Parcellation of the human substantia nigra based on anatomical connectivity to the striatum

Chowdhury, Rumana; Lambert, Christian; Dolan, Raymond J.; Düzel, Emrah

doi:10.1016/j.neuroimage.2013.05.043

Cited by 59 publications

(55 citation statements)

References 66 publications

(43 reference statements)

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“…Here we demonstrate a segregation between effort and reward learning within SN/VTA across the domains of task activation, functional connectivity, and gray matter density. In SN/VTA, a dorsomedial encoding of reward PEs, and a ventrolateral encoding of effort PEs, extends previous studies on SN/VTA subregions (56,57,67,68) by demonstrating that this segregation has functional implications that are exploited during multiattribute learning. In contrast to previous studies on SN/VTA substructures (56, 67-69), we performed whole-brain imaging, which allowed us to investigate the precise interactions between dopaminergic midbrain and striatal/ cortical areas.…”

Section: Discussionsupporting

confidence: 81%

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Separate mesocortical and mesolimbic pathways encode effort and reward learning signals

Hauser

Eldar

Dolan

2017

Proc. Natl. Acad. Sci. U.S.A.

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120

127

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Optimal decision making mandates organisms learn the relevant features of choice options. Likewise, knowing how much effort we should expend can assume paramount importance. A mesolimbic network supports reward learning, but it is unclear whether other choice features, such as effort learning, rely on this same network. Using computational fMRI, we show parallel encoding of effort and reward prediction errors (PEs) within distinct brain regions, with effort PEs expressed in dorsomedial prefrontal cortex and reward PEs in ventral striatum. We show a common mesencephalic origin for these signals evident in overlapping, but spatially dissociable, dopaminergic midbrain regions expressing both types of PE. During action anticipation, reward and effort expectations were integrated in ventral striatum, consistent with a computation of an overall net benefit of a stimulus. Thus, we show that motivationally relevant stimulus features are learned in parallel dopaminergic pathways, with formation of an integrated utility signal at choice. effort prediction errors | reward prediction errors | apathy | substantia nigra/ventral tegmental area | dorsomedial prefrontal cortex O rganisms need to make energy-efficient decisions to maximize benefits and minimize costs, a tradeoff exemplified in effort expenditure (1-3). A key example occurs during foraging, where an overestimation of effort can lead to inaction and starvation (4), whereas underestimation of effort can result in persistent failure, as exemplified in the myth of Sisyphus (5).In a naturalistic environment, we often simultaneously learn about success in expending sufficient effort into an action as well as the reward we obtain from this same action. The reward outcomes that signal success and failure of an action are usually clear, although the effort necessary to attain success is often less transparent. Only by repeatedly experiencing success and failure is it possible to acquire an estimate of an optimal level of effort needed to succeed, without unnecessary waste of energy. This type of learning is important in contexts as diverse as foraging, hunting, and harvesting (6-8). Hull in his "law of less work" proposed that organisms "gradually learn" how to minimize effort expenditure (9). Surprisingly, we know little regarding the neurocognitive mechanisms that guide this form of simultaneous learning about reward and effort.A mesolimbic dopamine system encodes a teaching signal tethered to prediction of reward outcomes (10, 11). These reward prediction errors (PEs) arise from dopaminergic neurons in substantia nigra and ventral tegmental area (SN/VTA) and are broadcast to ventral striatum (VS) to mediate reward-related adaptation and learning (12, 13). Dopamine is also thought to provide a motivational signal (14-18), while dopaminergic deficits in rodents impair how effort and reward are arbitrated (1, 4, 19). The dorsomedial prefrontal cortex (dmPFC; spanning presupplementary motor area [pre-SMA] and dorsal anterior cingulate cortex [dACC]) is a candidate substrate...

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Section: Discussionsupporting

confidence: 81%

“…A recent human structural study (57) segregated SN/VTA into ventrolateral and dorsomedial SN/VTA subregions. This motivated us to examine whether SN/VTA effort and reward PEs are dissociable along these axes (Fig.…”

Section: Simultaneous Representations Of Effort and Reward Pes In Dopmentioning

confidence: 99%

Separate mesocortical and mesolimbic pathways encode effort and reward learning signals

Hauser

Eldar

Dolan

2017

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

120

127

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“…We calculated the number of streamline samples from the seed mask, successfully arriving at the target ROI mask proportional to the total number of samples. We first used individual's cortical parcellation masks as the target ROIs and then excluded ROIs whose probabilistic measures did not reach a threshold of 0.02% of the total estimated streamlines; this is a commonly used threshold in prior studies (Forstmann et al, 2011;Li et al, 2012;Chowdhury et al, 2013). Thus, the connectivity measures represent ROI-to-ROI probabilistic connectivity.…”

Section: Exploratory Analysesmentioning

confidence: 99%

Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression

Posner

Cha

Wang

et al. 2015

Neuropsychopharmacol

111

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Research into the pathophysiology of major depressive disorder (MDD) has focused largely on individuals already affected by MDD. Studies have thus been limited in their ability to disentangle effects that arise as a result of MDD from precursors of the disorder. By studying individuals at high familial risk for MDD, we aimed to identify potential biomarkers indexing risk for developing MDD, a critical step toward advancing prevention and early intervention. Using resting-state functional connectivity MRI (rs-fcMRI) and diffusion MRI (tractography), we examined connectivity within the default mode network (DMN) and between the DMN and the central executive network (CEN) in 111 individuals, aged 11-60 years, at high and low familial risk for depression. Study participants were part of a threegeneration longitudinal, cohort study of familial depression. Based on rs-fcMRI, individuals at high vs low familial risk for depression showed increased DMN connectivity, as well as decreased DMN-CEN-negative connectivity. These findings remained significant after excluding individuals with a current or lifetime history of depression. Diffusion MRI measures based on tractography supported the findings of decreased DMN-CEN-negative connectivity. Path analyses indicated that decreased DMN-CEN-negative connectivity mediated a relationship between familial risk and a neuropsychological measure of impulsivity. Our findings suggest that DMN and DMN-CEN connectivity differ in those at high vs low risk for depression and thus suggest potential biomarkers for identifying individuals at risk for developing MDD.

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“…Except for a few midbrain and diencephalic nuclei [e.g., the substantia nigra (SN), the red nucleus (RN), and the subthalamic nucleus (STh) (Chowdhury et al, 2013;Keuken et al, 2014;Kwon et al, 2012;Menke et al, 2010;Xiao et al, 2014)], a major obstacle to precisely localizing individual Bn in vivo is the limited sensitivity and contrast between these small regions and adjacent white matter (WM) using standard neuroimaging methods, such as relaxivity-based magnetic resonance imaging (MRI).…”

mentioning

confidence: 99%

“…These nuclei included the median raphe (MnR), the dorsal raphe (DR), the raphe magnus (RMg), and the periaqueductal gray (PAG). To demonstrate the reliability of our approach, we also defined motor relay nuclei already identified in previous work using in vivo relaxivity-based images (Chowdhury et al, 2013;Keuken et al, 2014;Kwon et al, 2012;Menke et al, 2010;Xiao et al, 2014), such as the SN, the RN, and, in the diencephalon, the STh. Notably, to advance the in vivo investigation of these motor Bn in humans, we exploited our multi-contrast method to parcellate each of these nuclei into anatomically distinct subnuclei (e.g., by dividing the SN into two subregions compatible with pars compacta and pars reticulata).…”

mentioning

confidence: 99%

Toward an In Vivo Neuroimaging Template of Human Brainstem Nuclei of the Ascending Arousal, Autonomic, and Motor Systems

et al. 2015

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Brainstem nuclei (Bn) in humans play a crucial role in vital functions, such as arousal, autonomic homeostasis, sensory and motor relay, nociception, sleep, and cranial nerve function, and they have been implicated in a vast array of brain pathologies. However, an in vivo delineation of most human Bn has been elusive because of limited sensitivity and contrast for detecting these small regions using standard neuroimaging methods. To precisely identify several human Bn in vivo, we employed a 7 Tesla scanner equipped with multi-channel receive-coil array, which provided high magnetic resonance imaging sensitivity, and a multi-contrast (diffusion fractional anisotropy and T2-weighted) echo-planar-imaging approach, which provided complementary contrasts for Bn anatomy with matched geometric distortions and resolution. Through a combined examination of 1.3 mm 3 multi-contrast anatomical images acquired in healthy human adults, we semi-automatically generated in vivo probabilistic Bn labels of the ascending arousal (median and dorsal raphe), autonomic (raphe magnus, periaqueductal gray), and motor (inferior olivary nuclei, two subregions of the substantia nigra compatible with pars compacta and pars reticulata, two subregions of the red nucleus, and, in the diencephalon, two subregions of the subthalamic nucleus) systems. These labels constitute a first step toward the development of an in vivo neuroimaging template of Bn in standard space to facilitate future clinical and research investigations of human brainstem function and pathology. Proof-of-concept clinical use of this template is demonstrated in a minimally conscious patient with traumatic brainstem hemorrhages precisely localized to the raphe Bn involved in arousal.

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Parcellation of the human substantia nigra based on anatomical connectivity to the striatum

Cited by 59 publications

References 66 publications

Separate mesocortical and mesolimbic pathways encode effort and reward learning signals

Separate mesocortical and mesolimbic pathways encode effort and reward learning signals

Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression

Toward an In Vivo Neuroimaging Template of Human Brainstem Nuclei of the Ascending Arousal, Autonomic, and Motor Systems

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