Attention-dependent modulation of cortical taste circuits revealed by granger causality with signal-dependent noise

We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention

Balanced Input Allows Optimal Encoding in a Stochastic Binary Neural Network Model: An Analytical Study

Recent neurophysiological experiments have demonstrated a remarkable effect of attention on the underlying neural activity that suggests for the first time that information encoding is indeed actively influenced by attention. Single cell recordings show that attention reduces both the neural variability and correlations in the attended condition with respect to the non-attended one. This reduction of variability and redundancy enhances the information associated with the detection and further processing of the attended stimulus. Beyond the attentional paradigm, the local activity in a neural circuit can be modulated in a number of ways, leading to the general question of understanding how the activity of such circuits is sensitive to these relatively small modulations. Here, using an analytically tractable neural network model, we demonstrate how this enhancement of information emerges when excitatory and inhibitory synaptic currents are balanced. In particular, we show that the network encoding sensitivity -as measured by the Fisher information- is maximized at the exact balance. Furthermore, we find a similar result for a more realistic spiking neural network model. As the regime of balanced inputs has been experimentally observed, these results suggest that this regime is functionally important from an information encoding standpoint

Neural Correlates of Appetite and Hunger-Related Evaluative Judgments

How much we desire a meal depends on both the constituent foods and how hungry we are, though not every meal becomes more desirable with increasing hunger. The brain therefore needs to be able to integrate hunger and meal properties to compute the correct incentive value of a meal. The present study investigated the functional role of the amygdala and the orbitofrontal cortex in mediating hunger and dish attractiveness. Furthermore, it explored neural responses to dish descriptions particularly susceptible to value-increase following fasting. We instructed participants to rate how much they wanted food menu items while they were either hungry or sated, and compared the rating differences in these states. Our results point to the representation of food value in the amygdala, and to an integration of attractiveness with hunger level in the orbitofrontal cortex. Dishes particularly desirable during hunger activated the thalamus and the insula. Our results specify the functions of evaluative structures in the context of food attractiveness, and point to a complex neural representation of dish qualities which contribute to state-dependent value

A Computational Model of the Development of Separate Representations of Facial Identity and Expression in the Primate Visual System

Experimental studies have provided evidence that the visual processing areas of the primate brain represent facial identity and facial expression within different subpopulations of neurons. For example, in non-human primates there is evidence that cells within the inferior temporal gyrus (TE) respond primarily to facial identity, while cells within the superior temporal sulcus (STS) respond to facial expression. More recently, it has been found that the orbitofrontal cortex (OFC) of non-human primates contains some cells that respond exclusively to changes in facial identity, while other cells respond exclusively to facial expression. How might the primate visual system develop physically separate representations of facial identity and expression given that the visual system is always exposed to simultaneous combinations of facial identity and expression during learning? In this paper, a biologically plausible neural network model, VisNet, of the ventral visual pathway is trained on a set of carefully-designed cartoon faces with different identities and expressions. The VisNet model architecture is composed of a hierarchical series of four Self-Organising Maps (SOMs), with associative learning in the feedforward synaptic connections between successive layers. During learning, the network develops separate clusters of cells that respond exclusively to either facial identity or facial expression. We interpret the performance of the network in terms of the learning properties of SOMs, which are able to exploit the statistical indendependence between facial identity and expression

The Effect of Sugar-Free Versus Sugar-Sweetened Beverages on Satiety, Liking and Wanting: An 18 Month Randomized Double-Blind Trial in Children

BACKGROUND: Substituting sugar-free for sugar-sweetened beverages reduces weight gain. A possible explanation is that sugar-containing and sugar-free beverages cause the same degree of satiety. However, this has not been tested in long-term trials. METHODS: We randomized 203 children aged 7-11 years to receive 250 mL per day of an artificially sweetened sugar-free beverage or a similarly looking and tasting sugar-sweetened beverage. We measured satiety on a 5-point scale by questionnaire at 0, 6, 12 and 18 months. We calculated the change in satiety from before intake to 1 minute after intake and 15 minutes after intake. We then calculated the odds ratio that satiety increased by 1 point in the sugar-group versus the sugar-free group. We also investigated how much the children liked and wanted the beverages. RESULTS: 146 children or 72% completed the study. We found no statistically significant difference in satiety between the sugar-free and sugar-sweetened group; the adjusted odds ratio for a 1 point increase in satiety in the sugar group versus the sugar-free group was 0.77 at 1 minute (95% confidence interval, 0.46 to 1.29), and 1.44 at 15 minutes after intake (95% CI, 0.86 to 2.40). The sugar-group liked and wanted their beverage slightly more than the sugar-free group, adjusted odds ratio 1.63 (95% CI 1.05 to 2.54) and 1.65 (95% CI 1.07 to 2.55), respectively. CONCLUSIONS: Sugar-sweetened and sugar-free beverages produced similar satiety. Therefore when children are given sugar-free instead of sugar-containing drinks they might not make up the missing calories from other sources. This may explain our previous observation that children in the sugar-free group accumulated less body fat than those in the sugar group.<br /

Neural Network Mechanisms Underlying Stimulus Driven Variability Reduction

It is well established that the variability of the neural activity across trials, as measured by the Fano factor, is elevated. This fact poses limits on information encoding by the neural activity. However, a series of recent neurophysiological experiments have changed this traditional view. Single cell recordings across a variety of species, brain areas, brain states and stimulus conditions demonstrate a remarkable reduction of the neural variability when an external stimulation is applied and when attention is allocated towards a stimulus within a neuron's receptive field, suggesting an enhancement of information encoding. Using an heterogeneously connected neural network model whose dynamics exhibits multiple attractors, we demonstrate here how this variability reduction can arise from a network effect. In the spontaneous state, we show that the high degree of neural variability is mainly due to fluctuation-driven excursions from attractor to attractor. This occurs when, in the parameter space, the network working point is around the bifurcation allowing multistable attractors. The application of an external excitatory drive by stimulation or attention stabilizes one specific attractor, eliminating in this way the transitions between the different attractors and resulting in a net decrease in neural variability over trials. Importantly, non-responsive neurons also exhibit a reduction of variability. Finally, this reduced variability is found to arise from an increased regularity of the neural spike trains. In conclusion, these results suggest that the variability reduction under stimulation and attention is a property of neural circuits

Neuropsychological patterns following lesions of the anterior insula in a series of forty neurosurgical patients

In the present study we investigated the effects of lesions affecting mainly the anterior insula in a series of 22 patients with lesions in the left hemisphere (LH), and 18 patients with lesions involving the right hemisphere (RH). The site of the lesion was established by performing an overlap of the probabilistic cytoarchitectonic maps of the posterior insula. Here we report the patients\u2019 neuropsychological profile and an analysis of their pre-surgical symptoms. We found that pre-operatory symptoms significantly differed in patients depending on whether the lesion affected the right or left insula and a strict parallelism between the patterns emerged in the pre-surgery symptoms analysis, and the patients\u2019 cognitive profile. In particular, we found that LH patients showed cognitive deficits. By contrast, the RH patients, with the exception of one case showing an impaired performance at the visuo-spatial planning test were within the normal range in performing all the tests. In addition, a sub-group of patients underwent to the post-surgery follow-up examination