GrayMatters Health core technology has been extensively researched with peer-reviewd articles in prestigious medical journals. These publications form the clinical foundation of Prism for PTSD as an adjunct to standard-of-care therapies for PTSD patients.
The term Amygdala Electrical Finger-Print (AmygEFP) in clinical publications is now referred to as the EEG-fMRI-Pattern (EFP) biomarker.
15 October 2021
Amygdala electrical-finger-print (AmygEFP) NeuroFeedback guided by individually-tailored Trauma script for post-traumatic stress disorder: Proof-of-concept.
/ Fruchtman-Steinbok T, Keynan JN, Cohen A, Jaljuli I, Mermelstein S, Drori G, Routledge E, Krasnoshtein M, Playle R, Linden DEJ, Hendler T.
Neuroimage Clin. 2021;32:102859.
Demonstrating the feasibility of amygdala-EFP neurofeedback for PTSD treatment, by reducing PTSD symptoms and improving amygdala self-regulation.
The amygdala brain region is involved in emotional processing, and its dysregulation is associated with PTSD. Therefore, if we could teach a person to self-regulate their activity of this brain region, it could alleviate their symptoms. Such ‘brain training’ is accomplished by neurofeedback, in which the amygdala activity is recorded, analyzed in real-time and presented as feedback to the trainee. A major limitation in the scalability of this procedure for clinical use is that measurement of deep brain activity in the amygdala requires fMRI scanning. To overcome this limitation, an amygdala model was developed for use in an EEG-only neurofeedback procedure, termed amigdala EEG finger-print (EFP). It uses simultaneous EEG-fMRI recordings, training a machine-learning model to predict amygdala fMRI signals based on the EEG signals. The resulting amygdala EFP is implemented in EEG-based neurofeedback, without the need for patient MRI scanning.
In this study, PTSD patients treated with an 8-week neurofeedback protocol, followed by assessments at 3 and 6 months after completion. In a randomized clinical trial, 59 patients were assigned either to amygdala-EFP neurofeedback conditions (with two alternative feedback interfaces) or to no-neurofeedback control condition. Patients who trained with amygdala-EFP neurofeedback demonstrated greater reduction in PTSD symptoms (CAPS-5 questionnaire score) and improved fMRI down-regulation of the amygdala, compared to the control patients. Clinical improvement was preserved at 3 and 6 months following completion of the training, as measured via self-reported symptom severity (PCL questionnaire score). This demonstrates the potential benefit of amygdala-EFP neurofeedback training for PTSD treatment.
10 December 2018
Electrical fingerprint of the amygdala guides neurofeedback training for stress resilience.
/ Keynan JN, Cohen A, Jackont G, Green N, Goldway N, Davidov A, Meir-Hasson Y, Raz G, Intrator N, Fruchter E, Ginat K, Laska E, Cavazza M, Hendler T.
Nat Hum Behav. 2019 Jan;3(1):63-73.
Demonstrating the effects of amygdala-EFP neurofeedback on emotional resilience and amygdala self-regulation during ongoing intensive and stressful military training.
This study tested the ability of amygdala-EFP neurofeedback training to improve emotional resilience under stressful ongoing life conditions. In a double-blind experiment, 180 healthy individuals undergoing a stressful military training program were randomly assigned to either test or control conditions. During a 4-week long experimental scheme, test participants trained on amygdala-EFP neurofeedback, whereas control participants either trained on alpha/theta neurofeedback or no neurofeedback.
Emotional resilience, as measured via a psychological questionnaire of alexithymia and by a behavioral emotional-regulation test, improved after amygdala-EFP neurofeedback, but not after alpha/theta neurofeedback, and was worsened in participants who did not receive any form of feedback. Furthermore, in an fMRI scan performed after training, only participants who were trained with amygdala-EFP neurofeedback were able to down-regulate their amygdala activity. As compared with no neurofeedback, amygdala-EFP neurofeedback also resulted in higher co-activation of the amygdala together with another brain region involved in emotional regulation: the ventro-medial prefrontal cortex (vmPFC). These results demonstrate the beneficial effects of amygdala-EFP neurofeedback on emotional resilience during stress exposure.
24 August 2023
Amygdala-related EEG Neuro-Feedback as an add-on Therapy for treatment-resistant Childhood Sexual Abuse PTSD: Feasibility Study
/ Fine NB, Helpman L, Bardin Armon D, Gurevitch G, Sheppes G, Seligman Z, Hendler T, Bloch M.
Psychiatry Clin Neurosci 2023 Aug 24.
Testing the feasibility of amygdala-EFP neurofeedback for childhood sexual abuse (CSA) PTSD treatment facilitation.
The study tested the effects of amygdala-EFP neurofeedback training in 55 women with treatment-resistant CSA-PTSD during ongoing trauma-focused psychotherapy. Participants were randomly assigned to neurofeedback (with therapy) condition or therapy-only condition. Participants who underwent neurofeedback successfully learned to down-regulate the amygdala-EFP signal. PTSD symptoms (measured by PCL score) in the neurofeedback group improved over time, as measured in a 3- and 6-month follow-up, as compared to the therapy-only group.
24 May 2022
Volitional limbic neuromodulation exerts a beneficial clinical effect on Fibromyalgia.
/ Goldway N, Ablin J, Lubin O, Zamir Y, Keynan JN, Or-Borichev A, Cavazza M, Charles F, Intrator N, Brill S, Ben-Simon E, Sharon H, Hendler T.
NeuroImage 186 (2019) 758–770
Demonstrating the feasibility of amygdala-EFP neurofeedback for treatment of chronic pain in fibromyalgia.
Fibromyalgia is a somatic disorder characterized by widespread pain and associated with sleep disturbance and emotional dysregulation. The latter are known to be modulated by limbic activity, which involves the amygdala. The authors utilized the amygdala-EFP to examine its feasibility in treating fibromyalgia in a 5-week neurofeedback training protocol. Fibromyalgia patients were randomly assigned to either amygdala-EFP neurofeedback or sham-neurofeedback conditions. Sleep quality was largely improved following amygdala-EFP neurofeedback but not in the sham group. The same patients also reported an improvement in clinical symptoms during a follow-up assessment, but not immediately after training. The extent to which the training improved the patient’s sleep, predicted the later improvement in clinical symptoms.
This demonstrates the potential benefits of amygdala-EFP neurofeedback for treatment of somatic disorders, based on its close relationship with limbic dysregulation.
2. EEG-fMRI-PATTERN (EFP) BIOMARKER
6 January 2016
Limbic Activity Modulation Guided by Functional Magnetic Resonance Imaging-Inspired Electroencephalography Improves Implicit Emotion Regulation.
/ Keynan JN, Meir-Hasson Y, Gilam G, Cohen A, Jackont G, Kinreich S, Ikar L, Or-Borichev A, Etkin A, Gyurak A, Klovatch I, Intrator N, Hendler T.Biol Psychiatry. 2016 Sep 15;80(6):490-496
Demonstrating the effects of amygdala-EFP neurofeedback training on the ability to self-regulate amygdala activity and on emotional reactivity.
The amygdala EFP was developed with the intention of establishing, in the long run, a scalable method for training emotional regulation. Specifically, it is aimed to reduce emotional reactivity related to an over-active amygdala. Following the development of the amygdala EFP, which provided an EEG-based biomarker of amygdala activity, the innovation was tested in a neurofeedback procedure termed amyg-EFP-NF. Three questions were addressed: (1) Does amyg-EFP-NF increase one’s ability to down-regulate their own amygdala activity? (2) Does amyg-EFP-NF reduce one’s reactivity of the amygdala in response to emotional images? (3)
Does amyg-EFP-NF improve one’s behavioral emotional regulation? The study used a combination of fMRI, EEG and behavioral measurements to test, and successfully demonstrate, the effectiveness of amyg-EFP NF in accomplishing all three objectives. Thus, the amyg-EFP not only probes amygdala-related activity but also causally influences it when implemented in a neurofeedback procedure.
15 November 2013
An EEG Finger-Print of fMRI deep regional activation
/ Meir-Hasson Y, Kinreich S, Podlipsky I, Hendler T, Intrator N.
Neuroimage. 2014 Nov 15;102 Pt 1:128-141.
Introducing the EEG finger-print (EFP); a computational model that tracks the activity of deep brain regions via EEG, thereby reducing the need for fMRI scanning.
Traditional EEG neurofeedback paradigms, such as alpha/theta sampling, provide low spatial accuracy, which makes deep brain regions, such as the amygdala, largely inaccessible. The EFP model was developed in order to overcome this limitation, by using simultaneous EEG-fMRI recordings. It exploits the high spatial resolution imaging enabled by fMRI, and incorporates advanced signal processing and machine learning methods of EEG signals. Thereby, the model learns to predict a brain region’s activity as measured with the fMRI, based on the signals recorded in EEG.
An amygdala-EFP model successfully predicted the amygdala’s fMRI signal from a single EEG electrode. Moreover, it provided better prediction of amygdala activity than the traditional alpha/theta EEG sampling. Thus, the EFP is proposed as a more targeted biomarker of neural activity, which can be applied in EEG-based neurofeedback and other brain-guided procedures.
16 May 2016
One-Class FMRI-Inspired EEG Model for Self-Regulation Training
/ Meir-Hasson Y, Keynan JN, Kinreich S, Jackont G, Cohen A, Podlipsky-Klovatch I, Hendler T, Intrator N.PLoS One. 2016 May 10;11(5):e0154968.
Applying an EFP-neurofeedback procedure to train amygdala down-regulation in participants that did not undergo fMRI.
The amygdala brain region is involved in emotional processing, and its dysregulation is associated with emotional dysfunction. Therefore, if we could teach a person to self-regulate their activity of this brain region, it may alleviate their symptoms. Such neural-regulation training is accomplished via neurofeedback, in which the amygdala activity is recorded, analyzed in real time and presented as feedback to the trainee. A major limitation in the scalability of this procedure for clinical use is that measurement of such deep brain activity requires fMRI scanning. To remove this limitation, an amygdala EFP was developed for use in an EEG-only neurofeedback procedure.
The article describes the innovative computational methods that were used to achieve an effective common model for amygdala EFP. The model was developed from simultaneous EEG-fMRI recordings in one group of participants, and tested in EEG-only neurofeedback in a new group of participants. Participants in the new group learned to substantially reduce their amygdala EFP signal if they had been trained with true feedback, but not if they had been trained with sham feedback. This shows that amygdala EFP can be implemented in EEG-based neurofeedback without the need for patient MRI scanning.
22 May 2023
Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation
/ Singer N, Poker G, Dunsky-Moran N, Nemni S, Reznik Balter S, Doron M, Baker T, Dagher A, Zatorre RJ, Hendler T.
NeuroImage 276 (2023) 120183.
Demonstrating the feasibility of an EFP model for the ventral striatum (VS-EFP).
The ventral striatum (VS) is a key brain region involved in reward processing, in which the brain associates an event or stimulus with a positive feeling or desirable outcome. Therefore, learning to self-regulate the VS might be useful to individuals suffering from difficulties in reward processing, such as anhedonia (i.e., reduced ability to feel pleasure). This study examined the possibility to track VS activity using EEG signals.
Based on the successful approach that led to the generation of the amygdala-EFP, a new EFP model was generated to predict the fMRI response of the VS from EEG signals. The model was developed from simultaneous EEG-fMRI recordings in one group of participants, and validated in simultaneous EEG-fMRI recordings of a separate group, while participants listened to music.
The VS-EFP model produced from EEG signals in the first group successfully predicted VS activity, as measured by the fMRI signal, in both groups. The VS-EFP was also associated with the extent to which participants enjoyed the music they listened to during the experiment. The VS-EFP is therefore an effective biomarker of VS activity related to pleasurable experience.
24 May 2022
Feasibility and utility of amygdala neurofeedback/ Goldway N, Jalon I, Keynan JN, Hellrung L, Horstmann A, Paret C, Hendler T.Neurosci Biobehav Rev. 2022 Jul;138:104694.
A review of research studies that tested the effects of amygdala-neurofeedback (using either fMRI or amygdala-EFP) on the ability to self-regulate the amygdala.
This is a meta-analysis of 33 studies, in which amygdala neurofeedback was accomplished either in an EEG setting measuring the amygdala-EFP signal, or in an fMRI setting measuring amygdala activity. Overall, amygdala neurofeedback resulted in (1) increased regulation (relative to baseline), (2) improved self-regulation following multiple training sessions, and (3) improved clinical symptoms following multiple training sessions.
The article further analyzes aspects of study design that contribute to neurofeedback efficacy. An additional re-analysis of fMRI studies further revealed that when the amygdala is down-regulated by neurofeedback, the activity reduction in the amygdala is associated with a reduction in activity of other brain regions including the insula, prefrontal cortex, and parahippocampal cortex.
19 April 2019
Process-based framework for precise neuromodulation
/ Lubianiker N, Goldway N, Fruchtman-Steinbok T, Paret C, Keynan JN, Singer N, Cohen A, Kadosh KC, Linden DEJ, Hendler T.Nat Hum Behav. 2019 May;3(5):436-445
The authors bring forth the idea of a process-based approach to neural regulation.
Three aspects of neurofeedback training and testing are addressed: (1) Neural targeting – the part of the brain that we want to influence with neurofeedback. The authors propose moving from an approach that targets a single brain region, to targeting a mental process, which involves a network of multiple brain regions often activated in synchrony. For example, emotional regulation involves limbic regions [such as the amygdala], together with other brain regions [such as the insula and prefrontal cortex]. Even in single-region neurofeedback targeting, effects usually extend beyond the target region, to other brain regions; (2) Feedback interface – the interactive setup and manner in which the feedback is presented.
The authors propose designing a feedback interface that systematically targets the mental process we want to influence, by creating a contextual setting in which this mental process is typically expressed or triggered [such as an enjoyable setting to target reward processing, or a stressful setting to target emotional regulation]; (3) Neurofeedback specificity – the combination of test, control and placebo conditions by which we try to isolate the effects of a specific neurofeedback method. The authors propose designing randomized clinical trials combining multiple control conditions to allow better inference.
16 May 2016
Multi-modal Virtual Scenario Enhances Neurofeedback Learning
/ Cohen A, Keynan JN, Jackont G, Green N, Rashap I, Shani O, Charles F, Cavazza M, Hendler T, Raz G.
Front Robot AI, 2016 Aug 31; 3:52.
Introducing a gamified neurofeedback interface and its benefits for amygdala-EFP training.
The study introduces a novel neurofeedback interface, depicting an animated audiovisual scenario of a hospital waiting room. The level of stress in the waiting room is modulated by the neural signal. When amygdala-EFP increases, the animated characters crowd the reception area, and the room becomes noisier. The participants’ goal is to reduce their amygdala-EFP signal, causing the characters to quiet down and go back to their seats. Training with the animated scenario improved participants’ ability to self-regulate their amygdala-EFP significantly better than when training with a simple 2D thermometer feedback interface (a bar image that fills up and changes color as signal increases). This demonstrates the benefits of neurofeedback training with a gamified interface.