Recent letters
Displaying 11-20 letters out of 325 published in the last 9999 days
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No "discrepancy" in findings between Glajch et al. (2016) and Wall et al. (2013) papers
Submit responseA claim is made in the discussion that:
"While this corroborates our earlier findings (Hernandez et al., 2015), it is at odds with those of a previous study (Wall et al., 2013) that showed no input from the GPe to SPNs using similar approaches. The reason for this discrepancy is unclear, but it may be due to nuanced differences in the viral preparations."
The reason for the lack of reporting of GP inputs to striatum is clearly stated in the main text of the Wall et al. (2013) paper.
"A few cells in the GP were sometimes labeled (Figure 2A), indicating that these cells likely provide direct input to neurons in the dorsal striatum (Bevan et al., 1998). However, due to their proximity to the injection site, these inputs were not analyzed further."
Due to the virus injection site's proximity to the GP border, I could not guarantee that labeled cells were due to monosynaptic retrograde infection rather than direct infection. As such, GP inputs were excluded from the analysis.
Conflict of Interest:
None declared
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Public outreach needs to be more than a hobby
Submit responseAs a new assistant professor, I am not unaware of the pressure to publish, and to be focused while I am beginning my independent research career. I have also heard disparaging remarks about "popularizers," with the implication that they are sub-standard scientists. Dr. Martinez- Conde's review of studies on the subject refutes this idea, for which I am grateful. To me, it would be a frightening scientific landscape if the task of teaching the public about the content and importance of science were to be relegated to only "sub-par" scientists.
As scientists, we have an obligation to share our discoveries with the public. Most of us have had a significant investment of public funds in our professional development. This initial investment is followed by further funds to support our ongoing research programs. The public thus have a vested interest in, and a right to know about, the discoveries that are made using this public money. And we should feel an obligation to make the results of our work broadly accessible. Although doing this could be as straightforward as writing research articles in more accessible language, direct public outreach is also clearly desirable.
We should not be spurred only by a feeling of duty to communicate with the public, however. Although it is true that we owe a debt to those who are paying for the research we do, scientists should also be thinking about the future of research funding. How many of us have bemoaned the fact that pay lines are going down, the size of grants is being cut back, and the number of applications one must submit in order to obtain funding is going up? It is a bleak picture. I see a cynicism that has led many of my colleagues to pursue non-research industry jobs or jobs outside of science altogether, rather than deal with the funding woes of an academic scientist.
How do funding challenges relate to public outreach? I have frequently seen social media portrayals (often caricatures) of publically funded studies, given as justification for why research budgets should be reined in and funding of science curtailed. By a refusal to engage the public directly, we run the risk of losing control of the narrative about the importance of investing in science. All of us should be concerned about informing the public about what we do, why it is important, and how it fits in with their interests. In light of this, it is not only unfair to characterize those who have public visibility as less able researchers, it is inimical to the long-term survival of the scientific endeavor to do anything but encourage those who have a talent for and inclination toward public outreach. I applaud Dr. Martinez-Conde's effort to bring this important issue to our attention.
Conflict of Interest:
None declared
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The Burden of Proof Using Nanotechnology
Submit responseMinic and colleagues proposed a novel therapeutic approach to promote functional recovery after cervical spinal cord injury using a tripartite nanoconjugate to mediate transsynaptic delivery of DPCPX, an adenosine A1 receptor antagonist to premotor neurons in the rostral ventral respiratory group (rVRG) (Minic et al., 2016). This study builds upon their previous observation that acute systemic administration of DPCPX results in recovery of rhythmic phrenic nerve activity after high-cervical spinal hemisection (Kajana and Goshgarian, 2008). However, systemic delivery requires high concentrations of DPCPX, which also induce unwanted off- target side effects. Their goal in this study was to provide DPCPX at a fraction (0.1%) of the systemic dose using a wheat germ agglutinin-horse radish peroxidase (WGA-HRP)-coated gold DPCPX-nanoconjugate to mediate transsynaptic delivery to the rVRG via intramuscular diaphragm injections. They report that recovery of diaphragm activity occurred by 72 h and concluded that this was due to an increase in premotor drive mediated by transsynaptic delivery of DPCPX to the rVRG. However, it is unclear that DPCPX stimulates premotor drive to phrenic motoneurons via direct action in the rVRG; the underlying premise of the study. Furthermore, we believe that the authors failed to provide adequate supporting evidence to conclude that this outcome was mediated by targeted delivery of DPCPX specifically to the rVRG.
Importantly, they failed to validate targeted delivery of the DPCPX- nanoconjugate to the rVRG following intramuscular injection. The only evidence was bilateral WGA-HRP staining in both the phrenic nucleus and the rVRG following intramuscular injection of the DPCPX-nanoconjugate, which they observed in only three hemisected rats. DPCPX-nanoconjugate was injected unilaterally, but bilateral WGA-HRP staining in the phrenic nucleus indicates spillover without specific targeting. The authors present no data to support their conclusion that the DPCPX-nanoconjugate was successfully transported to phrenic motoneurons or transsynaptically to the rVRG, which is absolutely essential to interpret their results. Phrenic motoneurons also contain A1 receptors (Petrov et al., 2007); thus, functional recovery could be mediated by an effect of DPCPX at phrenic motoneurons alone.
The authors failed to support their conclusion that intramuscular injection of the DPCPX-nanoconjugate increased respiratory premotor drive emanating from the rVRG by 75%. They report that after injection, there was an increase in respiratory frequency, but this is not an effect reflecting increased premotor drive. They also reported that intramuscular injection of the DPCPX-nanoconjugate increased the amplitude of phrenic nerve activity, but this was recorded only in a terminal experiment using vagotomized animals where no pre- and post-injection comparisons were possible.
Finally, the current study does not provide critical information regarding the release kinetics of the DPCPX-nanoconjugate either in vitro or in vivo. Without pharmacokinetic profiling and determination of effective site concentrations, it is impossible to draw unambiguous conclusions regarding transsynaptic DPCPX-nanoconjugate delivery. In conclusion, although the goal of this study to introduce a novel therapeutic approach designed to target premotor neurons in respiratory disorders using nanotechnology was exciting, the burden of validation was not met and interpretation of the physiological mechanisms responsible for the observed effects requires further studies.
References
Kajana S, Goshgarian HG (2008) Administration of phosphodiesterase inhibitors and an adenosine A1 receptor antagonist induces phrenic nerve recovery in high cervical spinal cord injured rats. Experimental neurology 210:671-680.
Minic Z, Zhang Y, Mao G, Goshgarian HG (2016) Transporter Protein- Coupled DPCPX Nanoconjugates Induce Diaphragmatic Recovery after SCI by Blocking Adenosine A1 Receptors. The Journal of neuroscience : the official journal of the Society for Neuroscience 36:3441-3452.
Petrov T, Kreipke C, Alilain W, Nantwi KD (2007) Differential expression of adenosine A1 and A2A receptors after upper cervical (C2) spinal cord hemisection in adult rats. J Spinal Cord Med 30:331-337.
Conflict of Interest:
None declared
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Obesity Dyshomeostasis Linked to Ghrelin, Leptin and Dopamine Responses to Sustained Stress
Submit responseBurghardt et al. (2012) present interesting evidence that leptin serves a regulator function in humans and provides an etiological mechanism for differences in dopamine neurotransmission in response to salient stimuli as related to metabolic function. The authors suggest that the capacity for leptin to influence stress-induced dopaminergic function is potentially important for pathological states where dopamine is thought to play an integral role, such as mood, substance-use disorders, eating disorders, and obesity.
It is generally agreed that food intake is regulated by two complementary drives: the homeostatic and hedonic pathways (Lutter and Nestler, 2009). The homeostatic pathway controls energy balance by increasing the motivation to eat following depletion of energy stores. Hedonic or reward-based regulation can override the homeostatic pathway during periods of relative energy abundance by increasing the desire to consume foods that are highly palatable.
The paper by Burghart et al. (2012) is exclusively concerned with leptin. Another hormone involved in both homeostatic and hedonic regulation of food intake is ghrelin, the only mammalian peptide hormone able to increase food intake. Interestingly, ghrelin also responds to emotional arousal and stress (Labarthe, Fiquet, Hassouna, Zizzari et al., 2015; Mueller et al., 2015). During chronic stress, increased ghrelin secretion induces emotional eating by acting at the level of the hedonic/reward system. As ghrelin has anxiolytic action in response to stress, this adaptive response may contribute to control excessive anxiety and prevent depression (LaBarthe et al., 2015). In obesity, studies have shown a reduced ability to mobilize ghrelin in response to stress or central ghrelin resistance at the level of the hedonic/reward system which may explain the inability to cope with anxiety and increased susceptibility to depression. Reciprocally, studies have shown that people with depression have increased susceptibility to obesity and eating disorders (Marks, 2015).
Traditionally, the control of feeding has been associated with the hypothalamus (Kelley, Baldo, Pratt & Will, 2005). Circulating factors in the blood modulate the activity of energy sensing neurons in the arcuate nucleus, that modulate food-directed behaviours via their activation of outputs from lateral hypothalamic regions to thalamo- cortical systems, central autonomic effectors, and motor pattern generators. There is a convergence of inputs from amygdala, prefrontal cortex, and nucleus accumbens shell that allow direct modulation of feeding behaviours based upon cognitive and affective signaling. These avenues of influence on feeding control provide the entry point for a Circle of Discontent (Marks, 2015). When the environmental conditions are: (A) obesogenic, due to the ready availability of highly palatable high- energy foods; (B) stressful, due to the presence of stigma, depression and anxiety; and (C) engendering body dissatisfaction, due to the omnipresent socio-cultural thin-ideal, we have all the ingredients necessary for obesity formation. It is proposed that the cognitive and affective processes of the Circle of Discontent over-ride the homeostasis system for regulating feeding and energy-homeostasis breaks down (Marks, 2015). The capacity of both leptin and ghrelin to influence stress- induced dopaminergic function such as mood, substance-use disorders, eating disorders, and obesity warrants further investigation.
Burghardt PR, Love TM, Stohler CS, Hodgkinson C, Shen PH, Enoch MA, Goldman D, Zubieta JK. (2012) Leptin regulates dopamine responses to sustained stress in humans. The Journal of Neuroscience 32:15369-76.
Kenny P J (2010) Reward mechanisms in obesity: new insights and future directions. Neuron 69: 664 - 679.
Labarthe A, Fiquet O, Hassouna R, Zizzari P et al. (2015). Ghrelin- derived peptides: a link between appetite/reward, GH axis, and psychiatric disorders? Neurological and Psychiatric Disorders in Endocrine Diseases, 71.
Lutter m and nestler ej (2009) Homeostatic and hedonic signals interact in the regulation of food intake. Journal of Nutrition 139: 629- 632.
Marks D F (2015) Homeostatic theory of obesity Health Psychology Open 1(2).
Mueller T D, Nogueiras R, Andermann M L, Andrews Z B et al. (2015) Ghrelin. Molecular Metabolism 4: 437-460.
Conflict of Interest:
None declared
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Implications for Treatment of Cocaine Addiction
Submit responseThe research presented here demonstrates a truly novel approach to the treatment of cocaine addiction. More recent literature indicates activation associated with the limbic system in response to drug cues (Childress et al., 2015). Comprehensive literature searches indicate that, to date, there has not been any significant advancement in this regard. Treatment via drugs such as Baclofen remains an area of untapped potential.
While there is no doubt that the prevention of subliminal drug cues will play an instrumental role in the prevention of relapse in the future, would not the actual onset of these cues be virtually unknown to the individual him/herself? There continues to be a glaring paucity of research in this area. While conscious drug cues themselves are considered subjective in nature, cues of a subconscious nature will consequently be of a more controversial nature when treatment options are being considered. Among the findings mentioned in the paper, the authors conceded the possibility of Baclofen exerting more generalized effects on motivational processes, considering its role as a dopamine modulator. As a result, its role in pharmacotherapy becomes immediately questionable - would the advantages of using such a drug to treat essentially undetectable subliminal cues override the risk associated with generalized effects on motivational responses that extend to other facets of life? The practicality of using this drug so comes into question - how would clinicians be aware of the presence of subliminal drug cues so as to justify the use of Baclofen for treatment? The obvious answer is to use neuroimaging measures, such as fMRI. But would this be effective in the treatment of addiction when large populations are considered? Considering the number of addicted individuals in the present day, subjecting individuals who have been treated for cocaine addiction to fMRI tests at regular intervals seems like a sensible strategy, but definitely not cost-effective in the long-term.
The question I posit here by no means seeks to undermine the novel findings presented by the authors. As I mentioned earlier, the findings demonstrate a significant area of untapped potential when it comes to the treatment of cocaine addiction (and potentially addiction to other drugs). Indeed, there have been findings for Baclofen's usefulness in the treatment of alcohol dependence and comorbid anxiety (Morley et al., 2014), although, in this instance, the findings were quite selective to the specific condition of alcohol dependence and comorbid anxiety. This therefore highlights the need for more research with this specific focus.
Conflict of Interest:
None declared
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Re:An important previous study that the authors (and reviewers) should have referred to
Submit responseI am grateful to Professor Nakamura for bringing their elegant work (Kataoka et al., 2014) to our attention. This was a regrettable and unintentional omission that will be followed by a corrigendum to draw due attention to their excellent research, not just in this mentioned manuscript, but over many years.
To address, and even highlight, some of the comments provided by Dr. Nakamura, our results generally support those originally presented in Kataoka et al., 2014, together with those from the laboratory of Dr. DiMicco and colleagues. I am sympathetic with the frustrations of the nomenclature and of the difficulties of delineating clear nuclear boundaries in the posterior hypothalamic region, especially between what has traditionally been labeled as "posterior hypothalamic nucleus" and "dorsomedial nucleus of the hypothalamus". However, as exemplified by Dr. Nakamura's comment, the unqualified use of the term "DMH" does nothing to alleviate this confusion. To state that we attempted to "create a new brain area rPH" in our manuscript is a misrepresentation of the literature. In the context of cardiovascular regulation, some of the clearest definition of "DMH" include the dorsal hypothalamic area (DA), the dorsomedial hypothalamic nuclei (nucleus proper - DMN, compact area - DMC, and dorsal diffuse portion - DMD), a rostral portion of the posterior hypothalamic nucleus (PH), and the medial part of the perifornical area (Fontes et al., 2011, Figure 1). Based on efforts by DiMicco and colleagues (Samuels et al., 2004), a more precise anatomical and functional assessment of cardioresponsive sites in "DMH" concluded that "the presence of a dense population of RP-projecting neurons located within the DA (dorsal hypothalamic area) just dorsal to the dorsomedial nucleus at the level where a clear zona compacta is evident . . . provides the first evidence that activation of these neurons is largely responsible for the tachycardia resulting from chemical stimulation of the medial hypothalamus" (p. R477, Samuels et al, 2004). A report by Dr. McAllen's laboratory (Tanaka and McAllen, 2008) provided additional evidence for the role of different dorsal posterior hypothalamic regions, including a rostral portion of the posterior hypothalamic nucleus (PH). There is thus no basis for the assertion that we are "creating a new brain area", as this has been reported by multiple independent laboratories and appears to be the region most closely associated with our anatomical material based on Paxinos and Watson's Rat Brain Atlas nuclear parcellation (5th or 6th Ed; plate 61).
In response to the claim that the rPH was created "without showing any detailed anatomical assessments of the retrogradely labeled cells", we respectfully disagree with this opinion. Anatomical details were provided, including the Nissl stained series generated for Figure 3 to identify the region in which the largest numbers of retrogradely- labelled/Fos-positive cells were located in this study's material. In addition, the distribution of retrogradely-labeled cells (Figure 2E-G) provides a clear view of the location of the RPa- and PaMP-projecting neurons discussed in our manuscript. Finally, the region of RPa- projecting cells together with audiogenic stress-evoked Fos-positive neurons are indicated in Figure 6. The relatively high-powered photomicrographs of Figures 2 and 6 are necessary to provide the cellular details required for assessing colocalization. We agree that the RPa- projecting, stress-activated, neurons observed in our material are in a similar location to those displayed in the DA region by Samuels and colleagues (2004). Furthermore, the RPa-projecting and stress-activated population presented in Kataoka et al (2014), also appears to be similar to our results, even if these are shown as part of the "dDMH". As discussed above, Samuels et al (2004) have described this region as being dorsal to the dorsomedial nucleus.
As for the failure to show pictures of Fos-expressing, PaMP- projecting neurons, an extensive map of PaMP-projecting neurons colocalized with audiogenic stress-induced Fos-expression was published in 2000 by our group (Campeau and Watson, 2000; Figure 2), including some of the regions discussed in this manuscript if readers wish additional information. In the current manuscript, a gradient of retrogradely- labelled cells was observed from the two injected regions, with the RPa- projecting cells being more dorsal, and the PaMP-projecting cells being more ventral, with a region of overlap, as shown in Figure 2E-G. Figure 6 then shows the extent of stress-induced Fos-positive cells throughout the rPH region, including the more ventral portion where the PaMP-projecting neurons are observed in Figure 2. As discussed in our manuscript, there were several additional regions displaying high numbers of retrogradely- labeled and audiogenic stress-evoked Fos-immunoreactivity that were not shown, but the ventral division of the dorsomedial hypothalamic nucleus was definitely not one of the regions with the highest proportion of tracer/Fos-positive cells. The ventral division (below the compact division) of the dorsomedial hypothalamic nucleus was reported by Kataoka et al (2014) to provide the main focus of PVH-projecting and Fos-positive neurons in their material. This appears to be a genuine difference between our results and those of Kataoka et al (2014), that cannot be explained by simple nomenclature differences or failure to display results. Potential factors responsible for this difference may include slightly different paraventricular hypothalamic regional injections, specific tracer characteristics, or the use of different stress models influencing selective hypothalamic cell populations.
Finally, we made no claims as being the first to formulate the hypothesis that the DMH/rPH serves as a hub controlling autonomic, neuroendocrine and behavioral responses; this hypothesis has been stated repeatedly by DiMicco and colleagues since 2002 (DiMicco et al., 2002, Fontes et al., 2011). The complementarities of our studies is beginning to paint anatomical similarities and differences that provide important background for the overall understanding of coordinated responses triggered by stress, and the regulation of these responses by repeated stress.
References
Campeau S, and Watson SJ. 2000. Connections of some auditory- responsive posterior thalamic nuclei putatively involved in activation of the hypothalamo-pituitary-adrenocortical axis in response to audiogenic stress in rats: An anterograde and retrograde tract tracing study combined with Fos expression. J Comp Neurol 423:474-491.
DiMicco JA, Samuels BC, Zaretskaia MV, and Zaretsky DV. 2002. The dorsomedial hypothalamus and the response to stress: part renaissance, part revolution. Pharmacol Biochem Behav 71:469-480.
Fontes MAP, Xavier CH, de Menezes RCA, and DiMicco JA. 2011. The dorsomedial hypothalamus and the central pathways involved in the cardiovascular response to emotional stress. Neuroscience 184:64-74.
Kataoka N, Hioki H, Kaneko T, and Nakamura K. 2014. Psychological stress activates a dorsomedial hypothalamus-medullary raphe circuit driving brown adipose tissue thermogenesis and hyperthermia. Cell Metab 20:346-358.
Samuels BC, Zaretsky DV, and DiMicco JA. 2004. Dorsomedial hypothalamic sites where disinhibition evokes tachycardia correlate with location of raphe-projecting neurons. Am J Physiol Regul Integr Comp Physiol 287:R472-R478.
Tanaka M, and McAllen RM. 2008. Functional topography of the dorsomedial hypothalamus. Am J Physiol Regul Integr Comp Physiol 294:R477- R486.
Conflict of Interest:
None declared
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An important previous study that the authors (and reviewers) should have referred to
Submit responseNyhuis et al. performed double retrograde tracing from the paraventricular hypothalamic nucleus (PVH; called PaMP in the present study) and from the medullary raphe pallidus (RPa) in rats and reported that a part of the posterior hypothalamic area contained many retrogradely labeled neurons, which were further activated by loud noise stress. In the introduction, the authors state "Although retrograde tracing from both the RPa and PaMP was previously reported, the extent to which RPa and PaMP afferent inputs overlap and display stress-evoked activity was unknown." However, this is not true. We studied this issue in rats using acute social defeat stress, as described in Kataoka et al. (2014). The present double retrograde tracing study replicated our study using a different stress model, but failed to cite our paper.
In our paper, we presented detailed maps showing the distributions of PVH-projecting and RPa-projecting neurons in the caudal hypothalamus and their expression of Fos induced by social defeat stress. As shown in Figure 3 of our paper, clustering neuronal cells projecting to the RPa, many of which were activated by stress, were located in the dorsal part of the dorsomedial hypothalamus (DMH)--this nomenclature basically followed Paxinos and Watson's rat brain atlas 6th edition (see Figure 59-60). This neuronal cluster was always found as a single cluster located slightly rostral to bregma -3.3 mm, comparable to the observation by Dimicco and colleagues (see Samuels et al., 2004). It should be noted that Dimicco and colleagues have also referred to this site as the DMH.
In the present paper, the authors attempt to separate the belonging of the RPa-projecting neurons from the DMH by creating a new brain area "rPH" without showing any detailed anatomical assessments of the retrogradely labeled cells. This new nomenclature only causes a confusion in the readers. In light of the data shown in the present paper, I believe that the authors found the cluster of RPa-projecting, stress- activated DMH neurons that Dimicco and we have already reported.
In our paper, we also found that another clustering neurons in the ventral part of the DMH project to the PVH and are activated by stress. The authors of the present paper did not show any picture of Fos- expressing, PVH-projecting neurons, nor, again, show the distribution of these cells. This is odd because the muscimol study in the present study only focused on the neuroendocrine stress response that the PVH-projecting neurons potentially mediate. We know that PVH-projecting neurons are mostly distributed ventral to the area that the authors call "rPH" (see Figure 3 of Kataoka et al. (2014)). Therefore, if the authors did not limit their Fos study to the "rPH", but did look at the DMH as well, they could have found more stress-activated neurons that convey the signal to the PVH.
Whichever this dorsal hypothalamic site is called DMH or rPH, this site functions as an important hub for driving both sympathetic (through the RPa) and neuroendocrine (through the PVH) stress responses, and Kataoka et al. (2014) was the first to clearly present this notion.
References
Kataoka, N., Hioki, H., Kaneko, T. & Nakamura, K. Psychological stress activates a dorsomedial hypothalamus-medullary raphe circuit driving brown adipose tissue thermogenesis and hyperthermia. Cell Metab. 20:346-358, 2014. http://dx.doi.org/10.1016/j.cmet.2014.05.018
Samuels BC, Zaretsky DV, DiMicco JA. Dorsomedial hypothalamic sites where disinhibition evokes tachycardia correlate with location of raphe-projecting neurons. Am J Physiol Regul Integr Comp Physiol. 2004 Aug;287(2):R472-8. Epub 2004
Conflict of Interest:
None declared
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Changes in transcription for enzyme responsible for androgen production
Submit responseRead your article with great interest. Long ago as a grad student I stumbled on apo E and apo E synthetic peptides suppressing the mRNA for CYP17, the enzyme responsible for producing androgen by ovarian theca and interstitial cells (J Lipid Res. 1998 Dec;39(12):2406-14. An apolipoprotein E synthetic peptide selectively modulates the transcription of the gene for rat ovarian theca and interstitial cell P450 17alpha-hydroxylase, C17-20 lyase.). Ever since I have struggled to understand how apo E could access DNA, your work appears to finally provide exciting insight. Thank you, one mystery in my apo E research has had a door cracked opened.
Conflict of Interest:
None declared
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The "weak evidence" argument is unfounded and highlights strength of DA-BOLD link
Submit responseWe appreciate the interest in our work by the author of the "weakness of evidence" comment. Further, we also thank the commenter for allowing us the opportunity to revisit the strength of our evidence. The commenter suggests that inappropriate statistical analyses were used in this study and that there were undue influences from outliers on the association between fusiform gyrus BOLD and D1 binding potential (BP) reported in our study, as described in the article entitled Dopamine D1 Binding Potential Predicts Fusiform BOLD Activity during Face-Recognition Performance. Although the commenter argues that the use of his or her recommended statistical methods are more appropriate than those utilized in our study, the commenter fails to give evidence to demonstrate this assertion. Here we give a point-by-point response to the "weakness of evidence" argument. We conclude that the commenter's argument hinges upon misleading assertions. In fact, the contention that our results were in some way "weak" does not stand when using the commenter's suggested methods.
We do agree with the commenter that use of large sample sizes is optimal for drawing the most accurate conclusions about natural phenomena. Our sample size was not large (N = 18); although we confidently liken this size to many other studies within multimodal imaging research. We are also confident in the robustness of the D1-BOLD relationship we obtained, given the large proportion of shared variance we demonstrated between these two variables (see Cohen, 1988).
The commenter claimed that our original ordinary least squares (OLS) regression model had "overfit" our data. The commenter used leave-one-out cross-validation modeling to which he or she suggested that the use of this modeling technique showed a subjectively marked change in model fit between FFG D1 binding potential (BP) and BOLD. There are at least two problems with the commenter's approach and interpretation. The first and most obvious is that cross-validation modeling is not appropriate in this case because we are neither attempting to fit contending models nor are we assessing models for their ability to extrapolate to novel data. Second, if one were to use this approach, as the commenter did, one would see that the commenter's claim of a "weak" association between D1 BP and FFG BOLD is conventionally unfounded (e.g., Cohen, 1982). The model that the commenter used showed a subjectively reduced fit compared to our original model (i.e., r2 = .38 to r2 = ".20"). However, the commenter mistakenly elides over the fact that the effect size of his or her model is neither trivial nor weak (i.e., it is at least a medium effect size; see Cohen, 1988).
The commenter's suggestion to use a Spearman's rho is not supported given that the original, parametric model is not affected by potential outliers (see below). It is also important to note the commenter's calculation error of Spearman's rho (.0939). The actual value of this calculation is .3891.
Although our original work showed that possible outliers did not have any influence on the FFG D1 BP and BOLD model (see manuscript p. 14704), the commenter insinuated that the outlier detection methods used in our paper were antiquated. When he or she used "modern outlier detection techniques," these, the commenter claims, revealed several bivariate outliers. Although the commenter did not provide any context for his or her insinuation that our methods are antiquated, we must point out that several multivariate outlier methods and point influence diagnostics show that our model was not unduly affected by anomalous observations. First, a residual plot against fitted values reveals symmetry about zero with no noticeable slope that would depend upon magnitude (see http://www.utdallas.edu/research/nprlab/figure.htm). Second, Mahalanobis distance measures indicate that even the more extreme points of our model occur at a rate of about 8% on random bivariate normal distributions with our sample means and covariances. Third, influence statistics, such as Cook's distance measure, do not show any point that has greater influence on the FFG DA-BOLD parameter estimate compared to any other point within the model. Lastly, subjecting our model to a Monte Carlo (B = 1000) bootstrapping procedure, we find that the significance of our model remains (? = .615, 95% CI = .01-.96, p = .03). Such random resampling methods allow for equal probability of representation of each observation, minimizing the influence of outliers (see Efron, 1982). By these and many other measures, our model was not unduly influenced by potential outliers.
Regarding the commenter's criticism of Figure 3 within the article, we agree that one cannot claim a difference between correlations without testing them directly. We were surprised that the commenter would charge us with making such a claim. We did not say that D1 binding potential in ROIs outside of FFG have no correlation with BOLD in FFG, or for that matter are unimportant compared to D1 BP in FFG (p. 14705). Actually reading our manuscript would have assuaged any such concerns and revealed that our focus was on the importance of FFG in the context of DA intensive regions. Our emphasis on the relationship between FFG D1 and BOLD was specifically highlighted because it represents a unique contribution to the literature.
Our work demonstrated a novel finding, that FFG D1 BP was predictive of FFG BOLD signal during face recognition. As with any empirical findings, especially novel ones, our results must be subjected to further testing to confirm or negate their veracity. This should be done via rigorous replication efforts (e.g., Open Science Collaboration, 2015). The commenter's remarks did not offer replication data to support an alternative hypothesis, nor did it offer sound statistical reasoning for why our methodology was somehow flawed. Rather, the comments were unsupported by the commenter's own evidence and represent a flawed attempt to impugn our work.
References Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Edition). Hillsdale, NJ: Earlbaum.
Efron, B. (1982). The Jackknife, Bootstrap, and other Resampling Plans (1st Edition). Philadelphia, PA: Society for Industrial and Applied Mathematics.
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349 (6251).
Conflict of Interest:
None declared
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Letter to the Editor: "Developing Intuition: Neural Correlates of Cognitive-Skill Learning in Caudate Nucleus" by Wan et al (2012). J. Neurosci., 32(48), 17492-17501.
Submit responseThese experiments identified the Neural Correlates of Cognitive-Skill Learning. However it is debatable whether intuition was developed. It is also unclear why only males were considered, as females are presumably more intuitive.
The main objective of this letter is exploring the assumed definition of intuition within the context of ancient metaphysical circles and as evidenced through history (Eisenbud, 1981; Marquardt, 2002; Baude, 2007).
Life is about making decisions to act upon. As such it relies on one basic task: making predictions at conscious, subconscious and unconscious levels; non-stop. The predictions success depends on the level of knowledge and the proficiency to generate it. Predictions are basically about producing knowledge of anything anywhere, including current, past or future events, conditions, places, objects, equations and solutions, etc.
How predictions are made is what distinguishes intuition from rational thinking (Mega et al, 2015). Intuition can be considered both:
1-Noun i.e., intuitive knowledge or intuitive decision
2-Verb i.e., the process that delivers intuitive knowledge and intuitive decisions
Ultimately, intuitive knowledge, intuitive decisions or even rational knowledge are all basically knowledge, the difference being just how it is obtained. In those terms, it would be expected that intuition will have its own neural correlate, regardless of the type of knowledge generated. On the other hand, intuitive knowledge, or ultimately knowledge as explained above, may be "...domain specific...", which may explain why Wan et al (2009) and Mega et al (2015) found the neural correlates in different brain areas. Therefore, what they found may not necessarily be the neural correlates of intuition.
Intuition is assumed non-conscious, automatic and quick (Wan et al, 2009; Mega et al, 2015). Nevertheless, there is still no consensus about what exactly intuition is (Glockner and Witteman, 2010) or its neural basis. As rational thinking can also be quick, the adjective "spontaneous" may be better suited to define intuition, as it implies no time (to deliberate). In the mini-shogi experiments, what "...the short presentation time (2 s) and brief response window (3 s)..." achieved was "...minimizing the contribution of conscious search..." but not eliminating it altogether, putting thus into question whether intuition was developed. What probably happened by optimizing the "...presentation time..." and the "...response window..." was that the psychological function engaged in the process of learning simply became more proficient. Activating intuition could perhaps be achieved by minimizing the presentation times to the level that the individual has no conscious recollection of what was observed.
As referred to by Mega et al (2015) "...intuition is a psychological function that apprehends the totality of a given situation and synthesizes isolated bits of data and experiences related to the situational demands to reach a decision...". From this definition, which is similar to that assumed by Wan et al (2009), intuition seems a Psychological Processing Unit, analogous to rational thinking, but in the threshold of consciousness. It is like having a finite database and through various psychological functions new data associations are produced. Therefore, memory and operations are local, like having a Closed or Isolated System (thermodynamics). Intuition is certainly an ability that most people have but undeveloped. This is another reason why it is debatable that randomly chosen individuals (Mega et al, 2015; Wan et al, 2009) had their intuition activated.
From a different perspective, intuition is also a non-conscious process but seems to do with knowledge spontaneously loaded into memory and/or into awareness. Where knowledge came from is yet to be ascertained. Regardless of its source, ancient masters e.g. Lao-Tse, Plato, Empedocles, etc. (Hubral, 2014a,b,c) and modern empiricists affirm that the seat of intuition is not the brain but associated to the heart, although knowledge is ultimately made conscious in the brain. This heart-brain coupling has been observed in laboratory experiments based on EEG and ECG analysis (McCreaty et al, 2004a,b).
From this other perspective, telepathy, precognition, etc. are examples of intuition observed experimentally (Eisenbud, 1981; Marquardt, 2002; Braude, 2007). Einstein himself witnessed and endorsed telepathy experiments (Sinclair, 1930). Precognition is perhaps the most intriguing (Eisenbud, 1981; Marquardt, 2002) as it involves knowledge of future events that some individuals are spontaneously aware of without having any means of knowing i.e., knowledge that was not originally in memory or arrived at via an automated subconscious or non-conscious psychological function (Mega et al, 2015), although this foreknowledge must be ultimately related to memory.
It is speculated that intuition may be related to a non-local field, as opposed to rational knowledge that is local i.e., in memory, books, databases, etc. This non-locality is more evident in the case of precognition as several individuals from different geographical locations and having no connection among them or to the event, are spontaneously aware of the future event (Marquardt, 2002). This could mean that time may be distributed among multiple worlds (Everett, 1957; Hall et al, 2014) or that non-locality refers to a field of probabilities. Thus, it appears that intuition is more like an Open System (thermodynamics) where it has external interactions in the form of information, energy, matter, etc. into or out of the system boundary (Khalil, 1995).
Therefore, given the arguments above it is unlikely that intuition has been activated in Wan et al (2009) or in Mega et al (2015). Identifying the neural basis of intuition, as originally defined in ancient metaphysical circles, would require individuals to prove their intuitional abilities by providing knowledge they have no way of knowing: not derived from memory or from an automated subconscious or non-conscious "...psychological function...".
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Conflict of Interest:
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