Support provided by the University of Alabama at Birmingham Faculty Development Grant Program.

1. Psychophysiology
The Biopac Systems, Inc. physiological monitoring system (see Table of specific equipment) is non-standard equipment in most imaging facilities. Schedule 15-30 minutes prior to participant arrival to set up physiological monitoring and other equipment described in this protocol (Figure 1).
<ol>
<li>Connect a control room computer operating AcqKnowledge (Biopac Systems, Inc.) physiological monitoring software to the Biopac MP150 (MP150WSW) using a standard Ethernet crossover cable (CBLETH2).</li>
<li>Connect the Biopac Isolated Digital Interface (STP100C) to a control room computer operating Presentation (Neurobehavioral Systems, Inc; Albany, CA) software using a DB25 M/F ribbon cable.</li>
<li>Connect the Biopac GSR amplifier (EDA-100C-MRI) to the RF interference filter (MRIRFIF) within the control room using a shielded extension cable (MECMRI-3).</li>
<li>Connect the RF interference filter (MRIRFIF) to a shielded extension cable (MECMRI-1) within the MRI scanning chamber.</li>
<li>Connect the shielded extension cable to carbon fiber lead wires (LEAD 108) that attach to radio translucent electrodes (EL508). Note: Twisting the leads in a tight spiral reduces artifacts in the skin conductance data that can be created during scanning.</li>
<li>Attach radio translucent electrodes (EL508) to the distal phalanx of the middle and ring fingers of the participant's left hand.</li>
<li>Due to the nature of scanning equipment, MRI chamber room temperatures are often set below 21&deg;C. Cover the participant with a blanket to maintain hand temperature.</li>
</ol>
2. Behavioral Responses (Joystick) 
<ol>
 <li>Connect a control room computer operating Presentation software (Neurobehavioral Systems, Inc; Albany, CA) to the joystick's fORP Interface Unit (Current Designs, Inc; Philadelphia, PA) using a USB-mini cable.</li>
 <li>Connect a fiber optic cable to the fORP Interface Unit within the control room, then pass the cable through a wave guide into the MRI chamber.</li>
 <li>Connect the fiber optic cable to the MR-compatible joystick.</li>
 <li>Direct participants to place the joystick in a comfortable and easy to reach position.</li>
</ol>
3. Stimulus Presentation
<ol>
<li>Connect a control room computer operating Presentation software to the external VGA and audio ports of the IFIS-SA (Invivo Corp., Orlando, FL) control room console (Figure 1).</li>
<li>Check the fiber optic cable connections between the IFIS control room console and the IFIS Peripheral Interface Unit within the MRI chamber, as well as the connections between the Peripheral Interface Unit and the Audio/Visual Display Unit.</li>
<li>Place the Audio/Visual Display Unit behind the head-coil such that the participant can view the monitor through a mirror attached to the head-coil. </li>
<li>Connect the Audio/Visual Display Unit's acoustic interface box to the IFIS system's MR-compatible stereo headphones using vinyl tubing.</li>
<li>Calibrate the volume of auditory stimuli using a sound pressure level meter.</li>
</ol>
4. Experimental Procedure 
<ol>
<li> Inform participants that 2 tones will be presented several times during the study, and that the volume of the tones will vary above and below their perceptual threshold (Figure 2).</li>
<li> Direct participants to push a button on the joystick box immediately upon hearing either tone, then to update their expectation of receiving the UCS by moving the joystick to control the position of a rating bar on a 0 to 100 scale (Figure 3). </li>
<li> Instruct participants to rate their UCS expectancy on a continuous scale from 0 to 100. Inform them that ratings of 0 indicate they are certain the UCS will not be presented, ratings of 50 indicate they are uncertain whether the UCS will be presented, and ratings of 100 indicate they are certain the UCS will be presented. Direct participants to use other values on the scale to indicate intermediate expectations. Then, allow participants to practice using the joystick to make ratings.</li>
<li> Expose participants to a differential fear conditioning procedure using 2 tones (700 &amp; 1300 Hz; 10s duration; 20s ITI) as the conditioned stimuli (CS) and a loud white-noise (100dB, 500ms) as the UCS. </li>
<li>Present 60 trials of the CS+ (coterminating with the UCS) and 60 trials of the CS- (presented without the UCS) in a pseudorandom order such that no more than 2 trials of the same CS are presented consecutively. </li>
<li>Counterbalance the tones that serve as the CS+ and CS- across participants. </li>
<li>Modulate the volume of the CS+ and CS- independently. Adjust CS volume on the subsequent trial with the same CS. Decrease CS volume 5dB if a button press is made (i.e. following a perceived trial). Increase the volume 5dB if a button press is not made (i.e. following an unperceived trial). </li>
</ol>
5. Scanning Procedure 
<ol>
<li>Collect standard high resolution T1-weighted structural images (e.g. MPRAGE) to serve as an anatomical reference for functional data.</li>
<li>Collect BOLD fMRI of the whole brain during the conditioning procedure. Thirty six, 4mm thick slices should be sufficient to cover the brain with relatively standard imaging parameters (e.g. TR = 2000ms, TE = 30ms, FOV = 24cm, 64x64 matrix). Synchronize the fMRI acquisition with stimulus presentation using an fMRI trigger box.</li>
</ol>
6. SCR Data Acquisition &amp; Analysis
<ol>
<li>Sample skin conductance at 2,000 Hz using AcqKnowledge software and the MR-compatible Biopac physiological monitoring system described in section 1. </li>
<li> Apply a 1 Hz Infinite Impulse Response (IIR) low pass digital filter to the skin conductance data to reduce artifacts produced during imaging (see Figure 4).</li>
<li>Resample the skin conductance data at 250 Hz. </li>
<li>Calculate SCR as the difference in skin conductance level from response onset to response peak.</li>
<li>SCR data can be square root transformed to normalize the distribution of response amplitudes prior to statistical analysis. </li>
</ol>
7. UCS Expectancy Data Acquisition &amp; Analysis
<ol>
<li>Sample (40 Hz) and record UCS expectancy data using Presentation software.</li>
<li>Calculate UCS expectancy as the average (1s sample) response during the last second of CS presentation.</li>
</ol>
8. Functional MRI Data Acquisition &amp; Analysis
<ol>
 <li>Complete standard preprocessing of brain imaging data (e.g. slice timing correction, image registration, spatial smoothing) using a functional imaging analysis software package (e.g. AFNI 18).</li>
 <li> Create standard nuisance (e.g. motion) and stimulus-based regressors for perceived and unperceived trials of the CS+ and CS-, as well as the UCS.</li>
 <li> Create a motor response-based reference waveform to serve as a nuisance regressor to account for motor activity related to button press responses.
 <ol class="lalpha">
 <li>Create a stick function that codes for the timing of button press responses.</li>
 <li>Convolve the button press stick function with the canonical hemodynamic response function (HRF).</li>
</ol>
</li>
 <li>Create motor response-based reference waveform to serve as a nuisance regressor to account for motor activity related to joystick responses.
<ol class="lalpha">
 <li>Create a stick function that codes for the timing of changes in the slope (e.g. slope absolute value &gt; 10) of UCS expectancy ratings.</li>
 <li>Convolve the joystick slope stick function with the canonical HRF.</li>
</ol>
</li>
 <li>Perform first level analyses using all stimulus-based and nuisance regressors.</li>
 <li>Perform a second level repeated measures ANOVA to identify regions in which activation shows a main effect of CS type, a main effect of perception, or a CS type X perception interaction.</li>
</ol>
9. Representative Results:
The methodology presented here typically results in relatively high UCS expectancy ratings during perceived CS+ trials and low ratings during perceived CS- trials (Figure 5) 10,15,19. Such results indicate participants are aware of CS-UCS contingencies. On unperceived trials, UCS expectancy ratings typically remain unchanged from pre-CS ratings. UCS expectancies on these unperceived CS+ and CS- trials typically fall near 50 indicating participants are unsure of whether the UCS will be presented 10,15,19 (Figure 5). This inability to produce differential UCS expectancy ratings to the unperceived CS+ and CS- indicates that participants are unable to express their contingency awareness on unperceived conditioning trials (Figure 6). In contrast, learning-related changes in SCR have been observed during both perceived and unperceived conditioning trials 10,15,19. Specifically, SCRs were larger to the perceived CS+ than to the perceived CS-. Similarly, larger SCRs have been demonstrated during unperceived CS+ than unperceived CS- trials 10,15,19 (Figure 6). Taken together, these behavioral and autonomic data demonstrate fear conditioning with contingency awareness on perceived trials, and fear conditioning without contingency awareness on unperceived trials. The functional imaging research using this methodology has demonstrated learning-related hippocampal activation on perceived, but not unperceived conditioning trials15 (Figure 7). In contrast, differential amygdala activity was observed on both perceived and unperceived conditioning trials 15. These findings are consistent with the view that the hippocampus supports processes related to contingency awareness, while the amygdala supports CR expression with and without awareness.

<img src="/files/ftp_upload/3083/3083fig1.jpg" alt="Figure 1"/> 
Figure 1. Diagram of basic equipment for stimulus presentation and behavioral/psychophysiological response monitoring. Presentation software is used to present audio-visual stimuli and monitor UCS expectancy ratings made by moving a joystick with the right hand. AcqKnowledge software and Biopac equipment are used to monitor skin conductance from the left hand. Solid (Biopac), single dashed (IFIS Audio-Visual), and double dashed lines (Fiber optic joystick) depict cables for distinct stimulus presentation and response monitoring systems. Black arrows indicate direction of information flow. 
<img src="/files/ftp_upload/3083/3083fig2.jpg" alt="Figure 2"/> 
Figure 2. Conditioned Stimuli. Present the CS+ and CS- in a pseudorandom order such that no more than 2 trials of the same CS are presented consecutively. Vary the volume of the CS+ and CS- independently. If a CS is perceived (indicated by a button press), decrease CS volume 5dB on the subsequent trial of the same CS. If a CS is unperceived (indicated by no button press), raise CS volume 5db on the subsequent trial with the same CS. 
<img src="/files/ftp_upload/3083/3083fig3.jpg" alt="Figure 3"/> 
Figure 3. UCS expectancy rating scale. Instruct participants to rate their expectation of UCS presentation on a 0 to 100 scale. Ratings of 0 indicate certainty the UCS will not be presented, ratings of 100 indicate certainty the UCS will be presented, and ratings of 50 reflect uncertainty as to whether the UCS will be presented. Intermediate ratings should be used to indicate gradations in UCS expectancy.
<img src="/files/ftp_upload/3083/3083fig4.jpg" alt="Figure 4"/> 
Figure 4. Comparison of raw and filtered skin conductance data. a) Raw skin conductance data collected during fMRI. b) Skin conductance data after application of a 1Hz IIR low pass filter.
<img src="/files/ftp_upload/3083/3083fig5.jpg" alt="Figure 5"/> 
Figure 5. UCS expectancy ratings. -Participants typically report high UCS expectancies on perceived CS+ trials and low expectancies on perceived CS- trials. UCS expectancies on unperceived CS+ and CS- trials do not differ.
<img src="/files/ftp_upload/3083/3083fig6.jpg" alt="Figure 6"/> 
Figure 6. UCS expectancy and SCR. Differences in UCS expectancy are typically observed on perceived CS+ and CS- trials indicating participants are aware of the stimulus contingencies. On unperceived trials, UCS expectancy ratings typically do not differ indicating participants are unable to express their contingency awareness. In contrast, differences in conditioned SCRs are usually observed on both perceived and unperceived conditioning trials. Such findings reflect learned fear expression with (i.e. on perceived trials) and without (i.e. on unperceived trials) contingency awareness.
<img src="/files/ftp_upload/3083/3083fig7.jpg" alt="Figure 7"/> 
Figure 7. Functional MRI of the hippocampus and amygdala. Hippocampal responses are typically larger to the CS+ than CS- on perceived, but not unperceived conditioning trials. Differential amygdala responses are typically observed on both perceived and unperceived conditioning trials. These findings are consistent with the view that the hippocampus supports processes related to contingency awareness, while the amygdala supports fear expression with and without awareness.

<ol>
	<li>LaBar, K. S., Gatenby, J. C., Gore, J. C., LeDoux, J. E., Phelps, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+amygdala+activation+during+conditioned+fear+acquisition+and+extinction:+a+mixed-trial+fMRI+study.">Human amygdala activation during conditioned fear acquisition and extinction: a mixed-trial fMRI study.</a> Neuron. 20, 937-945 (1998).</li><li>Buchel, C., Morris, J., Dolan, R. J., Friston, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brain+systems+mediating+aversive+conditioning:+an+event-related+fMRI+study.">Brain systems mediating aversive conditioning: an event-related fMRI study.</a> Neuron. 20, 947-957 (1998).</li><li>Cheng, D. T., Knight, D. C., Smith, C. N., Stein, E. A., Helmstetter, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+MRI+of+human+amygdala+activity+during+Pavlovian+fear+conditioning:+stimulus+processing+versus+response+expression.">Functional MRI of human amygdala activity during Pavlovian fear conditioning: stimulus processing versus response expression.</a> Behav. Neurosci. 117, 3-10 (2003).</li><li>Knight, D. C., Smith, C. N., Stein, E. A., Helmstetter, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+MRI+of+human+Pavlovian+fear+conditioning:+patterns+of+activation+as+a+function+of+learning.">Functional MRI of human Pavlovian fear conditioning: patterns of activation as a function of learning.</a> Neuroreport. 10, 3665-3670 (1999).</li><li>Cheng, D. T., Knight, D. C., Smith, C. N., Helmstetter, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+amygdala+activity+during+the+expression+of+fear+responses.">Human amygdala activity during the expression of fear responses.</a> Behav. Neurosci. 120, 1187-1195 (2006).</li><li>Balderston, N. L., Helmstetter, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Conditioning+with+masked+stimuli+affects+the+timecourse+of+skin+conductance+responses.">Conditioning with masked stimuli affects the timecourse of skin conductance responses.</a> Behav. Neurosci. 124, 478-489 (2010).</li><li>Esteves, F., Parra, C., Dimberg, U., Ohman, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nonconscious+associative+learning:+Pavlovian+conditioning+of+skin+conductance+responses+to+masked+fear-relevant+facial+stimuli.">Nonconscious associative learning: Pavlovian conditioning of skin conductance responses to masked fear-relevant facial stimuli.</a> Psychophysiology. 31, 375-385 (1994).</li><li>Cheng, D. T., Richards, J., Helmstetter, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Activity+in+the+human+amygdala+corresponds+to+early,+rather+than+late+period+autonomic+responses+to+a+signal+for+shock.">Activity in the human amygdala corresponds to early, rather than late period autonomic responses to a signal for shock.</a> Learn. Mem. 14, 485-490 (2007).</li><li>Knight, D. C., Nguyen, H. T., Bandettini, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+the+human+amygdala+in+the+production+of+conditioned+fear+responses.">The role of the human amygdala in the production of conditioned fear responses.</a> Neuroimage. 26, 1193-1200 (2005).</li><li>Knight, D. C., Nguyen, H. T., Bandettini, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+awareness+in+delay+and+trace+fear+conditioning+in+humans.">The role of awareness in delay and trace fear conditioning in humans.</a> Cogn. Affect. Behav. Neurosci. 6, 157-162 (2006).</li><li>Schultz, D. H., Helmstetter, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Classical+conditioning+of+autonomic+fear+responses+is+independent+of+contingency+awareness.">Classical conditioning of autonomic fear responses is independent of contingency awareness.</a> J. Exp. Psychol. Anim. Behav. Process. 36, 495-500 (2010).</li><li>Dunsmoor, J. E., Bandettini, P. A., Knight, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+correlates+of+unconditioned+response+diminution+during+Pavlovian+conditioning.">Neural correlates of unconditioned response diminution during Pavlovian conditioning.</a> Neuroimage. 40, 811-817 (2008).</li><li>Katkin, E. S., Wiens, S., Ohman, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nonconscious+fear+conditioning,+visceral+perception,+and+the+development+of+gut+feelings.">Nonconscious fear conditioning, visceral perception, and the development of gut feelings.</a> Psychol. Sci. 12, 366-370 (2001).</li><li>Knight, D. C., Waters, N. S., King, M. K., Bandettini, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Learning-related+diminution+of+unconditioned+SCR+and+fMRI+signal+responses.">Learning-related diminution of unconditioned SCR and fMRI signal responses.</a> Neuroimage. 49, 843-848 (2010).</li><li>Knight, D. C., Waters, N. S., Bandettini, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+substrates+of+explicit+and+implicit+fear+memory.">Neural substrates of explicit and implicit fear memory.</a> Neuroimage. 45, 208-214 (2009).</li><li>Lovibond, P. F., Shanks, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+awareness+in+Pavlovian+conditioning:+empirical+evidence+and+theoretical+implications.">The role of awareness in Pavlovian conditioning: empirical evidence and theoretical implications.</a> J. Exp. Psychol. Anim. Behav. Process. 28, 3-26 (2002).</li><li>Hippocampus, . <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> 8, 620-626 (1998).</li><li>Cox, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=AFNI:+software+for+analysis+and+visualization+of+functional+magnetic+resonance+neuroimages.">AFNI: software for analysis and visualization of functional magnetic resonance neuroimages.</a> Comput. Biomed. Res. 29, 162-173 (1996).</li><li>Knight, D. C., Nguyen, H. T., Bandettini, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expression+of+conditional+fear+with+and+without+awareness.">Expression of conditional fear with and without awareness.</a> Proc. Natl. Acad. Sci. U. S. A. 100, 15280-15283 (2003).</li><li>Bunce, S. C., Bernat, E., Wong, P. S., Shevrin, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Further+evidence+for+unconscious+learning:+preliminary+support+for+the+conditioning+of+facial+EMG+to+subliminal+stimuli.">Further evidence for unconscious learning: preliminary support for the conditioning of facial EMG to subliminal stimuli.</a> J. Psychiatr. Res. 33, 341-347 (1999).</li><li>Kotze, H. F., Moller, A. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+auditory+subliminal+stimulation+on+GSR.">Effect of auditory subliminal stimulation on GSR.</a> Psychol. Rep. 67, 931-934 (1990).</li><li>Miller, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Threshold+variability+in+subliminal+perception+experiments:+fixed+threshold+estimates+reduce+power+to+detect+subliminal+effects.">Threshold variability in subliminal perception experiments: fixed threshold estimates reduce power to detect subliminal effects.</a> J. Exp. Psychol. Hum. Percept. Perform. 17, 841-851 (1991).</li><li>Tabbert, K., Stark, R., Kirsch, P., Vaitl, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dissociation+of+neural+responses+and+skin+conductance+reactions+during+fear+conditioning+with+and+without+awareness+of+stimulus+contingencies.">Dissociation of neural responses and skin conductance reactions during fear conditioning with and without awareness of stimulus contingencies.</a> Neuroimage. 32, 761-770 (2006).</li></ol>

No conflicts of interest declared.

The fear conditioning methodology described here provides a means to investigate the neural mechanisms of aware and unaware fear memory processes. This method takes advantage of the simultaneous monitoring of behavioral, autonomic, and fMRI data. Monitoring behavioral (i.e. UCS expectancy) and autonomic responses (i.e. SCR) is a critical component of this method. UCS expectancy provides a means to assess contingency awareness, while SCR provides an index of CR expression. Together, these behavioral and autonomic response...

<table border="1">
<tbody>
 <tr>
 <td>Equipment</td>
 <td>Company</td>
 <td>Item number</td>
 </tr>
 <tr>
 <td>Integrated Functional Imaging System (IFIS-SA)</td>
 <td>Invivo Corp., Orlando, FL</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Master Control Unit (located in the control room) 
 Peripheral Interface Unit (located in the MRI chamber) 
 Audio/Visual Display Unit (located in the MRI chamber), includes:
 <ul>
 <li>6.4" (diagonal) LCD video screen <ul>
 <li>640 x 480 resolution and 15&deg; field of view</li></ul></li>
 <li>acoustic interface box<ul>
 <li>delivers pneumatic sound in stereo</li></ul></li>
 <li>MR-compatible stereo headphones </li>
 </ul></td>
 <td>&nbsp;</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>PHYSIOLOGICAL MONITORING SYSTEM</td>
 <td>Biopac Systems, Inc., Goleta, CA</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Data Acquisition and Analysis System for Windows (MP150) 
 Isolated Digital Interface (Digital Interface) 
 Galvanic Skin Response (GSR) Amplifier 
 MRI Cable/Filter System to Transducer Amplifier set, includes: 
 <ul>
 <li>MRI extension cable (Chamber to filter)</li>
 <li>RF interference filter </li>
 <li>MRI extension Cable (GSR amplifier to filter)</li>
 </ul>
 Additional components: 
 DB25 M/F ribbon cable 
 Disposable radiotranslucent electrodes 
 Carbon fiber leads</td>
 <td>&nbsp;</td>
 <td valign="top">MP150WSW 
 STP100C 
 EDA100C-MRI 
 MECMRI-TRANS 
 - MECMRI-1 
 - MRIRFIF 
 - MECMRI-3 
 CBL110C 
 EL508 
 LEAD108
 </td>
 </tr>
 <tr>
 <td>JOYSTICK</td>
 <td>Current Designs, Inc., Philadelphia, PA</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Legacy Joystick</td>
 <td>&nbsp;</td>
 <td>HH-JOY-4</td>
 </tr>
 <tr>
 <td>Legacy fORP Interface</td>
 <td>&nbsp;</td>
 <td>FIU-005</td>
 </tr>
 </tbody>
</table>

investigating the neural mechanisms of aware and unaware fear memory with fmri

Pavlovian fear conditioning is often used in combination with functional magnetic resonance imaging (fMRI) in humans to investigate the neural substrates of associative learning 1-5. In these studies, it is important to provide behavioral evidence of conditioning to verify that differences in brain activity are learning-related and correlated with human behavior. 
Fear conditioning studies often monitor autonomic responses (e.g. skin conductance response; SCR) as an index of learning and memory 6-8. In addition, other behavioral measures can provide valuable information about the learning process and/or other cognitive functions that influence conditioning. For example, the impact unconditioned stimulus (UCS) expectancies have on the expression of the conditioned response (CR) and unconditioned response (UCR) has been a topic of interest in several recent studies 9-14. SCR and UCS expectancy measures have recently been used in conjunction with fMRI to investigate the neural substrates of aware and unaware fear learning and memory processes 15. Although these cognitive processes can be evaluated to some degree following the conditioning session, post-conditioning assessments cannot measure expectations on a trial-to-trial basis and are susceptible to interference and forgetting, as well as other factors that may distort results 16,17 .
Monitoring autonomic and behavioral responses simultaneously with fMRI provides a mechanism by which the neural substrates that mediate complex relationships between cognitive processes and behavioral/autonomic responses can be assessed. However, monitoring autonomic and behavioral responses in the MRI environment poses a number of practical problems. Specifically, 1) standard behavioral and physiological monitoring equipment is constructed of ferrous material that cannot be safely used near the MRI scanner, 2) when this equipment is placed outside of the MRI scanning chamber, the cables projecting to the subject can carry RF noise that produces artifacts in brain images, 3) artifacts can be produced within the skin conductance signal by switching gradients during scanning, 4) the fMRI signal produced by the motor demands of behavioral responses may need to be distinguished from activity related to the cognitive processes of interest. Each of these issues can be resolved with modifications to the setup of physiological monitoring equipment and additional data analysis procedures. Here we present a methodology to simultaneously monitor autonomic and behavioral responses during fMRI, and demonstrate the use of these methods to investigate aware and unaware memory processes during fear conditioning.

Watch this Scientific Journal Video about Investigating the Neural Mechanisms of Aware and Unaware Fear Memory with fMRI at JoVE.com

Investigating the Neural Mechanisms of Aware and Unaware Fear Memory with fMRI

A methodology to investigate the neural mechanisms that support aware and unaware memory processes during fear conditioning is described. This method monitors blood oxygen level dependent (BOLD) functional magnetic resonance imaging, skin conductance response, and unconditioned stimulus expectancy during Pavlovian fear conditioning to assess the neural correlates of distinct memory processes.

Pavlovian fear conditioning is often used in combination with functional magnetic resonance imaging (fMRI) in humans to investigate the neural substrates ...

investigating-neural-mechanisms-aware-unaware-fear-memory-with

Research

JoVE Journal

Neuroscience

12.8K Views.  University of Alabama at Birmingham. A methodology to investigate the neural mechanisms that support aware and unaware memory processes during fear conditioning is described. This method monitors blood oxygen level dependent (BOLD) functional magnetic resonance imaging, skin conductance response, and unconditioned stimulus expectancy during Pavlovian fear conditioning to assess the neural correlates of distinct memory processes.

Video: Investigating the Neural Mechanisms of Aware and Unaware Fear Memory with fMRI

Simultaneous fMRI and Electrophysiology in the Rodent Brain

To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in which functional MRI data and in vivo intracortical recording can be performed simultaneously. The combination of MRI and electrical recording is technically challenging because the electrodes used for recording distort the MRI images and the MRI acquisition induces noise in the electrical recording. To minimize the mutual interference of the two modalities, glass microelectrodes were used rather than metal and a noise removal algorithm was implemented for the electrophysiology data. In our studies, two microelectrodes were separately implanted in bilateral primary somatosensory cortices (SI) of the rat and fixed in place. One coronal slice covering the electrode tips was selected for functional MRI. Electrode shafts and fixation positions were not included in the image slice to avoid imaging artifacts. The removed scalp was replaced with toothpaste to reduce susceptibility mismatch and prevent Gibbs ringing artifacts in the images. The artifact structure induced in the electrical recordings by the rapidly-switching magnetic fields during image acquisition was characterized by averaging all cycles of scans for each run. The noise structure during imaging was then subtracted from original recordings. The denoised time courses were then used for further analysis in combination with the fMRI data. As an example, the simultaneous acquisition was used to determine the relationship between spontaneous fMRI BOLD signals and band-limited intracortical electrical activity. Simultaneous fMRI and electrophysiological recording in the rodent will provide a platform for many exciting applications in neuroscience in addition to elucidating the relationship between the fMRI BOLD signal and neuronal activity.

We have developed a method for simultaneous functional magnetic resonance imaging and electrophysiological recording in the rodent brain, providing a platform for the investigation of the relationship between neural activity and the blood oxygenation level dependent (BOLD) MRI signal.

To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in ...

Extinction Training During the Reconsolidation Window Prevents Recovery of Fear

Fear is maladaptive when it persists long after circumstances have become safe. It is therefore crucial to develop an approach that persistently prevents the return of fear. Pavlovian fear-conditioning paradigms are commonly employed to create a controlled, novel fear association in the laboratory. After pairing an innocuous stimulus (conditioned stimulus, CS) with an aversive outcome (unconditioned stimulus, US) we can elicit a fear response (conditioned response, or CR) by presenting just the stimulus alone1,2 . Once fear is acquired, it can be diminished using extinction training, whereby the conditioned stimulus is repeatedly presented without the aversive outcome until fear is no longer expressed3. This inhibitory learning creates a new, safe representation for the CS, which competes for expression with the original fear memory4. Although extinction is effective at inhibiting fear, it is not permanent. Fear can spontaneously recover with the passage of time. Exposure to stress or returning to the context of initial learning can also cause fear to resurface3,4.
Our protocol addresses the transient nature of extinction by targeting the reconsolidation window to modify emotional memory in a more permanent manner. Ample evidence suggests that reactivating a consolidated memory returns it to a labile state, during which the memory is again susceptible to interference5-9. This window of opportunity appears to open shortly after reactivation and close approximately 6hrs later5,11,16, although this may vary depending on the strength and age of the memory15. By allowing new information to incorporate into the original memory trace, this memory may be updated as it reconsolidates10,11. Studies involving non-human animals have successfully blocked the expression of fear memory by introducing pharmacological manipulations within the reconsolidation window, however, most agents used are either toxic to humans or show equivocal effects when used in human studies12-14. Our protocol addresses these challenges by offering an effective, yet non-invasive, behavioral manipulation that is safe for humans.
By prompting fear memory retrieval prior to extinction, we essentially trigger the reconsolidation process, allowing new safety information (i.e., extinction) to be incorporated while the fear memory is still susceptible to interference. A recent study employing this behavioral manipulation in rats has successfully blocked fear memory using these temporal parameters11. Additional studies in humans have demonstrated that introducing new information after the retrieval of previously consolidated motor16, episodic17, or declarative18 memories leads to interference with the original memory trace14. We outline below a novel protocol used to block fear recovery in humans.

Conditioned fear can be diminished through an inhibitory process called extinction, but can resurface under conditions such as the passage of time or exposure to stress. Our protocol presents a novel way of preventing fear recovery by introducing extinction during the reconsolidation window (the re-storage phase of a reactivated memory).

Fear is maladaptive when it persists long after circumstances have become safe. It is therefore crucial to develop an approach that persistently prevents ...

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also propagation of suprathreshold spiking activity involves populations of neurons. Empirical studies addressing cortical function directly thus require recordings from populations of neurons with high resolution. Here we describe an optical method and a deconvolution algorithm to record neural activity from up to 100 neurons with single-cell and single-spike resolution. This method relies on detection of the transient increases in intracellular somatic calcium concentration associated with suprathreshold electrical spikes (action potentials) in cortical neurons. High temporal resolution of the optical recordings is achieved by a fast random-access scanning technique using acousto-optical deflectors (AODs)1. Two-photon excitation of the calcium-sensitive dye results in high spatial resolution in opaque brain tissue2. Reconstruction of spikes from the fluorescence calcium recordings is achieved by a maximum-likelihood method. Simultaneous electrophysiological and optical recordings indicate that our method reliably detects spikes (&gt;97% spike detection efficiency), has a low rate of false positive spike detection (&lt; 0.003 spikes/sec), and a high temporal precision (about 3 msec) 3. This optical method of spike detection can be used to record neural activity in vitro and in anesthetized animals in vivo3,4.

Understanding the function of the vertebrate central nervous system requires recordings from many neurons because cortical function arises on the level of populations of neurons. Here we describe an optical method to record suprathreshold neural activity with single-cell and single-spike resolution, dithered random-access scanning. This method records somatic fluorescence calcium signals from up to 100 neurons with high temporal resolution. A maximum-likelihood algorithm deconvolves the underlying suprathreshold neural activity from the somatic fluorescence calcium signals. This method reliably detects spikes with high detection efficiency and a low rate of false positives and can be used to study neural populations in vitro and in vivo.

Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also ...

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)1, 2 protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.

We describe a novel approach for simultaneous analysis of brain function and structure using magnetic resonance imaging (MRI). We assess brain structure with high-resolution diffusion-weighted imaging and white-matter fiber tractography. Unlike standard structural MRI, these techniques allow us to directly relate anatomical connectivity to functional properties of brain networks.

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when ...

Whole Cell Patch Clamp for Investigating the Mechanisms of Infrared Neural Stimulation

It has been demonstrated in recent years that pulsed, infrared laser light can be used to elicit electrical responses in neural tissue, independent of any further modification of the target tissue. Infrared neural stimulation has been reported in a variety of peripheral and sensory neural tissue in vivo, with particular interest shown in stimulation of neurons in the auditory nerve. However, while INS has been shown to work in these settings, the mechanism (or mechanisms) by which infrared light causes neural excitation is currently not well understood. The protocol presented here describes a whole cell patch clamp method designed to facilitate the investigation of infrared neural stimulation in cultured primary auditory neurons. By thoroughly characterizing the response of these cells to infrared laser illumination in vitro under controlled conditions, it may be possible to gain an improved understanding of the fundamental physical and biochemical processes underlying infrared neural stimulation.

Infrared nerve stimulation has been proposed as an alternative to electrical stimulation in a range of nerve types, including those associated with the auditory system. This protocol describes a patch clamp method for studying the mechanism of infrared nerve stimulation in a culture of primary auditory neurons.

It has been  demonstrated in recent years that pulsed, infrared laser light can be used to  elicit electrical responses in neural tissue, independent of ...

Optogenetic Perturbation of Neural Activity with Laser Illumination in Semi-intact Drosophila Larvae in Motion

Drosophila larval locomotion is a splendid model system in developmental and physiological neuroscience, by virtue of the genetic accessibility of the underlying neuronal components in the circuits1-6. Application of optogenetics7,8 in the larval neural circuit allows us to manipulate neuronal activity in spatially and temporally patterned ways9-13. Typically, specimens are broadly illuminated with a mercury lamp or LED, so specificity of the target neurons is controlled by binary gene expression systems such as the Gal4-UAS system14,15. In this work, to improve the spatial resolution to "sub-genetic resolution", we locally illuminated a subset of neurons in the ventral nerve cord using lasers implemented in a conventional confocal microscope. While monitoring the motion of the body wall of the semi-intact larvae, we interactively activated or inhibited neural activity with channelrhodopsin16,17 or halorhodopsin18-20, respectively. By spatially and temporally restricted illumination of the neural tissue, we can manipulate the activity of specific neurons in the circuit at a specific phase of behavior. This method is useful for studying the relationship between the activities of a local neural assembly in the ventral nerve cord and the spatiotemporal pattern of motor output.

Optogenetic Perturbation of Neural Activity with Laser Illumination in Semi-intact Drosophila Larvae in Motion

Here we describe a protocol for optogenetic manipulation of motoneuronal activity while monitoring changes in motor output (muscle contraction) in semi-intact Drosophila larvae using lasers within a conventional confocal microscope. This technique enables researchers to achieve local perturbation of neural activity in a few neuromeres to elucidate the dynamics of motor circuits.

Drosophila larval locomotion is a splendid model system in developmental and physiological neuroscience, by virtue of the genetic accessibility of the ...

Deep Brain Stimulation with Simultaneous fMRI in Rodents

In order to visualize the global and downstream neuronal responses to deep brain stimulation (DBS) at various targets, we have developed a protocol for using blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) to image rodents with simultaneous DBS. DBS fMRI presents a number of technical challenges, including accuracy of electrode implantation, MR artifacts created by the electrode, choice of anesthesia and paralytic to minimize any neuronal effects while simultaneously eliminating animal motion, and maintenance of physiological parameters, deviation from which can confound the BOLD signal.&#160;Our laboratory has developed a set of procedures that are capable of overcoming most of these possible issues. For electrical stimulation, a homemade tungsten bipolar microelectrode is used, inserted stereotactically at the stimulation site in the anesthetized subject. In preparation for imaging, rodents are fixed on a plastic headpiece and transferred to the magnet bore. For sedation and paralysis during scanning, a cocktail of dexmedetomidine and pancuronium is continuously infused, along with a minimal dose of isoflurane; this preparation minimizes the BOLD ceiling effect of volatile anesthetics. In this example experiment, stimulation of the subthalamic nucleus (STN) produces BOLD responses which are observed primarily in ipsilateral cortical regions, centered in motor cortex. Simultaneous DBS and fMRI allows the unambiguous modulation of neural circuits dependent on stimulation location and stimulation parameters, and permits observation of neuronal modulations free of regional bias. This technique may be used to explore the downstream effects of modulating neural circuitry at nearly any brain region, with implications for both experimental and clinical DBS.

This protocol describes a standard method for simultaneous functional magnetic resonance imaging and deep brain stimulation in the rodent. The combined use of these experimental tools allows for the exploration of global downstream activity in response to electrical stimulation at virtually any brain target.

In order to visualize the global and downstream neuronal responses to deep brain stimulation (DBS) at various targets, we have developed a protocol for ...

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain.

The ability to induce and/or control neural plasticity may be critical in future treatments for neurologic disorders and the recovery from brain injury. In this paper, we present a protocol on the use of neurofeedback training with functional magnetic resonance imaging to modulate human brain function.

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control ...

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network dynamics in neuronal cultures. In contrast with more traditional methods, such as patch-clamping, which can only record activity from a single cell, MEAs can record simultaneously from multiple sites in a network, without requiring the arduous task of placing each electrode individually. Moreover, numerous control and stimulation configurations can be easily applied within the same experimental setup, allowing for a broad range of dynamics to be explored. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Mouse neuronal cells cultured on MEAs display an increase in response following training induced by electrical stimulation. This protocol demonstrates how to culture neuronal cells on MEAs; successfully record from over 95% of the plated dishes; establish a protocol to train the networks to respond to patterns of stimulation; and sort, plot, and interpret the results from such experiments. The use of a proprietary system for stimulating and recording neuronal cultures is demonstrated. Software packages are also used to sort neuronal units. A custom-designed graphical user interface is used to visualize post-stimulus time histograms, inter-burst intervals, and burst duration, as well as to compare the cellular response to stimulation before and after a training protocol. Finally, representative results and future directions of this research effort are discussed.

Mouse neuronal cells cultured on multi-electrode arrays display an increase in response following electrical stimulation. This protocol demonstrates how to culture neurons, how to record activity, and how to establish a protocol to train the networks to respond to patterns of stimulation.

Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network ...

Simultaneous Recordings of Cortical Local Field Potentials, Electrocardiogram, Electromyogram, and Breathing Rhythm from a Freely Moving Rat

Monitoring the physiological dynamics of the brain and peripheral tissues is necessary for addressing a number of questions about how the brain controls body functions and internal organ rhythms when animals are exposed to emotional challenges and changes in their living environments. In general experiments, signals from different organs, such as the brain and the heart, are recorded by independent recording systems that require multiple recording devices and different procedures for processing the data files. This study describes a new method that can simultaneously monitor electrical biosignals, including tens of local field potentials in multiple brain regions, electrocardiograms that represent the cardiac rhythm, electromyograms that represent awake/sleep-related muscle contraction, and breathing signals, in a freely moving rat. The recording configuration of this method is based on a conventional micro-drive array for cortical local field potential recordings in which tens of electrodes are accommodated, and the signals obtained from these electrodes are integrated into a single electrical board mounted on the animal's head. Here, this recording system was improved so that signals from the peripheral organs are also transferred to an electrical interface board. In a single surgery, electrodes are first separately implanted into the appropriate body parts and the target brain areas. The open ends of all of these electrodes are then soldered to individual channels of the electrical board above the animal's head so that all of the signals can be integrated into the single electrical board. Connecting this board to a recording device allows for the collection of all of the signals into a single device, which reduces experimental costs and simplifies data processing, because all data can be handled in the same data file. This technique will aid the understanding of the neurophysiological correlates of the associations between central and peripheral organs.

This study introduces a method for the simultaneous recording of local field potentials in the brain, electrocardiograms, electromyograms, and breathing signals of a freely moving rat. This technique, which reduces experimental costs and simplifies data analysis, will contribute to the understanding of the interactions between the brain and peripheral organs.

Monitoring the physiological dynamics of the brain and peripheral tissues is necessary for addressing a number of questions about how the brain controls ...