Absence of the Fragile X messenger ribonucleoprotein alters response patterns to sounds in the auditory midbrain

Among the different autism spectrum disorders, Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. Sensory and especially auditory hypersensitivity is a key symptom in patients, which is well mimicked in the Fmr1 -/- mouse model. However, the physiological mechanisms underlying FXS’s acoustic hypersensitivity in particular remain poorly understood. Here, we categorized spike response patterns to pure tones of different frequencies and intensities from neurons in the inferior colliculus (IC), a central integrator in the ascending auditory pathway. Based on this categorization we analyzed differences in response patterns between IC neurons of wild-type (WT) and Fmr1 -/- mice. Our results report broadening of frequency tuning, an increased firing in response to monaural as well as binaural stimuli, an altered balance of excitation-inhibition, and reduced response latencies, all expected features of acoustic hypersensitivity. Furthermore, we noticed that all neuronal response types in Fmr1 -/- mice displayed enhanced offset-rebound activity outside their excitatory frequency response area. These results provide evidence that the loss of Fmr1 not only increases spike responses in IC neurons similar to auditory brainstem neurons, but also changes response patterns such as offset spiking. One can speculate this to be an underlying aspect of the receptive language problems associated with Fragile X syndrome

Absence of the Fragile X messenger ribonucleoprotein alters response patterns to sounds in the auditory midbrain

Among the different autism spectrum disorders, Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. Sensory and especially auditory hypersensitivity is a key symptom in patients, which is well mimicked in the Fmr1 -/- mouse model. However, the physiological mechanisms underlying FXS’s acoustic hypersensitivity in particular remain poorly understood. Here, we categorized spike response patterns to pure tones of different frequencies and intensities from neurons in the inferior colliculus (IC), a central integrator in the ascending auditory pathway. Based on this categorization we analyzed differences in response patterns between IC neurons of wild-type (WT) and Fmr1 -/- mice. Our results report broadening of frequency tuning, an increased firing in response to monaural as well as binaural stimuli, an altered balance of excitation-inhibition, and reduced response latencies, all expected features of acoustic hypersensitivity. Furthermore, we noticed that all neuronal response types in Fmr1 -/- mice displayed enhanced offset-rebound activity outside their excitatory frequency response area. These results provide evidence that the loss of Fmr1 not only increases spike responses in IC neurons similar to auditory brainstem neurons, but also changes response patterns such as offset spiking. One can speculate this to be an underlying aspect of the receptive language problems associated with Fragile X syndrome.Peer Reviewe

Functional properties of feed-forward inhibition

ISBN : 978-2-9532965-0-1Neurons receive a large number of excitatory and inhibitory synaptic inputs whose temporal interplay determines the spiking behavior. On average, excitation and inhibition balance each other, such that spikes are elicited by fluctuations. In addition, it has been shown in vivo that excitation and inhibition are correlated, with inhibition lagging excitation only by few milliseconds (~6 ms), creating a small temporal integration window. This correlation structure could be induced by feed-forward inhibition (FFI), which has been shown to be present at many sites in the central nervous system. To characterize the functional properties of feed-forward inhibition, we constructed a simple circuit using spiking neurons with conductance based synapses and applied spike pulse packets with defined strength and width. We found that the small temporal integration window, induced by the FFI, changes the integrative properties of the neuron. Only transient stimuli could produce a response when the FFI was active, whereas without FFI the neuron responded to both steady and transient stimuli. In addition, the FFI increased the trial-by-trial precision

PyNN: A Common Interface for Neuronal Network Simulators

Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. This impedes communication between investigators and makes it harder to reproduce and build on the work of others. On the other hand, simulation results can be cross-checked between different simulators, giving greater confidence in their correctness, and each simulator has different optimizations, so the most appropriate simulator can be chosen for a given modelling task. A common programming interface to multiple simulators would reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware). PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators. PyNN is open-source software and is available from http://neuralensemble.org/PyNN

The Role of Thalamic Population Synchrony in the Emergence of Cortical Feature Selectivity

In a wide range of studies, the emergence of orientation selectivity in primary visual cortex has been attributed to a complex interaction between feed-forward thalamic input and inhibitory mechanisms at the level of cortex. Although it is well known that layer 4 cortical neurons are highly sensitive to the timing of thalamic inputs, the role of the stimulus-driven timing of thalamic inputs in cortical orientation selectivity is not well understood. Here we show that the synchronization of thalamic firing contributes directly to the orientation tuned responses of primary visual cortex in a way that optimizes the stimulus information per cortical spike. From the recorded responses of geniculate X-cells in the anesthetized cat, we synthesized thalamic sub-populations that would likely serve as the synaptic input to a common layer 4 cortical neuron based on anatomical constraints. We used this synchronized input as the driving input to an integrate-and-fire model of cortical responses and demonstrated that the tuning properties match closely to those measured in primary visual cortex. By modulating the overall level of synchronization at the preferred orientation, we show that efficiency of information transmission in the cortex is maximized for levels of synchronization which match those reported in thalamic recordings in response to naturalistic stimuli, a property which is relatively invariant to the orientation tuning width. These findings indicate evidence for a more prominent role of the feed-forward thalamic input in cortical feature selectivity based on thalamic synchronization

Image_1_Absence of the Fragile X messenger ribonucleoprotein alters response patterns to sounds in the auditory midbrain.tif

Among the different autism spectrum disorders, Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. Sensory and especially auditory hypersensitivity is a key symptom in patients, which is well mimicked in the Fmr1 -/- mouse model. However, the physiological mechanisms underlying FXS’s acoustic hypersensitivity in particular remain poorly understood. Here, we categorized spike response patterns to pure tones of different frequencies and intensities from neurons in the inferior colliculus (IC), a central integrator in the ascending auditory pathway. Based on this categorization we analyzed differences in response patterns between IC neurons of wild-type (WT) and Fmr1 -/- mice. Our results report broadening of frequency tuning, an increased firing in response to monaural as well as binaural stimuli, an altered balance of excitation-inhibition, and reduced response latencies, all expected features of acoustic hypersensitivity. Furthermore, we noticed that all neuronal response types in Fmr1 -/- mice displayed enhanced offset-rebound activity outside their excitatory frequency response area. These results provide evidence that the loss of Fmr1 not only increases spike responses in IC neurons similar to auditory brainstem neurons, but also changes response patterns such as offset spiking. One can speculate this to be an underlying aspect of the receptive language problems associated with Fragile X syndrome.</p

Functional consequences of correlated excitatory and inhibitory conductances in cortical networks

International audienc

Corrélation entre l'excitation et l'inhibition dans les circuits corticaux visuels (conséquences fonctionnelles et plausibilité biologique)

The primary visual cortex (V1) is one of the most studied cortical area in the brain. Together with the retina and the lateral geniculate nucleus (LGN) it forms the early visual system, which has become a common model for studying computational principles in sensory systems. Simple artificial stimuli (such as drifting gratings (DG)) have given insights into the neural basis of visual processing. However, recently more and more researchers have started to use more complex natural visual stimuli (NI), arguing that the low dimensional artificial stimuli are not sufficient for a complete understanding of the visual system. For example, whereas the responses of V1 neurons to DG are dense but with variable spike timings, the neurons respond with only few but precise spikes to NI. Furthermore, linear receptive field models provide a good fit to responses during simple stimuli, however, they often fail during NI. To investigate the mechanisms behind the stimulus dependent responses of cortical neurons we have built a biophysical, yet simple and comprehensible, model of the early visual system. We show how the spatial and temporal stimulus properties interact with the model architecture to give rise to the differential response behaviour. Our results show that during NI the LGN afferents show epochs of correlated activity. These temporal correlations induce transient excitatory synaptic inputs, resulting in precise spike timings in V1. Furthermore, the sparseness of the responses to NI can be explained by correlated and lagging inhibitory conductance, which is induced by the interactions of the thalamocortical circuit with the spatial-temporal correlations in the stimulus. We continue by investigating the origin of stimulus dependent nonlinear responses, by comparing models of different complexity. Our results suggest that adaptive processes shape the responses, depending on the temporal properties of the stimuli. The spatial properties can result in nonlinear inputs through the recurrent cortical network. We then study the functional consequences of correlated excitatory and inhibitory condutances in more details in generic models. These results show that: (1) spiking of individual neurons becomes sparse and precise, (2) the selectivity of signal propagation increases and the detailed delay allows to gate the propagation through feed-forward structures (3) and recurrent cortical networks are more stable and more likely to elicit in vivo type activity states. Lastly our work illustrates new advances in methods of constructing and exchanging models of neuronal systems by the means of a simulator independent description language (called PyNN). We use this new tool to investigate the feasibility of comparing software simulations with neuromorphic hardware emulations. The presented work gives new perspectives on the processing of the early visual system, in particular on the importance of correlated conductances. It thus opens the door for more elaborated models of the visual system.Le cortex visuel primaire (V1) est l aire corticale la plus étudiée en neurosciences. En effet, ce système complété de la rétine et du corps genouillé latéeral forme le système visuel de bas niveau et constitue une référence pour l étude de modèles de systèmes sensoriels. Des stimuli simples comme des réseaux sinusoïdaux en mouvement (DG) ont donné des informations fondamentales sur les bases neurales du traitement neural de l information visuelle. Cependant, de nombreux chercheurs utilisent des signaux plus complexes basés sur des images naturelles (NI) car des signaux de faibles complexité ne sont pas pertinents pour une vision complète du système visuel. Par exemple, alors que les réponses des neurones de V1 sont denses et imprécises pour des réseaux (DG), elles sont parcimonieuses et de grande résolution temporelle pour des scènes naturelles (NI). De plus, le modèle d un champ récepteur d intégration linéaire décrit bien la réponse à ces premiers stimuli mais est en échec pour une réponses aux images naturelles. Pour comprendre ces mécanismes corticaux dépendants du stimulus, nous avons construit un modèle biophysique simple et réaliste du système visuel de bas niveau. Nous montrons de cette façon comment les propriétés spatio-temporelles du stimulus interagissent au niveau de la structure du modèle afin de donner ces réponses différenciées. Nos r esultats montrent en particulier que, durant la stimulation NI, les afférents thalamiques montrent des phases d activité corrélée. Ces corrélations temporelles sont nécessaires pour générer dans V1 une réponse synaptique excitatrice phasique qui cause une réponse temporelle précise. En particulier, la parcimonie de la réponse peut être expliquée par une phase inhibitrice corrélée et légèrement retardée, ou fenêtre temporelle de conductance, induite par un circuit thalamocortical spécialisé en interaction avec l activité spatio-temporelle corrélée du stimulus entrant. Nous poursuivons en étudiant l origine des réponses non-linéaires observées pour les images naturelles en comparant des modèles de complexités croissantes. Nos résultats suggèrent premièrement que des processus adaptatifs modèlent le stimulus en fonction des propriétés temporelles du stimulus. Le propriétés spatiales peuvent aussi générer des effets non-linéaires amplifiés par l intermédiaire du réseau cortical récurrent que nous modélisons. Nous étudions alors les conséquences fonctionnelles de la phase corr el ee des conductances excitatrices et inhibitrices dans des modèles génériques. Nous montrons que : (1) des neurones individuels deviennent plus parcimonieux et précis, (2) la sélectivité de la propagation de l information dans une structure de type en-avant peut être contrôlée finement grâce au délai dans la fenêtre temporelle. (3) La r eponse d un modèle de réseau cortical récurrent est plus robuste et est compatible avec les états corticaux observés in vivo. En compl ement, ce travail illustre des avancées méthodologiques pour construire et échanger des modeles neuraux gr ace a un langage de description indépendant de l architecture appelé PyNN. Nous utilisons cet outil pour d evelopper ces modèles sur différentes solutions logicielles mais aussi sur des circuits intégrés neuromorphiques. En conclusion, ce travail ouvre des perspectives sur le rôle computationnel générique des conductances neurales et en particulier pour la mise en place de modele plus elabor es pour comprendre les m ecanismes de la vision.AIX-MARSEILLE2-BU Méd/Odontol. (130552103) / SudocSudocFranceGermanyFRD