Adaptive sampling by information maximization

The investigation of input-output systems often requires a sophisticated choice of test inputs to make best use of limited experimental time. Here we present an iterative algorithm that continuously adjusts an ensemble of test inputs online, subject to the data already acquired about the system under study. The algorithm focuses the input ensemble by maximizing the mutual information between input and output. We apply the algorithm to simulated neurophysiological experiments and show that it serves to extract the ensemble of stimuli that a given neural system ``expects'' as a result of its natural history.Comment: 4 pages, 2 figure

EFFECTS OF ESSENTIAL OILS AND AMINO ACID PROFILE ON THE GROWTH AND HEALTH OF RECEIVING CATTLE

The objective of this trial was to evaluate the effects of amino acid profile and essential oil products on receiving calf growth and feed efficiency, as well as evaluate the effects of amino acid profile and essential oil products on fecal and blood Immunoglobulin A (IgA) concentrations as a marker for systemic and gastrointestinal tract immune status of receiving calves. One hundred-thirty crossbred calves (500-600 lbs) were transported to the ADM Animal Nutrition Research Facility in Mendon, IL. On d -1, cattle were weighed, dewormed, implanted, vaccinated, and a rectal temperature was recorded. An at-risk group of cattle was targeted for this trial. Based on initial BW and health status, cattle were allotted to 12 pens with 10 calves per pen so that each pen had similar weight and distribution of sick animals. Treatments were randomly assigned to pens with 2 pens per treatment. Initial body weights were similar (P = 0.99) among treatments. Cattle were weighed on days -1, 0, 21, 42, 63, and 64. Treatments were arranged in a 2 x 3 factorial design of AminoGain formula (AminoGain 6 or AminoGain 6 Plus) and essential oil product (no essential oil, Stay Strong EO, or Spearmint Extract). Individual animal intake was recorded from d 0-63 using the GrowSafe® cattle feeding system. Stay Strong EO was targeted to deliver 1 g / 100 lb body weight. Based on calculations, 1.07 g/100 lb body weight was delivered. Preliminary analysis indicated the Spearmint Extract was composed of 13% limonene and 70% carvone. The Spearmint Extract treatment targeted to deliver 40 ppm limonene and 220 ppm carvone. Once the analysis came back, the extract actually contained 0.08% limonene and 91.73% carvone. There is a possibility that limonene was oxidized to carvone subsequent to initial analysis. Three animals from each pen were randomly selected for fecal and sample collection. Blood and fecal samples were collected on d 0, 21, and 42 for analyses of IgA concentrations. An interaction of AminoGain 6 formulation by essential oil source resulted (P \u3c 0.02) for cumulative ADG. Cumulative ADG did not differ (P \u3e 0.05) with the addition of Spearmint Extract or Stay Strong EO to the AminoGain 6 formula. However, the addition of Spearmint Extract worsened (P \u3c 0.03) cumulative ADG when added to the AminoGain 6 Plus formula. This was likely the result of cumulative feed intake tending (P ≤ 0.06) to be lower when the AminoGain 6 Plus x Spearmint Extract was fed. IgA concentrations in blood were not different (P \u3e 0.05) as a result of treatment for any of the measured time points. The responsiveness of IgA assay to changing disease status make it an effective tool to assess gross disease state of receiving cattle. Further research is needed to determine the effects of using essential oil as a feed additive upon health and growth of cattle

Demixing Population Activity in Higher Cortical Areas

Neural responses in higher cortical areas often display a baffling complexity. In animals performing behavioral tasks, single neurons will typically encode several parameters simultaneously, such as stimuli, rewards, decisions, etc. When dealing with this large heterogeneity of responses, cells are conventionally classified into separate response categories using various statistical tools. However, this classical approach usually fails to account for the distributed nature of representations in higher cortical areas. Alternatively, principal component analysis (PCA) or related techniques can be employed to reduce the complexity of a data set while retaining the distributional aspect of the population activity. These methods, however, fail to explicitly extract the task parameters from the neural responses. Here we suggest a coordinate transformation that seeks to ameliorate these problems by combining the advantages of both methods. Our basic insight is that variance in neural firing rates can have different origins (such as changes in a stimulus, a reward, or the passage of time), and that, instead of lumping them together, as PCA does, we need to treat these sources separately. We present a method that seeks an orthogonal coordinate transformation such that the variance captured from different sources falls into orthogonal subspaces and is maximized within these subspaces. Using simulated examples, we show how this approach can be used to demix heterogeneous neural responses. Our method may help to lift the fog of response heterogeneity in higher cortical areas

Optogenetic perturbations reveal the dynamics of an oculomotor integrator

Many neural systems can store short-term information in persistently firing neurons. Such persistent activity is believed to be maintained by recurrent feedback among neurons. This hypothesis has been fleshed out in detail for the oculomotor integrator (OI) for which the so-called “line attractor” network model can explain a large set of observations. Here we show that there is a plethora of such models, distinguished by the relative strength of recurrent excitation and inhibition. In each model, the firing rates of the neurons relax toward the persistent activity states. The dynamics of relaxation can be quite different, however, and depend on the levels of recurrent excitation and inhibition. To identify the correct model, we directly measure these relaxation dynamics by performing optogenetic perturbations in the OI of zebrafish expressing halorhodopsin or channelrhodopsin. We show that instantaneous, inhibitory stimulations of the OI lead to persistent, centripetal eye position changes ipsilateral to the stimulation. Excitatory stimulations similarly cause centripetal eye position changes, yet only contralateral to the stimulation. These results show that the dynamics of the OI are organized around a central attractor state—the null position of the eyes—which stabilizes the system against random perturbations. Our results pose new constraints on the circuit connectivity of the system and provide new insights into the mechanisms underlying persistent activity

Immunization strategies for epidemic processes in time-varying contact networks

Spreading processes represent a very efficient tool to investigate the structural properties of networks and the relative importance of their constituents, and have been widely used to this aim in static networks. Here we consider simple disease spreading processes on empirical time-varying networks of contacts between individuals, and compare the effect of several immunization strategies on these processes. An immunization strategy is defined as the choice of a set of nodes (individuals) who cannot catch nor transmit the disease. This choice is performed according to a certain ranking of the nodes of the contact network. We consider various ranking strategies, focusing in particular on the role of the training window during which the nodes' properties are measured in the time-varying network: longer training windows correspond to a larger amount of information collected and could be expected to result in better performances of the immunization strategies. We find instead an unexpected saturation in the efficiency of strategies based on nodes' characteristics when the length of the training window is increased, showing that a limited amount of information on the contact patterns is sufficient to design efficient immunization strategies. This finding is balanced by the large variations of the contact patterns, which strongly alter the importance of nodes from one period to the next and therefore significantly limit the efficiency of any strategy based on an importance ranking of nodes. We also observe that the efficiency of strategies that include an element of randomness and are based on temporally local information do not perform as well but are largely independent on the amount of information available