Coding of reward risk by orbitofrontal neurons is mostly distinct from coding of reward value

Risky decision-making is altered in humans and animals with damage to the orbitofrontal cortex. However, the cellular function of the intact orbitofrontal cortex in processing information relevant for risky decisions is unknown. We recorded responses of single orbitofrontal neurons while monkeys viewed visual cues representing the key decision parameters, reward risk and value. Risk was defined as the mathematical variance of binary symmetric probability distributions of reward magnitudes; value was defined as non-risky reward magnitude. Monkeys displayed graded behavioral preferences for risky outcomes, as they did for value. A population of orbitofrontal neurons showed a distinctive risk signal: their cues and reward responses covaried monotonically with the variance of the different reward distributions without monotonically coding reward value. Furthermore, a small but statistically significant fraction of risk responses also coded reward value. These risk signals may provide physiological correlates for the role of the orbitofrontal cortex in risk processing.     

Developmental Profiles of Lipogenic Enzymes and Their Regulators in the Neonatal Mouse Brain

It has been shown that lipogenic enzymes, such as fatty acid synthase (FAS) and acetyl-CoA carboxylase (ACC), are highly expressed in the rodent brain during the early neonatal period and decline thereafter. However, cellular localization of these enzymes is unknown. Presently, we examined developmental changes in the levels and cellular localization of FAS and ACC, and their putative regulators, sterol-regulatory element-binding protein (SREBP)-1 and AMP-activated protein kinase (AMPK) in the mouse brain. Levels of these proteins including phosphorylated forms of ACC and AMPK decreased between postnatal day 4 (P4) and P19. Immunohistochemical studies indicated that FAS, ACC, AMPK, and SREBP-1 were expressed in neurons at P7, while FAS was found mostly in cells of oligodendrocyte lineage at P19. These studies suggest that neurons in the early neonatal brain are involved in do novo fatty acid synthesis.     

Decorrelation of Neural-Network Activity by Inhibitory Feedback

Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between excitatory (E) and inhibitory (I) neurons, but a consequence of a particular structure of correlations among the three possible pairings (EE, EI, II).     

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the "damaged" network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times ([Formula: see text]) network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight.     

Senescent endothelial cells are prone to TNF-α-induced cell death due to expression of FAS receptor

The senescent endothelial cells show various phenotypes which can increase the incidence of inflammatory cardiovascular diseases, but the fundamental basis for such phenotypic changes of senescing cells remains to be elucidated. This study was undertaken to find transmembrane receptors that might be highly expressed in senescent endothelial cells and play a key role in cell death signal transduction. Comparison of mRNA expression in young and senescent human umbilical vein endothelial cells, using a cDNA microarray method, provided a list of transmembrane receptors including the FAS receptor (tumor necrosis factor receptor superfamily member 6) whose expression levels were significantly increased by cellular senescence. Additional studies focused on FAS demonstrated that a high expression of FAS receptor in senescent endothelial cells is responsible for the susceptibility to apoptotic cell death, as the siRNA-mediated suppression of FAS expression in senescent cells prevented the cell death, and overexpression of exogenous FAS in young cells increased cell death. We also verified that FAS expression level was closely associated with the activation of caspase-3 and caspase-9 involved in apoptosis. The senescence-induced transmembrane receptors including the FAS receptor may provide novel therapeutic targets to prevent cardiovascular diseases.     

Perisomatic feedback inhibition underlies cholinergically induced fast network oscillations in the rat hippocampus in vitro

Gamma frequency network oscillations are assumed to be important in cognitive processes, including hippocampal memory operations, but the precise functions of these oscillations remain unknown. Here, we examine the cellular and network mechanisms underlying carbachol-induced fast network oscillations in the hippocampus in vitro, which closely resemble hippocampal gamma oscillations in the behaving rat. Using a combination of planar multielectrode array recordings, imaging with voltage-sensitive dyes, and recordings from single hippocampal neurons within the CA3 gamma generator, active current sinks and sources were localized to the stratum pyramidale. These proximal currents were driven by phase-locked rhythmic inhibitory inputs to pyramidal cells from identified perisomatic-targeting interneurons. AMPA receptor-mediated recurrent excitation was necessary for the synchronization of interneuronal discharge, which strongly supports a synaptic feedback model for the generation of hippocampal gamma oscillations.     

Changes of mind in an attractor network of decision-making

Attractor networks successfully account for psychophysical and neurophysiological data in various decision-making tasks. Especially their ability to model persistent activity, a property of many neurons involved in decision-making, distinguishes them from other approaches. Stable decision attractors are, however, counterintuitive to changes of mind. Here we demonstrate that a biophysically-realistic attractor network with spiking neurons, in its itinerant transients towards the choice attractors, can replicate changes of mind observed recently during a two-alternative random-dot motion (RDM) task. Based on the assumption that the brain continues to evaluate available evidence after the initiation of a decision, the network predicts neural activity during changes of mind and accurately simulates reaction times, performance and percentage of changes dependent on difficulty. Moreover, the model suggests a low decision threshold and high incoming activity that drives the brain region involved in the decision-making process into a dynamical regime close to a bifurcation, which up to now lacked evidence for physiological relevance. Thereby, we further affirmed the general conformance of attractor networks with higher level neural processes and offer experimental predictions to distinguish nonlinear attractor from linear diffusion models.     

Zinc toxicity on neonatal cortical neurons: involvement of glutathione chelation

Several mechanisms have been implicated in pathological neuronal death including zinc neurotoxicity, calcium excitotoxicity and oxidative injury. Glutathione (GSH) serves to provide reducing equivalents for the maintenance of oxidant homeostasis, and also plays roles in intracellular and intercellular signaling in the brain. We investigated the role of GSH homeostasis in the neurotoxic action of zinc using both mixed cortical cultures containing neurons and glia, and cortical neurons prepared from 1-day-old rats. Zinc caused neuronal cell death in a concentration-dependent manner. In parallel, a high concentration of zinc depleted GSH, in a time-dependent manner, preceding the onset of neuronal damage. Depletion of GSH by diethylmaleate injured neurons and exacerbated zinc-induced death. In contrast, replenishment of GSH attenuated zinc neurotoxicity. The thiol-containing compounds N-acetylcysteine and GSH chemically chelated zinc leading to decreases in the influx of zinc, the fall in GSH level and neuronal death. Interestingly, the glycolytic substrate pyruvate, but not lactate, chelated zinc concentration dependently and prevented its toxicity. On the other hand, pyrrolidine dithiocarbamate, serving as a zinc chaperon, enhanced its entry and toxicity. The results suggest that zinc non-enzymatically depleted GSH, an intrinsic factor for neuron survival, leading to activation of the cellular death signal and eventually neuronal death.     

Opposing effects of the UV lesion repair protein XPA and UV bypass polymerase eta on ATR checkpoint signaling

An essential component of the ATR (ataxia telangiectasia-mutated and Rad3-related)-activating structure is single-stranded DNA. It has been suggested that nucleotide excision repair (NER) can lead to activation of ATR by generating such a signal, and in yeast, DNA damage processing through the NER pathway is necessary for checkpoint activation during G1. We show here that ultraviolet (UV) radiation-induced ATR signaling is compromised in XPA-deficient human cells during S phase, as shown by defects in ATRIP (ATR-interacting protein) translocation to sites of UV damage, UV-induced phosphorylation of Chk1 and UV-induced replication protein A phosphorylation and chromatin binding. However, ATR signaling was not compromised in XPC-, CSB-, XPF- and XPG-deficient cells. These results indicate that damage processing is not necessary for ATR-mediated S-phase checkpoint activation and that the lesion recognition function of XPA may be sufficient. In contrast, XP-V cells deficient in the UV bypass polymerase eta exhibited enhanced ATR signaling. Taken together, these results suggest that lesion bypass and not lesion repair may raise the level of UV damage that can be tolerated before checkpoint activation, and that XPA plays a critical role in this activation.     

Dystroglycan versatility in cell adhesion: a tale of multiple motifs

In the last fifteen years, rapid progress has been made in delineating the cellular response to DNA damage. The DNA damage response network is composed of a large number of proteins with different functions that detect and signal the presence of DNA damage in order to coordinate DNA repair with a variety of cellular processes, notably cell cycle progression. This signal, which radiates from the chromatin template, is driven primarily by phosphorylation events, mainly on serine and threonine residues. While we have accumulated detailed information about kinases and their substrates our understanding of the role of phosphatases in the DNA damage response is still preliminary. Identifying the phosphatases and their regulation will be instrumental to obtain a complete picture of the dynamics of the DNA damage response. Here we give an overview of the DNA damage response in mammalian cells and then review the data on the role of different phosphatases and discuss their biological relevance.     

Developmental changes of BOLD signal correlations with global human EEG power and synchronization during working memory

In humans, theta band (5-7 Hz) power typically increases when performing cognitively demanding working memory (WM) tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent) signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-)dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and synchronization and that these opposite correlations with different distributions undergo similar and significant neuronal developments with brain maturation.     

Gain modulation from background synaptic input

Gain modulation is a prominent feature of neuronal activity recorded in behaving animals, but the mechanism by which it occurs is unknown. By introducing a barrage of excitatory and inhibitory synaptic conductances that mimics conditions encountered in vivo into pyramidal neurons in slices of rat somatosensory cortex, we show that the gain of a neuronal response to excitatory drive can be modulated by varying the level of "background" synaptic input. Simultaneously increasing both excitatory and inhibitory background firing rates in a balanced manner results in a divisive gain modulation of the neuronal response without appreciable signal-independent increases in firing rate or spike-train variability. These results suggest that, within active cortical circuits, the overall level of synaptic input to a neuron acts as a gain control signal that modulates responsiveness to excitatory drive.     

Amyloid precursor protein-mediated free radicals and oxidative damage: implications for the development and progression of Alzheimer's disease

Alzheimer's disease (AD) is a late-onset dementia that is characterized by the loss of memory and an impairment of multiple cognitive functions. Advancements in molecular, cellular, and animal model studies have revealed that the formation of amyloid beta (Abeta) and other derivatives of the amyloid precursor protein (APP) are key factors in cellular changes in the AD brain, including the generation of free radicals, oxidative damage, and inflammation. Recent molecular, cellular, and gene expression studies have revealed that Abeta enters mitochondria, induces the generation of free radicals, and leads to oxidative damage in post-mortem brain neurons from AD patients and in brain neurons from cell models and transgenic mouse models of AD. In the last three decades, tremendous progress has been made in mitochondrial research and has provided significant findings to link mitochondrial oxidative damage and neurodegenerative diseases such as AD. Researchers in the AD field are beginning to recognize the possible involvement of a mutant APP and its derivatives in causing mitochondrial oxidative damage in AD. This article summarizes the latest research findings on the generation of free radicals in mitochondria and provides a possible model that links Abeta proteins, the generation of free radicals, and oxidative damage in AD development and progression.     

Brain signal predictions from multi-scale networks using a linearized framework

Simulations of neural activity at different levels of detail are ubiquitous in modern neurosciences, aiding the interpretation of experimental data and underlying neural mechanisms at the level of cells and circuits. Extracellular measurements of brain signals reflecting transmembrane currents throughout the neural tissue remain commonplace. The lower frequencies (≲ 300Hz) of measured signals generally stem from synaptic activity driven by recurrent interactions among neural populations and computational models should also incorporate accurate predictions of such signals. Due to limited computational resources, large-scale neuronal network models (≳ 10⁶ neurons or so) often require reducing the level of biophysical detail and account mainly for times of action potentials (‘spikes’) or spike rates. Corresponding extracellular signal predictions have thus poorly accounted for their biophysical origin.Here we propose a computational framework for predicting spatiotemporal filter kernels for such extracellular signals stemming from synaptic activity, accounting for the biophysics of neurons, populations, and recurrent connections. Signals are obtained by convolving population spike rates by appropriate kernels for each connection pathway and summing the contributions. Our main results are that kernels derived via linearized synapse and membrane dynamics, distributions of cells, conduction delay, and volume conductor model allow for accurately capturing the spatiotemporal dynamics of ground truth extracellular signals from conductance-based multicompartment neuron networks. One particular observation is that changes in the effective membrane time constants caused by persistent synapse activation must be accounted for.The work also constitutes a major advance in computational efficiency of accurate, biophysics-based signal predictions from large-scale spike and rate-based neuron network models drastically reducing signal prediction times compared to biophysically detailed network models. This work also provides insight into how experimentally recorded low-frequency extracellular signals of neuronal activity may be approximately linearly dependent on spiking activity. A new software tool LFPykernels serves as a reference implementation of the framework.     

A model for dynamic regulation of choline acetyltransferase by phosphorylation

Choline acetyltransferase (ChAT) synthesizes the neurotransmitter acetylcholine (ACh) and is a phenotypic marker for cholinergic neurons. Cholinergic neurons in brain are involved in cognitive function, attentional processing and motor control, and decreased ChAT activity is found in several neurological disorders including Alzheimer's disease. Dysregulation of ChAT and cholinergic communication is also associated with some spontaneous point-mutations in ChAT that alter its substrate binding kinetics, or by disruption of signaling pathways that could regulate protein kinases for which ChAT is a substrate. It has been identified recently that the catalytic activity and subcellular distribution of ChAT, and its interaction with other cellular proteins, can be modified by phosphorylation of the enzyme by protein kinase-C and Ca2+/calmodulin-dependent protein kinase II; these kinases appear also to mediate some of the effects of beta-amyloid peptides on cholinergic neuron functions, including the effects on ChAT. This review outlines a new model for the regulation of cholinergic transmission at the level of the presynaptic terminal that is mediated by hierarchically-regulated, multi-site phosphorylation of ChAT.     

Mechanisms of respiratory rhythm generation.

In mammals, a three-phasic respiratory rhythm is generated by a network of various types of neurons in the lower brainstem. The cellular mechanisms of rhythmogenesis involve cooperative interactions between synaptic processes and specific membrane properties. The network seems to be driven by extrinsic sources in mature animals, whereas in the immature network pacemaker neurons might be involved.     

Moderate traumatic brain injury causes acute dendritic and synaptic degeneration in the hippocampal dentate gyrus

Hippocampal injury-associated learning and memory deficits are frequent hallmarks of brain trauma and are the most enduring and devastating consequences following traumatic brain injury (TBI). Several reports, including our recent paper, showed that TBI brought on by a moderate level of controlled cortical impact (CCI) induces immature newborn neuron death in the hippocampal dentate gyrus. In contrast, the majority of mature neurons are spared. Less research has been focused on these spared neurons, which may also be injured or compromised by TBI. Here we examined the dendrite morphologies, dendritic spines, and synaptic structures using a genetic approach in combination with immunohistochemistry and Golgi staining. We found that although most of the mature granular neurons were spared following TBI at a moderate level of impact, they exhibited dramatic dendritic beading and fragmentation, decreased number of dendritic branches, and a lower density of dendritic spines, particularly the mushroom-shaped mature spines. Further studies showed that the density of synapses in the molecular layer of the hippocampal dentate gyrus was significantly reduced. The electrophysiological activity of neurons was impaired as well. These results indicate that TBI not only induces cell death in immature granular neurons, it also causes significant dendritic and synaptic degeneration in pathohistology. TBI also impairs the function of the spared mature granular neurons in the hippocampal dentate gyrus. These observations point to a potential anatomic substrate to explain, in part, the development of posttraumatic memory deficits. They also indicate that dendritic damage in the hippocampal dentate gyrus may serve as a therapeutic target following TBI.