STDP-driven networks and the \emph{C. elegans} neuronal network

We study the dynamics of the structure of a formal neural network wherein the strengths of the synapses are governed by spike-timing-dependent plasticity (STDP). For properly chosen input signals, there exists a steady state with a residual network. We compare the motif profile of such a network with that of a real neural network of \emph{C. elegans} and identify robust qualitative similarities. In particular, our extensive numerical simulations show that this STDP-driven resulting network is robust under variations of the model parameters.Comment: 16 pages, 14 figure

E is for Early Intervention: The Importance of Early Intervention Services in Providing Better Outcomes for Children Who Have or Are at Risk for Having a Developmental Delay

The purpose of this paper is to analyze the effects that early intervention services have on children who have or are at risk for a developmental delay due to medical or environmental circumstances. Throughout this paper, the following research questions were used as means to guide and provide focus to the paper: Why are early intervention services important in the first few years of life? Who benefits from early intervention services and how are these children affected? and Does early intervention affect the individual long-term? By using a combination of research articles, scientific journals, and data collected from federal research studies regarding early childhood early intervention and the outcomes of children, this paper provides a comprehensive overview of why early intervention services are needed early in life and the true impact of early childhood intervention programs on the lives of children both at the time of intervention and across the lifespan.Kayla SiddellHonors DiplomaHonors CollegeCunningham Memorial Library, Terre Haute, Indiana State UniversityUndergraduateTitle from document title page. Document formatted into pages: 33

Developmental and interspecies comparison of morphology and plasticity in neuronal circuits involved in olfactory information processing

The anterior piriform cortex (aPCx) is a three layered paleocortex receiving afferent inputs from the olfactory bulb as well as local and long-range associational inputs. Neurons in layer 2 are segregated into layer 2A and layer 2B according to their position, morphology and implementation in the sensory and associative circuits. The dendritic architecture of these neurons is determined during postnatal development and plays an important role for the functionality and circuit integration of the two cell types. Here, confocal imaging, electrophysiology, morphometry and Ca2+ imaging, were combined in order to study the development of the dendritic arborizations for both subtypes of layer 2 neurons. Three different growth phases were identified: branch complexity determination, branch elongation and pruning, occurring at different time windows during development. Layer 2A and layer 2B neurons showed morphological differences between their apical and basal dendrites from the very first postnatal days; as well as phase-specific differences during development associated to differences in circuit implementation. During the first postnatal week, early spontaneous network activity in layer 2 of the aPCx displayed differences between layer 2A and layer 2B neurons in their functional connectivity, reflected in the morphological dissimilarities between their basal dendritic trees during the period of branch complexity determination. Additionally, strong differences in growth phase three were observed. Pruning was exclusive for layer 2B neurons and selective for apical dendrites receiving layer 1A sensory inputs. These differences between layer 2A and layer 2B cells in their morphological and functional development exhibit the close association between circuit specificity and neuronal development. Finally, synaptic plasticity in the mossy fiber (MF) pathway of the hippocampus in shrews was investigated and compared to mice. Although hippocampal structure in shrews is preserved, short and long-term plasticity at the MF synapsis was lower compared to mice, suggesting different involvement of these synapses in the behavioral outcome of different species.Der Cortex piriformis anterior (aPCx auf Englisch) ist ein dreischichtiger Paläokortex, der sensorische afferente Eingänge aus dem Riechkolben sowie intracerebrale assoziative Eingänge empfängt. Die Neuronen in Schicht 2 werden nach ihrer Position, Morphologie und Einbindung in die sensorischen und rekurrenten Netzwerke in die Schichten 2A und 2B unterteilt. Die dendritische Architektur dieser Neurone wird während der postnatalen Entwicklung festgelegt und spielt eine wichtige Rolle für die Funktionalität und Netzwerkintegration der beiden Zelltypen. Hier wurden konfokales Imaging, Elektrophysiologie, Morphometrie und Kalzium-Imaging kombiniert, um die Entwicklung der Dendritenbäume für beide Subtypen von Schicht-2-Neuronen zu untersuchen. Es wurden drei verschiedene Wachstumsphasen identifiziert: Bestimmung der Komplexität der Verzweigung, Verlängerung der Verzweigung und strukturelle Vereinfachung, die in verschiedenen Zeitfenstern während der Entwicklung auftreten. Neurone der Schicht 2A und der Schicht 2B zeigten bereits in den ersten postnatalen Tagen morphologische Unterschiede zwischen ihren apikalen und basalen Dendriten sowie phasenspezifische Unterschiede während der Entwicklung, die mit Unterschieden in der Netzwerkimplementierung verbunden sind. Während der ersten postnatalen Woche zeigte die frühe spontane Netzwerkaktivität in Schicht 2 des aPCx Unterschiede in der funktionellen Konnektivität zwischen Neuronen der Schicht 2A und Schicht 2B, die sich in den morphologischen Unterschieden zwischen ihren basalen Dendritenbäumen während der Bestimmung der Verzweigungskomplexität widerspiegelten. Außerdem wurden starke Unterschiede in der dritten Wachstumsphase beobachtet. Die strukturelle Vereinfachung fand ausschließlich bei Neuronen der Schicht 2B statt und war selektiv für apikale Dendriten, die sensorische Inputs der Schicht 1A erhielten. Diese Unterschiede zwischen Zellen der Schicht 2A und der Schicht 2B in ihrer morphologischen und funktionellen Entwicklung zeigen den engen Zusammenhang zwischen Netzwerkspezifität und neuronaler Entwicklung. Schließlich wurde die synaptische Plastizität des Moosfaser (MF)-Trakts des Hippocampus bei Spitzmäusen untersucht und mit der von Mäusen verglichen. Obwohl die Struktur des Hippocampus bei Spitzmäusen erhalten ist, war die Kurz- und Langzeitplastizität an den MF-Synapsen im Vergleich zu Mäusen geringer, was auf eine unterschiedliche Beteiligung dieser Synapsen an spezifisch adaptierte Verhaltensweisen der beiden Spezies hindeutet

A neural circuit mechanism for regulating vocal variability during song learning in zebra finches

Motor skill learning is characterized by improved performance and reduced motor variability. The neural mechanisms that couple skill level and variability, however, are not known. The zebra finch, a songbird, presents a unique opportunity to address this question because production of learned song and induction of vocal variability are instantiated in distinct circuits that converge on a motor cortex analogue controlling vocal output. To probe the interplay between learning and variability, we made intracellular recordings from neurons in this area, characterizing how their inputs from the functionally distinct pathways change throughout song development. We found that inputs that drive stereotyped song-patterns are strengthened and pruned, while inputs that induce variability remain unchanged. A simple network model showed that strengthening and pruning of action-specific connections reduces the sensitivity of motor control circuits to variable input and neural ‘noise’. This identifies a simple and general mechanism for learning-related regulation of motor variability. DOI: http://dx.doi.org/10.7554/eLife.03697.00

Astrocytes mediate synapse elimination through MEGF10 and MERTK pathways

To achieve its precise neural connectivity, the developing mammalian nervous system undergoes extensive activity-dependent synapse remodeling. Recently microglial cells have been shown to be responsible for a portion of synaptic remodeling, but the remaining mechanisms remain mysterious. Here we report a new role for astrocytes in actively engulfing CNS synapses. This process helps to mediate synapse elimination, requires the Megf10 and Mertk phagocytic pathways, and is strongly dependent on neuronal activity. Developing mice deficient in both astrocyte pathways fail to normally refine their retinogeniculate connections and retain excess functional synapses. Lastly, we show that in the adult mouse brain, astrocytes continuously engulf both excitatory and inhibitory synapses. These studies reveal a novel role for astrocytes in mediating synapse elimination in the developing and adult brain, identify Megf10 and Mertk as critical players in the synapse remodeling underlying neural circuit refinement, and have important implications for understanding learning and memory as well as neurological disease processes

Astrocytes mediate synapse elimination through MEGF10 and MERTK pathways

To achieve its precise neural connectivity, the developing mammalian nervous system undergoes extensive activity-dependent synapse remodeling. Recently microglial cells have been shown to be responsible for a portion of synaptic remodeling, but the remaining mechanisms remain mysterious. Here we report a new role for astrocytes in actively engulfing CNS synapses. This process helps to mediate synapse elimination, requires the Megf10 and Mertk phagocytic pathways, and is strongly dependent on neuronal activity. Developing mice deficient in both astrocyte pathways fail to normally refine their retinogeniculate connections and retain excess functional synapses. Lastly, we show that in the adult mouse brain, astrocytes continuously engulf both excitatory and inhibitory synapses. These studies reveal a novel role for astrocytes in mediating synapse elimination in the developing and adult brain, identify Megf10 and Mertk as critical players in the synapse remodeling underlying neural circuit refinement, and have important implications for understanding learning and memory as well as neurological disease processes

Maintenance of cell type-specific connectivity and circuit function requires Tao kinase

Sensory circuits are typically established during early development, yet how circuit specificity and function are maintained during organismal growth has not been elucidated. To gain insight we quantitatively investigated synaptic growth and connectivity in the Drosophila nociceptive network during larval development. We show that connectivity between primary nociceptors and their downstream neurons scales with animal size. We further identified the conserved Ste20-like kinase Tao as a negative regulator of synaptic growth required for maintenance of circuit specificity and connectivity. Loss of Tao kinase resulted in exuberant postsynaptic specializations and aberrant connectivity during larval growth. Using functional imaging and behavioral analysis we show that loss of Tao-induced ectopic synapses with inappropriate partner neurons are functional and alter behavioral responses in a connection-specific manner. Our data show that fine-tuning of synaptic growth by Tao kinase is required for maintaining specificity and behavioral output of the neuronal network during animal growth

A biologically inspired recurrent neural network for sound source recognition incorporating auditory attention

In this paper, a human-mimicking model for sound source recognition is presented. It consists of an artificial neural network with three neuron layers (input, middle and output) that are connected by feedback connections between the output and middle layer, on top of feedforward connections from the input to middle and middle to output layers. Learning is accomplished by the model following the Hebb principle, dictating that " cells that fire together, wire together", with some important alterations, compared to standard Hebbian learning, in order to prevent the model from forgetting previously learned patterns, when learning new ones. In addition, short-term memory is introduced into the model in order to facilitate and guide learning of neuronal synapses (long-term memory). As auditory attention is an essential part of human auditory scene analysis (ASA), it is also indispensable in any computational model mimicking it, and it is shown that different auditory attention mechanism naturally emerge from the neuronal behaviour as implemented in the model described in this paper. The learning behavior of the model is further investigated in the context of an urban sonic environment, and the importance of shortterm memory in this process is demonstrated. Finally, the effectiveness of the model is evaluated by comparing model output on presented sound recordings to a human expert listeners evaluation of the same fragments