Biology subjects

Gjorgjieva, J.

Publications and source records attributed to Gjorgjieva, J..

4 recordsLinked to original sources

bioRxiv2018

Sensory Deprivation Independently Regulates Neocortical Feedforward and Feedback Excitation-Inhibition Ratio

Brief (2-3d) monocular deprivation (MD) during the critical period induces a profound loss of responsiveness within layer 4 of primary visual cortex (V1). This has largely been ascribed to long-term depression (LTD) at thalamocortical synapses onto pyramidal neurons, while a contribution from intracortical inhibition has been controversial. Here we used optogenetics to probe feedforward thalamocortical and feedback intracortical excitation-inhibition (E-I) ratios following brief MD. While thalamocortical inputs onto pyramidal neurons were depressed, there was stronger depression onto PV+ interneurons, which shifted the thalamocortical-evoked E-I ratio toward excitation. In contrast, feedback intracortical E-I ratio was shifted toward inhibition, and a computational model of layer 4 demonstrated that these opposing shifts produced an overall suppression of layer 4 excitability. Thus, feedforward and feedback E-I ratios onto the same postsynaptic target can be independently regulated by visual experience, and enhanced feedback inhibition is the primary driving force behind loss of visual responsiveness.

neuroscience↗

bioRxiv2018

Specific octopaminergic neurons arbitrate between perseverance and reward in hungry Drosophila

In pursuit of palatable food, hungry animals mobilize significant energy resources and overcome obstacles, exhaustion and fear. Their perseverance depends on metabolic state, internal motivation and the expected benefit. Sustained commitment to a trying task is crucial, however, disengagement from one behavior to engage into another can be essential for optimal adaptation and survival. How neural circuits allow prioritizing perseverance over withdrawal based on the animals need is not understood. Using a single fly spherical treadmill, we show that hungry flies display increasing perseverance to track a food odor in the repeated absence of the predicted food reward. While this perseverance is mediated by a group of dopaminergic neurons, a subset of neurons expressing octopamine, the invertebrate counterpart of noradrenaline, provide reward feedback and counteract dopamine-motivated food seeking. Our data and modeling suggest that two important neuromodulators tally internal and external signals to coordinate motivation-dependent antagonistic behavioral drives: perseverance vs. change of behavior.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC=\"FIGDIR/small/259119_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (21K):\norg.highwire.dtl.DTLVardef@9833e1org.highwire.dtl.DTLVardef@7616d4org.highwire.dtl.DTLVardef@d4e8bforg.highwire.dtl.DTLVardef@1fc615c_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LILack of reward stimulates perseverance, and not quitting.\nC_LIO_LIDopaminergic neurons previously implicated in aversive learning promote perseverance.\nC_LIO_LISugar responsive octopaminergic neurons directly counteract perseverant odor tracking through a downstream inhibitory neuron.\nC_LIO_LIComputational modeling supports a simple neural circuit featuring antagonistic functions for dopamine and octopamine as tallies of expense and gain.\nC_LI

neuroscience↗

bioRxiv2017

Optimal Sensory Coding By Populations Of ON And OFF Neurons

In many sensory systems the neural signal is coded by the coordinated response of heterogeneous populations of neurons. What computational benefit does this diversity confer on information processing? We derive an efficient coding framework assuming that neurons have evolved to communicate signals optimally given natural stimulus statistics and metabolic constraints. Incorporating nonlinearities and realistic noise, we study optimal population coding of the same sensory variable using two measures: maximizing the mutual information between stimuli and responses, and minimizing the error incurred by the optimal linear decoder of responses. Our theory is applied to a commonly observed splitting of sensory neurons into ON and OFF that signal stimulus increases or decreases, and to populations of monotonically increasing responses of the same type, ON. Depending on the optimality measure, we make different predictions about how to optimally split a population into ON and OFF, and how to allocate the firing thresholds of individual neurons given realistic stimulus distributions and noise, which accord with certain biases observed experimentally.

neuroscience↗

bioRxiv2017

Understanding Neural Circuit Development Through Theory And Models

How are neural circuits organized and tuned to achieve stable function and produce robust behavior? The organization process begins early in development and involves a diversity of mechanisms unique to this period. We summarize recent progress in theoretical neuroscience that has substantially contributed to our understanding of development at the single neuron, synaptic and network level. We go beyond classical models of topographic map formation, and focus on the generation of complex spatiotemporal activity patterns, their role in refinements of particular circuit features, and the emergence of functional computations. Aided by the development of novel quantitative methods for data analysis, theoretical and computational models have enabled us to test the adequacy of specific assumptions, explain experimental data and propose testable hypotheses. With the accumulation of larger data sets, theory and models will likely play an even more important role in understanding the development of neural circuits.

neuroscience↗