Review Special Issues

A dual-brain therapeutic approach using noninvasive brain stimulation based on two-person neuroscience: A perspective review


  • Received: 17 October 2023 Revised: 06 February 2024 Accepted: 19 February 2024 Published: 04 March 2024
  • Our actions and decisions in everyday life are heavily influenced by social interactions, which are dynamic feedback loops involving actions, reactions, and internal cognitive processes between individual agents. Social interactions induce interpersonal synchrony, which occurs at different biobehavioral levels and comprises behavioral, physiological, and neurological activities. Hyperscanning—a neuroimaging technique that simultaneously measures the activity of multiple brain regions—has provided a powerful second-person neuroscience tool for investigating the phase alignment of neural processes during interactive social behavior. Neural synchronization, revealed by hyperscanning, is a phenomenon called inter-brain synchrony- a process that purportedly facilitates social interactions by prompting appropriate anticipation of and responses to each other's social behaviors during ongoing shared interactions. In this review, I explored the therapeutic dual-brain approach using noninvasive brain stimulation to target inter-brain synchrony based on second-person neuroscience to modulate social interaction. Artificially inducing synchrony between the brains is a potential adjunct technique to physiotherapy, psychotherapy, and pain treatment- which are strongly influenced by the social interaction between the therapist and patient. Dual-brain approaches to personalize stimulation parameters must consider temporal, spatial, and oscillatory factors. Multiple data fusion analysis, the assessment of inter-brain plasticity, a closed-loop system, and a brain-to-brain interface can support personalized stimulation.

    Citation: Naoyuki Takeuchi. A dual-brain therapeutic approach using noninvasive brain stimulation based on two-person neuroscience: A perspective review[J]. Mathematical Biosciences and Engineering, 2024, 21(4): 5118-5137. doi: 10.3934/mbe.2024226

    Related Papers:

    [1] Mohra Zayed, Taghreed Alqurashi, Shahid Ahmad Wani, Cheon Seoung Ryoo, William Ramírez . Several characterizations of bivariate quantum-Hermite-Appell Polynomials and the structure of their zeros. AIMS Mathematics, 2025, 10(5): 11184-11207. doi: 10.3934/math.2025507
    [2] Limin Zhou, Qiuyang Wang . Simple PKE schemes from the TSPEM problem. AIMS Mathematics, 2024, 9(8): 22197-22212. doi: 10.3934/math.20241079
    [3] İsmet Gölgeleyen, Özlem Kaytmaz . Uniqueness for a Cauchy problem for the generalized Schrödinger equation. AIMS Mathematics, 2023, 8(3): 5703-5724. doi: 10.3934/math.2023287
    [4] Rutwig Campoamor-Stursberg, Eduardo Fernández-Saiz, Francisco J. Herranz . Generalized Buchdahl equations as Lie–Hamilton systems from the "book" and oscillator algebras: quantum deformations and their general solution. AIMS Mathematics, 2025, 10(3): 6873-6909. doi: 10.3934/math.2025315
    [5] Luigi Accardi, El Gheted Soueidi, Abdessatar Souissi, Mohamed Rhaima, Farrukh Mukhamedov, Farzona Mukhamedova . Structure of backward quantum Markov chains. AIMS Mathematics, 2024, 9(10): 28044-28057. doi: 10.3934/math.20241360
    [6] Nattapong Kamsrisuk, Donny Passary, Sotiris K. Ntouyas, Jessada Tariboon . Quantum calculus with respect to another function. AIMS Mathematics, 2024, 9(4): 10446-10461. doi: 10.3934/math.2024510
    [7] Abdessatar Souissi, El Gheteb Soueidy, Mohamed Rhaima . Clustering property for quantum Markov chains on the comb graph. AIMS Mathematics, 2023, 8(4): 7865-7880. doi: 10.3934/math.2023396
    [8] Nusrat Raza, Mohammed Fadel, Kottakkaran Sooppy Nisar, M. Zakarya . On 2-variable q-Hermite polynomials. AIMS Mathematics, 2021, 6(8): 8705-8727. doi: 10.3934/math.2021506
    [9] Husein Natur, Uzi Pereg . Empirical coordination of separable quantum correlations. AIMS Mathematics, 2025, 10(4): 10028-10061. doi: 10.3934/math.2025458
    [10] Chanon Promsakon, Muhammad Aamir Ali, Hüseyin Budak, Mujahid Abbas, Faheem Muhammad, Thanin Sitthiwirattham . On generalizations of quantum Simpson's and quantum Newton's inequalities with some parameters. AIMS Mathematics, 2021, 6(12): 13954-13975. doi: 10.3934/math.2021807
  • Our actions and decisions in everyday life are heavily influenced by social interactions, which are dynamic feedback loops involving actions, reactions, and internal cognitive processes between individual agents. Social interactions induce interpersonal synchrony, which occurs at different biobehavioral levels and comprises behavioral, physiological, and neurological activities. Hyperscanning—a neuroimaging technique that simultaneously measures the activity of multiple brain regions—has provided a powerful second-person neuroscience tool for investigating the phase alignment of neural processes during interactive social behavior. Neural synchronization, revealed by hyperscanning, is a phenomenon called inter-brain synchrony- a process that purportedly facilitates social interactions by prompting appropriate anticipation of and responses to each other's social behaviors during ongoing shared interactions. In this review, I explored the therapeutic dual-brain approach using noninvasive brain stimulation to target inter-brain synchrony based on second-person neuroscience to modulate social interaction. Artificially inducing synchrony between the brains is a potential adjunct technique to physiotherapy, psychotherapy, and pain treatment- which are strongly influenced by the social interaction between the therapist and patient. Dual-brain approaches to personalize stimulation parameters must consider temporal, spatial, and oscillatory factors. Multiple data fusion analysis, the assessment of inter-brain plasticity, a closed-loop system, and a brain-to-brain interface can support personalized stimulation.



    Abbreviations:

    OSROpen surgical repair
    EVAREndovascular aneurysm repair
    PTFEPolytetrafluoroethylene
    TEVARThoracic endovascular aneurysm repair
    ETElephant trunk
    FETFrozen elephant trunk
    SCISpinal cord ischemia
    SCPPSpinal cord perfusion pressure
    FDSFlow Diverter Stent
    PETPolyethylene terephthalate


    1. Introduction

    Cardiovascular disease is one of the leading causes of death in developed countries. One of the conditions that contribute to this mortality is aortic aneurysm. Aortic aneurysm is a condition whereby the aorta, a major blood vessel of the heart enlarges abnormally due to a weakened aortic wall [1]. Aortic aneurysm usually occurs in the abdominal aorta but can also extend into the thoracic region. When the aorta and thoracic aorta is beyond 55 and 65 mm in diameter, respectively and left untreated, life-threatening complications such as aortic rupture arise [1]. Aortic aneurysm is a primary cause of death for approximately 10,000 patients and a contributing cause of death for 17,000 patients annually in the United States [2]. Of these cases, more than 50% of the patients diagnosed with thoracic aortic aneurysms have complex or extensive aortic aneurysms [3]. Complex aneurysm is defined as aneurysm spanning from the aortic arch region to the descending thoracic aorta (Figure 1A).

    Figure 1. (A) Complex aortic aneurysm extending between aortic arch and thoracic aorta region, (B) Open surgical repair, (C) Endovascular repair, (D) Frozen elephant trunk hybrid repair. BA—Brachiocephalic artery, LCCA—Left common carotid artery, LSA—Left subclavian artery.

    There are two main treatment options for aortic aneurysms: open surgical repair (OSR) and endovascular aneurysm repair (EVAR). OSR is considered the gold standard for treating aneurysms and the procedure is associated with very few long-term complications. However, being a highly invasive procedure, the OSR results in high perioperative mortality and is unsuitable for high-risk elderly patients [4,5]. This limitation led to the development of minimally invasive procedures such as EVAR which has improved the treatment of aneurysm in the last two decades.

    While OSR and EVAR are suitable for aneurysms with straight aortic geometry (abdominal and thoracic aorta), treating complex aneurysms remains a clinical challenge as complicated anatomies involving acute aortic arch angulation and supra-aortic vessel re-construction (brachiocephalic artery, left common carotid artery, and left subclavian artery) need to be considered [6]. Even with recent technological advancements, both OSR and EVAR are still associated with significant post-operative complications and mortality [5,6]. These 2 procedures utilize a textile graft to treat the aneurysm and one of the factors that contributes to the post-operative complications is the structural design of the graft [7,8].Parameters such as size specifications and ease of handling during the procedure are considered important while the influence of the stent-graft design on biomechanics and its impact on the hemodynamics of the aortic arch is often overlooked [9,10]. The purpose of this review is to highlight major biomechanical shortcomings of current stent-graft devices in relation to aortic arch geometry and its mechanics, and thus prompting the development of devices better suited for complex aneurysm repair.


    2. Conventional Repair of Complex Aneurysms

    Complex aneurysms are usually treated via OSR or EVAR. OSR is an invasive treatment that requires an incision in the abdomen or chest along the aorta followed by an insertion of soft tubular graft prosthesis to replace the aneurysmal site of the aorta (Figure 1B). These surgical grafts are usually made from Dacron® polyester or polytetrafluoroethylene (PTFE) and sutured to re-connect the healthy ends of the aorta. The less invasive EVAR is a procedure which involves a small incision in the groin area and a stent-graft is inserted through the femoral artery and up to the site of aneurysm in the aorta (Figure 1C). A stent-graft consists of a thin metal framework referred to as a stent that is attached to a Dacron® or PTFE graft. The stent-graft is inserted into the body in a collapsed form and re-opened at the site of the aneurysm in a spring-like fashion. The expansion force provides a passive friction grip to hold the stent-graft in place.

    EVAR that is used to treat thoracic aortic aneurysm is referred to as thoracic EVAR (TEVAR) and this procedure has its own challenges due to the anatomy of the aortic arch. One of the limitations is the availability of appropriate landing zone to enable firm fixation of the stent-graft at its proximal and distal ends. Another major challenge is to deploy the stent-graft accurately in a large, mobile, curved aortic arch which is subject to high blood flow [11] and achieving conformability of the stent-graft with the curvature of the aortic arch [12]. Although TEVAR is less invasive, its long-term complication rates are higher than OSR [13,14]. The stent-graft related complications (migration, endoleaks, kinking, structural failure) occur because the stent-grafts which were designed for non-curved aneurysm treatment are also being used to treat complex aneurysms with little consideration to the morphological and hemodynamic characteristics of the aortic arch [15,16,17,18].


    3. Hybrid Repair of Complex Aneurysms

    In order to overcome the limitations of OSR and TEVAR, hybrid repair procedures, elephant trunk (ET; Figure 2) [19] and frozen elephant trunk (FET; Figure 3) [20,21] were introduced, respectively. These hybrid procedures had the major advantages of being easy to carry out and lower device related complications. This led to the procedures being used globally to treat complex aneurysms.

    Figure 2. Two stage hybrid elephant trunk procedure with a long graft prosthesis as proposed by Borst (1983).
    Figure 3. Single stage frozen elephant trunk hybrid repair procedure; (A) Stented trunk insertion in collapsed form in thoracic aorta, (B) Stented trunk deployed and aortic arch reconstructed with proximal graft.

    The ET procedure described by Borst in 1983 combined ascending aorta and aortic arch replacement, followed by placement of a free-floating graft into the descending thoracic aorta. This technique had the advantage of a graft already present in the descending thoracic aorta which could be utilised for thoracic aorta reconstruction at a later stage. The ET procedure offered the advantage of avoiding extensive dissection of the aorta in a single procedure. Additionally, clamping of the graft distal to the subclavian region rather than in the arch, as in the OSR, reduces hypothermic circulatory arrest time.

    The FET procedure came into existence in the 1990s after the advent of the endovascular era, when surgeons started to combine ascending aorta and aortic arch repair with deployment of an endovascular stent-graft into the descending thoracic aorta. The benefit of a FET procedure was that it reduced the operative time significantly by turning the complex 2-stage ET procedure into a single surgery. The FET procedure combines OSR and EVAR treatment whereby a prosthetic graft is used to reconstruct the aortic arch region while a stented graft bypasses the thoracic aneurysm region in a single stage procedure (Figure 3) [22].

    A typical hybrid device consists of a proximal non-stented woven Dacron® graft and a stented graft (trunk) at its distal end that bypasses the thoracic aortic aneurysm. The hybrid device is loaded in an introducer and inserted in an antegrade manner through the opened aortic arch (Figure 3A). The stented trunk is deployed deep inside the thoracic aorta supported by passive fixation at its distal end while the proximal end is sutured circumferentially in the distal aortic arch region (Figure 3B). The sutured anastomosis of the proximal end prevents the distal migration and type-1a endoleak complications associated with stent-grafts in TEVAR procedures [23]. The FET technique significantly reduced the mortality rate to 7%, compared to 8.9% (1st stage) and 7.7% (2nd stage) of the conventional hybrid procedure [6].The FET procedure thus offers a better treatment option for complex aneurysms than OSR and EVAR by reducing the operative time and improving stent-graft stability.


    4. Impact of Stent-graft Design in Complex Aneurysm Repair

    Currently, there are several types of stent-grafts available in the market, all differing in design, thickness profile, metallic composition, graft construction and fixation method, making each device unique in its structure [24]. However, none of the device is free from post-operative complications [25]. While there has been intensive research in the last 30 years into improving hybrid procedures, there has been no significant improvement in the design of the hybrid device, which plays an important role in the post-operative success of the procedure [26].


    4.1. Effect of stent-graft on hemodynamics of the aorta

    The stent-graft design influences the outcome of an aneurysm repair especially when it is being considered as a replacement conduit for the aortic arch [27,28]. This is because the aortic arch region encounters dynamic forces that are completely different to the rest of the aorta due to its multiplanar geometry [12,29]. The aortic arch undergoes dynamic motion because it is attached to the beating heart [30]. The geometrical changes occur due to the three-dimensional spiralling of the aortic arch caused by strong contraction and relaxation movement of left ventricle (flexion) and high volume rotational blood flow patterns (torsion) [31].

    An important function of the aorta is the windkessel function which maintains steady flow conditions throughout the arterial network [32]. The windkessel function prevents the arterial pressure from falling abruptly after the aortic valves close [33]. Aortic elasticity is a profoundly important determinant of windkesselfunction and hence the blood flow dynamics. The arterial compliance or elasticity of the ascending aorta and aortic arch is significantly higher than the rest of the aorta and is responsible for nearly 40% of the total arterial compliance [34,35]. On the contrary, biomechanical properties of stent-graft materials are significantly different to that of an aorta. A commercial woven Dacron® graft is 24 times stiffer than a healthy human aorta [36]. An unmatched radial compliance between a stent-graft device and aorta can trigger local hemodynamic disturbance after implantation [37,38,39,40,41]. The direct effect of this mismatch on aortic hemodynamics is observed as a deterioration in aortic windkessel function and increased cardiovascular load [42,43,44,45,46]. In the absence of systolic dilation, the stented aorta loses the ability to assist in diastolic flow (Figure 4). The stented region is unable to store extra blood volume during systole and hence the maximum portion of stroke volume flows through the aorta in a single systolic phase [47]. As a result, the diastolic phase experiences reduced blood flow, thus decreasing the diastolic blood pressure below the normal levels [47,48]. Lowered diastolic pressures, in turn, limit the blood flow to the coronary arteries [47,49,50,51].

    Figure 4. Role of aortic compliance in maintaining diastolic blood flow.

    Apart from altering the hemodynamics of the aorta, the poor radial compliance and longitudinal rigidity of the stent-graft also lead to migration from its fixation site. This is caused by the dilating aneurysm neck exceeding the maximum achievable diameter of the non-compliant stent-graft and thus disengaging it from the fixation site [52]. Similarly, lengthening of the aneurysm post-treatment can cause displacement of the stent-graft at the fixation site as its longitudinal rigidity does not allow it to extend to similar lengths [53,54].

    Another factor that contributes to poor stent-graft performance in tortuous anatomical location of the aortic arch is the high bending stiffness of the stent-graft [12,15,55,56,57]. Bending stiffness of the stent structure significantly hinders the ability of the device to conform to the aortic arch curvature. The stiffness also causes aortic wall injury due to pulsatile stress and configuration mismatch between stent-graft and aortic arch [56]. Commercial stent-grafts are designed to achieve high longitudinal rigidity as it provides columnar support to the structure and hence prevents migration [58,59]. However, this property is more beneficial when the device is used to treat straight abdominal aortas rather than the aortic arch and proximal thoracic aorta which have three-dimensional angulations. This is because blood traverses in curved regions of the aorta and creates centrifugal forces that are markedly higher than in straight regions [60]. A longitudinally rigid stent-graft that cannot be extended is incapable of absorbing pulsatile forces generated within the structure itself. Consequently, the collective lateral displacement forces from the curved section of stent-graft length are transmitted as migration (or drag) forces on distal fixation site leading to type-Ibendoleaks (Figure 5) [61,62,63,64,65]. The dreaded complication of stent-graft induced new entry (type-Ibendoleak) can also occur when a stiff stent-graft is implanted in the angulated regions of the aorta. The shear forces are high at the fixation point of the stent-graft which gets amplified with acute angulation of the aorta and oversizing of the stent-graft [66].

    Figure 5. Distal end migration (Type-1b endoleak) of stented trunk in a hybrid device subjected to traversing blood flow forces in curved proximal descending aorta region.

    5. Hybrid Stent-graft Designs


    5.1. Customised devices

    The first hybrid FET graft consisted of a stainless steel Z-shaped stent and woven polyester graft material [20]. This device was composed of a crimped graft prosthesis at the proximal end and an uncrimped graft with three Z-shape stent rings inserted and sutured to the graft circumference at the distal end (Figure 6). Following this, the Chavan-Haverich hybrid graft was created with similar design and composition which is currently manufactured in customised configurations by Curative Medical Devices GmbH, Germany [67]. Globally, most clinicians requiring customised hybrid grafts use the Chavan-Haverich graft tailored to the patients’ needs. Clinical and follow-up studies showed promising results in terms of ease, effectiveness and safety of the procedure [68,69,70,71,72,73,74]. Another FET graft, Cronus® (MicroPort Medical Co. Ltd, China) was claimed to be superior to Chavan-Haverich graft owing to its technical simplicity [75]. The authors claimed that an extra length of normal graft on both ends allowed anastomosis to be performed conventionally and helped in avoiding endoleaks.

    Figure 6. Typical design of first custom-built hybrid stent-graft device.

    5.2. Off-the shelf devices

    Currently available off-the-shelf devices have overcome a major shortcoming of early customised devices. The interconnections between adjacent stent rows (Figure 6) were eliminated in new devices which reduced the risk of stent rupture, commonly observed with early customised devices, due to repeated cyclic stresses. This also prevented occurrence of type-III endoleaks due to graft failure at interconnection points. The two commercially available FET hybrid devices are E-vita Open Plus graft (Jotec® GmbH, Germany) and Thoraflex hybrid graft (Vascutek®, Terumo, UK) [76,77]. The E-vita device consists of a crimped woven Dacron® graft 70 mm in length used for aortic arch reconstruction [78]. The graft further extends into a flexible nitinol z-shaped wire stented trunk with diameters and lengths ranging from 24-30 mm and 150-160 mm, respectively. The Thoraflex® hybrid graft consists of a four-branched arch graft (unlike the plain tubular graft of E-vita Open Plus device) with a stented trunk at the distal end [77]. The proximal part is a gel-coated woven polyester graft and the stented trunk is composed of oval shaped nitinol ring stents. The graft is available in different sizes (diameters of 28-40 mm and lengths of 100-150 mm). A major difference between E-vita Open Plus and Thoraflex hybrid graft is their stent ring configuration. The E-vita Open Plus has single wire stent rings, whereas the Thoraflex device consists of multiple wire rings which reduces the retraction force of the device and potentially improves longitudinal flexibility. However, to date, no data has been published on the comparison of mechanical properties between the 2 types of graft.


    6. Complications Associated with Hybrid Devices

    Clinical trials with new hybrid devices (E-vita and Thoraflex hybrid graft) have reported ease of deployment which significantly reduced the operative time compared to conventional OSR, TEVAR and ET procedures [79]. However, the FET procedure is not without complications (Table 1). Endoleaks, a commonly reported problem, has an incidence rate of 1-15%, which requires a second stage aortic surgery or a TEVAR completion [70,80]. A recent 4-year study comprising 100 patients using Thoraflex® graft reported a high endoleak rate (43%), and corresponding high reintervention rate (60%) [81]. The distal endoleaks (or type-1b endoleaks) occur as a result of the stented trunk migrating towards the aortic arch in large aneurysms (Figure 5) [68,71,72]. Excessively short trunks (<5 cm) are inadequate for sealing the stent-graft, especially in severely tortuous aortas while an excessively long trunk (>15 cm) is prone to kinks and migration. Additionally, the diameter of the stent-graft is an important criterion in the long-term success of FET technique [82]. The use of stent-graft with diameter larger than that of the aneurysm neck can help to improve fixation at the distal end. However, clinically, this may not be feasible as stented trunks with excessively large diameters can lead to severe aortic walldamage or tearing [6,82].

    Table 1. Limitations of current hybrid devices and future design concepts.
    CURRENT STENT-GRAFTSFUTURE STENT-GRAFTS
    DESIGN
    FEATURE
    LIMITATIONASSOCIATED
    COMPLICATION
    REFERENCEDESIGN
    FEATURE
    ASSOCIATED
    IMPROVEMENT
    Unibody
    structure
    Low flexibilityEndoleaks [68,70,71,72,77,83]Modular designImproved structural
    flexibility
    Migration, Kinking [84,85,86]Multi-component
    assembly
    Non-
    compliant
    structural
    materials
    (Dacron fibre,
    metallic
    stents)
    Low radial
    expandability
    Reduced diastolic
    pressure
    [47,49,50,51]Compliant
    structural materials
    (elastic polymeric
    fibres, knitted graft
    structure)
    Enhanced blood
    flow transmission
    Aortic wall injury [56]Reduced property
    mismatch with
    aortic tissue
    Disturbed spinal
    cord blood flow
    Delayed spinal cord
    ischemia
    [87,88,89,90,91,92]Enhanced spinal
    cord blood flow
    Diameter
    oversizing
    Aneurysm neck
    stress
    Aortic wall injury [82,93]Matched
    compliance with
    aortic wall
    Reduced property
    mismatch with
    aortic tissue
    Short trunk
    length
    Inadequate
    sealing
    Migration, Type 1b
    endoleaks
    [68,71,72]Biocompatible
    coatings and graft
    materials
    Better tissue
    ingrowth and
    sealing
    Long trunk
    length
    Extensive aortic
    coverage
    Spinal cord ischemia [70,94,95,96,97,98]Radially compliant
    trunk
    Flow diverter stents
    Enhanced spinal
    blood flow via
    collateral supply
    vessels
     | Show Table
    DownLoad: CSV

    Another device related complication, commonly reported in treatment of kinked or tortuous aortas, is that the insertion of stented trunk becomes very difficult or impossible due to the stiffness of the trunk and the introducer sheath [86]. Sakurai et al. and Toyama et al. reported mid-zone migration of stent-graft and kinking [84,85]. Some studies suggested that use of longer trunk lengths (10-20 cm) can help in thrombosis of false lumen which can permanently prevent retrograde perfusion [99]. However, long trunk lengths have been shown to contribute towards spinal cord ischemia (SCI) and paraplegia in patients [70,94,97]. Therefore, there is a need for innovative fixation techniques which do not rely only on pressure contact between stent-graft and aortic tissue or mechanical hooks and more compliant/flexible structures which prevent transmission of migration (or drag) forces to the fixation sites.

    SCI has recently been identified as a serious complication in hybrid repair with incidence rates ranging from 0 to 24% [100]. Incidence of SCI as high as 20% were reported in hybrid procedures using the E-vita graft [95,96,98]. The probable relationship of postoperative SCI and stent-graft design highlights the impact the design has on the hemodynamics of reduced aortic compliance after stent-graft implantation [38,46]. When a significant length of a compliant aorta is replaced with a non-compliant stent-graft, the pressure transmission ability of the aorta, within and at the distal end of the stented region is significantly reduced [43]. Consequently, windkesselfunction is lost over a long length of aorta (100-150 mm), leading to significant drop in diastolic pressure [87]. Since, a major portion of the spinal cord blood supply originates from non-compliant stented (left subclavian artery) and distal (intercostal arteries) regions during a hybrid repair, its effect on delayed SCI can be expected. Thus, the possible contribution of extensive coverage of supply arteries along with reduced pressure transmission ability of stented aorta towards SCI indicates that future design of stent-graft devices should take this aspect into consideration.


    7. Improvements and Future Concepts for Hybrid Graft Design

    The use flow diverter stents (FDS) is an emerging technique in treatment of complex aneurysms when endovascular and open surgical procedures are unsuitable. The FDSs are bare stents and designed to reduce the flow velocity vortex within the aneurysm and improve laminar flow in the main artery. When a FDS is placed inside an aneurysm, the blood flow into the sac becomes stagnant which promotes gradual thrombosis and neointimal modelling. At the same time, the blood flow into the branched vessels is maintained. The stent mesh density (or porosity) is an important factor deciding its healing performance and mechanical properties [101]. A mean porosity of 65% is considered optimal to modulate the flow in the sac [102]. The FDSs currently available are used for visceral and peripheral vascular applications which include the Pipeline Embolization Device (PED; ev3, Plymouth, Minn), the SILK Arterial Reconstruction Device (Balt Extrusion, Montmorency, France), and the Cardiatis Multilayer Stent (Cardiatis, Isnes, Belgium). The Cardiatis Multilayer Stent is a self-expanding stent consisting of multilayered braided structure of cobalt alloy wires. The stent is also available in sizes (20-45 mm) suitable of treating aortic aneurysms and has been reported to result in aneurysm thrombosis and aneurysm shrinkage while maintaining collateral branch patency [103,104,105,106]. Since branch vessel coverage is a critical issue during extensive coverage by hybrid stent-graft trunks, FDSs can be specifically beneficial in preventing SCI incidences by maintaining flow to the spinal cord supply vessels. However, the safety of FDSs in large aneurysms experiencing high blood flow rates is still not fully established and risk of aneurysm rupture requires close patient surveillance [107]. Also, the benefits of using FDSs are not immediate and can take months as complete aneurysm thrombosis is not instant and sac pressure can remain critically high during that time [102]. In such cases, with immediate risk of aneurysm rupture, use of covered hybrid stent-grafts is the only option. However, the dynamics of aortic arch and proximal descending aorta are so strong that simple stent-graft designs often fail due to their mismatched mechanical property. The use of even barbs/hooks are sometimes not sufficient to hold a stiff stent-graft in place [108,109], which directly suggests that longitudinal extensibility and flexibility of structure are important requirements especially in curved anatomic locations. However, the challenge is to maintain these features even under cyclic stretching force of high blood pressure inside them. This will require a detailed understanding of vascular wall structure and how aorta maintains its flexibility and extensibility without structural failure throughout its lifetime [110]. The windkesselor cushioning function of aorta has a practical importance as the heart behaves like a cyclic pump and flow fluctuations between phases (systolic and diastolic) can only be smoothed via this function which also relies on structural construction of the aortic wall.

    Based on these understandings, some novel graft designs such as use of bilayered walls which improve graft compliance and match the non-linear extensibility property of the aorta have been trialled recently. Chen et al. fabricated a bilayered graft consisting of Poly(trimethylene terephthalate) filaments for the inner layer and Polyethylene terephthalate (PET) filaments for the outer layer [111]. Poly(trimethylene terephthalate) has a low tensile modulus and good elasticity, and when used as the inner layer of the graft, it increases the compliance of the inner wall. PET used as the outer layer provided a stronger and stiffer covering due to its higher tensile modulus. The two layers were stitched together loosely and such a design enabled only the inner layer of the graft to expand and contract during a low pulsatile pressure. As the pressure increased, the expanded inner layer would come into contact with the outer layer, thus expanding in unison. This resulted in a minimised pressure-induced compliance during high pressure situations, a characteristic that mimicked the native artery.

    Other innovative solutions have utilized biomimetics to investigate biomechanical analogues of an aorta and created graft designs that mimic its multicomponent structure and hence exhibit matched biomechanical attributes, which have the potential to overcome current limitations (Table 1). Stent-graft comprising hard PET and soft spandex segments was created based on the hydroskeleton structure of caterpillars [112]. The biomimetic stent-graft demonstrated better radial compliance (0.0567 ± 0.006 ml/mmHg) than the commercial stent-graft device, Zenith™ FlexSG (0.0117 ± 0.004 ml/mmHg; Cook Medical Inc., USA) and was comparable to human aorta. Additionally, the soft segments were shown to absorb high extension and compression forces with minimal load transfer to the hard segments. This translated to the stent-graft improved flexibility and kink-free bending when pressure increased. These enhanced biomechanical properties also led to the multicomponent stent-graft to migrate less especially when placed in a curved configuration.

    As shown in Table 1, some of the complications such as endoleaks arose due to the inflexibility of the stent-grafts which has been attributed to the rigid Z stent rings. The introduction of new oval ring stent designs in Anaconda® (Vascutek Ltd) and Aorfix® (Lombard medical Inc.) offer promising solutions to achieve better flexibility and kink resistance than Z-type stent rings [113,114]. Finite element analysis showed that the traditional Z-ringed stents were less flexible and as the curvature increased to 180°, the lumen of the stent graft decreased up to 80% as compared to 14.6% for the oval-ringed stents. Unlike the current Z-shape rings, the oval/circular shape of stent rings allows high curvature bending by preventing adjacent stent-stent interlocking which is the main cause of stent-graft collapse in curved aortic regions.

    Although there are no current stent-grafts designed specifically for complex aortic arch aneurysm, there is increased awareness on designing stent-grafts that can be used for curved or complex geometric aneurysm instead of treating them similarly to the straight (abdominal) aneurysms. In addition, it is encouraging that more focus has been placed on addressing the current limitations by designing stent-grafts that are hemodynamically similar to native arteries.


    8. Conclusion

    Biomechanical shortcomings of current stent-grafts such as compliance mismatch and structural stiffness between stent-graft and aorta causes hemodynamic disturbances which can contribute to complications including graft migration, endoleaks, and spinal cord ischemia. A better understanding of factors that cause these complications has led to exploration of improved and innovative graft designs and modifications to produce mechanical properties that are comparable to the aorta. It is anticipated that the next generation of hybrid devices coupled with the current hybrid repair procedure will provide a treatment with fewer complications for patients with complex aneursym.


    Acknowledgments

    This research was partly supported under the Australian Research Council’s Linkage Projects scheme (LP110100678, LP140100287).


    Conflict of Interest

    All authors declare no conflict of interest in this paper.




    [1] R. Hari, M. V. Kujala, Brain basis of human social interaction: from concepts to brain imaging, Physiol. Rev., 89 (2009), 453–479. https://doi.org/10.1152/physrev.00041.2007 doi: 10.1152/physrev.00041.2007
    [2] L. Kingsbury, W. Hong, A multi-brain framework for social interaction, Trends Neurosci., 43 (2020), 651–666. https://doi.org/10.1016/j.tins.2020.06.008 doi: 10.1016/j.tins.2020.06.008
    [3] L. Tsoi, S. M. Burns, E. B. Falk, D. I. Tamir, The promises and pitfalls of functional magnetic resonance imaging hyperscanning for social interaction research, Soc. Pers. Psychol. Compass, 16 (2022), e12707. https://doi.org/10.1111/spc3.12707 doi: 10.1111/spc3.12707
    [4] I. Gordon, S. Wallot, Y. Berson, Group-level physiological synchrony and individual-level anxiety predict positive affective behaviors during a group decision-making task, Psychophysiology, 58 (2021), e13857. https://doi.org/10.1111/psyp.13857 doi: 10.1111/psyp.13857
    [5] V. Reindl, S. Wass, V. Leong, W. Scharke, S. Wistuba, C. L. Wirth, et al., Multimodal hyperscanning reveals that synchrony of body and mind are distinct in mother-child dyads, Neuroimage, 251 (2022), 118982. https://doi.org/10.1016/j.neuroimage.2022.118982 doi: 10.1016/j.neuroimage.2022.118982
    [6] J. Madsen, L. C. Parra, Cognitive processing of a common stimulus synchronizes brains, hearts, and eyes, PNAS Nexus, 1 (2022), pgac020. https://doi.org/10.1093/pnasnexus/pgac020 doi: 10.1093/pnasnexus/pgac020
    [7] L. D. Lotter, S. H. Kohl, C. Gerloff, L. Bell, A. Niephaus, J. A. Kruppa, et al., Revealing the neurobiology underlying interpersonal neural synchronization with multimodal data fusion, Neurosci. Biobehav. Rev., 146 (2023), 105042. https://doi.org/10.1016/j.neubiorev.2023.105042 doi: 10.1016/j.neubiorev.2023.105042
    [8] Y. Pan, G. Novembre, A. Olsson, The interpersonal neuroscience of social learning, Perspect. Psychol. Sci., 17 (2022), 680–695. https://doi.org/10.1177/17456916211008429 doi: 10.1177/17456916211008429
    [9] E. Redcay, L. Schilbach, Using second-person neuroscience to elucidate the mechanisms of social interaction, Nat. Rev. Neurosci., 20 (2019), 495–505. https://doi.org/10.1038/s41583-019-0179-4 doi: 10.1038/s41583-019-0179-4
    [10] L. Schilbach, B. Timmermans, V. Reddy, A. Costall, G. Bente, T. Schlicht, et al., Toward a second-person neuroscience, Behav. Brain Sci., 36 (2013), 393–414. https://doi.org/10.1017/s0140525x12000660 doi: 10.1017/s0140525x12000660
    [11] A. Czeszumski, S. H. Liang, S. Dikker, P. König, C. P. Lee, S. L. Koole, et al., Cooperative behavior evokes interbrain synchrony in the prefrontal and temporoparietal cortex: a systematic review and meta-analysis of fNIRS hyperscanning studies, eNeuro, 9 (2022), ENEURO.0268-21.2022. https://doi.org/10.1523/eneuro.0268-21.2022 doi: 10.1523/eneuro.0268-21.2022
    [12] S. Dikker, L. Wan, I. Davidesco, L. Kaggen, M. Oostrik, J. McClintock, et al., Brain-to-brain synchrony tracks real-world dynamic group interactions in the classroom, Curr. Biol., 27 (2017), 1375–1380. https://doi.org/10.1016/j.cub.2017.04.002 doi: 10.1016/j.cub.2017.04.002
    [13] D. A. Reinero, S. Dikker, J. J. Van Bavel, Inter-brain synchrony in teams predicts collective performance, Social Cognit. Affective Neurosci., 16 (2021), 43–57. https://doi.org/10.1093/scan/nsaa135 doi: 10.1093/scan/nsaa135
    [14] P. Fries, Rhythms for cognition: communication through coherence, Neuron, 88 (2015), 220–235. https://doi.org/10.1016/j.neuron.2015.09.034 doi: 10.1016/j.neuron.2015.09.034
    [15] M. Zee, H. M. Koomen, I. Van der Veen, Student-teacher relationship quality and academic adjustment in upper elementary school: the role of student personality, J. School Psychol., 51 (2013), 517–533. https://doi.org/10.1016/j.jsp.2013.05.003 doi: 10.1016/j.jsp.2013.05.003
    [16] R. Mogan, R. Fischer, J. A. Bulbulia, To be in synchrony or not? A meta-analysis of synchrony's effects on behavior, perception, cognition and affect, J. Exp. Social Psychol., 72 (2017), 13–20. https://doi.org/https://doi.org/10.1016/j.jesp.2017.03.009
    [17] J. Liu, R. Zhang, B. Geng, T. Zhang, D. Yuan, S. Otani, et al., Interplay between prior knowledge and communication mode on teaching effectiveness: Interpersonal neural synchronization as a neural marker, Neuroimage, 193 (2019), 93–102. https://doi.org/10.1016/j.neuroimage.2019.03.004 doi: 10.1016/j.neuroimage.2019.03.004
    [18] Y. Pan, S. Dikker, P. Goldstein, Y. Zhu, C. Yang, Y. Hu, Instructor-learner brain coupling discriminates between instructional approaches and predicts learning, Neuroimage, 211 (2020), 116657. https://doi.org/10.1016/j.neuroimage.2020.116657 doi: 10.1016/j.neuroimage.2020.116657
    [19] K. Yun, K. Watanabe, S. Shimojo, Interpersonal body and neural synchronization as a marker of implicit social interaction, Sci. Rep., 2 (2012), 959. https://doi.org/10.1038/srep00959 doi: 10.1038/srep00959
    [20] J. Levy, A. Goldstein, R. Feldman, Perception of social synchrony induces mother-child gamma coupling in the social brain, Social Cognit. Affective Neurosci., 12 (2017), 1036–1046. https://doi.org/10.1093/scan/nsx032 doi: 10.1093/scan/nsx032
    [21] A. Stolk, M. L. Noordzij, L. Verhagen, I. Volman, J. M. Schoffelen, R. Oostenveld, et al., Cerebral coherence between communicators marks the emergence of meaning, Proc. Natl. Acad. Sci. U.S.A., 111 (2014), 18183–18188. https://doi.org/10.1073/pnas.1414886111 doi: 10.1073/pnas.1414886111
    [22] S. Kinreich, A. Djalovski, L. Kraus, Y. Louzoun, R. Feldman, Brain-to-brain synchrony during naturalistic social interactions, Sci. Rep., 7 (2017), 17060. https://doi.org/10.1038/s41598-017-17339-5 doi: 10.1038/s41598-017-17339-5
    [23] D. M. Ellingsen, A. Duggento, K. Isenburg, C. Jung, J. Lee, J. Gerber, et al., Patient-clinician brain concordance underlies causal dynamics in nonverbal communication and negative affective expressivity, Transl. Psychiatry, 12 (2022), 44. https://doi.org/10.1038/s41398-022-01810-7 doi: 10.1038/s41398-022-01810-7
    [24] M. Schurz, J. Radua, M. G. Tholen, L. Maliske, D. S. Margulies, R. B. Mars, et al., Toward a hierarchical model of social cognition: A neuroimaging meta-analysis and integrative review of empathy and theory of mind, Psychol. Bull., 147 (2021), 293–327. https://doi.org/10.1037/bul0000303 doi: 10.1037/bul0000303
    [25] L. Ficco, L. Mancuso, J. Manuello, A. Teneggi, D. Liloia, S. Duca, et al., Disentangling predictive processing in the brain: a meta-analytic study in favour of a predictive network, Sci. Rep., 11 (2021), 16258. https://doi.org/10.1038/s41598-021-95603-5 doi: 10.1038/s41598-021-95603-5
    [26] G. Rizzolatti, L. Cattaneo, M. Fabbri-Destro, S. Rozzi, Cortical mechanisms underlying the organization of goal-directed actions and mirror neuron-based action understanding, Physiol. Rev., 94 (2014), 655–706. https://doi.org/10.1152/physrev.00009.2013 doi: 10.1152/physrev.00009.2013
    [27] M. Arioli, N. Canessa, Neural processing of social interaction: Coordinate-based meta-analytic evidence from human neuroimaging studies, Hum. Brain Mapp., 40 (2019), 3712–3737. https://doi.org/10.1002/hbm.24627 doi: 10.1002/hbm.24627
    [28] K. Lehmann, D. Bolis, K. J. Friston, L. Schilbach, M. J. D. Ramstead, P. Kanske, An active-inference approach to second-person neuroscience, Perspect. Psychol. Sci., 2023 (2023), 17456916231188000. https://doi.org/10.1177/17456916231188000 doi: 10.1177/17456916231188000
    [29] J. Barnby, G. Bellucci, N. Alon, L. Schilbach, V. Bell, C. Frith, et al., Beyond theory of mind: A formal framework for social inference and representation, PsyarXiv, 2023. https://doi.org/10.31234/osf.io/cmgu7
    [30] D. Wei, S. Tsheringla, J. C. McPartland, A. Allsop, Combinatorial approaches for treating neuropsychiatric social impairment, Philos. Trans. R. Soc. London, Ser. B, 377 (2022), 20210051. https://doi.org/10.1098/rstb.2021.0051 doi: 10.1098/rstb.2021.0051
    [31] T. Penton, C. Catmur, M. J. Banissy, G. Bird, V. Walsh, Non-invasive stimulation of the social brain: the methodological challenges, Social Cognit. Affective Neurosci., 17 (2022), 15–25. https://doi.org/10.1093/scan/nsaa102 doi: 10.1093/scan/nsaa102
    [32] H. K. Kim, D. M. Blumberger, J. Downar, Z. J. Daskalakis, Systematic review of biological markers of therapeutic repetitive transcranial magnetic stimulation in neurological and psychiatric disorders, Clin. Neurophysiol., 132 (2021), 429–448. https://doi.org/10.1016/j.clinph.2020.11.025 doi: 10.1016/j.clinph.2020.11.025
    [33] A. Czeszumski, S. Eustergerling, A. Lang, D. Menrath, M. Gerstenberger, S. Schuberth, et al., Hyperscanning: A valid method to study neural inter-brain underpinnings of social interaction, Front. Hum. Neurosci., 14 (2020), 39. https://doi.org/10.3389/fnhum.2020.00039 doi: 10.3389/fnhum.2020.00039
    [34] A. L. Valencia, T. Froese, What binds us? Inter-brain neural synchronization and its implications for theories of human consciousness, Neurosci. Conscious., 2020 (2020), niaa010. https://doi.org/10.1093/nc/niaa010 doi: 10.1093/nc/niaa010
    [35] U. Hakim, S. De Felice, P. Pinti, X. Zhang, J. A. Noah, Y. Ono, et al., Quantification of inter-brain coupling: A review of current methods used in haemodynamic and electrophysiological hyperscanning studies, Neuroimage, 280 (2023), 120354. https://doi.org/10.1016/j.neuroimage.2023.120354 doi: 10.1016/j.neuroimage.2023.120354
    [36] A. P. Burgess, On the interpretation of synchronization in EEG hyperscanning studies: a cautionary note, Front. Hum. Neurosci., 7 (2013), 881. https://doi.org/10.3389/fnhum.2013.00881 doi: 10.3389/fnhum.2013.00881
    [37] G. Dumas, J. Nadel, R. Soussignan, J. Martinerie, L. Garnero, Inter-brain synchronization during social interaction, PLoS One, 5 (2010), e12166. https://doi.org/10.1371/journal.pone.0012166 doi: 10.1371/journal.pone.0012166
    [38] K. Gugnowska, G. Novembre, N. Kohler, A. Villringer, P. E. Keller, D. Sammler, Endogenous sources of interbrain synchrony in duetting pianists, Cereb. Cortex, 32 (2022), 4110–4127. https://doi.org/10.1093/cercor/bhab469 doi: 10.1093/cercor/bhab469
    [39] W. Peng, W. Lou, X. Huang, Q. Ye, R. K. Tong, F. Cui, Suffer together, bond together: Brain-to-brain synchronization and mutual affective empathy when sharing painful experiences, Neuroimage, 238 (2021), 118249. https://doi.org/10.1016/j.neuroimage.2021.118249 doi: 10.1016/j.neuroimage.2021.118249
    [40] U. Lindenberger, S. C. Li, W. Gruber, V. Müller, Brains swinging in concert: cortical phase synchronization while playing guitar, BMC Neurosci., 10 (2009), 22. https://doi.org/10.1186/1471-2202-10-22 doi: 10.1186/1471-2202-10-22
    [41] V. Müller, U. Lindenberger, Probing associations between interbrain synchronization and interpersonal action coordination during guitar playing, Ann. N. Y. Acad. Sci., 1507 (2022), 146–161. https://doi.org/10.1111/nyas.14689 doi: 10.1111/nyas.14689
    [42] L. Astolfi, J. Toppi, A. Ciaramidaro, P. Vogel, C. M. Freitag, M. Siniatchkin, Raising the bar: Can dual scanning improve our understanding of joint action, Neuroimage, 216 (2020), 116813. https://doi.org/10.1016/j.neuroimage.2020.116813 doi: 10.1016/j.neuroimage.2020.116813
    [43] F. De Vico Fallani, V. Nicosia, R. Sinatra, L. Astolfi, F. Cincotti, D. Mattia, et al., Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements, PLoS One, 5 (2010), e14187. https://doi.org/10.1371/journal.pone.0014187 doi: 10.1371/journal.pone.0014187
    [44] L. Astolfi, J. Toppi, F. De Vico Fallani, G. Vecchiato, S. Salinari, D. Mattia, et al., Neuroelectrical hyperscanning measures simultaneous brain activity in humans, Brain Topogr., 23 (2010), 243–256. https://doi.org/10.1007/s10548-010-0147-9 doi: 10.1007/s10548-010-0147-9
    [45] M. O. Abe, T. Koike, S. Okazaki, S. K. Sugawara, K. Takahashi, K. Watanabe, et al., Neural correlates of online cooperation during joint force production, Neuroimage, 191 (2019), 150–161. https://doi.org/10.1016/j.neuroimage.2019.02.003 doi: 10.1016/j.neuroimage.2019.02.003
    [46] L. Liu, Y. Zhang, Q. Zhou, D. D. Garrett, C. Lu, A. Chen, et al., Auditory-articulatory neural alignment between listener and speaker during verbal communication, Cereb. Cortex, 30 (2020), 942–951. https://doi.org/10.1093/cercor/bhz138 doi: 10.1093/cercor/bhz138
    [47] P. Goldstein, I. Weissman-Fogel, G. Dumas, S. G. Shamay-Tsoory, Brain-to-brain coupling during handholding is associated with pain reduction, Proc. Natl. Acad. Sci. U.S.A., 115 (2018), e2528–e2537. https://doi.org/10.1073/pnas.1703643115 doi: 10.1073/pnas.1703643115
    [48] I. Davidesco, E. Laurent, H. Valk, T. West, S. Dikker, C. Milne, et al., Brain-to-brain synchrony predicts long-term memory retention more accurately than individual brain measures, bioRxiv, (2019), 644047. https://doi.org/10.1101/644047 doi: 10.1101/644047
    [49] Y. Tang, X. Liu, C. Wang, M. Cao, S. Deng, X. Du, et al., Different strategies, distinguished cooperation efficiency, and brain synchronization for couples: An fNIRS-based hyperscanning study, Brain Behav., 10 (2020), e01768. https://doi.org/10.1002/brb3.1768 doi: 10.1002/brb3.1768
    [50] J. Jiang, C. Chen, B. Dai, G. Shi, G. Ding, L. Liu, et al., Leader emergence through interpersonal neural synchronization, Proc. Natl. Acad. Sci. U.S.A., 112 (2015), 4274–4279. https://doi.org/10.1073/pnas.1422930112 doi: 10.1073/pnas.1422930112
    [51] Q. Wang, Z. Han, X. Hu, S. Feng, H. Wang, T. Liu, et al., Autism symptoms modulate interpersonal neural synchronization in children with autism spectrum disorder in cooperative interactions, Brain Topogr., 33 (2020), 112–122. https://doi.org/10.1007/s10548-019-00731-x doi: 10.1007/s10548-019-00731-x
    [52] Y. Hu, Y. Hu, X. Li, Y. Pan, X. Cheng, Brain-to-brain synchronization across two persons predicts mutual prosociality, Social Cognit. Affective Neurosci., 12 (2017), 1835–1844. https://doi.org/10.1093/scan/nsx118 doi: 10.1093/scan/nsx118
    [53] U. Hasson, Y. Nir, I. Levy, G. Fuhrmann, R. Malach, Intersubject synchronization of cortical activity during natural vision, Science, 303 (2004), 1634–1640. https://doi.org/10.1126/science.1089506 doi: 10.1126/science.1089506
    [54] S. A. Nastase, V. Gazzola, U. Hasson, C. Keysers, Measuring shared responses across subjects using intersubject correlation, Social Cognit. Affective Neurosci., 14 (2019), 667–685. https://doi.org/10.1093/scan/nsz037 doi: 10.1093/scan/nsz037
    [55] E. Simony, C. J. Honey, J. Chen, O. Lositsky, Y. Yeshurun, A. Wiesel, et al., Dynamic reconfiguration of the default mode network during narrative comprehension, Nat. Commun., 7 (2016), 12141. https://doi.org/10.1038/ncomms12141 doi: 10.1038/ncomms12141
    [56] J. P. Lachaux, E. Rodriguez, J. Martinerie, F. J. Varela, Measuring phase synchrony in brain signals, Hum. Brain Mapp., 8 (1999), 194–208. https://doi.org/10.1002/(sici)1097-0193(1999)8:4<194::aid-hbm4>3.0.co;2-c doi: 10.1002/(sici)1097-0193(1999)8:4<194::aid-hbm4>3.0.co;2-c
    [57] A. F. C. Hamilton, Hyperscanning: Beyond the hype, Neuron, 109 (2021), 404–407. https://doi.org/10.1016/j.neuron.2020.11.008 doi: 10.1016/j.neuron.2020.11.008
    [58] A. Grinsted, J. C. Moore, S. Jevrejeva, Application of the cross wavelet transform and wavelet coherence to geophysical time series, Nonlin. Processes Geophys., 11 (2004), 561–566. https://doi.org/10.5194/npg-11-561-2004 doi: 10.5194/npg-11-561-2004
    [59] L. S. Wang, J. T. Cheng, I. J. Hsu, S. Liou, C. C. Kung, D. Y. Chen, et al., Distinct cerebral coherence in task-based fMRI hyperscanning: cooperation versus competition, Cereb. Cortex, 33 (2022), 421–433. https://doi.org/10.1093/cercor/bhac075 doi: 10.1093/cercor/bhac075
    [60] A. K. Seth, A. B. Barrett, L. Barnett, Granger causality analysis in neuroscience and neuroimaging, J. Neurosci., 35 (2015), 3293–3297. https://doi.org/10.1523/jneurosci.4399-14.2015 doi: 10.1523/jneurosci.4399-14.2015
    [61] M. B. Schippers, A. Roebroeck, R. Renken, L. Nanetti, C. Keysers, Mapping the information flow from one brain to another during gestural communication, Proc. Natl. Acad. Sci. U.S.A., 107 (2010), 9388–9393. https://doi.org/10.1073/pnas.1001791107 doi: 10.1073/pnas.1001791107
    [62] E. Bilek, P. Zeidman, P. Kirsch, H. Tost, A. Meyer-Lindenberg, K. Friston, Directed coupling in multi-brain networks underlies generalized synchrony during social exchange, Neuroimage, 252 (2022), 119038. https://doi.org/10.1016/j.neuroimage.2022.119038 doi: 10.1016/j.neuroimage.2022.119038
    [63] C. B. Holroyd, Interbrain synchrony: on wavy ground, Trends Neurosci., 45 (2022), 346–357. https://doi.org/10.1016/j.tins.2022.02.002 doi: 10.1016/j.tins.2022.02.002
    [64] Y. Pan, X. Cheng, Two-person approaches to studying social interaction in psychiatry: Uses and clinical relevance, Front. Psychiatry, 11 (2020), 301. https://doi.org/10.3389/fpsyt.2020.00301 doi: 10.3389/fpsyt.2020.00301
    [65] V. Leong, L. Schilbach, The promise of two-person neuroscience for developmental psychiatry: using interaction-based sociometrics to identify disorders of social interaction, Br. J. Psychiatry, 215 (2019), 636–638. https://doi.org/10.1192/bjp.2019.73 doi: 10.1192/bjp.2019.73
    [66] S. V. Wass, M. Whitehorn, I. Marriott Haresign, E. Phillips, V. Leong, Interpersonal neural entrainment during early social interaction, Trends Cognit. Sci., 24 (2020), 329–342. https://doi.org/10.1016/j.tics.2020.01.006 doi: 10.1016/j.tics.2020.01.006
    [67] Y. Pan, G. Novembre, B. Song, X. Li, Y. Hu, Interpersonal synchronization of inferior frontal cortices tracks social interactive learning of a song, Neuroimage, 183 (2018), 280–290. https://doi.org/10.1016/j.neuroimage.2018.08.005 doi: 10.1016/j.neuroimage.2018.08.005
    [68] F. T. Ramseyer, Motion energy analysis (MEA): A primer on the assessment of motion from video, J. Couns. Psychol., 67 (2020), 536–549. https://doi.org/10.1037/cou0000407 doi: 10.1037/cou0000407
    [69] Z. Cao, G. Hidalgo, T. Simon, S. E. Wei, Y. Sheikh, OpenPose: Realtime multi-person 2D pose estimation using part affinity fields, IEEE Trans. Pattern Anal. Mach. Intell., 43 (2021), 172–186. https://doi.org/10.1109/tpami.2019.2929257 doi: 10.1109/tpami.2019.2929257
    [70] S. Guglielmini, G. Bopp, V. L. Marcar, F. Scholkmann, M. Wolf, Systemic physiology augmented functional near-infrared spectroscopy hyperscanning: a first evaluation investigating entrainment of spontaneous activity of brain and body physiology between subjects, Neurophotonics, 9 (2022), 026601. https://doi.org/10.1117/1.NPh.9.2.026601 doi: 10.1117/1.NPh.9.2.026601
    [71] R. Cañigueral, S. Krishnan-Barman, A. F. C. Hamilton, Social signalling as a framework for second-person neuroscience, Psychon. Bull. Rev., 29 (2022), 2083–2095. https://doi.org/10.3758/s13423-022-02103-2 doi: 10.3758/s13423-022-02103-2
    [72] L. Kingsbury, S. Huang, J. Wang, K. Gu, P. Golshani, Y. E. Wu, et al., Correlated neural activity and encoding of behavior across brains of socially interacting animals, Cell, 178 (2019), 429–446.e416. https://doi.org/10.1016/j.cell.2019.05.022 doi: 10.1016/j.cell.2019.05.022
    [73] V. Müller, D. Perdikis, M. A. Mende, U. Lindenberger, Interacting brains coming in sync through their minds: an interbrain neurofeedback study, Ann. N. Y. Acad. Sci., 1500 (2021), 48–68. https://doi.org/10.1111/nyas.14605 doi: 10.1111/nyas.14605
    [74] L. Duan, W. J. Liu, R. N. Dai, R. Li, C. M. Lu, Y. X. Huang, et al., Cross-brain neurofeedback: scientific concept and experimental platform, PLoS One, 8 (2013), e64590. https://doi.org/10.1371/journal.pone.0064590 doi: 10.1371/journal.pone.0064590
    [75] S. Dikker, G. Michalareas, M. Oostrik, A. Serafimaki, H. M. Kahraman, M. E. Struiksma, et al., Crowdsourcing neuroscience: Inter-brain coupling during face-to-face interactions outside the laboratory, Neuroimage, 227 (2021), 117436. https://doi.org/10.1016/j.neuroimage.2020.117436 doi: 10.1016/j.neuroimage.2020.117436
    [76] M. Hallett, Transcranial magnetic stimulation and the human brain, Nature, 406 (2000), 147–150. https://doi.org/10.1038/35018000 doi: 10.1038/35018000
    [77] J. Vosskuhl, D. Struber, C. S. Herrmann, Non-invasive brain stimulation: A paradigm shift in understanding brain oscillations, Front. Hum. Neurosci., 12 (2018), 211. https://doi.org/10.3389/fnhum.2018.00211 doi: 10.3389/fnhum.2018.00211
    [78] A. Liu, M. Vöröslakos, G. Kronberg, S. Henin, M. R. Krause, Y. Huang, et al., Immediate neurophysiological effects of transcranial electrical stimulation, Nat. Commun., 9 (2018), 5092. https://doi.org/10.1038/s41467-018-07233-7 doi: 10.1038/s41467-018-07233-7
    [79] C. S. Herrmann, M. M. Murray, S. Ionta, A. Hutt, J. Lefebvre, Shaping intrinsic neural oscillations with periodic stimulation, J. Neurosci., 36 (2016), 5328–5337. https://doi.org/10.1523/jneurosci.0236-16.2016 doi: 10.1523/jneurosci.0236-16.2016
    [80] S. Alagapan, S. L. Schmidt, J. Lefebvre, E. Hadar, H. W. Shin, F. Frӧhlich, Modulation of cortical oscillations by low-frequency direct cortical stimulation is state-dependent, PloS Biol., 14 (2016), e1002424. https://doi.org/10.1371/journal.pbio.1002424 doi: 10.1371/journal.pbio.1002424
    [81] N. Takeuchi, Perspectives on rehabilitation using non-invasive brain stimulation based on second-person neuroscience of teaching-learning interactions, Front. Psychol., 12 (2022), 789637. https://doi.org/10.3389/fpsyg.2021.789637 doi: 10.3389/fpsyg.2021.789637
    [82] Y. Cabral-Calderin, M. Wilke, Probing the link between perception and oscillations: Lessons from transcranial alternating current stimulation, Neuroscientist, 26 (2020), 57–73. https://doi.org/10.1177/1073858419828646 doi: 10.1177/1073858419828646
    [83] V. Müller, U. Lindenberger, Hyper-brain networks support romantic kissing in humans, PloS One, 9 (2014), e112080. https://doi.org/10.1371/journal.pone.0112080 doi: 10.1371/journal.pone.0112080
    [84] J. Toppi, G. Borghini, M. Petti, E. J. He, V. De Giusti, B. He, et al., Investigating cooperative behavior in ecological settings: An EEG hyperscanning study, PloS One, 11 (2016), e0154236. https://doi.org/10.1371/journal.pone.0154236 doi: 10.1371/journal.pone.0154236
    [85] V. Leong, E. Byrne, K. Clackson, S. Georgieva, S. Lam, S. Wass, Speaker gaze increases information coupling between infant and adult brains, Proc. Natl. Acad. Sci. U.S.A., 114 (2017), 13290–13295. https://doi.org/10.1073/pnas.1702493114 doi: 10.1073/pnas.1702493114
    [86] Y. Mu, C. Guo, S. Han, Oxytocin enhances inter-brain synchrony during social coordination in male adults, Social Cognit. Affective Neurosci., 11 (2016), 1882–1893. https://doi.org/10.1093/scan/nsw106 doi: 10.1093/scan/nsw106
    [87] O. A. Heggli, I. Konvalinka, J. Cabral, E. Brattico, M. L. Kringelbach, P. Vuust, Transient brain networks underlying interpersonal strategies during synchronized action, Social Cognit. Affective Neurosci., 16 (2021), 19–30. https://doi.org/10.1093/scan/nsaa056 doi: 10.1093/scan/nsaa056
    [88] A. Pérez, M. Carreiras, J. A. Duñabeitia, Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening, Sci. Rep., 7 (2017), 4190. https://doi.org/10.1038/s41598-017-04464-4 doi: 10.1038/s41598-017-04464-4
    [89] J. Sünger, V. Müller, U. Lindenberger, Directionality in hyperbrain networks discriminates between leaders and followers in guitar duets, Front. Hum. Neurosci., 7 (2013), 234. https://doi.org/10.3389/fnhum.2013.00234 doi: 10.3389/fnhum.2013.00234
    [90] Y. Mu, S. Han, M. J. Gelfand, The role of gamma interbrain synchrony in social coordination when humans face territorial threats, Social Cognit. Affective Neurosci., 12 (2017), 1614–1623. https://doi.org/10.1093/scan/nsx093 doi: 10.1093/scan/nsx093
    [91] N. Kopell, G. B. Ermentrout, M. A. Whittington, R. D. Traub, Gamma rhythms and beta rhythms have different synchronization properties, Proc. Natl. Acad. Sci. U.S.A., 97 (2000), 1867–1872. https://doi.org/10.1073/pnas.97.4.1867 doi: 10.1073/pnas.97.4.1867
    [92] P. J. Uhlhaas, W. Singer, Neuronal dynamics and neuropsychiatric disorders: toward a translational paradigm for dysfunctional large-scale networks, Neuron, 75 (2012), 963–980. https://doi.org/10.1016/j.neuron.2012.09.004 doi: 10.1016/j.neuron.2012.09.004
    [93] K. J. Friston, T. Parr, Y. Yufik, N. Sajid, C. J. Price, E. Holmes, Generative models, linguistic communication and active inference, Neurosci. Biobehav. Rev., 118 (2020), 42–64. https://doi.org/10.1016/j.neubiorev.2020.07.005 doi: 10.1016/j.neubiorev.2020.07.005
    [94] E. Tognoli, J. A. Kelso, The coordination dynamics of social neuromarkers, Front. Hum. Neurosci., 9 (2015), 563. https://doi.org/10.3389/fnhum.2015.00563 doi: 10.3389/fnhum.2015.00563
    [95] C. Peylo, Y. Hilla, P. Sauseng, Cause or consequence? Alpha oscillations in visuospatial attention, Trends Neurosci., 44 (2021), 705–713. https://doi.org/10.1016/j.tins.2021.05.004 doi: 10.1016/j.tins.2021.05.004
    [96] W. Klimesch, α-band oscillations, attention, and controlled access to stored information, Trends Cognit. Sci., 16 (2012), 606–617. https://doi.org/10.1016/j.tics.2012.10.007 doi: 10.1016/j.tics.2012.10.007
    [97] S. Hoehl, M. Fairhurst, A. Schirmer, Interactional synchrony: signals, mechanisms and benefits, Social Cognit. Affective Neurosci., 16 (2021), 5–18. https://doi.org/10.1093/scan/nsaa024 doi: 10.1093/scan/nsaa024
    [98] N. J. Davis, S. P. Tomlinson, H. M. Morgan, The role of beta-frequency neural oscillations in motor control, J. Neurosci., 32 (2012), 403–404. https://doi.org/10.1523/jneurosci.5106-11.2012 doi: 10.1523/jneurosci.5106-11.2012
    [99] B. Pollok, D. Latz, V. Krause, M. Butz, A. Schnitzler, Changes of motor-cortical oscillations associated with motor learning, Neuroscience, 275 (2014), 47–53. https://doi.org/10.1016/j.neuroscience.2014.06.008 doi: 10.1016/j.neuroscience.2014.06.008
    [100] V. Müller, J. Sünger, U. Lindenberger, Intra- and inter-brain synchronization during musical improvisation on the guitar, PloS One, 8 (2013), e73852. https://doi.org/10.1371/journal.pone.0073852 doi: 10.1371/journal.pone.0073852
    [101] C. S. Herrmann, D. Strüber, R. F. Helfrich, A. K. Engel, EEG oscillations: From correlation to causality, Int. J. Psychophysiol., 103 (2016), 12–21. https://doi.org/10.1016/j.ijpsycho.2015.02.003 doi: 10.1016/j.ijpsycho.2015.02.003
    [102] S. H. Williams, D. Johnston, Kinetic properties of two anatomically distinct excitatory synapses in hippocampal CA3 pyramidal neurons, J. Neurophysiol., 66 (1991), 1010–1020. https://doi.org/10.1152/jn.1991.66.3.1010 doi: 10.1152/jn.1991.66.3.1010
    [103] G. Novembre, G. Knoblich, L. Dunne, P. E. Keller, Interpersonal synchrony enhanced through 20 Hz phase-coupled dual brain stimulation, Social Cognit. Affective Neurosci., 12 (2017), 662–670. https://doi.org/10.1093/scan/nsw172 doi: 10.1093/scan/nsw172
    [104] C. Szymanski, V. Müller, T. R. Brick, T. von Oertzen, U. Lindenberger, Hyper-transcranial alternating current stimulation: experimental manipulation of inter-brain synchrony, Front. Hum. Neurosci., 11 (2017), 539. https://doi.org/10.3389/fnhum.2017.00539 doi: 10.3389/fnhum.2017.00539
    [105] Y. Pan, G. Novembre, B. Song, Y. Zhu, Y. Hu, Dual brain stimulation enhances interpersonal learning through spontaneous movement synchrony, Social Cognit. Affective Neurosci., 16 (2021), 210–221. https://doi.org/10.1093/scan/nsaa080 doi: 10.1093/scan/nsaa080
    [106] R. T. Canolty, R. T. Knight, The functional role of cross-frequency coupling, Trends Cognit. Sci., 14 (2010), 506–515. https://doi.org/10.1016/j.tics.2010.09.001 doi: 10.1016/j.tics.2010.09.001
    [107] B. Asamoah, A. Khatoun, M. Mc Laughlin, tACS motor system effects can be caused by transcutaneous stimulation of peripheral nerves, Nat. Commun., 10 (2019), 266. https://doi.org/10.1038/s41467-018-08183-w doi: 10.1038/s41467-018-08183-w
    [108] G. Novembre, G. D. Iannetti, Hyperscanning alone cannot prove causality. Multibrain stimulation can, Trends Cognit. Sci., 25 (2021), 96–99. https://doi.org/10.1016/j.tics.2020.11.003 doi: 10.1016/j.tics.2020.11.003
    [109] S. L. Koole, W. Tschacher, Synchrony in psychotherapy: A review and an integrative framework for the therapeutic alliance, Front. Psychol., 7 (2016), 862. https://doi.org/10.3389/fpsyg.2016.00862 doi: 10.3389/fpsyg.2016.00862
    [110] M. Bishop, N. Kayes, K. McPherson, Understanding the therapeutic alliance in stroke rehabilitation, Disability Rehabil., 43 (2021), 1074–1083. https://doi.org/10.1080/09638288.2019.1651909 doi: 10.1080/09638288.2019.1651909
    [111] P. Søndenå, G. Dalusio-King, C. Hebron, Conceptualisation of the therapeutic alliance in physiotherapy: is it adequate, Musculoskeletal Sci. Pract., 46 (2020), 102131. https://doi.org/10.1016/j.msksp.2020.102131 doi: 10.1016/j.msksp.2020.102131
    [112] P. Mistiaen, M. van Osch, L. van Vliet, J. Howick, F. L. Bishop, Z. Di Blasi, et al., The effect of patient-practitioner communication on pain: a systematic review, Eur. J. Pain, 20 (2016), 675–688. https://doi.org/10.1002/ejp.797 doi: 10.1002/ejp.797
    [113] L. Schilbach, Towards a second-person neuropsychiatry, Philos. Trans. R. Soc. London, Ser. B, 371 (2016), 20150081. https://doi.org/10.1098/rstb.2015.0081 doi: 10.1098/rstb.2015.0081
    [114] L. Schilbach, J. M. Lahnakoski, Clinical neuroscience meets second-person neuropsychiatry, in Social and Affective Neuroscience of Everyday Human Interaction: From Theory to Methodology, Cham (CH): Springer, (2023), 177–191.
    [115] L. E. Quiñones-Camacho, F. A. Fishburn, K. Belardi, D. L. Williams, T. J. Huppert, S. B. Perlman, Dysfunction in interpersonal neural synchronization as a mechanism for social impairment in autism spectrum disorder, Autism Res., 14 (2021), 1585–1596. https://doi.org/10.1002/aur.2513 doi: 10.1002/aur.2513
    [116] E. Bilek, G. Stößel, A. Schüfer, L. Clement, M. Ruf, L. Robnik, et al., State-dependent cross-brain information flow in borderline personality disorder, JAMA Psychiatry, 74 (2017), 949–957. https://doi.org/10.1001/jamapsychiatry.2017.1682 doi: 10.1001/jamapsychiatry.2017.1682
    [117] Y. Zhang, T. Meng, Y. Hou, Y. Pan, Y. Hu, Interpersonal brain synchronization associated with working alliance during psychological counseling. Psychiatry Res. Neuroimaging, 282 (2018), 103–109. https://doi.org/10.1016/j.pscychresns.2018.09.007 doi: 10.1016/j.pscychresns.2018.09.007
    [118] N. Takeuchi, T. Mori, Y. Suzukamo, S. I. Izumi, Integration of teaching processes and learning assessment in the prefrontal cortex during a video game teaching-learning task, Front. Psychol., 7 (2017), 2052. https://doi.org/10.3389/fpsyg.2016.02052 doi: 10.3389/fpsyg.2016.02052
    [119] L. Zheng, C. Chen, W. Liu, Y. Long, H. Zhao, X. Bai, et al., Enhancement of teaching outcome through neural prediction of the students' knowledge state, Hum. Brain Mapp., 39 (2018), 3046–3057. https://doi.org/10.1002/hbm.24059 doi: 10.1002/hbm.24059
    [120] L. Zhang, X. Xu, Z. Li, L. Chen, L. Feng, Interpersonal neural synchronization predicting learning outcomes from teaching-learning interaction: A Meta-analysis, Front. Psychol., 13 (2022), 835147. https://doi.org/10.3389/fpsyg.2022.835147 doi: 10.3389/fpsyg.2022.835147
    [121] S. M. Fleming, R. J. Dolan, The neural basis of metacognitive ability, Philos. Trans. R. Soc. London, Ser. B, 367 (2012), 1338–1349. https://doi.org/10.1098/rstb.2011.0417 doi: 10.1098/rstb.2011.0417
    [122] A. G. Vaccaro, S. M. Fleming, Thinking about thinking: A coordinate-based meta-analysis of neuroimaging studies of metacognitive judgements, Brain Neurosci. Adv., 2 (2018), 2398212818810591. https://doi.org/10.1177/2398212818810591 doi: 10.1177/2398212818810591
    [123] J. F. Martín-Rodríguez, J. León-Carrión, Theory of mind deficits in patients with acquired brain injury: a quantitative review, Neuropsychologia, 48 (2010), 1181–1191. https://doi.org/10.1016/j.neuropsychologia.2010.02.009 doi: 10.1016/j.neuropsychologia.2010.02.009
    [124] M. Al Banna, N. A. Redha, F. Abdulla, B. Nair, C. Donnellan, Metacognitive function poststroke: a review of definition and assessment, J. Neurol. Neurosurg. Psychiatry, 87 (2016), 161–166. https://doi.org/10.1136/jnnp-2015-310305 doi: 10.1136/jnnp-2015-310305
    [125] B. Nijsse, J. M. Spikman, J. M. A. Visser-Meily, P. L. M. de Kort, C. M. van Heugten, Social cognition impairments are associated with behavioural changes in the long term after stroke, PloS One, 14 (2019), e0213725. https://doi.org/10.1371/journal.pone.0213725 doi: 10.1371/journal.pone.0213725
    [126] Y. X. Yeo, C. F. Pestell, R. S. Bucks, F. Allanson, M. Weinborn, Metacognitive knowledge and functional outcomes in adults with acquired brain injury: A meta-analysis, Neuropsychol. Rehabil., 31 (2021), 453–478. https://doi.org/10.1080/09602011.2019.1704421 doi: 10.1080/09602011.2019.1704421
    [127] P. Lakatos, J. Gross, G. Thut, A new unifying account of the roles of neuronal entrainment, Curr. Biol., 29 (2019), R890–R905. https://doi.org/10.1016/j.cub.2019.07.075 doi: 10.1016/j.cub.2019.07.075
    [128] K. B. Jensen, P. Petrovic, C. E. Kerr, I. Kirsch, J. Raicek, A. Cheetham, et al., Sharing pain and relief: neural correlates of physicians during treatment of patients, Mol. Psychiatry, 19 (2014), 392–398. https://doi.org/10.1038/mp.2012.195 doi: 10.1038/mp.2012.195
    [129] S. G. Shamay-Tsoory, N. I. Eisenberger, Getting in touch: A neural model of comforting touch, Neurosci. Biobehav. Rev., 130 (2021), 263–273. https://doi.org/10.1016/j.neubiorev.2021.08.030 doi: 10.1016/j.neubiorev.2021.08.030
    [130] B. M. Fitzgibbon, M. J. Giummarra, N. Georgiou-Karistianis, P. G. Enticott, J. L. Bradshaw, Shared pain: from empathy to synaesthesia, Neurosci. Biobehav. Rev., 34 (2010), 500–512. https://doi.org/10.1016/j.neubiorev.2009.10.007 doi: 10.1016/j.neubiorev.2009.10.007
    [131] D. M. Ellingsen, K. Isenburg, C. Jung, J. Lee, J. Gerber, I. Mawla, et al., Dynamic brain-to-brain concordance and behavioral mirroring as a mechanism of the patient-clinician interaction, Sci. Adv., 6 (2020), eabc1304. https://doi.org/10.1126/sciadv.abc1304 doi: 10.1126/sciadv.abc1304
    [132] T. J. Kaptchuk, F. G. Miller, Placebo effects in medicine, N. Engl. J. Med., 373 (2015), 8–9. https://doi.org/10.1056/NEJMp1504023 doi: 10.1056/NEJMp1504023
    [133] M. Ienca, R. W. Kressig, F. Jotterand, B. Elger, Proactive ethical design for neuroengineering, assistive and rehabilitation technologies: the cybathlon lesson, J. Neuroeng. Rehabil., 14 (2017), 115. https://doi.org/10.1186/s12984-017-0325-z doi: 10.1186/s12984-017-0325-z
    [134] R. Cohen Kadosh, N. Levy, J. O'Shea, N. Shea, J. Savulescu, The neuroethics of non-invasive brain stimulation, Curr. Biol., 22 (2012), R108–111. https://doi.org/10.1016/j.cub.2012.01.013 doi: 10.1016/j.cub.2012.01.013
    [135] S. G. Shamay-Tsoory, Brains that fire together wire together: Interbrain plasticity underlies learning in social interactions, Neuroscientist, 28 (2022), 543–551. https://doi.org/10.1177/1073858421996682 doi: 10.1177/1073858421996682
    [136] A. Gramfort, M. Luessi, E. Larson, D. A. Engemann, D. Strohmeier, C. Brodbeck, et al., MNE software for processing MEG and EEG data, Neuroimage, 86 (2014), 446–460. https://doi.org/10.1016/j.neuroimage.2013.10.027 doi: 10.1016/j.neuroimage.2013.10.027
    [137] R. D. Pascual-Marqui, C. M. Michel, D. Lehmann, Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain, Int. J. Psychophysiol., 18 (1994), 49–65. https://doi.org/10.1016/0167-8760(84)90014-x doi: 10.1016/0167-8760(84)90014-x
    [138] J. Onton, M. Westerfield, J. Townsend, S. Makeig, Imaging human EEG dynamics using independent component analysis, Neurosci. Biobehav. Rev., 30 (2006), 808–822. https://doi.org/10.1016/j.neubiorev.2006.06.007 doi: 10.1016/j.neubiorev.2006.06.007
    [139] C. S. Nam, Z. Traylor, M. Chen, X. Jiang, W. Feng, P. Y. Chhatbar, Direct communication between brains: A systematic PRISMA review of brain-to-brain interface, Front. Neurorobot., 15 (2021), 656943. https://doi.org/10.3389/fnbot.2021.656943 doi: 10.3389/fnbot.2021.656943
    [140] G. Thut, T. O. Bergmann, F. Fröhlich, S. R. Soekadar, J. S. Brittain, A. Valero-Cabré, et al., Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions: A position paper, Clin. Neurophysiol., 128 (2017), 843–857. https://doi.org/10.1016/j.clinph.2017.01.003 doi: 10.1016/j.clinph.2017.01.003
    [141] S. Kohli, A. J. Casson, Removal of gross artifacts of transcranial alternating current stimulation in simultaneous EEG monitoring, Sensors (Basel), 19 (2019), 190. https://doi.org/10.3390/s19010190 doi: 10.3390/s19010190
    [142] D. Bolis, J. Balsters, N. Wenderoth, C. Becchio, L. Schilbach, Beyond autism: introducing the dialectical misattunement hypothesis and a Bayesian account of intersubjectivity, Psychopathology, 50 (2017), 355–372. https://doi.org/10.1159/000484353 doi: 10.1159/000484353
    [143] G. Zarubin, C. Gundlach, V. Nikulin, A. Villringer, M. Bogdan, Transient amplitude modulation of alpha-band oscillations by short-time intermittent closed-loop tACS, Front. Hum. Neurosci., 14 (2020), 366. https://doi.org/10.3389/fnhum.2020.00366 doi: 10.3389/fnhum.2020.00366
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2423) PDF downloads(251) Cited by(0)

Article outline

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog