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W2984652593 abstract "Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract To understand brain circuits it is necessary both to record and manipulate their activity. Transcranial ultrasound stimulation (TUS) is a promising non-invasive brain stimulation technique. To date, investigations report short-lived neuromodulatory effects, but to deliver on its full potential for research and therapy, ultrasound protocols are required that induce longer-lasting ‘offline’ changes. Here, we present a TUS protocol that modulates brain activation in macaques for more than one hour after 40 s of stimulation, while circumventing auditory confounds. Normally activity in brain areas reflects activity in interconnected regions but TUS caused stimulated areas to interact more selectively with the rest of the brain. In a within-subject design, we observe regionally specific TUS effects for two medial frontal brain regions – supplementary motor area and frontal polar cortex. Independently of these site-specific effects, TUS also induced signal changes in the meningeal compartment. TUS effects were temporary and not associated with microstructural changes. https://doi.org/10.7554/eLife.40541.001 eLife digest Ultrasound is well known for making visible what is hidden, for example, when giving parents a glimpse of their child before birth. But researchers are now using these high-frequency sound waves – beyond the range of human hearing – for a wholly different purpose: to manipulate the activity of the brain. Conventional brain stimulation techniques use electric currents or magnetic fields to alter brain activity. These techniques, however, have limitations. They can only reach the surface of the brain and are not particularly precise. By contrast, beams of ultrasound can be focused at a millimetre scale, even deep within the brain. Ultrasound thus has the potential to provide new insights into how the brain works. Most studies of ultrasound stimulation have looked at what happens to the brain during the stimulation itself. But could ultrasound also induce longer-lasting changes in brain activity? Changes that persist after the stimulation has ended would be valuable for research. They would also make it more likely that we could use ultrasound to treat brain disorders by changing brain activity. Verhagen, Gallea et al. used a brain scanner to measure brain activity in macaque monkeys after ultrasound stimulation. The results showed that 40 seconds of repetitive ultrasound changed brain activity for up to two hours. Ultrasound caused the stimulated brain area to interact more selectively with the rest of the brain. Notably, only the stimulated area changed its activity in this way. This helps rule out the possibility that the changes reflect non-specific effects. If the monkeys had been able to hear the ultrasound, for example, it would have changed the activity of the parts of the brain related to hearing. Most important of all, the changes were reversible and did not harm the brain. The results of Verhagen, Gallea et al. show that repetitive ultrasound can induce long-lasting alterations in brain activity. It can target areas deep within the brain, including those that are out of reach with other techniques. If this procedure also shows longer-lasting effects in people, it could yield valuable insights into the links between brain and behaviour. It could also help us develop new treatments for neurological and psychiatric disorders. https://doi.org/10.7554/eLife.40541.002 Introduction In neuroscience, to understand brain circuits a two-pronged approach, entailing both recording and manipulating brain activity, is essential. In recent years, there has been extensive progress in this field, which was in part made possible by the availability of new technologies (Bestmann and Walsh, 2017; Dayan et al., 2013; Polanía et al., 2018). While techniques for transiently manipulating activity in rodents, such as microstimulation, optogenetics, and chemogenetics (Sternson and Roth, 2014; Vanduffel, 2016), are increasingly accessible and applied, techniques for manipulating activity in the primate brain are less widely available and remain accessible to comparatively few researchers in a limited number of research centres worldwide (Galvan et al., 2018; Krug et al., 2015; Vanduffel, 2016). A prominent limitation for many brain stimulation tools for research and therapeutic interventions is the duration of the induced neuromodulatory effects, often not outlasting the stimulation by more than a few seconds or minutes. Here we report on a particular protocol of low intensity pulsed transcranial focused ultrasound stimulation (TUS) that we show induces a sustained period of neuromodulation in primates without inducing structural damage. The TUS approach in general is a relatively new one (Dallapiazza et al., 2018; Tufail et al., 2011; Tyler et al., 2018; Yoo et al., 2011; Younan et al., 2013) and like transcranial magnetic stimulation (Dayan et al., 2013) and transcranial electric stimulation (Polanía et al., 2018) it can be applied in the absence of a craniotomy. In vitro recordings have identified several mechanisms by which ultrasound stimulation could affect neurons. It has been proposed that the sound pressure wave exerts a mechanical effect on neuronal activity through ion channel gating and changes to the membrane capacitance (Blackmore et al., 2018; Kubanek et al., 2018; Kubanek et al., 2016; Prieto et al., 2013). While the precise mechanism is being determined, early applications, including the current results, suggest TUS may be suitable as a tool for focal manipulation of activity in many brain areas in primates (Fomenko et al., 2018; Lee et al., 2016a; Legon et al., 2018; Munoz et al., 2018; Naor et al., 2016; Tufail et al., 2011; Tyler et al., 2018; Yoo et al., 2011). In the macaque, its application over the frontal eye field (FEF) affects the same aspects of oculomotor behaviour that are compromised by FEF lesion, whilst leaving intact those aspects of oculomotor behaviour that are unaffected by FEF lesion (Deffieux et al., 2013). Pioneering work in humans has focused on modulating and eliciting evoked responses by focused ultrasound in both cortical and subcortical sensorimotor regions (Lee et al., 2016a; Lee et al., 2015; Legon et al., 2018; Legon et al., 2014). To date ultrasonic applications are primarily focused on direct ‘online’ effects. Nonetheless, some studies have observed neuromodulatory effects outlasting the sonication by several minutes before returning to baseline, with more pronounced effects for protocols delivered at higher intensities (Isppa >5 W/cm2) and higher duty cycles (>5%; Kim et al., 2015; Yoo et al., 2011). For example, following ultrasound protocols with a relatively high rate of acoustic energy deposition, characterized by pulses tens of milliseconds long, repeated at 10 Hz, the neuromodulatory effects outlast the sonication period: for up to 10 min following 43.7 ms long 1.14MHz pulses repeated at 10 Hz for 40 s (Dallapiazza et al., 2018), or for up to 20 min following 30 ms long 350 kHz pulses repeated at 10 Hz for 40 s (Ahnine et al., 2018). We have built on such protocols when designing the current experiment. Recent work has highlighted the possibility that in rodents some TUS protocols can evoke a startle response when the stimulation is modulated at audible frequencies (Guo et al., 2018; Sato et al., 2018). Importantly, this auditory effect is limited to the stimulation period and dissipates within 75 ms to 4 s. This work has also emphasized that in more deeply anaesthetized animals, when the intrinsic neural activity of a system is suppressed, some TUS protocols might fail to evoke action potentials at the site of stimulation. This suggests TUS’ actions might be primarily neuromodulatory in nature and/or that they are most prominently observable when they interact with ongoing physiological activity. However, as has been noted (Airan and Butts Pauly, 2018) the impact that any stimulation protocol might have, will be a function of the animal model being used and the precise details of the ultrasound frequencies, pulse shape, protocol, and ongoing brain activity. With the offline protocol and anaesthesia regime we used we control for such potential artefacts and show that TUS has an effect that cannot be attributed to them. Here we focused on the effects of TUS outlasting the stimulation period, investigating the impact of 40 s trains of TUS on measurements of neural activity in three macaque monkeys provided by functional magnetic resonance imaging (fMRI) up to 2 hr after stimulation (Figure 1, top panel). FMRI is one of the most widely used methods for estimating neural activity. Despite limitations in its spatial and temporal resolution, fMRI remains important because it is non-invasive and can often be used to provide information about activity throughout the whole brain. Rather than providing a direct measure of neural activity, however, it provides an estimate of how activity changes in tandem with sensory, cognitive, or motor events or with activity in another brain region. Typically, fMRI-measured activity in any given brain area is a function of activity in other brain areas, especially those with which it is closely interconnected (Neubert et al., 2015; O'Reilly et al., 2013). Although many brain areas may share any given individual connection (for example both areas A and B may project to C), the overall pattern of connections of each area is unique (Passingham et al., 2002); as such, the overall pattern of connections therefore constitutes a ‘connectional fingerprint’. As a result it is possible to use fMRI measurements of correlations in the blood oxygen level dependent (BOLD) signal across brain regions to estimate the connectivity fingerprints of a given brain area (Figure 1, bottom right panel; Caspari et al., 2018; Ghahremani et al., 2017; Margulies et al., 2016, Margulies et al., 2009; Mars et al., 2013; Sallet et al., 2013; Shen, 2015; Shen et al., 2015). This implies that activity in any given brain area is a function of the activity in the areas with which it is interconnected. Figure 1 Download asset Open asset Overview of the experimental design, time-line, pre-processing pipeline, and analysis strategy. Top panel: The same three macaque monkeys (MK1, MK2, MK3) participated in experiments 1 and 2, and a control experiment conducted in the absence of TUS. Three other monkeys (MK4, MK5, MK6) participated in experiment 3. In all experiments anaesthesia was induced ~1.45 hr before the TUS intervention or no-TUS control. In experiment 1 the 40 s TUS protocol was delivered over the supplementary motor area (SMA), while in experiments 2 and 3, the protocol was targeted at frontal polar cortex (FPC). In all sessions, three consecutive runs of resting fMRI (26 min per run) were acquired starting ~40 min after the TUS or control protocol. Bottom left panel: Data from the resting fMRI runs were pre-processed following a standardized pipeline to address artefacts, improve image quality and signal-to-noise ratio, and prepare for connectivity analyses. By default, non-neuronal confounds were removed from the timeseries, but to allow an analysis of the effect of TUS on non-neuronal signal the data was also processed in parallel in a second pipeline, distinct from the default by omitting the non-neuronal confound regression procedure. Bottom right panel: The effect of TUS on the coupling patterns of the stimulated regions were quantified as ‘connectional fingerprints’ employing pre-defined targets (here illustrated for the SMA in the control state). These fingerprint analyses allowed us to test for the presence and duration of TUS effects in the stimulated areas (SMA after SMA TUS; FPC after FPC TUS), and in control areas, including non-stimulated areas (FPC after SMA TUS; SMA after FPC TUS) and the auditory cortex. Whole brain connectivity maps supported exploratory analyses and an assessment of the impact of TUS on non-neuronal signal (here illustrated for SMA in the control state). https://doi.org/10.7554/eLife.40541.003 We exploited this feature of activity to examine the impact of TUS application to two brain regions in the frontal cortex: supplementary motor area (SMA; experiment 1) and frontal polar cortex (FPC; experiments 2 and 3). Simulations showed we were able to selectively target these regions (Figure 2; see Acoustic and thermal modelling for more details). These regions have distinct anatomical and functional connections; SMA is most strongly coupled with the sensorimotor system, while the FPC interacts primarily with the prefrontal cortex and only interacts indirectly with the sensorimotor system via SMA (Petrides and Pandya, 2007; Sallet et al., 2013). This allows us to test the spatial and connectional specificity of TUS effects. In the control state, each area’s activity is normally a function of the activity in the areas that constitute its connectional fingerprint. If this pattern is altered by TUS in a manner that is dependent on the location of the stimulation, then this will constitute evidence that TUS exerts a spatially selective effect on neural activity. In a within-subject design, the same three animals participated in experiments 1 and 2, and a control experiment conducted in the absence of TUS (Figure 1). As such, fMRI was acquired in three conditions for all animals: following SMA TUS, following FPC TUS, and in a control state. In turn, each of the MRI sessions consisted of three consecutive runs. We also validated the results of experiment two in a new set of three different animals (experiment 3). Figure 2 Download asset Open asset Stimulation targets and thermal modelling. (a) Stimulation target positions in SMA are shown for each of the three individual animals in three different colours on sagittal and coronal views. (b) Estimates of the focused ultrasound peak intensities and spatial distribution when targeting SMA are derived from numerical simulations using a high-resolution macaque whole-head CT scan, here displayed on a midline sagittal section. (c) FPC targets in three animals are shown on sagittal and coronal sections. (d) Estimated peak intensities and spatial distribution when targeting FPC shown on a sagittal section. (e) Whole-head simulations of the acoustic wave and thermal dynamics provided estimates of the maximum pressure amplitude (left panel) and the temperature after 40 s TUS (right panel). The data depict a cropped plane of the whole-head simulations with the sonic coupling cone at the top and the brain at the bottom; the skull is outlined in black. Pressure and temperature are maximal in the skull, which is more absorbing than soft tissue. (f) Temperature dynamics for the maximum temperature in the skull (blue), maximum temperature in the brain (red) and at the geometrical focal point in the cortex (yellow). https://doi.org/10.7554/eLife.40541.004 Ultrasound modulation of SMA and FPC led to focal, area-specific changes in each stimulated region’s connectivity profile. In each area, a region’s activity pattern after TUS application was more a function of its own activity and that of strongly connected regions, but less a function of activity in more remote and weakly interconnected areas. Independent of these specific grey matter signal changes, TUS also interacted with non-neuronal structures, as evidenced by more widespread signal changes observed in the meningeal compartment (including cerebral spinal fluid and vasculature). Finally, in experiment four we demonstrate that TUS application had no observable impact on cortical microstructure apparent on histological examination. In summary, TUS over dorsomedial frontal cortex causes spatially specific sharpening of the stimulated region’s connectivity profile with high efficacy and reproducibility, independent of non-neuronal signal changes. Results Experiment 1, TUS modulation of SMA connectivity Transcranial focused ultrasound stimulation of SMA induced spatially specific changes to the connectivity profile of SMA. At rest, in the control state, SMA’s activity is coupled with activity throughout sensorimotor regions in frontal and parietal cortex, inferior parietal, prefrontal, and parts of cingulate cortex (Figure 3a). Many of these regions are anatomically connected with SMA (Dum and Strick, 2005; Geyer et al., 2000; Strick et al., 1998). If we change the responsiveness of SMA neurons to such activity in interconnected regions by artificially modulating SMA activity with TUS, then we should see a change in the coupling between SMA activity and activity in other regions. Following ultrasound stimulation, SMA changed its coupling with the sensorimotor system, anterior and posterior cingulate, anterior temporal, inferior parietal, and prefrontal cortex (Figure 3b). This can be seen on the whole brain functional connectivity maps for the SMA region (Figure 3, compare panels a and b, representative changes highlighted by dashed black circles) and on the whole brain differential connectivity maps in Figure 4 (panels b and c). Figure 3 with 1 supplement see all Download asset Open asset Coupling of activity between stimulated areas and the rest of the brain in experiments 1 (SMA) and 2 (FPC). The left panels show activity coupling between SMA and the rest of the brain in the control state (a), after SMA TUS (b), and after FPC TUS (c). The right panels show activity coupling between FPC and the rest of the brain in the control state (d), after SMA TUS (e), and after FPC TUS (f). Functional connectivity from TUS-targeted regions is therefore summarized in panels (b) and (f) (i.e. SMA connectivity after SMA TUS and FPC connectivity after FPC TUS). Each type of TUS had a relatively selective effect on the stimulated area: SMA coupling was changed by SMA TUS (b) and FPC coupling was changed by FPC TUS (f). Positive correlations are represented in warm colours from red to yellow, negative correlations are represented in cool colours from blue to green. Key regions of change are highlighted by black dashed ovals. TUS target sites are indicated with arrows. Connectivity seed regions are indicated with black asterisks. Key anatomical features are labelled in panel (a): pos, parieto-occipital sulcus; cal, calcarine sulcus; cgs, cingulate sulcus; ps, principal sulcus; as, arcuate sulcus; cs, central sulcus; ips, intraparietal sulcus; sts, superior temporal sulcus; ls, lunate sulcus. https://doi.org/10.7554/eLife.40541.005 Figure 4 Download asset Open asset Differential effect of TUS on coupling of activity between stimulated areas and the rest of the brain in experiments 1 (SMA) and 2 (FPC). The left panels show activity coupling between SMA and the rest of the brain in the control state (a), the differential effect of SMA TUS for areas positively coupled (z > 0.1) with SMA in the control state (b), and for areas negatively coupled (z < −0.1) with SMA in the control state (c). The right panels show activity coupling between FPC and the rest of the brain in the control state (d), the differential effect of FPC TUS for areas positively coupled (z > 0.1) with FPC in the control state (e), and for areas negatively coupled (z < −0.1) with FPC in the control state (f). Panels (a) and (b) are reproduced here from Figure 3 for reference and to illustrate the location and extent of the ROIs used in the fingerprint analyses (Figure 5). Hot colours in (b) and (e) indicate enhanced coupling following TUS compared to the control state, while cool colours indicate reduced coupling. In (c) and (f) hot colours indicate reduced negative coupling, while cool colours indicate further negative coupling. All other conventions as in Figure 3. The TUS induced changes to the coupling of the stimulated regions were not limited to the a-priori defined ROIs but extended across many regions according to the connectional topography of the stimulated region. https://doi.org/10.7554/eLife.40541.007 It is also apparent in the illustration of SMA’s connectional fingerprint (Figure 5a). The distance of each coloured line from the centre of the figure (and hence its proximity to the circumference of the figure) indicates the strength of activity coupling between SMA and each of the other brain areas indicated on the circumference. Compared to the control state (blue line), after TUS over SMA (red line), SMA’s positive coupling is enhanced with proximal areas in the sensorimotor system but reduced in many long-range connections (non-parametric permutation test, p=0.017). The primary motor cortex (M1), superior parietal lobe (SPL), and middle cingulate cortex (MCC) in the dorsomedial sensorimotor network have been reported to be closely connected with the SMA, whereas prefrontal regions on the dorsomedial (area 9m and FPC), dorsolateral (areas 9-46d and 8A), and ventromedial (area 11m) surface, and those in the temporal lobe (anterior superior temporal gyrus, aSTG; middle superior temporal sulcus, midSTS), and parietal cortex (caudal inferior parietal lobule, IPLc; posterior parietal cortex, PCC) have been reported to be less closely connected with the SMA (Dum and Strick, 2005; Geyer et al., 2000; Strick et al., 1998). TUS increased positive coupling between the stimulated area and proximal areas normally closely connected with it, while, at the same time, decreasing coupling between the stimulated area and many areas normally less closely connected with it. This pattern not only emerges from the fingerprint analyses, but constitutes a principle evident across the brain, as illustrated by whole-brain differential SMA-connectivity maps of the effect of SMA TUS (Figure 4). Figure 5 with 1 supplement see all Download asset Open asset Connectional fingerprints of the stimulated areas. Fingerprint target regions were drawn from the literature and chosen based on their known and distinct connectivity, either strong or weak, with the seed region. Activity coupling in the control state is indicated in blue, following SMA TUS in red, and FPC TUS in yellow. (a) SMA connectional fingerprint. In the control state (blue) SMA is strongly coupled to areas in the dorsomedial sensorimotor system (M1, SPL, MCC). Coupling with each of these areas is enhanced after SMA TUS (red). In contrast, coupling with regions that SMA is weakly connected with in the control state are even further reduced after SMA TUS (red). However, SMA’s fingerprint is relatively unaffected after FPC TUS (yellow), but some effects are visible for regions that are strongly coupled with FPC (compare to panel b). (b) FPC connectional fingerprint is sharpened following FPC TUS, but not following SMA TUS. The latter only affected coupling with SMA itself and regions strongly connected to it (MCC). (c) TUS induced more homogenous activity within the stimulated area (SMA in red on the left, FPC in yellow on the right). (d–f) Temporal evolution of the effect of SMA TUS on the SMA connectional fingerprint. The left panel depicts effects observed in the first fMRI run, followed by the second run in the middle, and the third and last run on the right. For each run, the time after TUS refers to the duration between the end of TUS and the midpoint of the run, averaged across the three animals. (g–h) TUS-induced effects on the connectional fingerprints of SMA and FPC could not be explained by auditory activity. (i) There were no changes in the coupling between the stimulation sites and auditory cortex. In all plots, thick lines and histograms indicate mean activity coupling; lighter coloured error bands and error bars depict standard-error of the mean; the asterisk denotes the interaction between TUS and connectivity seed (p<0.001). https://doi.org/10.7554/eLife.40541.008 These specific effects of TUS were sustained over the duration of our experiment, lasting up to 2 hr (Figure 5d–f). Disruptive effects of TUS on long-range coupling were especially prominent immediately following the end of TUS application (Figure 5d), and gradually reduced towards the end of our recording session (Figure 5f). The enhancing effects that TUS exerted on SMA’s coupling with adjacent and strongly connected areas had a relatively delayed appearance, arising well after the TUS had ended (more than 1 hr, Figure 5e), but again decreasing towards the end of the recording session. In summary, the most important finding was of a protracted period of connectivity change after TUS. While we are cautious about overinterpreting precise timing differences between long-range connectivity reductions and local connectivity increments, we note that the observed pattern could signify distinct time courses for TUS-induced long-term depression and long-term potentiation. However, the observed pattern is also consistent with the notion that early disruption of long-range input to a network (Figure 5d) leaves relatively more signal variance in this network to be explained by remaining local input, driving the observation of subsequent within-network coupling increments (Figure 5e). Both these mechanisms would lead to a sharpening of the stimulated region’s connectivity profile, as observed here. Experiment 2, TUS modulation of FPC connectivity Like SMA, FPC’s activity is coupled with that in interconnected brain regions even when animals are at rest in the control state (Figure 3d). FPC’s activity is positively correlated with activity in a number of adjacent dorsomedial and lateral prefrontal areas and in the central portion of the superior temporal sulcus (midSTS) and posterior cingulate cortex with which it is monosynaptically interconnected (Petrides and Pandya, 2007). By contrast there was, at a rest, a negative relationship with the activity in sensorimotor areas, with which FPC is indirectly connected via regions such as SMA. In comparison to the control state, FPC stimulation induced an enhancement in the normal short-range connectivity between FPC and adjacent dorsomedial (area 9m) and lateral prefrontal cortex (area 9-46d) with which it is particularly strongly connected. In addition, a similar effect was seen in more distant regions with which it is also strongly connected – the midSTS, IPLc and PCC, together comprising temporal and parietal segments of the primate ‘default mode network’ (Petrides and Pandya, 2007). By contrast, there was reduced coupling with other areas in prefrontal cortex, including ventromedial (area 14m), subgenual cingulate (area 25), and lateral orbitofrontal cortex (area 47-12o). These are all areas that FPC is connected to but less strongly (Petrides and Pandya, 2007). Finally, TUS applied to FPC also led to a change in long-range connectivity between FPC and several motor association regions with which it is not directly connected, especially those in the ventrolateral parieto-frontal sensorimotor network (areas PF and F4 Petrides and Pandya, 2007). As noted, in the control state, the activity in FPC and these sensorimotor association areas is negatively or anti-correlated, but this anti-correlation was reduced by FPC TUS. These results are apparent in the whole brain functional connectivity maps for the FPC region (Figure 3, compare panels d and f, representative changes highlighted by dashed black circles) and on the whole brain differential connectivity maps in Figure 4 (panels d and f). It is also apparent in the illustration of FPC’s connectional fingerprint (Figure 5b). Here the blue line indicates the strength of activity coupling between FPC and each of the other brain areas indicated on the circumference in the control state. The yellow line shows that FPC’s coupling with each area is changed after FPC TUS (non-parametric permutation test, p=0.027). Comparing experiments 1 (SMA) and 2 (FPC) It is important to test the claim that TUS induces effects that are spatially specific to each sonicated area by directly comparing effects between stimulation sites. Although FPC TUS significantly altered FPC functional connectivity, it had comparatively little impact on SMA’s pattern of functional connectivity; there was no difference in SMA’s functional connectivity between the control state and after FPC TUS (non-parametric permutation test, p=0.231; whole-brain map in Figure 3c and yellow line in connectivity fingerprint in Figure 5a). Importantly, the effects of TUS over SMA on SMA’s connectivity were significantly dissociable from the effects of FPC TUS (non-parametric permutation test, p=0.041). Similarly, SMA TUS had some but comparatively little impact on FPC’s pattern of functional connectivity (non-parametric permutation tests, SMA versus control, p=0.047; SMA versus FPC, p=0.028; whole-brain map in Figure 3e and red line in connectivity fingerprint in Figure 5b). In fact, the most prominent changes in each area’s connectional fingerprint that were induced by stimulation of the other area were the disruption of functional connectivity between FPC and sensorimotor areas when SMA was stimulated (Figure 3e, encircled). This particular result may have occurred because, as already noted, FPC has no direct monosynaptic connections with these sensorimotor areas (Petrides and Pandya, 2007) and so its functional coupling with these areas is likely to be mediated by areas such as SMA and the areas that surround it such as the pre-supplem" @default.
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W2984652593 title "Author response: Offline impact of transcranial focused ultrasound on cortical activation in primates" @default.
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