The representation of perceived shape similarity and its role for category learning in monkeys: A modeling study

AbstractCategorization models often assume an intermediate stimulus representation by units implementing “distance functions”, that is, units that are activated according to the distance or similarity among stimuli. Here we show that a popular example of these models, ALCOVE, is able to account for the performance of monkeys during category learning when it takes the perceived similarity among stimuli into account. Similar results were obtained with a slightly different model (ITCOVE) that included experimentally measured tuning curves of neurons in inferior temporal (IT) cortex. These results show the intimate link between category learning and perceived similarity as represented in IT cortex

The “resort effect”: Can tourist islands act as refuges for coral reef species?

There is global consensus that marine protected areas offer a plethora of benefits to the biodiversity within and around them. Nevertheless, many organisms threatened by human impacts also find shelter in unexpected or informally protected places. For coral reef organisms, refuges can be tourist resorts implementing local environment-friendly bottom-up management strategies. We used the coral reef ecosystem as a model to test whether such practices have positive effects on the biodiversity associated with de facto protected areas.USAI

Stimulus-Dependent Adjustment of Reward Prediction Error in the Midbrain

Previous reports have described that neural activities in midbrain dopamine areas are sensitive to unexpected reward delivery and omission. These activities are correlated with reward prediction error in reinforcement learning models, the difference between predicted reward values and the obtained reward outcome. These findings suggest that the reward prediction error signal in the brain updates reward prediction through stimulus–reward experiences. It remains unknown, however, how sensory processing of reward-predicting stimuli contributes to the computation of reward prediction error. To elucidate this issue, we examined the relation between stimulus discriminability of the reward-predicting stimuli and the reward prediction error signal in the brain using functional magnetic resonance imaging (fMRI). Before main experiments, subjects learned an association between the orientation of a perceptually salient (high-contrast) Gabor patch and a juice reward. The subjects were then presented with lower-contrast Gabor patch stimuli to predict a reward. We calculated the correlation between fMRI signals and reward prediction error in two reinforcement learning models: a model including the modulation of reward prediction by stimulus discriminability and a model excluding this modulation. Results showed that fMRI signals in the midbrain are more highly correlated with reward prediction error in the model that includes stimulus discriminability than in the model that excludes stimulus discriminability. No regions showed higher correlation with the model that excludes stimulus discriminability. Moreover, results show that the difference in correlation between the two models was significant from the first session of the experiment, suggesting that the reward computation in the midbrain was modulated based on stimulus discriminability before learning a new contingency between perceptually ambiguous stimuli and a reward. These results suggest that the human reward system can incorporate the level of the stimulus discriminability flexibly into reward computations by modulating previously acquired reward values for a typical stimulus

Top-down and bottom-up modulation in processing bimodal face/voice stimuli

<p>Abstract</p> <p>Background</p> <p>Processing of multimodal information is a critical capacity of the human brain, with classic studies showing bimodal stimulation either facilitating or interfering in perceptual processing. Comparing activity to congruent and incongruent bimodal stimuli can reveal sensory dominance in particular cognitive tasks.</p> <p>Results</p> <p>We investigated audiovisual interactions driven by stimulus properties (bottom-up influences) or by task (top-down influences) on congruent and incongruent simultaneously presented faces and voices while ERPs were recorded. Subjects performed gender categorisation, directing attention either to faces or to voices and also judged whether the face/voice stimuli were congruent in terms of gender. Behaviourally, the unattended modality affected processing in the attended modality: the disruption was greater for attended voices. ERPs revealed top-down modulations of early brain processing (30-100 ms) over unisensory cortices. No effects were found on N170 or VPP, but from 180-230 ms larger right frontal activity was seen for incongruent than congruent stimuli.</p> <p>Conclusions</p> <p>Our data demonstrates that in a gender categorisation task the processing of faces dominate over the processing of voices. Brain activity showed different modulation by top-down and bottom-up information. Top-down influences modulated early brain activity whereas bottom-up interactions occurred relatively late.</p

Harnessing Wicked Problems in Multi-stakeholder Partnerships

Despite the burgeoning literature on the governance and impact of cross-sector partnerships in the past two decades, the debate on how and when these collaborative arrangements address globally relevant problems and contribute to systemic change remains open. Building upon the notion of wicked problems and the literature on governing such wicked problems, this paper defines harnessing problems in multi-stakeholder partnerships (MSPs) as the approach of taking into account the nature of the problem and of organizing governance processes accordingly. The paper develops an innovative analytical framework that conceptualizes MSPs in terms of three governance processes (deliberation, decision-making and enforce-ment) harnessing three key dimensions of wicked problems (knowledge uncertainty, value conflict and dynamic complexity). The Roundtable on Sustainable Palm Oil provides an illustrative case study on how this analytical framework describes and explains organizational change in partnerships from a problem-based perspective. The framework can be used to better understand and predict the complex relationships between MSP governance processes, systemic change and societal problems, but also as a guiding tool in (re-)organizing governance processes to continuously re-assess the problems over time and address them accordingly

The BLLAST field experiment: Boundary-Layer late afternoon and sunset turbulence

Due to the major role of the sun in heating the earth's surface, the atmospheric planetary boundary layer over land is inherently marked by a diurnal cycle. The afternoon transition, the period of the day that connects the daytime dry convective boundary layer to the night-time stable boundary layer, still has a number of unanswered scientific questions. This phase of the diurnal cycle is challenging from both modelling and observational perspectives: it is transitory, most of the forcings are small or null and the turbulence regime changes from fully convective, close to homogeneous and isotropic, toward a more heterogeneous and intermittent state. These issues motivated the BLLAST (Boundary-Layer Late Afternoon and Sunset Turbulence) field campaign that was conducted from 14 June to 8 July 2011 in southern France, in an area of complex and heterogeneous terrain. A wide range of instrumented platforms including full-size aircraft, remotely piloted aircraft systems, remote-sensing instruments, radiosoundings, tethered balloons, surface flux stations and various meteorological towers were deployed over different surface types. The boundary layer, from the earth's surface to the free troposphere, was probed during the entire day, with a focus and intense observation periods that were conducted from midday until sunset. The BLLAST field campaign also provided an opportunity to test innovative measurement systems, such as new miniaturized sensors, and a new technique for frequent radiosoundings of the low troposphere. Twelve fair weather days displaying various meteorological conditions were extensively documented during the field experiment. The boundary-layer growth varied from one day to another depending on many contributions including stability, advection, subsidence, the state of the previous day's residual layer, as well as local, meso- or synoptic scale conditions. Ground-based measurements combined with tethered-balloon and airborne observations captured the turbulence decay from the surface throughout the whole boundary layer and documented the evolution of the turbulence characteristic length scales during the transition period. Closely integrated with the field experiment, numerical studies are now underway with a complete hierarchy of models to support the data interpretation and improve the model representations.publishedVersio

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong