Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity

In rodent visual cortex, synaptic connections between orientation-selective neurons are unspecific at the time of eye opening, and become to some degree functionally specific only later during development. An explanation for this two-stage process was proposed in terms of Hebbian plasticity based on visual experience that would eventually enhance connections between neurons with similar response features. For this to work, however, two conditions must be satisfied: First, orientation selective neuronal responses must exist before specific recurrent synaptic connections can be established. Second, Hebbian learning must be compatible with the recurrent network dynamics contributing to orientation selectivity, and the resulting specific connectivity must remain stable for unspecific background activity. Previous studies have mainly focused on very simple models, where the receptive fields of neurons were essentially determined by feedforward mechanisms, and where the recurrent network was small, lacking the complex recurrent dynamics of large-scale networks of excitatory and inhibitory neurons. Here we studied the emergence of functionally specific connectivity in large-scale recurrent networks with synaptic plasticity. Our results show that balanced random networks, which already exhibit highly selective responses at eye opening, can develop feature-specific connectivity if appropriate rules of synaptic plasticity are invoked within and between excitatory and inhibitory populations. If these conditions are met, the initial orientation selectivity guides the process of Hebbian learning and, as a result, functionally specific and a surplus of bidirectional connections emerge. Our results thus demonstrate the cooperation of synaptic plasticity and recurrent dynamics in large-scale functional networks with realistic receptive fields, highlight the role of inhibition as a critical element in this process, and paves the road for further computational studies of sensory processing in neocortical network models equipped with synaptic plasticity

Impact of a non-Gaussian density field on Sunyaev-Zeldovich observables

The main statistical properties of the Sunyaev-Zeldovich (S-Z) effect - the power spectrum, cluster number counts, and angular correlation function - are calculated and compared within the framework of two density fields which differ in their predictions of the cluster mass function at high redshifts. We do so for the usual Press and Schechter mass function, which is derived on the basis of a Gaussian density fluctuation field, and for a mass function based on a chi^2 distributed density field. These three S-Z observables are found to be very significantly dependent on the choice of the mass function. The different predictions of the Gaussian and non-Gaussian density fields are probed in detail by investigating the behaviour of the three S-Z observables in terms of cluster mass and redshift. The formation time distribution of clusters is also demonstrated to be sensitive to the underlying mass function. A semi-quantitative assessment is given of its impact on the concentration parameter and the temperature of intracluster gas.Comment: 17 pages, 11 figures, accepted for publication in MNRA

Focus of attention in an activity-based scheduler

Earlier research in job shop scheduling has demonstrated the advantages of opportunistically combining order-based and resource-based scheduling techniques. An even more flexible approach is investigated where each activity is considered a decision point by itself. Heuristics to opportunistically select the next decision point on which to focus attention (i.e., variable ordering heuristics) and the next decision to be tried at this point (i.e., value ordering heuristics) are described that probabilistically account for both activity precedence and resource requirement interactions. Preliminary experimental results indicate that the variable ordering heuristic greatly increases search efficiency. While least constraining value ordering heuristics have been advocated in the literature, the experimental results suggest that other value ordering heuristics combined with our variable-ordering heuristic can produce much better schedules without significantly increasing search

Computational assessment of visual coding across mouse brain areas and behavioural states

Introduction: Our brain is bombarded by a diverse range of visual stimuli, which are converted into corresponding neuronal responses and processed throughout the visual system. The neural activity patterns that result from these external stimuli vary depending on the object or scene being observed, but they also change as a result of internal or behavioural states. This raises the question of to what extent it is possible to predict the presented visual stimuli from neural activity across behavioural states, and how this varies in different brain regions. Methods: To address this question, we assessed the computational capacity of decoders to extract visual information in awake behaving mice, by analysing publicly available standardised datasets from the Allen Brain Institute. We evaluated how natural movie frames can be distinguished based on the activity of units recorded in distinct brain regions and under different behavioural states. This analysis revealed the spectrum of visual information present in different brain regions in response to binary and multiclass classification tasks. Results: Visual cortical areas showed highest classification accuracies, followed by thalamic and midbrain regions, with hippocampal regions showing close to chance accuracy. In addition, we found that behavioural variability led to a decrease in decoding accuracy, whereby large behavioural changes between train and test sessions reduced the classification performance of the decoders. A generalised linear model analysis suggested that this deterioration in classification might be due to an independent modulation of neural activity by stimulus and behaviour. Finally, we reconstructed the natural movie frames from optimal linear classifiers, and observed a strong similarity between reconstructed and actual movie frames. However, the similarity was significantly higher when the decoders were trained and tested on sessions with similar behavioural states. Conclusion: Our analysis provides a systematic assessment of visual coding in the mouse brain, and sheds light on the spectrum of visual information present across brain areas and behavioural states

Contribution of behavioural variability to representational drift

Neuronal responses to similar stimuli change dynamically over time, raising the question of how internal representations can provide a stable substrate for neural coding. Recent work has suggested a large degree of drift in neural representations even in sensory cortices, which are believed to store stable representations of the external world. While the drift of these representations is mostly characterized in relation to external stimuli, the behavioural state of the animal (for instance, the level of arousal) is also known to strongly modulate the neural activity. We therefore asked how the variability of such modulatory mechanisms can contribute to representational changes. We analysed large-scale recording of neural activity from the Allen Brain Observatory, which was used before to document representational drift in the mouse visual cortex. We found that, within these datasets, behavioural variability significantly contributes to representational changes. This effect was broadcasted across various cortical areas in the mouse, including the primary visual cortex, higher order visual areas, and even regions not primarily linked to vision like hippocampus. Our computational modelling suggests that these results are consistent with independent modulation of neural activity by behaviour over slower time scales. Importantly, our analysis suggests that reliable but variable modulation of neural representations by behaviour can be misinterpreted as representational drift, if neuronal representations are only characterized in the stimulus space and marginalised over behavioural parameters

Processing of Feature Selectivity in Cortical Networks with Specific Connectivity

Although non-specific at the onset of eye opening, networks in rodent visual cortex attain a non-random structure after eye opening, with a specific bias for connections between neurons of similar preferred orientations. As orientation selectivity is already present at eye opening, it remains unclear how this specificity in network wiring contributes to feature selectivity. Using large-scale inhibition-dominated spiking networks as a model, we show that feature-specific connectivity leads to a linear amplification of feedforward tuning, consistent with recent electrophysiological single-neuron recordings in rodent neocortex. Our results show that optimal amplification is achieved at an intermediate regime of specific connectivity. In this configuration a moderate increase of pairwise correlations is observed, consistent with recent experimental findings. Furthermore, we observed that feature-specific connectivity leads to the emergence of orientation-selective reverberating activity, and entails pattern completion in network responses. Our theoretical analysis provides a mechanistic understanding of subnetworks’ responses to visual stimuli, and casts light on the regime of operation of sensory cortices in the presence of specific connectivity

Using P300 to evaluate the effect of object color knowledge in novelty detection

Background & Objective: In an oddball experiment, the context in which novel stimuli are presented affects characteristics of novelty P3, i.e. as long as there is a difficult task in which the difference between standard and target stimuli is small, recurrent presentation of a highly discrepant stimulus can lead to P300 highly similar to novelty P3. Effect of stimulus properties on P300 has also been previously examined and it has been shown that it plays a significant role in P300 topography, its amplitude and latency. Here we have examined the effect of surface color of objects of high color-diagnosticity in a visual oddball paradigm. Materials & Methods: In two separate conditions, we used pictures of fruits as target and novel stimuli. In condition one, novel stimuli were pictures of fruits in their canonical colors. In the second condition, novel stimuli were the same photo filtered to have a different non-canonical color. P300 was compared among these conditions. Results: Both target P3 and novelty P3 were detected in the two conditions but no significant difference was evident between conditions. Conclusion: This result suggests that comparing to shape information; color cue does not play a significant role in detecting context novelty

Modeling Integrated Properties and the Polarization of the Sunyaev-Zeldovich Effect

Two little explored aspects of Compton scattering of the CMB in clusters are discussed: The statistical properties of the Sunyaev-Zeldovich (S-Z) effect in the context of a non-Gaussian density fluctuation field, and the polarization patterns in a hydrodynamcially-simulated cluster. We have calculated and compared the power spectrum and cluster number counts predicted within the framework of two density fields that yield different cluster mass functions at high redshifts. This is done for the usual Press & Schechter mass function, which is based on a Gaussian density fluctuation field, and for a mass function based on a chi^2-distributed density field. We quantify the significant differences in the respective integrated S-Z observables in these two models. S-Z polarization levels and patterns strongly depend on the non-uniform distributions of intracluster gas and on peculiar and internal velocities. We have therefore calculated the patterns of two polarization components that are produced when the CMB is doubly scattered in a simulated cluster. These are found to be very different than the patterns calculated based on spherical clusters with uniform structure and simplified gas distribution.Comment: 22 pages, 25 figures, Proceedings of the Francesco Melchiorri memorial conference, New Astronomy Reviews, in pres