@lim_onat

Representation of Simple Stimuli across the Visual Cortex

Moving edges, which consist of drifting dark and bright bars, are kind of stimuli that are commonly used in physiological experiments mainly because of their parametrically controllable aspects.

The video below shows the large-scale cortical dynamics at the spatial scale of several millimeters during presentation of such visual stimuli.

Overlaid on the well-known orientation maps (shown at the bottom row), which are evoked by the specific orientation of the stimuli, drifting edges are furthermore represented by propagating waves (top row). The original publication can be found here.

NeuroImage from sonat on Vimeo.

Caption: Multiplexing of space and orientation information. The data presented in Fig. 1 and 2 is presented as a video. Upper video: Propagating activity reconstructed by combining oscillatory SVD components, averaged across several propagation cycles during stimulus presentation (cf. Fig. 3 and Fig. 4a). M = Medial, P = Posterior. Lower video: Propagating waves are shown in combination with tonic SVD components representing the orientation maps. The weight of both components were equalized prior to their combination. Contour lines are drawn at 90th activity percentiles of the tonic components.

Decomposition of evoked cortical responses to gratings of 0.2 c/deg drifting for 2 s at a temporal frequency of 6.25 Hz. (a) Evoked spatio-temporal activity patterns (top rows) and time courses obtained by spatial averages across the images (bottom traces) expressed as fractional change in fluorescence relative to blank condition (ΔF/F). Top left frame shows the vascular image of the recorded right hemisphere, P = posterior, L = lateral; here and in all figures scale bar 1 mm. Leftmost frame in 2nd row depicts the time-averaged orientation map derived by subtracting evoked responses to the vertical grating from horizontal. Green trace = responses to vertical grating, drifting rightwards in visual space; blue trace = horizontal grating, drifting downwards. (b) Top left corner, singular values, gi, ranked in order of their contributions. Components of significant contribution to variance are colored (gray area depicts significance level). The contribution of each single SVD component to single recorded trials (n=35) was computed, their correlations across trials are represented as a matrix. Spatial (ui(x)) and temporal (vi(t)) modes of the SVD components were clustered according to their correlation (red, yellow, and green boxes; curves represent weight of each spatial mode [y-axes] as a function of time [400–1800 ms]).

PhD Thesis, Presentation, Latex Template

I recently defended my thesis. I am uploading my presentation with idea that somebody might find it useful and get some inspiration.

The pdf file can be found here here.

If you like the layout of this thesis, you may find it useful to download the latex template that is used to generate it from here.

I share this with the idea that anyone who would like to start writing their theses, could easily use this template to start up producing, rather than wasting time to optimize the look of the final thesis. It might take considerable time until everything appears reasonably good.

The good starting point is the PhDThesis_Selim.tex file, where all the subsequent chapters (in the form of .tex files) are referred and included. The figures are not included in the zip package therefore if you compile PhDThesis_Selim.tex file it will not succeed.

Singing Gabors: Visual stimulus locking of EEG is modulated by temporal congruency of auditory stimuli

In this study, we used what we called back then the "Singing Gabors".

These consist of Gabor functions, where one of the parameters (here orientation parameter) is modulated either in a congruent or incongruent way with the audio signal.

Guess which of the following videos is the congruent one:

In the congruent case, the audio signal's frequency changes simultaneously with the orientation of the Gabor. This leads (in my case) to a vivid illusion of agency, meaning that I perceive the animated Gabor function as if it was producing the sound itself (the paper deals with much simpler questions though).

In the incongruent case, the audio signal is orthogonal to the changes in the orientation parameter of the Gabor function. Still it is interesting to realize how human perception is biased for fusing these two as if they were congruent.