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Nasiotis, K.

Publications and source records attributed to Nasiotis, K..

2 recordsLinked to original sources

Tracking the dynamics of perisaccadic visual signals with magnetoencephalography

Many brain functions are difficult to localize, as they involve distributed networks that reconfigure themselves on short timescales. One example is the integration of oculomotor and visual signals that occurs with each eye movement: The brain must combine motor signals about the eye displacement with retinal signals, to infer the structure of the surrounding environment. Our understanding of this process comes primarily from single-neuron recordings, which are limited in spatial extent, or fMRI measurements, which have poor temporal resolution. We have therefore studied visual processing during eye movements, using magnetoencephalography (MEG), which affords high spatiotemporal resolution. Human subjects performed a task in which they reported the orientation of a visual stimulus while executing a saccade. After removal of eye movement artifacts, time-frequency analysis revealed a signal that propagated in the beta-frequency band from parietal cortex to visual cortex. This signal had the characteristics of perisaccadic "remapping", a neural signature of the integration of oculomotor and visual signals. These results reveal a novel mechanism of visual perception and demonstrate that MEG can provide a useful window into distributed brain functions.

neuroscience↗

Integrated Open-Source Software for Multiscale Electrophysiology

The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results.\n\nHere, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

neuroscience↗