scholarly journals Variance adaptation in navigational decision making

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ruben Gepner ◽  
Jason Wolk ◽  
Digvijay Shivaji Wadekar ◽  
Sophie Dvali ◽  
Marc Gershow
Keyword(s):  
Sensory Input ◽  
Variance Estimation ◽  
Temporal Dynamics ◽  
Sensory Systems ◽  
Redundant Information ◽  
Environmental Variance ◽  
Mean And Variance ◽  
The Mean ◽  
Light Signals ◽  
The Brain

Sensory systems relay information about the world to the brain, which enacts behaviors through motor outputs. To maximize information transmission, sensory systems discard redundant information through adaptation to the mean and variance of the environment. The behavioral consequences of sensory adaptation to environmental variance have been largely unexplored. Here, we study how larval fruit flies adapt sensory-motor computations underlying navigation to changes in the variance of visual and olfactory inputs. We show that variance adaptation can be characterized by rescaling of the sensory input and that for both visual and olfactory inputs, the temporal dynamics of adaptation are consistent with optimal variance estimation. In multisensory contexts, larvae adapt independently to variance in each sense, and portions of the navigational pathway encoding mixed odor and light signals are also capable of variance adaptation. Our results suggest multiplication as a mechanism for odor-light integration.

scholarly journals Reward skewness coding in the insula independent of probability and loss

2011 ◽  
Vol 106 (5) ◽  
pp. 2415-2422 ◽  
Author(s):  
Christopher J. Burke ◽  
Philippe N. Tobler
Keyword(s):  
Loss Aversion ◽  
Natural Environment ◽  
Potential Outcomes ◽  
Preference Formation ◽  
Individual Preferences ◽  
Data Support ◽  
Mean And Variance ◽  
The Mean ◽  
The Asymmetry ◽  
The Brain

Rewards in the natural environment are rarely predicted with complete certainty. Uncertainty relating to future rewards has typically been defined as the variance of the potential outcomes. However, the asymmetry of predicted reward distributions, known as skewness, constitutes a distinct but neuroscientifically underexplored risk term that may also have an impact on preference. By changing only reward magnitudes, we study skewness processing in equiprobable ternary lotteries involving only gains and constant probabilities, thus excluding probability distortion or loss aversion as mechanisms for skewness preference formation. We show that individual preferences are sensitive to not only the mean and variance but also to the skewness of predicted reward distributions. Using neuroimaging, we show that the insula, a structure previously implicated in the processing of reward-related uncertainty, responds to the skewness of predicted reward distributions. Some insula responses increased in a monotonic fashion with skewness (irrespective of individual skewness preferences), whereas others were similarly elevated to both negative and positive as opposed to no reward skew. These data support the notion that the asymmetry of reward distributions is processed in the brain and, taken together with replicated findings of mean coding in the striatum and variance coding in the cingulate, suggest that the brain codes distinct aspects of reward distributions in a distributed fashion.

Asymmetric Dynamics in Optimal Variance Adaptation

1998 ◽  
Vol 10 (5) ◽  
pp. 1179-1202 ◽  
Author(s):  
Michael DeWeese ◽  
Anthony Zador
Keyword(s):  
Time Course ◽  
Variance Estimation ◽  
Broad Class ◽  
Sensory Systems ◽  
Abrupt Increase ◽  
Abrupt Decrease ◽  
Nonstationary Signals ◽  
Variance Estimate ◽  
The Mean ◽  
Optimal Adaptation

It has long been recognized that sensory systems adapt to their inputs. Here we formulate the problem of optimal variance estimation for a broad class of nonstationary signals. We show that under weak assumptions, the Bayesian optimal causal variance estimate shows asymmetric dynamics: an abrupt increase in variance is more readily detectable than an abrupt decrease. By contrast, optimal adaptation to the mean displays symmetric dynamics when the variance is held fixed. After providing several empirical examples and a simple intuitive argument for our main result, we prove that optimal adaptation is asymmetrical in a broad class of model environments. This observation makes specific and falsifiable predictions about the time course of adaptation in neurons probed with certain stimulus ensembles.

No Evidence of Creative Benefit Accompanying Dyslexia: A Meta-Analysis

2021 ◽  
pp. 002221942110103
Author(s):  
Florina Erbeli ◽  
Peng Peng ◽  
Marianne Rice
Keyword(s):  
Random Effects ◽  
Variance Estimation ◽  
Meta Analysis ◽  
Robust Variance ◽  
Summary Effect ◽  
Significant Performance ◽  
Mean And Variance ◽  
Robust Variance Estimation ◽  
The Mean ◽  
Creativity Task

Research on the question of creative benefit accompanying dyslexia has produced conflicting findings. In this meta-analysis, we determined summary effects of mean and variance differences in creativity between groups with and without dyslexia. Twenty studies were included ( n = 770 individuals with dyslexia, n = 1,671 controls). A random-effects robust variance estimation (RVE) analysis indicated no mean ( g = −0.02, p = .84) or variance differences ( g = −0.0004, p = .99) in creativity between groups. The mean summary effect was moderated by age, gender, and creativity domain. Compared with adolescents, adults with dyslexia showed an advantage over nondyslexic adults in creativity. In addition, a higher proportion of males in the dyslexia group was associated with poorer performance compared with the controls. Finally, the dyslexia group showed a significant performance disadvantage in verbal versus figural creativity. Regarding variance differences, they varied across age and creativity domains. Compared with adults, adolescents showed smaller variability in the dyslexia group. If the creativity task measured verbal versus figural or combined creativity, then the dyslexia group exhibited smaller variability. Altogether, our results suggest that individuals with dyslexia as a group are no more creative or show greater variability in creativity than peers without dyslexia.

scholarly journals Removal of Scanner Effects in Covariance Improves Multivariate Pattern Analysis in Neuroimaging Data

2019 ◽  
Author(s):  
Andrew A. Chen ◽  
Joanne C. Beer ◽  
Nicholas J. Tustison ◽  
Philip A. Cook ◽  
Russell T. Shinohara ◽  
...  
Keyword(s):  
Pattern Analysis ◽  
Multivariate Pattern Analysis ◽  
Neuroimaging Data ◽  
Mean And Variance ◽  
The Mean ◽  
Improved Performance ◽  
Sensitivity Specificity ◽  
Multivariate Pattern ◽  
The Brain ◽  
Multivariate Image

AbstractTo acquire larger samples for answering complex questions in neuroscience, researchers have increasingly turned to multi-site neuroimaging studies. However, these studies are hindered by differences in images acquired across multiple scanners. These effects have been shown to bias comparison between scanners, mask biologically meaningful associations, and even introduce spurious associations. To address this, the field has focused on harmonizing data by removing scanner-related effects in the mean and variance of measurements. Contemporaneously with the increase in popularity of multi-center imaging, the use of multivariate pattern analysis (MVPA) has also become commonplace. These approaches have been shown to provide improved sensitivity, specificity, and power due to their modeling the joint relationship across measurements in the brain. In this work, we demonstrate that methods for removing scanner effects in mean and variance may not be sufficient for MVPA. This stems from the fact that such methods fail to address how correlations between measurements can vary across scanners. Data from the Alzheimer’s Disease Neuroimaging Initiative is used to show that considerable differences in covariance exist across scanners and that popular harmonization techniques do not address this issue. We also propose a novel methodology that harmonizes covariance of multivariate image measurements across scanners and demonstrate its improved performance in data harmonization.

scholarly journals Experimental validation of variance estimation in the statistical energy analysis of a structural-acoustic system

2019 ◽  
Vol 233 (18) ◽  
pp. 6448-6459
Author(s):  
Luis Andrade ◽  
Robin S Langley ◽  
Tore Butlin ◽  
Matthew de Brett ◽  
Ole M Nielsen
Keyword(s):  
Experimental Evidence ◽  
Variance Estimation ◽  
Energy Analysis ◽  
Statistical Energy Analysis ◽  
Acoustic System ◽  
Analysis Model ◽  
Vibrating Structures ◽  
Mean And Variance ◽  
The Mean ◽  
Acoustic Cavities

The Statistical Energy Analysis (SEA) approach has largely been used in vibro-acoustic modelling to predict the averaged energy in coupled vibrating structures and acoustic cavities. The average is performed over an ensemble of nominally identical built-up systems where random responses are observed at high frequencies after excitation. Over the years, this approach has been extended to predict the energy variance employing the statistics of the Gaussian Orthogonal Ensemble, and numerical and experimental evidence has supported the predictions of the mean and variance of energy of coupled vibrating structures. However, little experimental evidence is found to validate the prediction of the variance of energy in coupled structural-acoustic systems. In this work, the mean and variance of energies predicted from a statistical energy analysis model have been validated with experimental measurements on a structural-acoustic system, comprised by a flat thin plate coupled to an enclosed acoustic volume. The structural system has been randomised by adding small masses on arbitrary positions on the plate, whereas the randomisation of the acoustic cavity is achieved by allocating rigid baffles in random positions within the acoustic volume. In general, good agreement is found between the predictions of the model and the experimental results.

scholarly journals Use of genomic models to study genetic control of environmental variance

2011 ◽  
Vol 93 (2) ◽  
pp. 125-138 ◽  
Author(s):  
YE YANG ◽  
OLE F. CHRISTENSEN ◽  
DANIEL SORENSEN
Keyword(s):  
Complex Traits ◽  
Simulated Data ◽  
Environmental Variance ◽  
Mcmc Algorithms ◽  
Mean And Variance ◽  
Fat Thickness ◽  
The Mean ◽  
Genomic Regions ◽  
Accuracy Of Prediction ◽  
Qtl Effects

SummaryVast amount of genetic marker information is being used to obtain insight into the genetic architecture of complex traits, for locating genomic regions (quantitative trait loci (QTL)) affecting disease and for enhancing the accuracy of prediction of genetic values in selection programmes. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm is proposed.

scholarly journals Desynchronizing to be faster? Perceptual- and attentional-modulation of brain rhythms in sub-millisecond scale

2018 ◽  
Author(s):  
Yasuki Noguchi ◽  
Yi Xia ◽  
Ryusuke Kakigi
Keyword(s):  
Information Transfer ◽  
Visual Stimulation ◽  
Neural Population ◽  
Neural Computations ◽  
Mean And Variance ◽  
The Mean ◽  
Beta Rhythms ◽  
High Level ◽  
The Brain

AbstractNeural oscillatory signals has been associated with many high-level functions (e.g. attention and working memory), because they reflect correlated behaviors of neural population that would facilitate the information transfer in the brain. On the other hand, a decreased power of oscillation (event-related desynchronization or ERD) has been associated with an irregular state in which many neurons behave in an uncorrelated manner. In contrast to this view, here we show that the human ERD is linked to the increased regularity of oscillatory signals. Using magnetoencephalography, we found that presenting a visual stimulus not only induced the ERD of alpha (8-13 Hz) and beta (13-30 Hz) rhythms in the contralateral visual cortex but also reduced the mean and variance of their inter-peak intervals (IPIs). This indicates that the suppressed alpha/beta rhythms became faster (reduced mean) and more regular (reduced variance) during visual stimulation. The same changes in IPIs, especially those of beta rhythm, were observed when subjects allocated their attention to a contralateral visual field. Those results revealed a new role of the ERD and further suggested that our brain regulates and accelerates a clock for neural computations by actively inducing the desynchronization in task-relevant regions.

Comparison of Fluorine(18)-fluorodeoxyglucose and Gallium(68)-citrate PET/CT in patients with tuberculosis

2019 ◽  
Vol 58 (05) ◽  
pp. 371-378
Author(s):  
Alfred O. Ankrah ◽  
Ismaheel O. Lawal ◽  
Tebatso M.G. Boshomane ◽  
Hans C. Klein ◽  
Thomas Ebenhan ◽  
...  
Keyword(s):  
Tracer Uptake ◽  
Pet Ct ◽  
The Mean ◽  
18F Fdg ◽  
Definition Of ◽  
Gallium 68 ◽  
Attending Physician ◽  
Pet Scans ◽  
The Brain

Abstract 18F-FDG and 68Ga-citrate PET/CT have both been shown to be useful in the management of tuberculosis (TB). We compared the abnormal PET findings of 18F-FDG- and 68Ga-citrate-PET/CT in patients with TB. Methods Patients with TB on anti-TB therapy were included. Patients had a set of PET scans consisting of both 18F-FDG and 68Ga-citrate. Abnormal lesions were identified, and the two sets of scans were compared. The scan findings were correlated to the clinical data as provided by the attending physician. Results 46 PET/CT scans were performed in 18 patients, 11 (61 %) were female, and the mean age was 35.7 ± 13.5 years. Five patients also had both studies for follow-up reasons during the use of anti-TB therapy. Thirteen patients were co-infected with HIV. 18F-FDG detected more lesions than 68Ga-citrate (261 vs. 166, p < 0.0001). 68Ga-citrate showed a better definition of intracerebral lesions due to the absence of tracer uptake in the brain. The mean SUVmax was higher for 18F-FDG compared to 68Ga-citrate (5.73 vs. 3.01, p < 0.0001). We found a significant correlation between the SUVmax of lesions that were determined by both tracers (r = 0.4968, p < 0.0001). Conclusion Preliminary data shows 18F-FDG-PET detects more abnormal lesions in TB compared to 68Ga-citrate. However, 68Ga-citrate has better lesion definition in the brain and is therefore especially useful when intracranial TB is suspected.

scholarly journals Stability and flexibility in multisensory sampling: insights from perceptual illusions

2019 ◽  
Vol 121 (5) ◽  
pp. 1588-1590 ◽  
Author(s):  
Luca Casartelli
Keyword(s):  
Temporal Dynamics ◽  
Multisensory Processing ◽  
General Idea ◽  
Perceptual Illusions ◽  
The Brain ◽  
Multisensory Processes

Neural, oscillatory, and computational counterparts of multisensory processing remain a crucial challenge for neuroscientists. Converging evidence underlines a certain efficiency in balancing stability and flexibility of sensory sampling, supporting the general idea that multiple parallel and hierarchically organized processing stages in the brain contribute to our understanding of the (sensory/perceptual) world. Intriguingly, how temporal dynamics impact and modulate multisensory processes in our brain can be investigated benefiting from studies on perceptual illusions.

Sign in / Sign up

Export Citation Format

Share Document