3,109 research outputs found
A common neural scale for the subjective pleasantness of different primary rewards.
When an economic decision is taken, it is between goals with different values, and the values must be on the same scale. Here, we used functional MRI to search for a brain region that represents the subjective pleasantness of two different rewards on the same neural scale. We found activity in the ventral prefrontal cortex that correlated with the subjective pleasantness of two fundamentally different rewards, taste in the mouth and warmth on the hand. The evidence came from two different investigations, a between-group comparison of two independent fMRI studies, and from a within-subject study. In the latter, we showed that neural activity in the same voxels in the ventral prefrontal cortex correlated with the subjective pleasantness of the different rewards. Moreover, the slope and intercept for the regression lines describing the relationship between activations and subjective pleasantness were highly similar for the different rewards. We also provide evidence that the activations did not simply represent multisensory integration or the salience of the rewards. The findings demonstrate the existence of a specific region in the human brain where neural activity scales with the subjective pleasantness of qualitatively different primary rewards. This suggests a principle of brain processing of importance in reward valuation and decision-making
Representational capacity of a set of independent neurons
The capacity with which a system of independent neuron-like units represents
a given set of stimuli is studied by calculating the mutual information between
the stimuli and the neural responses. Both discrete noiseless and continuous
noisy neurons are analyzed. In both cases, the information grows monotonically
with the number of neurons considered. Under the assumption that neurons are
independent, the mutual information rises linearly from zero, and approaches
exponentially its maximum value. We find the dependence of the initial slope on
the number of stimuli and on the sparseness of the representation.Comment: 19 pages, 6 figures, Phys. Rev. E, vol 63, 11910 - 11924 (2000
Reduced long-range dependence combining Poisson bursts with on--off sources
A workload model using the infinite source Poisson model for bursts is
combined with the on--off model for within burst activity. Burst durations and
on--off durations are assumed to have heavy-tailed distributions with infinite
variance and finite mean. Since the number of bursts is random, one can
consider limiting results based on "random centering" of a random sum for the
total workload from all sources. Convergence results are shown to depend on the
tail indices of both the on--off durations and the lifetimes distributions.
Moreover, the results can be separated into cases depending on those tail
indices. In one case where all distributions are heavy tailed it is shown that
the limiting result is Brownian motion. In another case, convergence to
fractional Brownian motion is shown, where the Hurst parameter depends on the
heavy-tail indices of the distribution of the on, off and burst durations.Comment: Published in at http://dx.doi.org/10.1214/09-BJPS105 the Brazilian
Journal of Probability and Statistics (http://www.imstat.org/bjps/) by the
Brazilian Statistical Association/Institute of Mathematical Statistics
(http://www.redeabe.org.br/
The texture and taste of food in the brain
Oral texture is represented in the brain areas that represent taste, including the primary taste cortex, the orbitofrontal cortex, and the amygdala. Some neurons represent viscosity, and their responses correlate with the subjective thickness of a food. Other neurons represent fat in the mouth, and represent it by its texture not by its chemical composition, in that they also respond to paraffin oil and silicone in the mouth. The discovery has been made that these fat-responsive neurons encode the coefficient of sliding friction and not viscosity, and this opens the way for the development of new foods with the pleasant mouth feel of fat and with health-promoting designed nutritional properties. A few other neurons respond to free fatty acids (such as linoleic acid), do not respond to fat in the mouth, and may contribute to some 'off' tastes in the mouth. Some other neurons code for astringency. Others neurons respond to other aspects of texture such as the crisp fresh texture of a slice of apple vs the same apple after blending. Different neurons respond to different combinations of these texture properties, oral temperature, taste, and in the orbitofrontal cortex to olfactory and visual properties of food. In the orbitofrontal cortex, the pleasantness and reward value of the food is represented, but the primary taste cortex represents taste and texture independently of value. These discoveries were made in macaques that have similar cortical brain areas for taste and texture processing as humans, and complementary human functional neuroimaging studies are described. This article is protected by copyright. All rights reserved. [Abstract copyright: This article is protected by copyright. All rights reserved.
Experiential Learning as an Adjunct to the Basic Course: Student Responses to a Pedagogical Model
An experiential learning model requiring regular weekly attendance at a communication lab, videotaped classroom presentations, and journal submissions as adjunctive course requirements is described as assessed. A content analysis of lab evaluation forms and journal entries clearly shows that the model works. Students report they enjoy the experience, improve their interpersonal skills, become more sensitive communicators, experience personal growth, and feel they are more successful in classroom presentations as a results of the lab experience
Extending the impulse response in order to reduce errors due to impulse noise and signal fading
A finite impulse response (FIR) digital smearing filter was designed to produce maximum intersymbol interference and maximum extension of the impulse response of the signal in a noiseless binary channel. A matched FIR desmearing filter at the receiver then reduced the intersymbol interference to zero. Signal fades were simulated by means of 100 percent signal blockage in the channel. Smearing and desmearing filters of length 256, 512, and 1024 were used for these simulations. Results indicate that impulse response extension by means of bit smearing appears to be a useful technique for correcting errors due to impulse noise or signal fading in a binary channel
Collaboration in neuroscience: the young PI perspective.
Wellcome Trust, University of Cambridge, CIG, Adelis FoundationThis is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1111/ejn.1322
Neural systems underlying decisions about affective odors.
Decision making about affective value may occur after the reward value of a stimulus is represented and may involve different brain areas to those involved in decision-making about the physical properties of stimuli, such as intensity. In an fMRI study, we delivered two odors separated by a delay, with instructions on different trials to decide which odor was more pleasant or more intense or to rate the pleasantness and intensity of the second odor without making a decision. The fMRI signals in the medial pFC area 10 and in regions to which it projects, including the ACC and insula, were higher when decisions were being made compared with ratings, implicating these regions in decision-making. Decision-making about affective value was related to larger signals in the dorsal part of medial area 10 and the agranular insula, whereas decisions about intensity were related to larger activations in the dorsolateral pFC, ventral premotor cortex, and anterior insula. For comparison, the mid-OFC had activations related not to decision making but to subjective pleasantness ratings, providing a continuous representation of affective value. In contrast, areas such as medial area 10 and the ACC are implicated in reaching a decision in which a binary outcome is produced
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