Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks V: self-organization schemes and weight dependence

Spike-timing-dependent plasticity (STDP) determines the evolution of the synaptic weights according to their pre- and post-synaptic activity, which in turn changes the neuronal activity on a (much) slower time scale. This paper examines the effect of STDP in a recurrently connected network stimulated by external pools of input spike trains, where both input and recurrent synapses are plastic. Our previously developed theoretical framework is extended to incorporate weight-dependent STDP and dendritic delays. The weight dynamics is determined by an interplay between the neuronal activation mechanisms, the input spike-time correlations, and the learning parameters. For the case of two external input pools, the resulting learning scheme can exhibit a symmetry breaking of the input connections such that two neuronal groups emerge, each specialized to one input pool only. In addition, we show how the recurrent connections within each neuronal group can be strengthened by STDP at the expense of those between the two groups. This neuronal self-organization can be seen as a basic dynamical ingredient for the emergence of neuronal maps induced by activity-dependent plasticity.     

Birth Origin Differentially Affects Depressive-Like Behaviours: Are Captive-Born Cynomolgus Monkeys More Vulnerable to Depression than Their Wild-Born Counterparts?

Background

Adverse early-life experience might lead to the expression of abnormal behaviours in animals and the predisposition to psychiatric disorder (e.g. major depressive disorder) in Humans. Common breeding processes employ weaning and housing conditions different from what happens in the wild.

Methods

The present study, therefore, investigated whether birth origin impacts the possible existence of spontaneous atypical/abnormal behaviours displayed by 40 captive-born and 40 wild-born socially-housed cynomolgus macaques in farming conditions using an unbiased ethological scan-sampling analysis followed by multifactorial correspondence and hierarchical clustering analyses.

Results

We identified 10 distinct profiles (groups A to J) that significantly differed on several behaviours, body postures, body orientations, distances between individuals and locations in the cage. Data suggest that 4 captive-born and 1 wild-born animals (groups G and J) present depressive-like symptoms, unnatural early life events thereby increasing the risk of developing pathological symptoms. General differences were also highlighted between the captive- and wild-born populations, implying the expression of differential coping mechanisms in response to the same captive environment.

Conclusions

Birth origin thus impacts the development of atypical ethologically-defined behavioural profiles, reminiscent of certain depressive-like symptoms. The use of unbiased behavioural observations might allow the identification of animal models of human mental/behavioural disorders and their most appropriate control groups.     

Coexistence of Reward and Unsupervised Learning During the Operant Conditioning of Neural Firing Rates

A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditioning, are performed by the brain. Typical and well studied examples of operant conditioning, in which the firing rates of individual cortical neurons in monkeys are increased using rewards, provide an opportunity for insight into this. Studies of reward-modulated spike-timing-dependent plasticity (RSTDP), and of other models such as R-max, have reproduced this learning behavior, but they have assumed that no unsupervised learning is present (i.e., no learning occurs without, or independent of, rewards). We show that these models cannot elicit firing rate reinforcement while exhibiting both reward learning and ongoing, stable unsupervised learning. To fix this issue, we propose a new RSTDP model of synaptic plasticity based upon the observed effects that dopamine has on long-term potentiation and depression (LTP and LTD). We show, both analytically and through simulations, that our new model can exhibit unsupervised learning and lead to firing rate reinforcement. This requires that the strengthening of LTP by the reward signal is greater than the strengthening of LTD and that the reinforced neuron exhibits irregular firing. We show the robustness of our findings to spike-timing correlations, to the synaptic weight dependence that is assumed, and to changes in the mean reward. We also consider our model in the differential reinforcement of two nearby neurons. Our model aligns more strongly with experimental studies than previous models and makes testable predictions for future experiments.     

Herbal medicine use in the districts of Nakapiripirit, Pallisa, Kanungu, and Mukono in Uganda

ABSTRACT: BACKGROUND: Traditional medicine (TM) occupies a special place in the management of diseases in Uganda. Not with standing the many people relying on TM, indigenous knowledge (IK) related to TM is getting steadily eroded. To slow down this loss it is necessary to document and conserve as much of the knowledge as possible. This study was conducted to document the IK relevant to traditional medicine in the districts of Mukono, Nakapiripirit, Kanungu and Pallisa, in Uganda. METHODS: An ethnobotanical survey was conducted between October 2008 and February 2009 using techniques of key informant interviews and household interviews. RESULTS: The common diseases and conditions in the four districts include malaria, cough, headache, diarrhea, abdominal pain, flu, backache and eye diseases. Respondents stated that when they fall sick they self medicate using plant medicines or consult western-trained medicine practitioners. Self medication using herbal medicines was reported mostly by respondents of Nakapiripirit and Mukono. Respondents have knowledge to treat 78 ailments using herbal medicines. 44 species, mentioned by three or more respondents have been prioritized. The most frequently used part in herbal medicines is the leaf, followed by the stem and root. People sometime use animal parts, soil, salt and water from a grass roof, in traditional medicines. Herbal medicines are stored for short periods of time in bottles. The knowledge to treat ailments is acquired from parents and grandparents. Respondents' age and tribe appears to have a significant influence on knowledge of herbal medicine, while gender does not. CONCLUSION: This survey has indicated that IK associated with TM stills exists and that TM is still important in Uganda because many people use it as a first line of health care when they fall sick. Age and tribe influence the level of IK associated with herbal medicine, but gender does not.     

Spectral analysis of input spike trains by spike-timing-dependent plasticity

Spike-timing-dependent plasticity (STDP) has been observed in many brain areas such as sensory cortices, where it is hypothesized to structure synaptic connections between neurons. Previous studies have demonstrated how STDP can capture spiking information at short timescales using specific input configurations, such as coincident spiking, spike patterns and oscillatory spike trains. However, the corresponding computation in the case of arbitrary input signals is still unclear. This paper provides an overarching picture of the algorithm inherent to STDP, tying together many previous results for commonly used models of pairwise STDP. For a single neuron with plastic excitatory synapses, we show how STDP performs a spectral analysis on the temporal cross-correlograms between its afferent spike trains. The postsynaptic responses and STDP learning window determine kernel functions that specify how the neuron "sees" the input correlations. We thus denote this unsupervised learning scheme as 'kernel spectral component analysis' (kSCA). In particular, the whole input correlation structure must be considered since all plastic synapses compete with each other. We find that kSCA is enhanced when weight-dependent STDP induces gradual synaptic competition. For a spiking neuron with a "linear" response and pairwise STDP alone, we find that kSCA resembles principal component analysis (PCA). However, plain STDP does not isolate correlation sources in general, e.g., when they are mixed among the input spike trains. In other words, it does not perform independent component analysis (ICA). Tuning the neuron to a single correlation source can be achieved when STDP is paired with a homeostatic mechanism that reinforces the competition between synaptic inputs. Our results suggest that neuronal networks equipped with STDP can process signals encoded in the transient spiking activity at the timescales of tens of milliseconds for usual STDP.     

Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients

Background

Bone marrow stromal cell antigen 2 (BST-2) is a cellular factor that restricts the egress of viruses such as human immunodeficiency virus (HIV-1) from the surface of infected cells, preventing infection of new cells. BST-2 is variably expressed in most cell types, and its expression is enhanced by cytokines such as type I interferon alpha (IFN-??). In this present study, we used the beta-retrovirus, mouse mammary tumor virus (MMTV) as a model to examine the role of mouse BST-2 in host infection in vivo.

Results

By using RNA interference, we show that loss of BST-2 enhances MMTV replication in cultured mammary tumor cells and in vivo. In cultured cells, BST-2 inhibits virus accumulation in the culture medium, and co-localizes at the cell surface with virus structural proteins. Furthermore, both scanning electron micrograph (SEM) and transmission electron micrograph (TEM) show that MMTV accumulates on the surface of IFN??-stimulated cells.

Conclusions

Our data provide evidence that BST-2 restricts MMTV release from naturally infected cells and that BST-2 is an antiviral factor in vivo.     

Lack of association between glucocorticoid use and presence of the metabolic syndrome in patients with rheumatoid arthritis: a cross-sectional study

Lupus nephritis is a major contributor to morbidity and mortality in systemic lupus erythematosus, but little is known about the pathogenic processes that underlie the progressive decay in renal function. A common finding in lupus nephritis is thickening of glomerular basement membranes associated with immune complex deposition. It has been speculated that alterations in the synthesis or degradation of membrane components might contribute to such changes, and thereby to initiation and progression of nephritis through facilitation of immune complex deposition. Matrix metalloproteinases (MMPs) are enzymes that are intimately involved in the turnover of major glomerular basement membrane constituents, including collagen IV and laminins. Alterations in the expression and activity of MMPs have been described in a number of renal diseases, suggesting their relevance to the pathogenesis of various glomerulopathies. The same is true for their natural inhibitors, the tissue inhibitor of metalloproteinase family. Recent data from our group have identified an increase in proteolytic activity within the glomerulus coinciding with the development of proteinuria in the mouse model of systemic lupus erythematosus. (NXB × NZW)F₁ Here we review current understanding of MMP/tissue inhibitor of metalloproteinase function within the kidney, and discuss their possible involvement in the development and progression of lupus nephritis.