EEG and MEG Data Analysis in SPM8

Litvak, Vladimir; Mattout, Jérémie; Kiebel, Stefan J.; Phillips, Christophe; Henson, Richard N.; Kilner, James M.; Barnes, Gareth R.; Oostenveld, Robert; Daunizeau, Jean; Flandin, Guillaume; Penny, Will D.; Friston, Karl J.

doi:10.1155/2011/852961

Cited by 534 publications

(473 citation statements)

References 69 publications

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“…After epoching, the data were baseline-corrected relative to the 100-ms prespeech period and low-pass filtered below 40 Hz, and the EEG data were referenced to the average over all EEG sensors. Finally, the data were robust averaged across trials (68,69) to down-weight outlying samples, minimize non-phaselocked activity, and derive the evoked response. To remove any high-frequency components that were introduced to the data by the robust averaging procedure, low-pass filtering was repeated after averaging.…”

Section: Methodsmentioning

confidence: 99%

Perceptual learning of degraded speech by minimizing prediction error

Sohoglu

Davis

2016

Proc. Natl. Acad. Sci. U.S.A.

104

154

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Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single-and dualmechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learninginduced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech.perceptual learning | predictive coding | speech perception | magnetoencephalography | vocoded speech S uccessful perception in a dynamic and noisy environment critically depends on the brain's capacity to change how sensory input is processed based on past experience. Consider the way in which perception is enhanced by accurate prior knowledge or expectations. Sudden and dramatic changes in subjective experience can occur when a distorted and otherwise unrecognizable perceptual object is seen or heard after the object's identity is revealed (1-4). Such effects occur almost immediately; striking changes in perceptual outcomes occur over a timescale of seconds or less. However, not all effects of past experience emerge as rapidly as these effects of prior knowledge. With perceptual learning, practice in perceiving certain types of stimuli results in gradual and incremental improvements in perception that develop over a timescale of minutes or longer (Fig. 1A) (5, 6, 7). Critically, perceptual learning can generalize beyond the stimuli experienced during training, e.g., to visual forms presented in dif...

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Section: Methodsmentioning

confidence: 99%

Perceptual learning of degraded speech by minimizing prediction error

Sohoglu

Davis

2016

Proc. Natl. Acad. Sci. U.S.A.

104

154

View full text Add to dashboard Cite

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“…We then removed any DC offset by filtering with a time constant of 1 s. The resulting data were exported to MATLAB (MathWorks) for subsequent analysis using custom scripts and the FieldTrip (http:// www.ru.nl/neuroimaging/fieldtrip/) and SPM8 (http://www.fil.ion.ucl. ac.uk/spm/) toolboxes (Litvak et al, 2011;Oostenveld et al, 2011). The data were first epoched into trials, excluding trials with errors, and the average signal over all correct trials was removed from each individual trial to generate the induced response.…”

Section: Methodsmentioning

confidence: 99%

Beta Reactivity, Prospective Facilitation of Executive Processing, and Its Dependence on Dopaminergic Therapy in Parkinson's Disease

Oswal¹,

Litvak²,

Sauleau³

et al. 2012

Journal of Neuroscience

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Oscillatory activity in the beta frequency band has been shown to be modulated during the preparation and execution of voluntary movements at both cortical and subcortical levels. The exaggeration of beta activity in the basal ganglia of patients with Parkinson's disease has heightened interest in this phenomenon. However, the precise function, if any, subserved by modulations in beta activity remains unclear. Here we test the hypothesis that beta reactivity can be dissociated from processing of specific actions and can index the salience of cues with respect to future behavior in a way that might help prospectively prioritize resources. To this end we used an experimental paradigm designed to dissociate salient warning cues from processing of specific motor or cognitive actions. We recorded local field potential activity from the subthalamic nucleus of humans undergoing functional neurosurgery for the treatment of Parkinson's disease, while the same patients were on or off the dopamine prodrug levodopa. In this way we demonstrate that beta reactivity is indeed dependent on the salience of cues with respect to future motor and cognitive action and is promoted by dopamine. The loss of normal beta encoding of saliency may underlie some of the motor and cognitive features of basal ganglia disorders such as Parkinson's disease.

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“…In the current study, we used the software packages spm8 (www.fil.ion.ucl.ac.uk/spm/software/spm8/) and Fieldtrip (http://fieldtrip.fcdonders.nl) to generate a transfer matrix for EEG, a so-called lead-field matrix (LFM) to be used for the forward modeling of EEG data (Litvak et al, 2011). In a first step, we loaded the electrode positions of our 64-channel MR-compatible EEG cap (Easy Cap) from a standard file containing 97 positions of the International 10-20 system, subsequently deleting the positions not represented by our cap, resulting in 61 remaining positions (the remaining three channels were used for recording of electrocardiography required to correct the heartbeat-related artifacts in the EEG caused by the static field B0 field of the MR scanner and for Electrooculography).…”

Section: Fig 1 (A)mentioning

confidence: 99%

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

et al. 2013

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Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro-to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected-ideally functionally relevant-aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the modelbased simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept.

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EEG and MEG Data Analysis in SPM8

Cited by 534 publications

References 69 publications

Perceptual learning of degraded speech by minimizing prediction error

Perceptual learning of degraded speech by minimizing prediction error

Beta Reactivity, Prospective Facilitation of Executive Processing, and Its Dependence on Dopaminergic Therapy in Parkinson's Disease

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

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