<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03268694</url>
  </required_header>
  <id_info>
    <org_study_id>17-1301</org_study_id>
    <secondary_id>R21NS094988-01A1</secondary_id>
    <nct_id>NCT03268694</nct_id>
  </id_info>
  <brief_title>Investigation of Oscillations Underlying Human Cognitive and Affective Processing Using Intracranial EEG</brief_title>
  <official_title>Investigation of Oscillations Underlying Human Cognitive and Affective Processing Using Intracranial EEG</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of North Carolina, Chapel Hill</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>National Institute of Neurological Disorders and Stroke (NINDS)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
  </sponsors>
  <source>University of North Carolina, Chapel Hill</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Purpose: To investigate the electrophysiological correlates of human cognition and affective&#xD;
      processing. Participants: Drug-resistant epilepsy patients undergoing epilepsy surgery&#xD;
      cortical mapping with continuous electrocorticography (ECoG) with intracranial electrodes.&#xD;
      Procedures (methods): Participants will perform computer-based cognitive and affective&#xD;
      processing tasks during routine long-term monitoring. Intracranial EEG will be collected&#xD;
      during the task&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Oscillations in different frequency bands like theta, alpha, beta, gamma and high gamma are&#xD;
      thought to underlie processing of cognitive and emotional information. For example, theta (3&#xD;
      - 7 Hz) and alpha (8 - 12 Hz) oscillations are known to underlie working memory as well as&#xD;
      attentional processing. Theta oscillations are known to differentiate emotional and neutral&#xD;
      stimuli while gamma oscillations (30 - 50 Hz) are known to underlie rapid integration of&#xD;
      information. The fact that these oscillations are also disrupted in neuropsychiatric&#xD;
      disorders underline the importance of these oscillations.&#xD;
&#xD;
      A lot of our understanding of these oscillations come from non invasive methods in humans&#xD;
      like electroencephalography (EEG), magnetoencephalography (MEG) and invasive methods in&#xD;
      animal models. However, EEG and MEG measure oscillations that are generated by collective&#xD;
      firing of large cortical patches thereby losing spatial resolution. Also activity from deeper&#xD;
      structures like amygdala and hippocampus cannot be picked up in these modalities. Animal&#xD;
      models often suffer from the poor translation of behavior from animals to humans and vice&#xD;
      versa. Intracranial EEG or Electrocorticography (ECoG) helps overcome the drawbacks described&#xD;
      above.&#xD;
&#xD;
      Studies using ECoG have become widespread and have been helpful in elucidating the functional&#xD;
      roles of different brain regions in cognition and emotion. The investigators aim to utilize&#xD;
      these established procedures to study the role of oscillations recorded from different brain&#xD;
      regions in cognition and emotion.&#xD;
&#xD;
      Patients with medically refractory epilepsy undergo long-term invasive monitoring for&#xD;
      surgical resection planning. Electrodes are implanted subdurally over seizure focus to&#xD;
      identify seizure onset zone and patients are often in the epilepsy monitoring unit at the&#xD;
      Neuroscience hospital for approximately a week. During this period, intracranial EEG is&#xD;
      constantly acquired for clinical investigation. The investigators plan to recruit these&#xD;
      patients while they undergo long-term monitoring to leverage the rare access to direct brain&#xD;
      recordings and study the role of oscillations in cognitive and affective processing. Patients&#xD;
      who provide informed consent to participate in the study will perform computer based&#xD;
      cognitive and emotional processing tasks.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Terminated</overall_status>
  <why_stopped>
    Competition with other ongoing projects with this population.&#xD;
  </why_stopped>
  <start_date type="Actual">August 7, 2017</start_date>
  <completion_date type="Actual">July 29, 2018</completion_date>
  <primary_completion_date type="Actual">July 29, 2018</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Basic Science</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Intracranial EEG Spectra Power</measure>
    <time_frame>Intracranial EEG will be collected simultaneously when the participants perform the task. 1 Hour</time_frame>
    <description>Spectral analysis of electrophysiology data will be performed using multi-taper fft and wavelet transforms. The measures will be compared between different epochs within the tasks to determine what oscillations are modulated by the task. The correlation between the measures described above and the task performance will also be estimated.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Task Performance: Reaction Times</measure>
    <time_frame>1 Hour</time_frame>
    <description>For all the tasks described above, the time from when the response is prompted and when the response is obtained is collected as reaction time. Reaction time is measured in milliseconds.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Intracranial EEG Functional Connectivity Analysis</measure>
    <time_frame>Intracranial EEG will be collected simultaneously when the participants perform the task. 1 Hour</time_frame>
    <description>Functional connectivity between the different electrodes will be measured using phase locking value and Granger causality.</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">4</enrollment>
  <condition>Working Memory</condition>
  <condition>Emotions</condition>
  <arm_group>
    <arm_group_label>Cognitive and Emotion Processing Tasks</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>As a part of the clinical monitoring, intracranial EEG is continuously collected when the participant is at the Epilepsy Monitoring Unit at the UNC Neuroscience Hospital. We will use an FDA approved EEG amplifier/data acquisition system to collect the research data. Computer-based tasks will be presented through a laptop and task related timing information will be transmitted from the laptop to the data acquisition system. Computer-based tasks will include Working Memory task, Reward Learning Task and Facial Emotion Recognition Task</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Working Memory Task</intervention_name>
    <description>Sternberg Task Items, which can be visually presented alphabets, shapes or numbers or sound tones presented through speakers, will be presented to the participant. The participant will need to maintain the presented items in their memory and indicate, when a single probe item is presented, whether the probe item was present in the immediately preceding list by pressing a key on the keyboard.&#xD;
N-Back Task Items are presented continuously sequentially and participants are instructed to indicate whether items are repeated n items before by pressing a key on the keyboard. The task is divided into blocks of 0,1,2,3 -back trials based on the 'n'. For example in the 2 - back task, the participant has to indicate if the item presented 2 items before matches the current item. Similar to the previous task, the items can be presented visually or auditorily.</description>
    <arm_group_label>Cognitive and Emotion Processing Tasks</arm_group_label>
    <other_name>Sternberg Task</other_name>
    <other_name>N-Back Task</other_name>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Reward Learning Task</intervention_name>
    <description>Two abstract visual stimuli are presented on the screen and participant is asked to choose one. Unknown to the participant, each stimulus is associated with distinct probabilities of virtual reward such that one stimulus is associated with net gain while the other is associated with net loss. The participant's goal is to maximize the reward. Once the participant identifies the stimulus associated with net gain, the reward probabilities are reversed. This process is repeated 5 times.</description>
    <arm_group_label>Cognitive and Emotion Processing Tasks</arm_group_label>
    <other_name>Learning reversal task</other_name>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Facial Emotion Recognition Task</intervention_name>
    <description>On a given trial, participants will be presented with images of two faces side-by-side. The faces will either match in terms of emotion category (e.g., 2 anger faces) or not (e.g., an anger face and a fear face). Faces presented together will always be of the same gender but different identities. Participants will be asked to determine whether the two faces presented depict the same emotion category.</description>
    <arm_group_label>Cognitive and Emotion Processing Tasks</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. History of medically intractable epilepsy&#xD;
&#xD;
          2. Capable of giving informed consent&#xD;
&#xD;
          3. Aged 18 - 80 years, either sex&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Major systemic illness&#xD;
&#xD;
          2. Severe cognitive impairment defined as mini-mental state examination of less than 20&#xD;
&#xD;
          3. Severe psychiatric illness&#xD;
&#xD;
          4. Excessive use of alcohol or other substances&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>80 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Flavio Frohlich, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of North Carolina, Chapel Hill</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Hae Won Shin, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of North Carolina, Chapel Hill</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of North Carolina at Chapel Hill</name>
      <address>
        <city>Chapel Hill</city>
        <state>North Carolina</state>
        <zip>27599</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <reference>
    <citation>Hsieh LT, Ranganath C. Frontal midline theta oscillations during working memory maintenance and episodic encoding and retrieval. Neuroimage. 2014 Jan 15;85 Pt 2(0 2):721-9. doi: 10.1016/j.neuroimage.2013.08.003. Epub 2013 Aug 8.</citation>
    <PMID>23933041</PMID>
  </reference>
  <reference>
    <citation>Klimesch W. alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn Sci. 2012 Dec;16(12):606-17. doi: 10.1016/j.tics.2012.10.007. Epub 2012 Nov 7.</citation>
    <PMID>23141428</PMID>
  </reference>
  <reference>
    <citation>Sauseng P, Klimesch W, Heise KF, Gruber WR, Holz E, Karim AA, Glennon M, Gerloff C, Birbaumer N, Hummel FC. Brain oscillatory substrates of visual short-term memory capacity. Curr Biol. 2009 Nov 17;19(21):1846-52. doi: 10.1016/j.cub.2009.08.062.</citation>
    <PMID>19913428</PMID>
  </reference>
  <reference>
    <citation>Symons AE, El-Deredy W, Schwartze M, Kotz SA. The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication. Front Hum Neurosci. 2016 May 25;10:239. doi: 10.3389/fnhum.2016.00239. eCollection 2016.</citation>
    <PMID>27252638</PMID>
  </reference>
  <reference>
    <citation>Bonnefond M, Jensen O. Alpha oscillations serve to protect working memory maintenance against anticipated distracters. Curr Biol. 2012 Oct 23;22(20):1969-74. doi: 10.1016/j.cub.2012.08.029. Epub 2012 Oct 4.</citation>
    <PMID>23041197</PMID>
  </reference>
  <reference>
    <citation>Khader PH, Jost K, Ranganath C, Rosler F. Theta and alpha oscillations during working-memory maintenance predict successful long-term memory encoding. Neurosci Lett. 2010 Jan 14;468(3):339-43. doi: 10.1016/j.neulet.2009.11.028. Epub 2009 Nov 14.</citation>
    <PMID>19922772</PMID>
  </reference>
  <reference>
    <citation>Miller EK, Buschman TJ. Cortical circuits for the control of attention. Curr Opin Neurobiol. 2013 Apr;23(2):216-22. doi: 10.1016/j.conb.2012.11.011. Epub 2012 Dec 22.</citation>
    <PMID>23265963</PMID>
  </reference>
  <reference>
    <citation>Bastos AM, Vezoli J, Bosman CA, Schoffelen JM, Oostenveld R, Dowdall JR, De Weerd P, Kennedy H, Fries P. Visual areas exert feedforward and feedback influences through distinct frequency channels. Neuron. 2015 Jan 21;85(2):390-401. doi: 10.1016/j.neuron.2014.12.018. Epub 2014 Dec 31.</citation>
    <PMID>25556836</PMID>
  </reference>
  <reference>
    <citation>Jacobs J, Kahana MJ. Direct brain recordings fuel advances in cognitive electrophysiology. Trends Cogn Sci. 2010 Apr;14(4):162-71. doi: 10.1016/j.tics.2010.01.005. Epub 2010 Feb 25.</citation>
    <PMID>20189441</PMID>
  </reference>
  <reference>
    <citation>Mendez-Bertolo C, Moratti S, Toledano R, Lopez-Sosa F, Martinez-Alvarez R, Mah YH, Vuilleumier P, Gil-Nagel A, Strange BA. A fast pathway for fear in human amygdala. Nat Neurosci. 2016 Aug;19(8):1041-9. doi: 10.1038/nn.4324. Epub 2016 Jun 13.</citation>
    <PMID>27294508</PMID>
  </reference>
  <reference>
    <citation>Huijgen J, Dinkelacker V, Lachat F, Yahia-Cherif L, El Karoui I, Lemarechal JD, Adam C, Hugueville L, George N. Amygdala processing of social cues from faces: an intracrebral EEG study. Soc Cogn Affect Neurosci. 2015 Nov;10(11):1568-76. doi: 10.1093/scan/nsv048. Epub 2015 May 11.</citation>
    <PMID>25964498</PMID>
  </reference>
  <reference>
    <citation>Murray RJ, Brosch T, Sander D. The functional profile of the human amygdala in affective processing: insights from intracranial recordings. Cortex. 2014 Nov;60:10-33. doi: 10.1016/j.cortex.2014.06.010. Epub 2014 Jun 19.</citation>
    <PMID>25043736</PMID>
  </reference>
  <verification_date>January 2020</verification_date>
  <study_first_submitted>August 29, 2017</study_first_submitted>
  <study_first_submitted_qc>August 29, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">August 31, 2017</study_first_posted>
  <last_update_submitted>January 9, 2020</last_update_submitted>
  <last_update_submitted_qc>January 9, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">January 13, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03268694
org study id: 17-1301
secondary id: R21NS094988-01A1
nct id: NCT03268694
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Purpose: To investigate the electrophysiological correlates of human cognition and affective
      processing. Participants: Drug-resistant epilepsy patients undergoing epilepsy surgery
      cortical mapping with continuous electrocorticography (ECoG) with intracranial electrodes.
      Procedures (methods): Participants will perform computer-based cognitive and affective
      processing tasks during routine long-term monitoring. Intracranial EEG will be collected
      during the task
Oscillations in different frequency bands like theta, alpha, beta, gamma and high gamma are
      thought to underlie processing of cognitive and emotional information. For example, theta (3
      - 7 Hz) and alpha (8 - 12 Hz) oscillations are known to underlie working memory as well as
      attentional processing. Theta oscillations are known to differentiate emotional and neutral
      stimuli while gamma oscillations (30 - 50 Hz) are known to underlie rapid integration of
      information. The fact that these oscillations are also disrupted in neuropsychiatric
      disorders underline the importance of these oscillations.

      A lot of our understanding of these oscillations come from non invasive methods in humans
      like electroencephalography (EEG), magnetoencephalography (MEG) and invasive methods in
      animal models. However, EEG and MEG measure oscillations that are generated by collective
      firing of large cortical patches thereby losing spatial resolution. Also activity from deeper
      structures like amygdala and hippocampus cannot be picked up in these modalities. Animal
      models often suffer from the poor translation of behavior from animals to humans and vice
      versa. Intracranial EEG or Electrocorticography (ECoG) helps overcome the drawbacks described
      above.

      Studies using ECoG have become widespread and have been helpful in elucidating the functional
      roles of different brain regions in cognition and emotion. The investigators aim to utilize
      these established procedures to study the role of oscillations recorded from different brain
      regions in cognition and emotion.

      Patients with medically refractory epilepsy undergo long-term invasive monitoring for
      surgical resection planning. Electrodes are implanted subdurally over seizure focus to
      identify seizure onset zone and patients are often in the epilepsy monitoring unit at the
      Neuroscience hospital for approximately a week. During this period, intracranial EEG is
      constantly acquired for clinical investigation. The investigators plan to recruit these
      patients while they undergo long-term monitoring to leverage the rare access to direct brain
      recordings and study the role of oscillations in cognitive and affective processing. Patients
      who provide informed consent to participate in the study will perform computer based
      cognitive and emotional processing tasks.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Basic Science
masking: None (Open Label)
measure: Intracranial EEG Spectra Power
time frame: Intracranial EEG will be collected simultaneously when the participants perform the task. 1 Hour
description: Spectral analysis of electrophysiology data will be performed using multi-taper fft and wavelet transforms. The measures will be compared between different epochs within the tasks to determine what oscillations are modulated by the task. The correlation between the measures described above and the task performance will also be estimated.
measure: Task Performance: Reaction Times
time frame: 1 Hour
description: For all the tasks described above, the time from when the response is prompted and when the response is obtained is collected as reaction time. Reaction time is measured in milliseconds.
measure: Intracranial EEG Functional Connectivity Analysis
time frame: Intracranial EEG will be collected simultaneously when the participants perform the task. 1 Hour
description: Functional connectivity between the different electrodes will be measured using phase locking value and Granger causality.
arm group label: Cognitive and Emotion Processing Tasks
arm group type: Experimental
description: As a part of the clinical monitoring, intracranial EEG is continuously collected when the participant is at the Epilepsy Monitoring Unit at the UNC Neuroscience Hospital. We will use an FDA approved EEG amplifier/data acquisition system to collect the research data. Computer-based tasks will be presented through a laptop and task related timing information will be transmitted from the laptop to the data acquisition system. Computer-based tasks will include Working Memory task, Reward Learning Task and Facial Emotion Recognition Task
intervention type: Behavioral
intervention name: Working Memory Task
description: Sternberg Task Items, which can be visually presented alphabets, shapes or numbers or sound tones presented through speakers, will be presented to the participant. The participant will need to maintain the presented items in their memory and indicate, when a single probe item is presented, whether the probe item was present in the immediately preceding list by pressing a key on the keyboard.
N-Back Task Items are presented continuously sequentially and participants are instructed to indicate whether items are repeated n items before by pressing a key on the keyboard. The task is divided into blocks of 0,1,2,3 -back trials based on the 'n'. For example in the 2 - back task, the participant has to indicate if the item presented 2 items before matches the current item. Similar to the previous task, the items can be presented visually or auditorily.
arm group label: Cognitive and Emotion Processing Tasks
other name: Sternberg Task
other name: N-Back Task
intervention type: Behavioral
intervention name: Reward Learning Task
description: Two abstract visual stimuli are presented on the screen and participant is asked to choose one. Unknown to the participant, each stimulus is associated with distinct probabilities of virtual reward such that one stimulus is associated with net gain while the other is associated with net loss. The participant's goal is to maximize the reward. Once the participant identifies the stimulus associated with net gain, the reward probabilities are reversed. This process is repeated 5 times.
arm group label: Cognitive and Emotion Processing Tasks
other name: Learning reversal task
intervention type: Behavioral
intervention name: Facial Emotion Recognition Task
description: On a given trial, participants will be presented with images of two faces side-by-side. The faces will either match in terms of emotion category (e.g., 2 anger faces) or not (e.g., an anger face and a fear face). Faces presented together will always be of the same gender but different identities. Participants will be asked to determine whether the two faces presented depict the same emotion category.
arm group label: Cognitive and Emotion Processing Tasks
criteria: 
gender: All
minimum age: 18 Years
maximum age: 80 Years
healthy volunteers: No
last name: Flavio Frohlich, PhD
role: Principal Investigator
affiliation: University of North Carolina, Chapel Hill
last name: Hae Won Shin, MD
role: Principal Investigator
affiliation: University of North Carolina, Chapel Hill
facility: 
country: United States
citation: Hsieh LT, Ranganath C. Frontal midline theta oscillations during working memory maintenance and episodic encoding and retrieval. Neuroimage. 2014 Jan 15;85 Pt 2(0 2):721-9. doi: 10.1016/j.neuroimage.2013.08.003. Epub 2013 Aug 8.
PMID: 23933041
citation: Klimesch W. alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn Sci. 2012 Dec;16(12):606-17. doi: 10.1016/j.tics.2012.10.007. Epub 2012 Nov 7.
PMID: 23141428
citation: Sauseng P, Klimesch W, Heise KF, Gruber WR, Holz E, Karim AA, Glennon M, Gerloff C, Birbaumer N, Hummel FC. Brain oscillatory substrates of visual short-term memory capacity. Curr Biol. 2009 Nov 17;19(21):1846-52. doi: 10.1016/j.cub.2009.08.062.
PMID: 19913428
citation: Symons AE, El-Deredy W, Schwartze M, Kotz SA. The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication. Front Hum Neurosci. 2016 May 25;10:239. doi: 10.3389/fnhum.2016.00239. eCollection 2016.
PMID: 27252638
citation: Bonnefond M, Jensen O. Alpha oscillations serve to protect working memory maintenance against anticipated distracters. Curr Biol. 2012 Oct 23;22(20):1969-74. doi: 10.1016/j.cub.2012.08.029. Epub 2012 Oct 4.
PMID: 23041197
citation: Khader PH, Jost K, Ranganath C, Rosler F. Theta and alpha oscillations during working-memory maintenance predict successful long-term memory encoding. Neurosci Lett. 2010 Jan 14;468(3):339-43. doi: 10.1016/j.neulet.2009.11.028. Epub 2009 Nov 14.
PMID: 19922772
citation: Miller EK, Buschman TJ. Cortical circuits for the control of attention. Curr Opin Neurobiol. 2013 Apr;23(2):216-22. doi: 10.1016/j.conb.2012.11.011. Epub 2012 Dec 22.
PMID: 23265963
citation: Bastos AM, Vezoli J, Bosman CA, Schoffelen JM, Oostenveld R, Dowdall JR, De Weerd P, Kennedy H, Fries P. Visual areas exert feedforward and feedback influences through distinct frequency channels. Neuron. 2015 Jan 21;85(2):390-401. doi: 10.1016/j.neuron.2014.12.018. Epub 2014 Dec 31.
PMID: 25556836
citation: Jacobs J, Kahana MJ. Direct brain recordings fuel advances in cognitive electrophysiology. Trends Cogn Sci. 2010 Apr;14(4):162-71. doi: 10.1016/j.tics.2010.01.005. Epub 2010 Feb 25.
PMID: 20189441
citation: Mendez-Bertolo C, Moratti S, Toledano R, Lopez-Sosa F, Martinez-Alvarez R, Mah YH, Vuilleumier P, Gil-Nagel A, Strange BA. A fast pathway for fear in human amygdala. Nat Neurosci. 2016 Aug;19(8):1041-9. doi: 10.1038/nn.4324. Epub 2016 Jun 13.
PMID: 27294508
citation: Huijgen J, Dinkelacker V, Lachat F, Yahia-Cherif L, El Karoui I, Lemarechal JD, Adam C, Hugueville L, George N. Amygdala processing of social cues from faces: an intracrebral EEG study. Soc Cogn Affect Neurosci. 2015 Nov;10(11):1568-76. doi: 10.1093/scan/nsv048. Epub 2015 May 11.
PMID: 25964498
citation: Murray RJ, Brosch T, Sander D. The functional profile of the human amygdala in affective processing: insights from intracranial recordings. Cortex. 2014 Nov;60:10-33. doi: 10.1016/j.cortex.2014.06.010. Epub 2014 Jun 19.
PMID: 25043736
responsible party type: Sponsor