthesia. This model predicts that hysteresis should collapse with a time scale independent of anaesthetic drug pharmacokinetics

Scale invariance in the dynamics of spontaneous behavior

Typically one expects that the intervals between consecutive occurrences of a particular behavior will have a characteristic time scale around which most observations are centered. Surprisingly, the timing of many diverse behaviors from human communication to animal foraging form complex self-similar temporal patterns re-produced on multiple time scales. We present a general framework for understanding how such scale invariance may arise in nonequilibrium systems, including those that regulate mammalian behaviors. We then demonstrate that the predictions of this framework are in agreement with detailed analysis of spontaneous mouse behavior observed in a simple unchanging environment. Neural systems operate on a broad range of time scales, from milliseconds to hours. We analytically show that such a separation between time scales could lead to scale-invariant dynamics without any fine tuning of parameters or other model-specific constraints. Our analyses reveal that the specifics of the distribution of resources or competition among several tasks are not essential for the expression of scale-free dynamics. Rather, we show that scale invariance observed in the dynamics of behavior can arise from the dynamics intrinsic to the brain

Regulation of afferent transmission in the feeding circuitry of Aplysia

Although feeding in Aplysia is mediated by a central pattern generator (CPG), the activity of this CPG is modified by afferent input. To determine how afferent activity produces the widespread changes in motor programs that are necessary if behavior is to be modified, we have studied two classes of feeding sensory neurons. We have shown that afferent-induced changes in activity are widespread because sensory neurons make a number of synaptic connections. For example, sensory neurons make monosynaptic excitatory connections with feeding motor neurons. Sensori-motor transmission is, however, regulated so that changes in the periphery do not disrupt ongoing activity. This results from the fact that sensory neurons are also electrically coupled to feeding interneurons. During motor programs sensory neurons are, therefore, rhythmically depolarized via central input. These changes in membrane potential profoundly affect sensori-motor transmission. For example, changes in membrane potential alter spike propagation in sensory neurons so that spikes are only actively transmitted to particular output regions when it is behaviorally appropriate. To summarize, afferent activity alters motor output because sensory neurons make direct contact with motor neurons. Sensori-motor transmission is, however, centrally regulated so that changes in the periphery alter motor programs in a phase-dependent manner