Candidate Review:

Identifying the Functional Architecture of the Human Ventral Tegmental Area and the Substantia Nigra using High Resolution Magnetic Resonance Imaging

Mariam Eapen* and John C. Gore§

*Neuroscience Graduate Program, Vanderbilt University Medical School, U1205 Medical Center North, Nashville, TN 37232, USA.
§Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA.
Correspondence to M.E. e-mail:

Abstract | Full Text | PDF

ABSTRACT | The ventral tegmental area (VTA) and the substantia nigra pars compacta (SNc) are subcortical areas within the ventral midbrain that are primary synthesizers of the neurotransmitter, dopamine (DA). Dopaminergic neurons from these areas have widespread projections to many subcortical and cortical parts of the brain. However, to date, the In vivo studies in rodents and non-human primates have shown that the dopaminergic neurons in the VTA and SNc are similar in their firing properties and release of DA1,2,39. However, these firing patterns are believed to facilitate multiple functional roles associated with reward related learning, motivation, and other goal directed behaviors1,50,51,60.

Since most of the studies on the VTA and SNc have been done in non-human species, it is difficult to translate this work into humans and accurately characterize the functional role of these two regions in normal human brain function. Non-invasive functional magnetic resonance imaging (fMRI) is one technique used to study human brain function in vivo. In particular, high resolution fMRI performed in ultra high field magnets (7 Tesla) can be especially beneficial in segmenting the anatomical substructure of brain areas in close proximity. This paper reviews the anatomical layout and functional significance of the VTA and SNc and proposes the use of ultra high field high resolution MRI to study the functional architecture of these two midbrain areas.


The anatomy of the VTA and SNc is unique and challenging to study because of its location in the brain, cellular profile and complex interconnections. Nonetheless, an overview of the anatomy is essential to localize the source of an MRI signal, optimize the parameters required to image this part of the brain and correlate it with brain function.

The VTA and SNc are located in the ventral portion of the midbrain brain stem area, and they both vary in size and cytoarchitecture. The VTA is approximately 60mm3 in size3 and consists of heterogeneous groups of neurons that are part of the A10 dopaminergic system5,6. The SNc is approximately 1100mm in size3-4 and is part of the A9 dopaminergic system5,6. A10 DA fibers contained within the ventromedial midbrain, consist of small diameter (15-30μm), non-myelinated axons that ascend in the medial forebrain bundle (MFB)7,8. The A9 DA fibers, on the other hand, vary in size (20-40μm) and extend from the medial lemniscus to the lateral border of the cerebral peduncles9.

The VTA is further subdivided into separate nuclei based on their location and cellular profile10,15, and the neuronal populations in these subdivisions tend to be mediolaterally arranged11. The SN is topographically divided into two subdivisions, the pars compacta and pars reticulata9. The compacta cells (SNc) have larger cell bodies, thicker and longer dendrites, more numerous dendritic segments and denser neuromelanin granules compared to the reticulata cells12,13,14.

The DA neurons in the VTA have widespread reciprocal connections with sub-cortical and cortical areas of the brain, making this region a major site of information integration. It has reciprocal connections with limbic cortices through the mesolimbic pathway, including the nucleus accumbens (NAc), amygdala, cingulate cortex, and the hippocampal complex15. It has efferent and afferent associations with the prefrontal cortex, insular cortex, some sensory, motor and association areas (the mesocortical pathway), and with various nuclei of the thalamus and hypothalamus15,16,17. It is also reciprocally connected to the dorsal raphe nuclei, locus ceruleus, various brain stem nuclei, the superior colliculus, reticular formation periaqueductal gray, and the spinal cord15,17,18,19,20. Mesocortical projections tend to have their origin dorsorostrally in the VTA21 ,22, and the mesolimbic projections originate in the ventrocaudal VTA15. Within the midbrain, the VTA receives glutamatergic input from the laterodorsal tegmentum (in the mesopontine brainstem)23, and cholinergic input from the pedunculopontine tegmentum24,25.

Within the ventral midbrain, there is a dorsoventral topography of the DA neurons26,27,28. In primates, the dorsal tier of neurons forms a medio-lateral continuum of DA cell groups that include the dorsal SNc, the retrorubral area and the VTA9,12. The neurons in this tier are calbindin-D28k-positive, contain low levels of mRNA for DA D2 receptor27, have dendrites that are oriented mediolaterally, and project to the ventral forebrain as the mesolimbic pathway. In contrast, the ventral tier of neurons consists of the ventral SNc (densocellular zone) and the cell columns extending into the pars reticulata. These neurons are calbindin-D28k-negative, have relatively high levels of mRNA for the DA D2 receptor27, contain dendrites oriented ventrally, and project to the dorsolateral striatal regions as the niagrostriatal pathway. The neurons in the densocellular zone project to both the ventral and sensorimotor-related striatum28.

The majority of efferent and afferent pathways of the SNc form the niagrostriatal and striatonigral pathways. The SNc receives topographically organized input from different parts of the striatum in an inverse dorsoventral fashion32. Sensorimotor areas of the striatum project to the ventrolateral pallidum and ventrolateral SNc cell columns29,30,31. Projections from the central striatum terminate more centrally in both the pallidum and ventral densocellular SNc. Ventral striatum projects topographically into the ventral pallidum, VTA and densocellular SNc32.

Therefore, the VTA and SNc vary in their cellular architecture along the ventral mediolateral span of the midbrain. Projections to and from the VTA and medial SNc seem to be associated with the limbic areas, whereas the lateral and ventral SNc regions are connected to the association and motor related areas. The next section reviews the functional significance of these structural connections.


Electrophysiological recordings from the VTA/SNc and their projection sites show DA neurons having a characteristic pattern of activity comprising: (i) a hyperpolarized, inactive state; (ii) a slow, irregular, single spike or ‘tonic’ firing pattern; and (iii) a burst or ‘phasic’ pattern of activity33,34. Interactions between these distinct firing patterns are known to encode behaviorally relevant signals that facilitate reward related learning, motivation, novelty assessment and other goal directed behaviors.

The phasic firing pattern is dependent on afferent input into the neuron and constitutes a rapid, high concentration efflux of DA released into the synaptic space35. This burst release of DA is believed to be the functionally relevant signal sent to post synaptic sites to indicate reward and other goal directed behaviors1,36. The DA released in this manner may function selectively on DA receptors localized within or around the synapse and therefore affect only a selected number of post synaptic neurons (for example, in the NAc and striatum) 37.

On the other hand, the single-spike or tonic firing pattern is driven by an intrinsic pacemaker potential38 that results in a slow changing, low tonic concentration of DA released into the extra-synaptic space37,39. The overall activity of DA tonic firing is thus more spatially distributed affecting a large pool of post synaptic neurons (for example, in the ventral striatum) and modulating input from other neurons. The phasic and tonic firing patterns were both observed in the VTA37 as well as the SNc33,35,38. The unique behavioral significance of these two firing patterns is reviewed next.

Single unit studies in non-human primates conducted by Schultz and colleagues1 ,40,41,42,43 showed that the phasic firing pattern of midbrain DA neurons (primarily in the VTA and SNc) encodes a learning signal that predicts the error in the occurrence of a rewarding or aversive stimulus. These neurons responded robustly to primary food and liquid rewards and conditioned cues predicting the reward40,41,44,45. However, they seemed to respond much less to aversive stimuli like air puffs, saline drops to the mouth and foot pinches46,47. Even though most of the midbrain neurons measured in the reward prediction error studies were DA in nature, the non-DA neurons, in contrast, were shown to respond robustly to aversive stimuli47. Human neuroimaging studies using fMRI have corroborated Schultz’s evidence, showing that the VTA and ventral striatum are involved in processing positive prediction errors during conditional associative tasks using appetitive or monetary rewards 48,49. However, due to the limited spatial and temporal resolution of the blood oxygen level dependent (BOLD) response, it is not conclusively credible that the activity seen in the VTA is contributed solely by the phasic firing pattern of the DA neurons.

In contrast, the slowly changing and low concentration tonic firing pattern is thought to be involved in setting up a motivational state, providing initial input to other neuronal systems subserving reward seeking or general goal-directed functions50,51. Voltammetry studies52, micro dialysis studies53,54 and electrophysiological experiments55 conducted in the NAc (a major projection site of the VTA) indicate that DA release is maximum during the performance of a behavior or the presentation of a stimulus that triggers a behavioral response. This activity in the NAc is attributed to its role in engaging with other brain structures to influence parameters for motor activity56,57. Thus, the NAc in association with the midbrain DA neurons appears to be involved in higher order sensorimotor functions that are important for motivational processes.

Schultz’s studies also showed that the DA neurons in the VTA and SNc fired phasically when the animals were exposed to unexpected or novel aspects of the reward (novel magnitude or reinforcing properties of the reward or novel time of reward delivery)40,44,45. Human neuroimaging studies using fMRI also found that the SNc/VTA region preferentially responded to stimulus novelty over other forms of stimulus salience like rareness, target response and negative emotional arousal58. However, the spatial resolution in these neuroimaging studies was not feasible to differentiate activity between the VTA and the SNc.

While DA is known to be involved in reward processing, it is more specifically involved in directing attention to salient stimuli in order to prepare an appropriate behavioral response40,42. Haber and colleagues32,59,60 suggested that the process from detecting a salient stimulus to preparing an appropriate behavioral response involves a complex chain of events that recruits an ascending spiral feed-forward organization of the niragro-striatal-niagro pathways. It begins with motivation in the dorsal tier DA cells (VTA, SNc and their connections with the NAc shell), proceeds through cognitive processing in the ventral tier DA cells (SNc and its connections with the NAc core and central striatum); and finally shapes motor outcomes though the ventral tier DA cell columns of the SNc and its connections with the dorsolateral striatum.

In summary, the studies reviewed thus far indicate that the midbrain DA neurons are known to be involved in reward related learning when responding to an unpredicted reward or a cue that reliably predicts the reward. Moreover, they respond preferentially to novel aspects of the stimulus compared to other salience properties. While it is difficult to draw a fine distinction between the role of the VTA and SNc DA neurons, these studies suggest that the VTA DA neurons seem to respond to the motivational, novelty and salience aspects of the stimulus. On the other hand, the SNc DA neurons seem to be associated with preparing an appropriate behavioral response to the stimulus. The role of the midbrain DA neurons in human brain function was not well characterized in the above mentioned fMRI studies. Advanced imaging techniques that can accurately localize the MR signal can provide better insight into the fine grained functional architecture of midbrain substructures like the VTA and SN. Understanding how to achieve this step in imaging technology is discussed in the next section.


The aforementioned studies have attempted to characterize the function of the VTA and SNc in rodents and non-human primates. However, very little work has been done to functionally delineate the midbrain DA neurons in humans. Given DA’s role in reward related learning, novelty assessment and motivation, it would be important to understand how DA produced in these midbrain areas are relevant in human brain function.

While DA release can be directly imaged using PET (Positron Emission Tomography), this technique does not provide high spatial resolution required to segment brain regions in close proximity. Anatomical MR imaging affords the visualization of high resolution images of the human brain and was initially developed for diagnostic purposes. With the advent of current high resolution MRI techniques, areas like the brainstem can be segmented, revealing details approaching those seen in histological specimens61. Current three dimensional high resolution MR methods can produce images with an isotropic voxel dimension of 700μm in a 7 Tesla magnet (Figure 1).

MRI based on the BOLD response is a potential way to study the functional roles of brain stem areas like the VTA and the SNc. Most fMRI studies involving the brain stem to date have been conducted in low field scanners (1.5 Tesla or 3 Tesla) with imaging protocols that have certain limitations on sensitivity and signal to noise ratios (SNR). However, at higher field strengths (7 Tesla or higher), some of these limitations can be ameliorated because of the ability to view smaller voxel dimensions from more localized regions, and because BOLD signals increase with increasing field strength. However, higher field strength imaging has various technical challenges, especially when imaging the midbrain. Some of these challenges include signal artifacts and distortions caused by magnetic susceptibility variations in the brain and the behavior of radio frequency coils at high frequency.

Figure 1 | 7 Tesla MRI image from a T2 weighted GRASE (Gradient And Spin Echo) pulse sequence. a | Axial image of the midbrain at the level of the superior colliculus; b | Enlarged view of the midbrain area highlighted in A. CP = Cerebral Peduncles; SN = Substantia Nigra; R = Red nucleus; VTA = Ventral Tegmental Area; PCA = Posterior Cerebral Artery; MB = Mammillary Body. (Click image for larger view.)

The location of the midbrain (apposing the interpeduncular cistern) is such that the tissue magnetic susceptibility varies within and across the region, thereby distorting the applied magnetic field. This results in signal artifacts like geometric distortions (macroscopic spatial image distortion) and variations in signal intensity (microscopic, due to dephasing of the proton spins). In order to compensate for susceptibility artifacts, techniques like asymmetric spin echo imaging62, modified single shot echo planar and spiral imaging63,64,65, multiple linear gradients66, and higher order gradients67 have been used. A recent study used the magnetic susceptibility differences (phase changes) across tissues in a human 7 Tesla to generate high contrast to noise ratios in cortical structures 68. While none of these techniques can completely eliminate the distortion and signal dropout observed at high field, in various combinations they can be used to improve image quality.

Noise also increases as you go to higher field strengths. The intrinsic noise (thermal noise in the body and from scanner electronics) increases linearly with increasing frequency; while the physiological noise caused by head motion, respiration, and cardiac cycles also increases with increasing field strength. However, specific technical advances are possible to overcome these fields, such as the use of array coils69 and dynamic shimming70,76.

While the above mentioned techniques can help to improve image quality, they are not sufficient for accurately localizing fMRI signal (both spatially and temporally) with respect to neuronal activity. The BOLD signal measures neuronal activity indirectly by detecting relative changes in deoxygenated and oxygenated hemoglobin in the vascular region adjacent to the activation site. In order to spatially localize the BOLD signal, different techniques such as diffusion weighted imaging, perfusion weighted imaging (imaging blood flow in capillaries), MR angiography and susceptibility weighted imaging (imaging the venous system at the region of activation) can be used. At higher fields, these methods become more practical because of the higher SNR.

The temporal resolution of fMRI is on the order of seconds, limited mainly by the delay in the hemodynamic correlate of neuronal activity, though in practice, the ability to assess the onset of events is limited by the SNR. Methods to improve the temporal resolution of the data acquisition time include multiple channel acquisition (by using more receiver coils), partial k-space imaging71 and the development of efficient k-space trajectories that use both x and y gradients to sample k-space in a diagonal or spiral direction65. These techniques may only improve the image data acquisition time, but the temporal resolution is still limited by the BOLD dynamics. However, at high resolution, we have the ability to parse out different parts of the BOLD signal as the SNR is higher at higher field strengths.

Apart from reward prediction error tasks, several human fMRI studies conducted in low field magnets have shown BOLD activation in the mesolimbic regions like VTA, SNc, hippocampus and amygdala. These were observed in tasks using pleasant tasting stimuli72, monetary rewarding tasks73, novelty and memory recall tasks74, reward anticipation and reward related memory recall tasks75. However, these studies have not accurately mapped the spatial and temporal profile of the BOLD signal within the midbrain, especially at a resolution required to delineate functional differences between the VTA and SNc.

fMRI techniques mentioned above using high resolution imaging in ultra high filed magnets (like 7 Tesla) promises to improve the localization of the BOLD signal from functionally important areas like the midbrain VTA and SNc. Optimization of already existing imaging techniques and the use of complementary imaging protocols (perfusion weighted imaging, susceptibility weighted imaging, proton density imaging) tailored to the midbrain area would enable us to achieve this.


Given what we know of the distinct anatomy and structural connections of the VTA and the SNc, and their functional relevance in various goal directed behaviors, it would be a likely next step to parse out the individual function of these two areas, especially within the human brain. As described in this review, neuroimaging techniques, particularly those using high resolution imaging, offers a plausible approach to investigate the functional architecture of these midbrain regions. This would enable us to ask ecologically valid questions about the role of these midbrain areas in humans, which is typically challenging to do in non-human species. Moreover, the advancement of research methodologies used to examine these midbrain areas can potentially translate into the clinical realm to investigate the role of DA in midbrain related pathologies.


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This article details one method by which we can deal with physiological noise associated with respiration.

77.    Napadow V, Dhond R, Kennedy D, Hui KK and Makris N (2006). Automated Brainstem Co-registration (ABC) for MRI. Neuroimage. 32 (3): 1113-9.


John Gore’s Lab