Where is striatum located

It is continuous with the head of the caudate nucleus. Nucleus accumbens is located in basal forebrain in the preoptic area. It has an outer shell and an inner core. The inner core is a part of the ventral striatum. Most of the neurons in nucleus accumbens are GABAergic neurons. Olfactory tubercle is a processing center that is common to both the olfactory cortex and ventral striatum. It is also located in the basal area of the forebrain. Corpus striatum receives a number of connections from other areas of the brain.

These connections can be divided into the afferent fibers entering the striatum and the efferent fibers leaving it. A brief detail is given below. The most important input fibers come to striatum from the cortex. It receives projection fibers arising from the pyramidal neurons located in the fifth layer of cortex. These neurons are glutaminergic neurons. Striatum is considered to have its own microcircuit of neurons in which neurons of one part send and receive fibers from other parts of striatum.

Ventral striatum receives fibers from amygdala and hypothalamus. Nucleus accumbens in ventral striatum receives mesolimbic pathway from the ventral tegmental area. Basal ganglia receive fibers from the ventral striatum. It also receives nigrostriatal fibers from substantia nigra located in midbrain.

Efferent fibers from the striatum project mainly to the dorsal pallidum and dorsomedial nucleus of the thalamus. It also sends fibers to globus pallidus and pars reticulata of substantia nigra. These neurons are inhibitory GABAergic neurons. The blood supply to the striatum is mainly provided via anterior and middle cerebral arteries. Recurrent branch of anterior cerebral artery and striatal branches as well as anterior choroidal branch of middle cerebral artery provide blood to most of the parts of striatum.

Indeed, an exciting prospect for the future is the use of tracing techniques for studies of macrocircuitry in combination with the use of optical and genetic approaches for the elucidation of microcircuitry with cellular resolution.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Weixing X. Pan, Tianyi Mao, and Joshua T. Dudman performed the experiments. Joshua T. Dudman and Weixing X.

Pan analyzed the data and wrote the paper. We thank Alla Karpova for a careful reading of the manuscript. Albin, R. The functional anatomy of basal ganglia disorders. Trends Neurosci. Alloway, K. Topography of cortical projections to the dorsolateral neostriatum in rats: multiple overlapping sensorimotor pathways. Overlapping corticostriatal projections from the rodent vibrissal representations in primary and secondary somatosensory cortex.

Balleine, B. The integrative function of the basal ganglia in instrumental conditioning. Brain Res. Barroso-Chinea, P. Expression of vesicular glutamate transporters 1 and 2 in the cells of origin of the rat thalamostriatal pathway. Selective GABAergic innervation of thalamic nuclei from zona incerta.

CrossRef Full Text. Belin, D. Parallel and interactive learning processes within the basal ganglia: relevance for the understanding of addiction. Belova, M. Moment-to-moment tracking of state value in the amygdala.

Bernardo, K. Axonal trajectories between mouse somatosensory thalamus and cortex. Bevan, M. Selective innervation of neostriatal interneurons by a subclass of neuron in the globus pallidus of the rat.

Pubmed Abstract Pubmed Full Text. Brazhnik, E. Brown, L. Somatotopic organization in rat striatum: evidence for a combinational map. Representation of a single vibrissa in the rat neostriatum: peaks of energy metabolism reveal a distributed functional module. Neuroscience 75, — Metabolic mapping of rat striatum: somatotopic organization of sensorimotor activity. Organizing principles of cortical integration in the rat neostriatum: corticostriate map of the body surface is an ordered lattice of curved laminae and radial points.

Cardinal, R. Emotion and motivation: the role of the amygdala, ventral striatum, and prefrontal cortex. Cepeda, C. Cohen, M. Neurocomputational models of basal ganglia function in learning, memory and choice. Daw, N. Opponent interactions between serotonin and dopamine. Deniau, J. The pars reticulata of the substantia nigra: a window to basal ganglia output. Di Matteo, V. Doya, K. Modulators of decision making. Erro, E. Relationships between thalamostriatal neurons and pedunculopontine projections to the thalamus: a neuroanatomical tract-tracing study in the rat.

Striatal input from the ventrobasal complex of the rat thalamus. Cell Biol. Re-examination of the thalamostriatal projections in the rat with retrograde tracers. Flaherty, A. Corticostriatal transformations in the primate somatosensory system.

Projections from physiologically mapped body-part representations. Motor and somatosensory corticostriatal projection magnifications in the squirrel monkey. Floresco, S. Cortico-limbic-striatal circuits subserving different forms of cost-benefit decision making. Gerfen, C. The neostriatal mosaic: compartmentalization of corticostriatal input and striatonigral output systems. Nature , — The neostriatal mosaic: striatal patch-matrix organization is related to cortical lamination.

Science , — The neostriatal mosaic: multiple levels of compartmental organization in the basal ganglia. The neostriatal mosaic: II. Patch- and matrix-directed mesostriatal dopaminergic and non-dopaminergic systems. Goldman, P. An intricately patterned prefronto-caudate projection in the rhesus monkey.

Gray, T. Functional and anatomical relationships among the amygdala, basal forebrain, ventral striatum, and cortex. An integrative discussion. Graybiel, A. The basal ganglia and adaptive motor control. Haber, S. The primate basal ganglia: parallel and integrative networks.

The cortico-basal ganglia integrative network: the role of the thalamus. Striatonigrostriatal pathways in primates form an ascending spiral from the shell to the dorsolateral striatum. Hersch, S.

A quantitative study of the thalamocortical and other synapses in layer IV of pyramidal cells projecting from mouse SmI cortex to the caudate—putamen nucleus. Hoffer, Z. Organization of corticostriatal projections from the vibrissal representations in the primary motor and somatosensory cortical areas of rodents.

Functional circuits mediating sensorimotor integration: quantitative comparisons of projections from rodent barrel cortex to primary motor cortex, neostriatum, superior colliculus, and the pons. Hofstetter, K. The auditory cortex of the mouse: connections of the ultrasonic field.

Humphries, M. The ventral basal ganglia, a selection mechanism at the crossroads of space, strategy, and reward. Electrophysiological and morphological characteristics and synaptic connectivity of tyrosine hydroxylase-expressing neurons in adult mouse striatum. Kelley, A. The amygdalostriatal projection in the rat-an anatomical study by anterograde and retrograde tracing methods.

Neuroscience 7, — Malach, R. The pallial amygdala of amniote vertebrates: evolution of the concept, evolution of the structure. Mattiace, L. McDonald, R. A complex associative structure formed in the mammalian brain during acquisition of a simple visual discrimination task: dorsolateral striatum, amygdala, and hippocampus.

Hippocampus 17, — Mink, J. The basal ganglia: focused selection and inhibition of competing motor programs.

Miura, M. Compartment-specific modulation of GABAergic synaptic transmission by mu-opioid receptor in the mouse striatum with green fluorescent protein-expressing dopamine islands. Novejarque, A. Amygdalostriatal projections in reptiles: a tract-tracing study in the lizard Podarcis hispanica. Packard, M. Learning and memory functions of the Basal Ganglia. Striatal afferents arrive from three major sources: cortex, midbrain and thalamus Selemon and Goldman-Rakic, ; Haber, Depiction of the brain's reward circuit highlighting the role of the striatum and its anatomical connections.

Based on Haber and Knutson , reproduced with permission. The striatum has two main efferent pathways. MSN that express D2 receptors mostly target the external segment of the globus pallidus GPe and form the indirect pathway Parent et al. The SNr and GPi are the output nuclei of the basal ganglia. Cholinergic interneuron activity has a relationship to reward-predicting stimuli and reward and punishment Apicella et al. These firing properties suggest that these neurons may play a role in learning Schulz and Reynolds, Fast-firing interneurons are also involved in reward prediction error coding Stalnaker et al.

However, for brevity we will limit this review to MSN and refer to them as striatal neurons. Functionally, striatal neurons show motor and reward responses Hikosaka et al. Neurons in the striatum integrate information about expected reward with motor information to guide behavior Hollerman et al.

We review MSN neurophysiological responses to action and reward in the next section. The striatum contains neuronal activity related to movements, rewards and the conjunction of both movement and reward. Striatal neurons show activity related to the preparation, initiation and execution of movements Hollerman et al. These neurons are also active before overt goal-directed movements Schultz and Romo, ; Romo et al. Some of these neurons are exclusively active during self-initiated movements, whilst other neurons are only active during instructed trials, and some others do not discriminate between self-initiated and instructed movements.

In addition to this, striatal neurons also show reward related activity. Neuronal activity in the striatum is modulated by reward expectation independent of the movement necessary to obtain it Hikosaka et al. Striatal neurons that discharge after reward delivery do so in two main modes: phasic or tonic. By contrast, tonic responses have longer latencies and can last as long as the intertrial interval, i. Furthermore, there are striatal neurons coding which action is associated to reward and which action is not Hollerman et al.

This coding is independent of the stimuli indicating the action required to obtain reward Kimchi and Laubach, ; Kimchi et al. Reward-predicting cues modulate the activity of caudate neurons Kawagoe et al. Together, these data suggest that striatal neurons response is modulated by action and reward. These responses are not limited to the moment of movement or reward receipt; rather they are present during cue and during reward expectation.

Action and reward coding by striatal neurons. A Example striatal neuron active before movement go and silent before no-movement no-go. Based on Schultz and Romo , reproduced with permission. B Example striatal neurons coding reward. First row depicts a neuron with phasic active after juice reward delivery independent of the action to obtain reward.

Second row depicts a neuron with tonic activity after juice reward delivery. Third row shows a neuron with tonic activity after no reward is delivered. Based on Hollerman et al. C Example caudate neuron coding the conjunction of action and reward. This neuron is active during the presentation of a cue indicating the saccade necessary to complete the trial if the trial will be rewarded rewarded direction is highlighted by a bulls eye.

R, right; U, up; L, left; D, down. Polar plots show the average response for each cue and direction. Based on Kawagoe et al. D Top Depiction of the probability of larger rewards associated with left or right actions on each condition block. Colored numbers refer to the probability associated with left-right actions. Bottom Example striatal neuron coding right action value.

Based on Samejima et al. Most striatal neurons that respond during task performance show higher activity when a reward is expected compared to when no reward is expected Hollerman et al. However, there are also neurons that are active preferentially after the monkey is instructed to not move to obtain reward Hollerman et al. These data suggest that striatal neurons flexibly encode the type of action that will produce reward.

An action-value neuron tracks the value of one action, independent of the performed action. By tracking the value of different candidate actions and comparing their values an organism can decide to exploit the most valuable action or to explore the value of other actions.

Samejima et al. Neuronal activity tracked over time the value of performing one action regardless of the animal's choice. Later, Lau and Glimcher trained macaques to perform a matching task. In this task rewards are distributed probabilistically between two options and subjects match the frequency with which they choose one action with its reward probability Herrnstein, This task opens the possibility of investigating the presence of action-value and chosen-value i.

Indeed, Lau found that caudate neurons code both action-value and chosen-value. These signals can inform decision making mechanisms. In conclusion, the striatum contains neuronal activity related to movements, rewards and the conjunction of both movement and reward.

These neuronal representations serve many functions like goal directed movements and decision making. Rewards are events or objects that elicit learning, elicit approach behavior and produce positive emotions Schultz, Social rewards are just like any other rewards with the particularity that they occur in a social context. We propose a simple classification of social rewards using two axes: who acts and who receives reward.

For example, observing others is a social reward Anderson, ; Deaner et al. Pro-social behavior refers to a preference to increase the welfare of others Fehr and Camerer, Depending on individual social preferences these choices can be rewarding by themselves, e. Vicarious reward refers to the situation when observing someone else receive reward is rewarding in itself Mobbs et al. Finally, in several social rewards the recipient is the individual and the actor is someone else.

Examples of other's actions that are rewarding include praise and pleasant touch Francis et al. Building a desired reputation is also considered a social reward; critically, reputation depends on other's perception of the individual, not on the individual's perception of herself Izuma et al. Receiving gifts or social actions that result in own reward can also be considered as other-generated social rewards.

Social inclusion can be considered a social reward and facilitates learning Eger et al. Although this classification might further our understanding of the neuronal underpinnings of social rewards, further experimentation might validate its use. Fuelling a brain entails a huge cost, and the ratio of brain size to body size is larger in primates than any other Order in the animal kingdom Laughlin and Sejnowski, ; Dunbar and Shultz, The huge cost of fuelling a large brain begs the question what is the benefit of such large brains?

Byrne and Whitten suggest that only a costly primate brain can deal with the complexity of primate social living, the so-called social brain hypothesis Dunbar and Shultz, The primate brain has a great deal of specializations to acquire information about conspecifics. Neurons in the ventral visual pathway respond selectively to biological motion, gaze direction, body parts and faces Perrett et al. Social information arrives through all senses. For example, the superior temporal polysensory area contains neurons that selectively respond to conspecific calls Perrodin et al.

The volume of gray matter correlates with the size of the individual's troop in mid superior temporal sulcus, inferotemporal cortex, rostral superior temporal sulcus, amygdala—all areas involved in perceiving individuals—and rostral PFC in macaques Sallet et al.

These findings suggest that the brain has specialized structures dealing with the acquisition and representation of information about conspecifics. If the brain has specialized structures for the acquisition and representation of information about conspecifics, then acquiring this information must be valuable for the individual. In a clever paradigm Deaner and colleagues measured the value of acquiring access to observe pictures of conspecifics Deaner et al.

They pitted a constant amount of juice against a variable amount of juice plus the opportunity to observe the picture of a conspecific.

The monkeys made their choices depending on the amount of juice offered along with the picture. If the monkey chose a smaller amount of juice plus the opportunity to watch an image, it strongly indicated that the monkey valued watching the image equivalent to the difference between offered juice volumes. For example, a monkey that likes watching a high-ranking monkey will choose watching the image and receiving 0.

When the monkey chose with equal probability between the two alternatives then the difference in offered juice volume is the subjective value for observing the image, the so-called point of subjective equivalence. Researchers using this method can measure the subjective value of varying juice magnitudes fluid value and that of social images image value. Another advantage of this method is that it facilitates the comparison of different goods Glimcher, , e.

Using this method Deaner and colleagues reported that male monkeys valued highly looking at dominant monkeys and the perinea of female monkeys compared to looking at subordinate monkeys or a non-salient visual stimulus Deaner et al. Neuronal activity during this task has been measured in different brain regions. LIP neuronal activity correlates with both image value and fluid value when the monkeys chose to look at the image Klein et al. OFC neurons showed distinct coding of reward magnitude or image value, but not both Watson and Platt, Thus, these results suggest that OFC neurons do not code reward on a single currency e.

Intriguingly, these animals strongly preferred looking at pictures of subordinates, a finding at odds with previously reported strong preferences for dominant faces in the same paradigm Deaner and Platt, ; Deaner et al. Neurons in the anterior striatum showed an interesting response pattern in the same paradigm Klein and Platt, The large majority of reward responsive neurons were selective for reward type.

These neurons also showed a regional pattern: those in the caudate were more strongly modulated by social reward, conversely, putamen neurons were more strongly modulated by liquid reward. This pattern can be alternatively explained by simple saccade direction coding because caudate neurons are tuned for saccade direction, particularly for contralateral saccades Hikosaka et al. Humans also value observing other humans; and among different targets we value highly observing our romantic partners and mothers Bartels and Zeki, , ; Aron, ; Acevedo et al.

This effect is present either when the relationship is recent Aron, or when has been long established Acevedo et al. These BOLD responses are a neural correlate of the value of observing a loved one. Peak activation coordinates in the striatum of the fMRI studies cited in this review color-coded for each section as illustrated in the legend. Studies using a region of interest analysis strategy were not included in this image. These striatal responses are compatible with a general activation in response to social behaviors, including social rewards.

A functional subdivisions according to types of social rewards need to await further experiments. In summary, acquiring social information, in particular looking at conspecifics, is valuable for the individual Deaner et al. The primate temporal lobe contains regions whose function includes the processing of social information Tsao et al. Both social information and value converge in the striatum, opening the possibility of social reward coding in this brain region—as shown by Klein and Platt A positive reputation is a social reward as it can elicit learning, approach behavior and positive emotions.

This difference is likely due to insensitivity to social rewards in autistics Dawson et al. Other social rewards that also increase BOLD activity in the striatum include charitable donations Moll et al. This social vs. Taken together, these data suggest that social rewards are associated with BOLD activity in the striatum and can be modulated by the social context. Social life is rife with opportunities to learn about others. For example, we learn to trust or mistrust other people. The trust game is an economic game that measures how trust is built between two individuals.

During the trust game the investor receives an initial endowment that she can choose to invest in a trustee, the trustee receives three times the investment and decides how much of the gains to return to the investor.

When this game is played iteratively the investor learns to trust or mistrust the trustee and vice versa. Thus, both players develop a model of the other's reputation King-Casas et al. To build a trust model investors use previous behavior to predict future behavior. If there is a deviation from what is predicted—a reward prediction error—then the model is updated. When an investor returned more than what a trustee expected the trustee reciprocated by increasing her investment.

During the investment phase activity increased in middle cingulate cortex of the investor and also in ACC of the trustee. Activity in both areas correlated with activity in the trustee's caudate; most importantly the peak of these correlations shifted from the repayment epoch to the investment epoch King-Casas et al.

These results suggest that generating someone else's reputation engages a reinforcement learning algorithm that uses prediction errors and the latter are reflected in striatal BOLD activity. Prior information about someone's trustworthiness sets the initial state of the trust model. Prior information diminishes the magnitude of the reward prediction error signal in the striatum during the repayment phase Fouragnan et al. Following advice to solve a task a type of prior information generates an outcome-bonus in a version of the Iowa gambling task Biele et al.

These studies suggest that prior information not only sets the initial state of the trust model, but it has a long lasting effect on its computation. Depth-of-thought refers to a person's inference about someone else's intention and to how many iterations of this inference they perform Dixit and Skeath, Players in the trust game solve the game with different levels of depth-of-thought Xiang et al. If the investor makes no inference about the trustee's intention to reciprocate, then a prediction error occurs when the trustee does not reciprocate trust.

If the investor infers that he plays this game against a trustee that infers what he will offer, then the prediction error occurs when the investor submits its investment to the trustee; again, the striatum reflects this prediction error Xiang et al. Thus, the computation of prediction errors, during the trust game, depends on depth-of-thought. Oxytocin, a neuropeptide, also modifies how we update the trust model. Intranasal administration of this neuropeptide increases the rate of trust decisions compared to placebo, even after repeated violations of trust Kosfeld et al.

Correspondingly, people that received oxytocin showed a smaller negative prediction error signal in the striatum after repeated violations of trust Baumgartner et al. Social life is also rife with opportunities to learn from others. Observational learning is another social cognitive process that can be modeled with reinforcement learning.

Burke and colleagues hypothesized that observational learning is composed of two prediction errors, an action observation prediction error and an outcome observation prediction error Burke et al. In their task two individuals took turns to learn which one of two decks of cards provided a better outcome. In order to disentangle individual learning from imitation learning and observational learning the individuals performed the task in three conditions: other's actions and outcomes were private, only the other's outcome was visible and both the partner's action and outcome were observable.

Specifically, VMPFC activity correlated positively and ventral striatum correlated negatively with the outcome observation prediction error Burke et al. Thus, they found neural correlates of observational learning in frontal cortex and ventral striatum.

In conclusion, the neuronal mechanism of learning to trust someone else or from someone else is based on a reinforcement learning algorithm. This algorithm makes predictions about other's behavior and prediction errors help to update the model. The type of predictions depends on depth-of-thought and prior information modifies the rate to which the model is updated.

These learning signals are reflected in changes in BOLD activity in the striatum. Inequity arises from an asymmetric distribution of resources between two or more conspecifics.

These brain areas get grouped together because they all play a role in how people make decisions and respond to rewards. The ventral striatum helps someone determine that a pizza is rewarding, and that they want more of it. It also plays a role in motivation — whether we want to try something. That means that the ventral striatum is important in things like mood, learning and addiction.