• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

How predictable are “Spontaneous Decisions” and “Hidden Intentions”?, comparing classification results based on previous responses with multivariate pattern analysis of fMRI BOLD signals. (2012)

by M ages, K Jaworska
Venue:Frontiers in Psychology,
Add To MetaCart

Tools

Sorted by:
Results 1 - 2 of 2

Real-time fMRI-brain computer interfaces for rehabilitation of Parkinson’s disease patients.

by Sergio Ruiz , Korhan Buyukturkoglu , Mohit Rana , Niels Birbaumer , Ranganatha Sitaram , 2012
"... a b s t r a c t With the advent of brain computer interfaces based on real-time fMRI (rtfMRI-BCI), the possibility of performing neurofeedback based on brain hemodynamics has become a reality. In the early stage of the development of this field, studies have focused on the volitional control of act ..."
Abstract - Cited by 7 (2 self) - Add to MetaCart
a b s t r a c t With the advent of brain computer interfaces based on real-time fMRI (rtfMRI-BCI), the possibility of performing neurofeedback based on brain hemodynamics has become a reality. In the early stage of the development of this field, studies have focused on the volitional control of activity in circumscribed brain regions. However, based on the understanding that the brain functions by coordinated activity of spatially distributed regions, there have recently been further developments to incorporate real-time feedback of functional connectivity and spatio-temporal patterns of brain activity. The present article reviews the principles of rtfMRI neurofeedback, its applications, benefits and limitations. A special emphasis is given to the discussion of novel developments that have enabled the use of this methodology to achieve selfregulation of the functional connectivity between different brain areas and of distributed brain networks, anticipating new and exciting applications for cognitive neuroscience and for the potential alleviation of neuropsychiatric disorders.
(Show Context)

Citation Context

...then computed based on the number of correct and incorrect redictions from several test data. For more details on the SVM patern classification one can refer to a number of excellent tutorials nd articles on the topic (Schölkopf & Smola, 2001; Shawe-Taylor Cristianini, 2004; Steinwart & Christmann, 2008). Pattern analysis has been used for understanding the spatial nd temporal neural patterns of different brain functions and their tates. Recent studies that used this approach are: automated clasification of sleep stages (Tagliazucchi et al., 2012), spontaneous ecisions and hidden intentions (Lages & Jaworska, 2012), trackng the unconscious generation of free decision (Bode et al., 2011),ages after every scan (at an interval of 1.5 s) to the fMRI-BCI computer. memory recall (Polyn, Natu, Cohen, & Norman, 2005), lie detection (Davatzikos et al., 2005), visual perception (Xu, Jiang, Ma, Yang, & Weng, 2012), task related intentions (Haynes et al., 2007), fear perception (Pessoa & Padmala, 2005), and emotion detection (Sitaram et al., 2011a), to name a few. How can pattern classification be incorporated in real-time fMRI studies? LaConte et al. (2007) were the first to demonstrate the realtime implementation...

Quantifying the effect of intertrial dependence on perceptual decisions

by Felix A. Wichmann, Eberhard Karls Universität, Jakob H. Macke
"... In the perceptual sciences, experimenters study the causal mechanisms of perceptual systems by probing observers with carefully constructed stimuli. It has long been known, however, that perceptual decisions are not only determined by the stimulus, but also by internal factors. Internal factors coul ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
In the perceptual sciences, experimenters study the causal mechanisms of perceptual systems by probing observers with carefully constructed stimuli. It has long been known, however, that perceptual decisions are not only determined by the stimulus, but also by internal factors. Internal factors could lead to a statistical influence of previous stimuli and responses on the current trial, resulting in serial dependencies, which complicate the causal inference between stimulus and response. However, the majority of studies do not take serial dependencies into account, and it has been unclear how strongly they influence perceptual decisions. We hypothesize that one reason for this neglect is that there has been no reliable tool to quantify them and to correct for their effects. Here we develop a statistical method to detect, estimate, and correct for serial dependencies in behavioral data. We show that even trained psychophysical observers suffer from strong history dependence. A substantial fraction of the decision variance on difficult stimuli was independent of the stimulus but dependent on experimental history. We discuss the strong dependence of perceptual decisions on internal factors and its implications for correct data interpretation.
(Show Context)

Citation Context

...ging measurements (e.g., Soon, Brass, Heinze, & Haynes, 2008); thus, although the absolute numbers seem low, they could potentially be big enough to lead to confounds in the analysis of imaging data (=-=Lages & Jaworska, 2012-=-). As expected, performance on easy stimuli was largely driven by the stimulus, and previous trials explained only 1.4% 6 0.3% of the variance of the decision variable and predicted choices at 52.7% 6...

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University