FENS Poster: Increased influence of low-level stimulus features on fixations in neglect patients

SFN 2013: Investigation of Fear Generalization with fMRI Using Multivariate Pattern Similarity Analysis

Investigation of Fear Generalization with fMRI Using Multivariate Pattern Similarity Analysis

Onat S., Büchel C.
Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf

Generalization of aversive events to previously neutral events relates to problems in anxiety regulation. This is generally investigated by using simplified stimuli that are parametrically modified to span a similarity space with respect to the aversive event and measuring the tuning width of autonomic responses. However on the neuronal level our knowledge about which brain regions underpin this generalization is scarce. Multivariate pattern analysis of BOLD responses offer a valuable tool to investigate brain regions which are responsible in controlling the fear generalization.

We investigated fear generalization using faces as ecologically relevant stimuli using an event-related fMRI design using healthy humans. These stimuli were organized along a circular similarity continuum and two opposing faces were randomly selected as the aversive and neutral face for each participant. Autonomic measures of anxiety such as skin conductance and pupil size showed a gradual decrease in amplitude with increasing distance to the aversive face. These fear tuning profiles were well-captured with a circular Gaussian function that showed a large natural variability in the width of the generalization profiles across participants.

Using multi-variate similarity analysis at the single subject level, we evaluated which brain regions exhibited a similarity gradient with respect to the neuronal activity patterns evoked by the aversive face. In cingulate cortex, putamen, insular cortex and frontal regions, including medial frontal and orbito-frontal cortex, the similarity of neuronal activity patterns decayed with increasing distance from the aversive face and reached lowest values for the neutral face.

Our current results extend our current knowledge about fear generalization and most importantly provide new tools to investigate neuronal sites that are responsible for anxiety regulation.

During the Experiment

The participant is being recorded in the scanner while this movie is taken.

The movie starts with a view on the monitor of the Eyelink 2000 stimulus-computer that shows the current stimuli presented to the subject being scanned, together with his eye position depicted as a bluish circle moving from mouth toward between the eyes. At some point later one can see the eye of the participant with the detected pupil and Purkinje images. 

The second view is on the physio-computer that records breathing, pulse-oxymeter, and the skin conductance data. The physio-data is AD converted using CED system, it all runs with Spike2 software. Skin-conductance recordings are carried out with a BioPac system. The TRIO scanner is also connected directly to the CED system to record the start of each volume acquisition.

In the next few seconds, there is a glimpse on the CED rack that is used to A/D convert the data. The Digitimer current generator that is connected to the participant's hand via an electrode for Pavlovian conditioning is unfortunately not seen.

The third view is on the stimulus computer that presents images to the participant. Stimuli are presented using Matlab and Psychophysics Toolbox. The connection between Matlab and the Eyelink system is done via Eyelink Toolbox through an ethernet connection. Matlab is also connected to the CED system to store the onset of the relevant events as sequences of pulses together with the pulses of the scanner.

Last few shots wander around control desk showing some basic brain slices and the volunteer lying in the magnet on a background of noisy people.


Real-time recurrent image editing modulated by sound amplitude

kinect camera to control stop-motion video flow

In this post I would like to explore embodied ways on how one could interact with a visual stream. More specifically, this is about controlling the flow of a video stream with one own's body movements.

The system I am using is based on Microsoft's Kinect camera. On the computer side I am using the Quartz Composer to connect different streams of information on the one side body related parameters and on the other parameters related to the video stream.

In the following video, I am showing a simple situation where the movie is controlled by vertical movements of my hand.

Kinect controlled video playing from sonat on Vimeo.

Testing Stimulus Presentation Program using Emulated Scanner Pulses

If you fancy Psychophysics toolbox to present stimuli during an fMRI experiment, you will need to know exactly at which time point the volume acquisition occurs with respect to important events of the experiment, such as for example stimulus onsets. 

Scanners usually send pulses and these are needed to be recorded by the stimulus computer in order to solve this problem. In the specific setup I am using, these pulses are collected in a circuit, called cogent-box, and accumulated. This cumulated count is sent to the serial port of the stimulus computer in the form of 2 bytes. The stimulus program can now correctly time events from different sources e.g. stimulus onsets and the start of volume acquisitions.

The downside is generally that one would need to go to the scanner's console room and run few dummy experiments with the scanner until the presentation code is devoid of any bugs.

However, it would be much nicer to test the stimulus presentation program in the office without the need of having a scanner sending pulses. Therefore some labs have a mobile version of the cogent box with the aim of testing your presentation program without the need of having a scanner to send pulses. But even then, today many modern computers do not have serial ports, making impossible the use such mobile boxes. 

A software solution can circumvent many of the problems associate to a mobile box. In a modern computer, one may create any arbitrary number of virtual ports (Serial or Parallel), read and write data to and from these ports. There are softwares that let you specify any number of virtual ports easily, for example "Virtual Serial Port Deriver". 

Once you have this software you can create a pair of virtual serial port, say COM1 and COM2. You can fire the Matlab, use COM2  and write information in the form of two bytes (to emulate what the cogent-box would be doing in response to pulses received from the scanner at each TR). These two bytes imitates the situation where the cogent-box is counting the number of volumes that have been so far acquired. In another instance of Matlab, running in parallel to the first one, you can set COM1 and read data from it. This will be analogous to the situation you are in the scanner room, without the need of a mobile cogent box or a scanner.

The following psychophysics toolbox function can be used to send pulses.

function SendPulses(N,TR)
%function SendPulses(N)
%Sends N pulses to COM2 serial port. TR is the interpulse TR (that is
%the "TR").
%Selim Onat, 24-Jan-2013 10:55:53

box.port = IOPort('OpenSerialPort', 'COM2');
counter  = 0;
t        = GetSecs;%now
t        = t:TR:t+TR*N;%time of the future pulses
for n = 1:N
    tobesent = [floor(n./255) n];%two byte to be sent
    WaitSecs('untiltime',t(n));%wait and fire.
    [~,t_]=IOPort( 'Write' , box.port , [char(tobesent(1))+1,char(tobesent(2))]);
    counter = counter +1;
    fprintf('Pulse No: %3d sent at %0.10g was due to at %0.10g\n',counter,t_,t(n));
    drawnow%give some time for Control-C