Massimo Scanziani - US grants

DESCRIPTION (provided by applicant): Synaptic inhibition exerts a crucial function in shaping the activity of neuronal populations in space and time and in preventing excitation to spread unrestrained through networks of cortical neurons. Feedback inhibitory circuits are a major source of synaptic inhibition and thus, play a very important role in the control of hyperexcitability. Feedback inhibition occurs when inhibitory neurons project to the population of neurons from whom they receive excitation. Such circuits are stereotypical in cortical areas and are regarded as a general principle of cortical organization. In contrast to the wealth of knowledge on the anatomical properties of feedback inhibition, the specific means by which this circuit controls the activity of networks of neurons is poorly understood. This proposal addresses the mechanism by which feedback inhibitory circuits control the excitability of pyramidal neurons in the hippocampus, a structure where a slight imbalance between excitation and inhibition can lead to epileptiform activity. Our preliminary data suggest that at least two independent feedback pathways inhibit hippocampal pyramidal cells. One pathway is preferentially activated by low spiking frequencies (< 10 Hz) while the other is activated at higher spiking frequencies (>10 Hz) of pyramidal cells. Furthermore, one pathway inhibits the soma while the other inhibits the dendrites of pyramidal cells, suggesting that they may affect different sets of excitatory inputs. This study will reveal the mechanism by which a simple but powerful and ubiquitous neuronal circuit controls excitation in the hippocampus and may thus contribute to the development of therapies aimed a preventing hyperexcitability and epileptogenesis in cortical areas. Furthermore, elucidating the functional properties of elementary circuits, like feedback inhibition, will allow us, in the long term, to understand the mechanisms that determine the spatial and temporal activity patterns of larger networks of neurons.

DESCRIPTION (provided by applicant): Feed-forward inhibitory circuits are a major source of synaptic inhibition to cortical neurons. The specific means by which they control the activity of cortical neurons is, however, poorly understood. The goal of this proposal is to address the mechanism by which feed-forward inhibitory circuits activated by thalamic afferents control the excitability of cortical neurons. We will test the hypothesis that thalamo-cortical feed-forward inhibition reduces the integration time window of cortical neurons, and enforces temporal fidelity of signal transmission between the thalamus and the cortex. This proposal has two aims: Aim 1 addresses the role of thalamo-cortical feed-forward inhibition in controlling the integration time window and spike timing of cortical neurons. Aim 2 addresses the cellular mechanism of thalamo-cortical feed-forward inhibition. The experiments will be performed on acute mouse thalamo-cortical slices using electrophysiological and morphological techniques. This study will provide insight into the functional role of feed-forward inhibition and the mechanisms by which neuronal networks balance excitation with synaptic inhibition. A deeper understanding of the mechanisms that control cortical excitability may contribute to the development of therapies aimed at preventing epileptogenesis in cortical areas.

Project Summary Sensory experience influences brain development by activating neural circuits. The activation of these pathways leads to calcium-dependent regulation of various aspects of neuronal function such as synaptic plasticity, cell survival, and axonal and dendritic remodeling. In most of these instances calcium signals exert long-lasting cellular effects by activating transcription factors that induce expression of target genes. Our overall goal is to gain insight into the mechanisms by which calcium signals influence brain development via transcriptional activation. One of the major effects of calcium signaling in neurons is to regulate changes in synaptic strength. At many synapses, the direction and extent of change in synaptic strength depends on the stimulus parameters. For example, at the CA3-CA1 Schaffer collateral synapse in the hippocampus, low frequency stimulation leads to long term depression (LTD) and high frequency stimulation leads to long term potentiation (LTP). The ability of a synapse to undergo plasticity can itself be modified by various manipulations, and the resulting shift in the plasticity state of the cell is often referred to as metaplasticity. We propose to explore the hypothesis that metaplasticity at the CA3- CA1 synapse is regulated by CREST-mediated transcription. The goals of the project are: (i) To examine the role of CREST in activity-dependent down-regulation of GluR2 expression; (ii) To examine the role CREST in activity-dependent regulation of NR2B expression; (iii) To examine the role of CREST in regulating the AMPA: NMDA ratio in vivo and to determine if CREST regulates the fraction of silent synapses; and (iv) To determine if CREST regulates LTP in hippocampal CA3-CA1 synapses and whether loss of CREST compromises metaplasticity.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Activity in the thalamus triggers widespread cortical inhibition. This is not because thalamic neurons are inhibitory (they release the excitatory transmitter glutamate) but because they form powerful synapses with inhibitory interneurons in Layer IV of the cortex. We will examine the ultrastructure of these unusually strong connections in a joint light/electron microscopic study using dye labeling of both the thalamic inputs and their postsynaptic interneuron targets.

? DESCRIPTION (provided by applicant): The classification of neurons into distinct types is a fundamental endeavor in neuroscience. Neuronal classification allows one to gain insight into the building blocks of the nervous system, is essential for a mechanistic understanding of the function of the nervous system and is a prerequisite for unambiguous communication between investigators. No single unequivocal categorization scheme exists yet for neurons in the mammalian cerebral cortex. The classification based on morphological characteristics has led to tremendous advances in our understanding of the nervous system, yet is often ambiguous in cortical neurons because many morphological properties are difficult to parameterize. Other classifications based on immunohistochemistry or electrophysiology have been helpful but, alone, fail to capture the rich diversity of cortical neurons. Evidence indicates that distinct neuron types express different genes. Thus, in principle, the gene expression pattern could be used to generate an unambiguous and objective classification scheme. Furthermore, a classification based on gene expression would allow one, using molecular approaches, to selectively tag and perturb a given neuron type both for basic research and for clinical purposes. However, classifying neurons exclusively based on their gene expression pattern is, a priori, uninformative with regard to their function, location or integration into the cortical network. The goal of this proposal is to classify cortical neurons based on those genes that best predict neuronal function and location. Thus, to find those genes we need to correlate the transcriptional profile of a neuron in the mammalian cerebral cortex to its function and location. We propose to investigate the primary visual cortex because it is the cortical sensory area where the function of neurons has been described in greatest detail. We will perform calcium imaging of the primary visual cortex of mice to determine the tuning of visual cortical neurons in response to visual stimuli. We will tag the imaged neurons with photoactivatable GFP. We will harvest the RNA from the labeled neurons. We will perform next generation RNAseq to reveal the transcriptional profile of each individual neuron imaged in vivo. We will correlate the transcriptional profile of a neuron with its specific response to visual stimuli. Finally, we will se clustering algorithms and principal component analysis to classify neurons in different types based on those genes that best correlate with function. The result will be a genetically based classification method that provides functional information about cell types.

? DESCRIPTION (provided by applicant): The cerebral cortex of mammals has the ability to control and modulate innate, reflexive behaviors mediated by subcortical structures. By adjusting innate and reflexive behaviors to the prevailing conditions or by adapting these behaviors according to past experiences the cortex greatly expands the behavioral repertoire of mammals. Despite the fundamental role that the cortex plays on regulating subcortically mediated behaviors very little is known about the underlying mechanisms. Solving this problem is crucial for our understanding of among the most basic functions performed by the cerebral cortex of mammals. This proposal addresses the mechanisms by which the cortex modulate the performance of the optokinetic reflex, an innate behavior that is essential for stabilizing images on retinas during slow self motions or motions of the environment. The proposed study will be performed in mice because of the large palette of genetic, viral, optical and electrophysiological tools especially developed to study neural circuit function in this animal. In humans, both developmental retardation of the visual cortex as well as lesions or strokes to the visual cortex can profoundly impair optokinetic performance. Optokinetic performance is part of the standard neurological tests in the medical practice because of its simplicity and diagnostic power with regard to subcortical and cortical function. Understanding the fundamental mechanisms that regulate the various properties of optokinetic performance will inevitably contribute to the expansion of the diagnostic power of this simple and widely used neurological test on human patients. The ability of cortex to control subcortically mediated innate behaviors represents a fundamental evolutionary adaptation. This control becomes particularly pronounced in organisms with high levels of encephalization, humans being the supreme example. Revealing the circuit mechanisms through which the cortex controls the activity of subcortical structures will provide crucial insight into how the cortex orchestrates innate behavior in health and disease.

Our current mechanistic understanding of sensory representation in primary visual cortex (V1) is principally ?feed-forward?. That is, the spatio-temporal structure of the receptive field (RF) of V1 neurons results from the combination of receptive filed elements transmitted by earlier stages of visual processing (i.e. retina and thalamus), in a feed-forward manner. While computational models based on this feed-forward understanding of V1 are relatively accurate at predicting the response of neurons to visual stimuli presented within the borders of the neuron?s RF, they generally fail when the stimuli exceed the size of the RF, as is the case for every-day visual scenes that encompass the entire field of view. One of the main reason for the inability of current models to predict responses of V1 neuron to naturalistic stimuli is that the response of neurons in V1 to stimuli in their RF is strongly modulated by what happens outside of their RF. In other words, how neurons in V1 respond to a stimulus presented in their RF depends on the context or ?surround? within which the stimulus is presented. In the natural world, visual stimuli falling in the RF of a V1 neuron are never devoid of a surround. Consistent with these neurophysiological observations, psychophysical experiments in humans and animals show that the perception of a visual stimulus depends on its relationship to the surrounding visual context. Thus, the ability to process visual information depending on the context is a key property of visual cortex and has a profound impact on how we perceive the world. Only a clear mechanistic, circuit level understanding of how the context modulates the response of V1 will allow us generate realistic models capable of accurately predicting the response of this area to naturalistic stimuli. Neurophysiological data indicate that contextual modulation of neuronal responses in V1 most likely relies on intra-cortical interactions. That is, while the classical RF structure of a V1 neuron results from a feed-forward process, the modulation by the surround likely depends on intra- cortical circuit elements, their connectivity pattern and their dynamic interactions. This proposal aims at elucidating these cortical circuit elements and how their interaction gives rise to the contextual modulation of the response to visual stimuli in V1. A thorough mechanistic understanding of contextual modulation in V1 will allow us to build realistic models capable of capturing the response of visual cortex to naturalistic stimuli. Thus, data obtained from this proposal will be essential in informing and validating realistic models of V1.

Understanding the cerebral cortex requires data-based theoretical models that can yield in- sight into the circuit mechanisms of cortical computation, and reproduce detailed cortical dynamics across stimuli and brain states. The primary visual cortex (V1) is the best-studied cortical area by both theorists and experimen- talists, yet current models - whether statistical or circuit based ? only poorly capture how V1 neurons respond to complex stimuli, such as natural scenes. The ultimate goal of this team project is to obtain the necessary experimental data and build the detailed circuit-based models that explain how V1 circuits encode natural visual stimuli. In so doing, we aim not only to provide a mechanistic understanding for how V1 dynamics forms the basis of vision, but also to establish a more generalizable paradigm for understanding any cortical area. Our assumption is that current models fall short for two reasons: on the experimental side, we are still missing most of the fundamental details about the synaptic connectivity and physiological responses of V1 cell types; while on the theory side, prevailing circuit-based models reduce V1 to just a few cell types, and either capture the static responses of V1 neurons to simple stimuli but not their trial to trial ?uctuations, or capture ?uctuations, but not their rich array of non-linear responses properties that are central to visual computation. Our hypothesis is that we can achieve a circuit-based model that explains cortical responses and dynamics to natural stimuli by implementing the following three steps: 1) identify and incorporate all the differentiable V1 neuronal cell types into our model; 2) measure and incorporate the synaptic connectivity and intrinsic properties of these cell types; 3) measure and accurately predict the visual responses of each of these cell types to diverse visual stimuli and in multiple brain states. We focus on circuit-based rather than statistical models of V1 for two reasons: they can provide insight into neural mechanisms of visual computation and the regimes of cortical operation, and because they will permit us to test their accuracy by validating their predictions for how V1 responds to de?ned experimen- tal perturbations. To implement these perturbations, we will employ multiphoton holographic optogenetics, which allows us to manipulate V1 circuits with the level of precision formerly only possible in the realm of theory. Here we bring together an outstanding team of theorists, experimentalists, and data scientists to leverage cutting edge new brain mapping technologies that we will use to build and validate dramatically improved models of visual cortical function and dynamics.

PROJECT SUMMARY The precise assembly of neural circuits ensures accurate neurological function and behavior. For example, to communicate specific aspects of the visual world to the brain, retinal ganglion cells (RGCs) find and form synaptic contacts with specific postsynaptic partners out of the heterogeneous neuronal population of retino-recipient areas in the brain. One such area is the superior colliculus (SC), which receives direct retinal inputs and sends commands for direct innate behaviors such as escape or prey capture. What are the molecular determinants for selective RGC to SC neuron wiring? How are parallel retinotectal circuits sorted onto different SC laminae and neuronal relays? How are distinct retinotectal circuits linked to defined visual evoked behaviors? This proposed study aims to answer these questions in the mouse visual system. To accomplish this goal, first, we will map out parallel retinotectal circuits. We have established an integrated anterograde-tracing and sequencing platform, Trans-Seq, that defines the outputome of a genetically- defined RGC subtype. We applied Trans-Seq to all RGC subtypes globally, ?-RGCs, and On-Off direction- selective-ganglion-cells and reconstructed their differential outputomes onto superficial superior-collicular (sSC) neuron subtypes. We propose to apply Trans-Seq to other major RGC subtypes representing different visual features. The proposed studies will determine retinotectal circuit convergence and divergence at neuron subtype resolution. Second, we aim to understand cellular and molecular mechanisms regulating specific retinotectal circuit wiring. We have analyzed ?-RGC specific outputomes and revealed a selective sSC neuron subtype, Nephronectin-positive-wide-field neurons (NPWFs). The ?-RGC-to-NPWF circuit was genetically validated using imaging, electrophysiology, and retrograde tracing. We propose to study how Nephronectin mediates ?-RGC selective axonal lamination onto the deep sSC layer and whether Nephronectin determines the subsequent synaptic specificity from ?-RGCs to NPWFs. We will also investigate what molecular mechanisms mediate Nephronectin binding and lead to a selective mammalian retinotectal circuit assembly. Third, we will link specific retinotectal circuits to defined visual evoked behaviors. We propose to combine genetic and optogenetic tools established above to determine whether the ?-RGC-to-NPWF circuit contributes to visual evoked innate behaviors, such as looming triggered defense responses. We will also examine whether molecular determinants for connectivity, such as Nephronectin, regulate this behavioral output via these retinotectal circuits. Our circuit mapping platform builds a precise connectivity map at neuronal subtype resolution. Further, this work will align the precise neuronal wiring diagram to innate visual evoked behaviors, informing future functional and behavioral analysis. The new knowledge gained here may include molecular principles underlying mammalian circuit wiring relevant beyond the visual system.