Monoaminergic Neuromodulation of Sensory Processing

Abstract

All neuronal circuits are subject to neuromodulation. Modulatory effects on neuronal processing and resulting behavioral changes are most commonly reported for higher order cognitive brain functions. Comparatively little is known about how neuromodulators shape processing in sensory brain areas that provide the signals for downstream regions to operate on. In this article, we review the current knowledge about how the monoamine neuromodulators serotonin, dopamine and noradrenaline influence the representation of sensory stimuli in the mammalian sensory system. We review the functional organization of the monoaminergic brainstem neuromodulatory systems in relation to their role for sensory processing and summarize recent neurophysiological evidence showing that monoamines have diverse effects on early sensory processing, including changes in gain and in the precision of neuronal responses to sensory inputs. We also highlight the substantial evidence for complementarity between these neuromodulatory systems with different patterns of innervation across brain areas and cortical layers as well as distinct neuromodulatory actions. Studying the effects of neuromodulators at various target sites is a crucial step in the development of a mechanistic understanding of neuronal information processing in the healthy brain and in the generation and maintenance of mental diseases.

Introduction

Even at the earliest stages of sensory processing, the neuronal representation of external stimuli is modulated by internal brain states (Aston-Jones and Cohen, 2005; Harris and Thiele, 2011). While the evidence for such modulation is long-standing, the analysis of sensory representations has typically focused on the feed-forward stimulus-driven component while regarding the modulation by internal states as noise. However, recent results based on population recordings (Reimer et al., 2014; Rabinowitz et al., 2015; Schölvinck et al., 2015) that highlight the extent of brain-state dependent modulation of sensory processing, the discovery of substantial modulation of sensory activity with locomotion (Niell and Stryker, 2010; Polack et al., 2013), as well as novel tools to more selectively target modulatory circuit elements genetically have contributed to reviving the interest in the neuromodulation of sensory processing. Since the role of acetylcholine has received substantial attention and has been the subject of excellent recent reviews (Sarter et al., 2009; Harris and Thiele, 2011), we will focus here on the modulation by the monoamines dopamine (DA), noradrenaline (NA), and serotonin (5HT). For each of these modulatory systems, we will summarize anatomical data and electrophysiological findings to provide insights into their role in the modulation of sensory processing, placing an emphasis on studies in non-human primates and rodents, and highlighting the complementarity of these neuromodulatory systems (Figure 1). We will cover key classical studies and then shift our focus toward more recent work.

FIGURE 1

Serotonergic Modulation of Sensory Processing

Serotonin Sources

Serotonin-synthesizing neurons are located in the brainstem in a small group of clusters [named B1–B9 after Dahlström and Fuxe (1964)]. These were first identified in the rat brain (Dahlström and Fuxe, 1964) but their anatomical localizations in mouse and primate species, e.g., Jacobowitz and MacLean (1978), have been found to be largely consistent with that in the rat. These clusters are typically divided into a caudal and a rostral group (Hornung, 2010). The caudal group, which consists of the raphe pallidus (B1), the raphe obscurus (B2), and raphe magnus (B3) (Lesch and Waider, 2012), projects mainly to the spinal cord and brain stem. The rostral group includes the dorsal raphe nucleus (B6, B7) and the median raphe nucleus (B5, B8, and B9) and projects to the cortex. Within this group, there is some topographic organization of the serotonergic innervation (Hornung, 2010) that reflects a rostral (frontal cortex) to caudal (occipital cortex) gradient (Wilson and Molliver, 1991b). Such topographical organization suggests that rather than reflecting a signal that is broadcasted uniformly throughout the brain, serotonergic projections to different areas are more specific and may serve different roles. Indeed, retrograde studies in rats support topographically specific projections, for example to the prefrontal cortex (PFC) (Chandler et al., 2013). Although serotonergic neurons represent only a very small number of the neurons in the brain [approx. 28,000 in the mouse (Ishimura et al., 1988) to several 100,000 in humans (Hornung, 2010)], they give rise to diverging projections to virtually all regions of the mammalian brain (Hornung, 2010). Here, we will focus on the serotonergic projections to primary sensory cortical areas and subcortical structures involved in sensory processing.

Serotonergic Projections to Early Sensory Areas

Anatomical studies in different rodent and monkey species have identified substantial serotonergic projections from the raphe nuclei to early sensory areas including the primary auditory, visual, and somatosensory areas, the olfactory bulb, and subcortical structures involved in sensory processing (Table 1). [Note that while in the auditory system, serotonergic innervation of the cochlear nucleus is established (Klepper and Herbert, 1991), serotonergic projections to the retina have been controversial (Schnyder and Künzle, 1984; Frazão et al., 2008)].

Comparisons of monoaminergic innervation found that the serotonergic innervation was substantially more pronounced than that for NA or DA in the macaque primary auditory cortex (Campbell et al., 1987) and in the macaque primary visual cortex (Morrison et al., 1982a; Kosofsky et al., 1984; Morrison and Foote, 1986; Lewis et al., 1987). This pattern mirrors early reports of regional differences in cortical monoaminergic distribution (Brown et al., 1979), with a pronounced decrease in DA from frontal to occipital cortex, a weaker gradient (interrupted by a peak in the somatosensory cortex) for NA, and a roughly uniform distribution for serotonin (Figure 1B).

Within primary sensory cortical areas, the distribution of serotonergic fibers in primates shows a characteristic laminar profile. In the primary visual cortex, anatomical data for different primate species agree that the distribution of serotonergic axons is highest in layer 4 (Kosofsky et al., 1984; Morrison and Foote, 1986). This suggests that the serotonergic modulation in the primary visual cortex is biased toward targeting the visual input stage. Serotonergic fibers are also consistently found in cortical layer 4 in the primary auditory cortex (Campbell et al., 1987) and somatosensory cortex (Wilson and Molliver, 1991a,b), although not preferentially.

This contrasts with the monoaminergic innervation of primary sensory areas by NA and DA (see below) that is typically sparse if not absent in layer 4 (Figure 1B). (Note that while a transient dominance of serotonergic input to layer 4 occurs during the early post-natal development in the rodent primary visual cortex and barrel cortex (Fujimiya et al., 1986; Dori et al., 1996), regional and laminar differences are less pronounced in rodents than in the primate species.)

Consistent serotonergic innervation is also found in subcortical structures involved in sensory processing such as the sensory thalamus (Vertes et al., 2010), the superior (Dori et al., 1998) and inferior (Klepper and Herbert, 1991) colliculi, and the cochlear nucleus (Klepper and Herbert, 1991). In the olfactory bulb, serotonergic fibers reach the glomerular layer, the primary input stage (Takeuchi et al., 1982). Together, the extent of serotonergic innervation at the earliest stages of sensory processing makes this system well suited to directly modulate the incoming sensory information.

Serotonergic Synapses and Receptors

The serotonergic projections to the primary sensory areas consist of small varicose axons that are widely distributed (Hornung, 2010). Only a very small proportion of synaptic specializations, typically asymmetric, is found (Descarries et al., 2010), suggesting that serotonin predominantly acts by volume transmission from varicosities. Note, however, that the degree to which neuromodulatory systems rely on “wired” transmission, i.e., highly localized and typically synaptic, or “volume” transmission, i.e., more spatially diffuse, is subject to debate (e.g., Rice and Cragg, 2008; Sarter et al., 2009; Fuxe and Borroto-Escuela, 2016; Sulzer et al., 2016). In the mammalian brain, seven serotonin receptor families, most with several subtypes, have been identified to date and contribute to the functional diversity of serotonin (Mengod et al., 2010). A detailed overview is outside the scope of this review, but a few receptors should be highlighted. 5HT1A is expressed on cortical pyramidal neurons (DeFelipe et al., 2001). In the macaque primary visual cortex, the most densely expressed receptors are 5HT1B and 5HT2A (Watakabe et al., 2009), predominantly in layer 4. 5HT1B is also strongly expressed in the LGN, but only weakly in other cortical areas including the auditory and somatosensory cortex (Watakabe et al., 2009). In the mouse, GABAergic neurons that express the 5HT3A do not express the calcium binding protein parvalbumin or somatostatin and may form a third non-overlapping class of inhibitory interneurons (Rudy et al., 2011).

Serotonergic Modulation of Sensory Physiology

Given the complexity of the input to serotonergic neurons (Pollak Dorocic et al., 2014), the wide distribution of serotonergic projections in the brain and the diversity of serotonin receptors, it is unsurprising that serotonin has been implicated in a spectrum of brain functions. These include the sleep–wake cycle, hormonal regulation, regulation during development as well as affective, cognitive, and sensorimotor functions. Serotonergic neurons show tonic and phasic modes of discharge that are thought to signal different information. For example, in the mouse transient responses of putative serotonergic neurons in the dorsal raphe nucleus reflect a variety of behavioral, sensorimotor, and reward-linked information (Ranade and Mainen, 2009). Phasic and tonic response patterns of optogenetically identified serotonergic neurons in the mouse dorsal raphe have been proposed to reflect the contextual valence on different time-scales (Cohen et al., 2015). Serotonergic neurons have also been linked to signaling patience (Fonseca et al., 2015). But, even for the intensely studied links to reward signaling a simple computational account has proved challenging (Ranade et al., 2014; Dayan and Huys, 2015). Although it is unclear whether its modulatory role can be conceptualized by a simple overarching computational function, serotonin is thought to modulate sensory processing according to behavioral–motivational context.

In reviewing studies of serotonergic modulation of early sensory processing across modalities, consistencies are notable, which will be our focus here (Table 2). This focus contrasts with previous perspectives highlighting the diversity of findings (Hurley et al., 2004). (Note that we restricted this summary to studies of short-term sensory modulation and did not consider reports on adaptation or plasticity.) Some variability in the findings likely results from comparing results across anesthetized animals using different anesthetics or awake animals and different experimental approaches.

Despite this variability, most findings are consistent with an overall serotonin-mediated decrease of the sensory response. In the auditory system, a decrease of the extracellular response was observed for the majority of neurons both in the cochlear nucleus of the rat (Ebert and Ostwald, 1992) and the inferior colliculus (IC) of bats (Hurley and Pollak, 1999), although some variability of the effects between cells was observed. Behaviorally, a reduced startle response to auditory tones was observed for intraventricular injection of serotonin (Davis et al., 1980), which is consistent with reduced auditory response (but could also reflect downstream processing). Similarly, a reduced mechanosensory response was observed in behaving mice during optogenetic stimulation of serotonergic raphe neurons (Dugué et al., 2014), which could reflect downstream processing but would also be expected for a reduced sensory response in the somatosensory cortex as previously reported (Waterhouse et al., 1986).

For early visual processing, predominantly decreased responses were observed for the iontophoretic application of serotonin in the cat lateral geniculate nucleus (LGN) (Phillis et al., 1967) and rat V1 (Waterhouse et al., 1990). In the anesthetized macaque, when attempting to dissect the role of the two most strongly expressed receptors in V1, 5HT1B and 5HT2A, using receptor specific ligands, a diverse pattern and bi-directional modulation were observed for both (Watakabe et al., 2009). However, these effects were not compared to spontaneous variability of the responses resulting from the anesthesia or the iontophoretic application itself. For example, slow fluctuations in the neuronal responses have been shown to contribute to stimulus-independent co-variability (“noise correlations”) between neurons (Ecker et al., 2014). When instead iontophoretically applying the endogenous ligand serotonin in awake macaques and comparing the effects against those of pH matched saline application, a recent study found an overall decrease of the sensory responses with serotonin (Seillier et al., 2017). While there was some variability across cells, consistent with the results of Watakabe et al. (2009), the inhibitory effect of serotonin was the dominant pattern across the sizeable neuronal population. This decrease was predominantly explained by a multiplicative change (gain change) of the neuronal tuning curves. Behaviorally, a recent study that systemically administered a serotonin-reuptake inhibitor to enhance the effect of serotonin while macaques performed a color discrimination task observed slowed reaction times as well as deteriorated perceptual performance (Costa et al., 2016), as expected for such reduced visual responses. Conversely, a gain reduction of the spontaneous response (Lottem et al., 2016), consistent with an increased signal-to-noise ratio (SNR), or a gain reduction of the tuning curves (Petzold et al., 2009) for serotonin was observed in the mouse olfactory bulb.

Taken together, a surprisingly consistent pattern of the serotonergic modulation of early sensory processing across modalities emerges. The decreased sensory response by serotonin – effectively lowering the salience of the sensory input – may reflect a sensory signature of how serotonin shapes behavior in downstream circuits, such as its proposed role as a behavioral inhibitor (Soubrie, 1986), to promote waiting (Miyazaki et al., 2014; Ranade et al., 2014; Fonseca et al., 2015) or persistence (Lottem et al., 2018).

Noradrenergic Modulation of Sensory Processing

Noradrenergic Sources

In rodents (Dahlström and Fuxe, 1964) and primates (Jacobowitz and MacLean, 1978), neurons that produce NA are located in the brainstem in clusters named A1–A7 after (Dahlström and Fuxe, 1964). Of these, the locus coeruleus (LC, A6) projects to most areas in the brain (Loughlin et al., 1986), except for to the basal ganglia [reviewed in Berridge and Waterhouse (2003)], and is the sole source of the noradrenergic innervation of the cerebral cortex (Jones et al., 1977; Moore and Bloom, 1979). Immunohistochemical evidence indicates that within the LC the vast majority of neurons are noradrenergic (Grzanna and Molliver, 1980). Similar to the serotonergic and dopaminergic systems, the absolute number of noradrenergic neurons in the LC is small [estimated between approx. 1500 per hemisphere in rodents and approx. 15,000 per hemisphere in humans, reviewed in Sara and Bouret (2012)], but the projections of these neurons are divergent and wide-spread throughout the brain. Despite these wide-spread projections recent findings indicate a modular organization of the LC in rats (Uematsu et al., 2017) and substantial anatomical specificity of the connections, for example to the prefrontal versus the motor cortex (Chandler et al., 2014), or different modules projecting to the amygdala compared to the medial PFC (mPFC) (Uematsu et al., 2017). It therefore seems likely that at least some degree of modularity is also characteristic of projections to sensory areas. In the following, we will again focus on the projections to the primary sensory areas and subcortical structures involved in early sensory processing.

Noradrenergic Projections to Early Sensory Areas

The LC sends divergent projections to the cortex and subcortical structures. Within the LC, these projections are roughly topographically organized [reviewed in Berridge and Waterhouse (2003)]. In the rat, cortex-projecting neurons are more prominent in the caudal portion of the LC and show some ventral (frontal cortex) to dorsal (occipital cortex) organization (Waterhouse et al., 1983). Despite the rough topography, a recent study combining retrograde labeling and optogenetic stimulation in the mouse found that the LC projections to primary sensory cortices are not modality-specific (Kim et al., 2016) (contrasting with these authors’ findings for the cholinergic system). Nonetheless, projections from LC show clear regional differences (Table 3). Early studies in rats (Kehr et al., 1976) and macaques (Brown et al., 1979) observed an overall frontal (higher concentration) to occipital (lower concentration) gradient of NA throughout cortex, with the exception of somatosensory cortex where the concentration was highest (Brown et al., 1979). This gradient was weaker than that for DA and differed markedly from the absence of a gradient for serotonin (reviewed above and see Figure 1).

Within the primary sensory cortex, the noradrenergic innervation shows some laminar specialization, particularly in primates. In the primate somatosensory cortex, noradrenergic fibers are fairly uniform and dense throughout layers (Morrison et al., 1982b; Lewis et al., 1987). The innervation of the primary auditory cortex (Campbell et al., 1987) and primary visual cortex (Kosofsky et al., 1984; Morrison and Foote, 1986), in contrast, is sparser overall, and a “striking absence” (Foote and Morrison, 1987) of layer 4 innervation, particularly in V1, has been observed. Combined with the near absent innervation of the LGN (Morrison and Foote, 1986), which provides the dominant feed-forward visual input to V1, this suggests that – in contrast to the serotonergic system – noradrenergic modulation does not target the visual input stage. Interestingly, such complementarity between the serotonergic and noradrenergic innervation of the sensory input stage is also present in the rat olfactory bulb. While “virtually no label” was observed in the glomerular layer (the site of the first synapse of the olfactory input) using anterograde tracer injections in the LC (McLean et al., 1989), this layer showed the densest serotonergic innervation (McLean and Shipley, 1987) (see above). Instead, pronounced noradrenergic innervation in the rat olfactory bulb was observed for the consecutive processing stages, the internal plexiform, granule, and external plexiform layers (McLean et al., 1989).

Noradrenergic Synapses and Receptors

Similar to the other monoaminergic systems, noradrenergic neurons in the LC show both tonic and phasic modes of activation [reviewed in Berridge and Waterhouse (2003)]. Their axons have characteristic NA-containing varicosities that can form synapses (e.g., Papadopoulos et al., 1989) and likely have non-synaptic release sites (Callado and Stamford, 2000). Three adrenergic receptor families are expressed in the brain (alpha 1, alpha 2, and beta 1–3), which have characteristic pre- and postsynaptic sites and laminar expression patterns across cortex (Berridge and Waterhouse, 2003). Noradrenaline has the highest affinity for the α2 receptors, intermediate for α1 receptors, and lowest affinity for the β adrenergic receptors [reviewed in Ramos and Arnsten (2007)]. In the primate PFC, these differences in affinity have been implicated in differentially modulating cognitive processes as a function of the level of noradrenergic tone (Ramos and Arnsten, 2007). They are likely also an important factor in the substantial diversity in modulation of sensory processing observed for NA (see below).

Noradrenergic Modulation of Sensory Physiology

The brain’s noradrenergic system has long been linked to arousal (e.g., O’Hanlon, 1965; reviewed in, e.g., Berridge and Waterhouse, 2003; Sara and Bouret, 2012) and to adapting network activity for optimal, flexible behavior (Aston-Jones and Cohen, 2005; Bouret and Sara, 2005). Consistent with such a general function, NA has been shown to modulate sensory processing in complex ways (Table 4).

Earlier findings have been reviewed in detail (Berridge and Waterhouse, 2003). In brief, activating the LC or local application of NA has been found to result in a variety of effects, including inhibitory and/or facilitating modulation, selective gating, changes to a neuron’s receptive field, and changes to its SNR. For example, iontophoretic application of NA was found to predominantly decrease responses in the dLGN, dorsal, and ventral thalamus of cats (Phillis et al., 1967; Phillis and Teběcis, 1967), in A1 of squirrel monkeys (Foote et al., 1975) and of rats (Manunta and Edeline, 1997), and in rat S1 (Armstrong-James and Fox, 1983; Bassant et al., 1990). Conversely, a predominantly facilitating effect was observed for iontophoretic application of NA or LC stimulation in the rat dLGN (Rogawski and Aghajanian, 1980; Kayama et al., 1982) or V1 (Waterhouse et al., 1990), and for phasic LC stimulation in rat S1 (Waterhouse and Woodward, 1980; Waterhouse et al., 1980, 1998) or rat piriform cortex (Bouret and Sara, 2002). In cat V1 Sato and colleagues (Sato et al., 1989), observed a substantial layer-dependence of the response modulation with LC stimulation. It was predominantly inhibitory in layers 2–4, mostly α receptor mediated facilitation in layer 5 and approximately balanced in both directions in layer 6. These laminar differences likely reflect different receptor expression profiles across layers. The results suggest that some of the variability between studies may also reflect laminar differences between studies within the targeted structures in addition to, e.g., dose-dependent effects. Mirroring this variability, noradrenergic effects on the neuronal SNR differed between studies. While some reported an enhanced SNR (e.g., Foote et al., 1975; Waterhouse and Woodward, 1980; Kasamatsu and Heggelund, 1982) and others (Sato et al., 1989; Manunta and Edeline, 1997) reported no net effect on SNR across the population. In line with the notion of optimizing the neuronal gain for behavior (Aston-Jones and Cohen, 2005), this variability may reflect the noradrenergic role in different states of a dynamical system.

Indeed, simultaneous recordings in the LC and barrel cortex of anesthetized rats combined with dynamical systems modeling showed that activity in the LC was highly predictive of dynamic changes in cortical excitability (Safaai et al., 2015). Moreover, phasic responses in the LC or urethane anesthetized rats were elicited by aversive somatosensory stimuli and modulated the stimulus-induced gamma oscillations in the mPFC, suggesting a corresponding modulation of somatosensory processing (Neves et al., 2018). In awake mice, visual responses have been found to be substantially enhanced during phases when the animals were running compared to no locomotion (Niell and Stryker, 2010). Intriguingly, intracellular recordings showed that this effect was accompanied by a depolarization of the membrane potential in layer 2/3 neurons, which in turn was blocked by noradrenergic antagonists (Polack et al., 2013). Indeed, both noradrenergic and cholinergic mechanisms were linked to this locomotion-dependent modulation, with partially complementary functions (Polack et al., 2013; Reimer et al., 2016). These findings align with the notion of a noradrenergic role in adapting sensory circuits for optimal behavior (Aston-Jones and Cohen, 2005). Additionally, they highlight the importance of interactions between neuromodulatory systems that go beyond the scope of this review.

Dopaminergic Modulation of Sensory Processing

Dopamine Sources

Dopamine synthesizing neurons represent a comparatively small population of neurons in the mammalian brain (Bentivoglio and Morelli, 2005). The majority of DA neurons are found in three cell groups in the ventral midbrain (mesencephalon) (Dahlström and Fuxe, 1964). Based on cytoarchitectonic features, most dopaminergic cells reside in the substantia nigra (SN) pars compacta (SNc, A9), the ventral tegmental area (VTA, A10) medial to the SN and in the retrorubral area (RRA; A8), which lies caudal and dorsal to the SN. Other, smaller dopaminergic cell groups are present in the periaqueductal gray matter (PAG; A11) and in the hypothalamus (A12–A15), the lateral parabrachial nucleus, the olfactory bulb (A16), and in the retina (A17) (Sánchez-González et al., 2005).

The most frequently used marker for identifying dopaminergic neurons is tyrosine hydroxylase (TH), the rate-limiting enzyme of DA synthesis. For TH-immunopositive neurons, the A8 group comprises approx. 5% of cells, while A9 and A10 account for the remaining 95% with a slight dominance of A9 over A10 (Bentivoglio and Morelli, 2005). The DA system undergoes considerable expansion from rodents to primates (Berger et al., 1991). By immunostaining for TH, the number of mesencephalic DA neurons has been estimated at approx. 20,000–30,000 in total in mice (Nelson et al., 1996), 45,000 in rats (German and Manaye, 1993), 110,000–220,000 in the SN in rhesus monkeys (Emborg et al., 1998), and between 230,000 and 430,000 in the human SN (Chu et al., 2002). Thus, a large dopaminergic A9 group is a distinctive feature of the primate brain.

Tyrosine hydroxylase labeling to identify dopaminergic neurons has been called into question because of a lack of specificity (Lammel et al., 2015). Staining for the dopamine transporter (DAT), which removes DA from the extracellular space and is largely responsible for the termination of dopaminergic neurotransmission, is more specific and is not detected, e.g., in noradrenergic cells (Ciliax et al., 1995). However, DAT is not expressed in all DA neurons. For example, it cannot be used to label the diencephalic (hypothalamic) cell groups (Sánchez-González et al., 2005). The subgroup of VTA DA neurons that project to the PFC also contains very little DAT (Lammel et al., 2008). Distinct expression profiles of TH and DAT can therefore be exploited to trace independent populations among dopaminergic neurons.

There is mounting evidence that DA is also released from terminals of LC neurons as a co-transmitter of NA (Devoto et al., 2001, 2003, 2005). These important findings underscore the potential caveats of using cellular protein markers instead of the transmitter receptor or the transmitter itself to investigate monoaminergic neurotransmission. Considerable complexity within the monoaminergic system is therefore likely to shape sensory and higher-order cognitive processing (Takeuchi et al., 2016).

Dopamine Projections

A variety of different techniques has been used to investigate dopaminergic innervation of target structures, including direct (e.g., photometric or autoradiographic) neurotransmitter measurements (Brown et al., 1979; Descarries et al., 1987), immunostaining for TH in comparison to staining for DA-β hydroxylase (Lewis et al., 1987) and DAT (Sánchez-González et al., 2005), DA receptor autoradiography (Lidow et al., 1991), and DA receptor mRNA assays (Weiner et al., 1991; Hurd et al., 2001; Santana et al., 2009). It is important to keep in mind that these methods differ not just with regard to their sensitivity and specificity, but that they also target distinct stages of DA production and neurotransmission. This is a likely source of variability and even discrepancy in the literature. Ultimately, functional evidence is required that local DA modulates neuronal processing in target areas. Physiological studies are therefore the gold-standard for demonstrating effective dopaminergic innervation (see below).

The DA system projects extensively to many subcortical and cortical structures of the brain, albeit with a clear concentration. Lewis et al. (1987) noted, summarizing their work on the cortical distribution of dopaminergic afferents in the non-human primate, that “dopaminergic fibers preferentially innervate motor over sensory regions, sensory association over primary sensory regions, and auditory association over visual association regions.”

The dopaminergic projections from the midbrain are typically subdivided into the mesostriatal pathway and the mesocorticolimbic pathway. The striatum is the major target of mesencephalic DA neurons (Bentivoglio and Morelli, 2005). Ipsilateral projections to the dorsal striatum mainly arise from the SNc (nigrostriatal pathway). Limbic efferents including projections to the ventral striatum (nucleus accumbens) emanate largely from the VTA.

The mesocortical pathways target in particular the motor cortex, the prefrontal, the anterior cingulate, and the rhinal cortices in rodents (Descarries et al., 1987) and in the non-human primate (Berger et al., 1988; Lidow et al., 1991). Similar to the number of dopaminergic midbrain neurons, however, the density of cortical DA terminals varies considerably from species to species, reaching a maximum in primates (Berger et al., 1991). Unlike NA and, especially, serotonin, cortical levels of DA in the macaque brain exhibit a prominent gradient with a strong decrease along the fronto-occipital axis and only minimal amounts detectable in visual cortex (Brown et al., 1979; see Figure 1B).

Mesocortical projections originate from all major cell groups in the ventral mesencephalon, with a looser organization compared to the mesostriatal system. A clear topographical relationship, however, has been described for the most densely innervated frontal lobe. Dopaminergic projections to the dorsolateral PFC in the macaque brain arise from the dorsal and lateral regions of three midbrain cell groups A8, A9, and A10, whereas the ventromedial regions of the PFC receive projections from the medial parabrachial pigmented nucleus and the midline nuclei of the VTA (Williams and Goldman-Rakic, 1998). A similar medial–lateral arrangement has been found in rats (Loughlin and Fallon, 1984). Here, most of the dopaminergic innervation of the medial frontal cortex comes from VTA neurons that project to the deep layers 5 and 6 of the mPFC and in particular to the orbitofrontal cortex (Chandler et al., 2013), with substantially fewer cells from the SNc innervating predominately the superficial mPFC layers (Berger et al., 1991). SNc DA neurons preferentially target the lateral frontal cortex, e.g., the premotor areas (Loughlin and Fallon, 1984; Muller et al., 2014).

Overall, VTA dopaminergic neurons show little collateralization to extensive terminal fields, somewhat in contrast to SNc cells (Loughlin and Fallon, 1984; Chandler et al., 2013). This suggests that, in light of the topographical arrangement described above, discrete, anatomically circumscribed dopaminergic subsystems exist that could modulate selected target regions.

Dopamine Synapses and Receptors

Dopamine-containing varicosities can form multiple synaptic contacts along the course of an axonal fiber. In frontal cortex, these terminals establish conventional, symmetric synapses with postsynaptic dendritic shafts and spines, preferentially on pyramidal neurons (Berger et al., 1991). At the ultrastructural level, dopaminergic afferents form synaptic triads with postsynaptic spines that receive a second, presumably glutamatergic input (Goldman-Rakic et al., 1989). This configuration would allow DA to modulate ongoing neuronal transmission both pre- and postsynaptically.

Dopamine receptors are expressed by pyramidal neurons and GABAergic interneurons alike, indicating that DA modulates excitatory and inhibitory synaptic transmission (Santana et al., 2009). Dopamine receptors are categorized into two major families: the D1 family comprising the D₁ and D₅ receptors, and the D2 family comprising the D₂, D₃, and D₄ receptors. Both D1 and D2 families of receptors are G protein-coupled receptors, which initiate intracellular signaling cascades rather than directly inducing postsynaptic currents (Missale et al., 1998; Bentivoglio and Morelli, 2005). D1 and D2 receptors are largely expressed in different cell populations (Vincent et al., 1993). In most rat brain structures except for the VTA and some midbrain cell groups, D1 receptors outnumber D2 receptors (Boyson et al., 1986; Weiner et al., 1991). In the human brain, D1 receptor mRNA clearly dominates over D2 receptor mRNA in the cortical mantle, whereas D2 receptor mRNA is more abundant in the hippocampal formation, brainstem, and in subcortical structures such as the thalamus (Hurd et al., 2001). Of note, a high proportion of DA (D1) receptors are found at extrasynaptic sites, suggesting that DA might also exert its effects via diffusion in the neuropil (volume transmission) (Smiley et al., 1994).

Cortical DA receptors show a laminar-specific distribution profile. D1 receptors are expressed in all cortical layers in the primate frontal brain (Lidow et al., 1991; Huntley et al., 1992), often with a bilaminar infra-supragranular pattern with a relative paucity in layer 4 (Lewis et al., 1987) and a predilection for deeper layers. D2 receptors, in contrast, are typically confined to cortical layer 5 (Weiner et al., 1991; Lidow et al., 1998).

Dopaminergic Innervation of Sensory Brain Structures

Compared to the densely innervated frontal cortex, the sensory cortices receive very sparse dopaminergic afferents (Table 5). In both rat and primate studies, the primary visual cortex shows the lowest DA fiber density of all investigated cortical structures (Descarries et al., 1987; Lidow et al., 1991). TH immunoreactivity in primate primary visual cortex V1 is restricted to layer 1, and few fibers reach layer 6 as well in V2 (Lewis et al., 1987; Berger et al., 1988). The same layers are targeted by dopaminergic fibers in the rat primary visual cortex (Phillipson et al., 1987).

A slight increase in fiber density is seen in primary auditory cortex. In the gerbil, D1 receptors are found in infragranular layers mainly associated with pyramidal neurons (Schicknick et al., 2008). TH positive fibers loosely innervate auditory cortex layers 1 and 6 in primates (Lewis et al., 1987). In primary somatosensory cortex, labeled fibers are also found in layer 5. A further increase in dopaminergic innervation is then observed in the association cortices of the temporal, parietal, and frontal lobe, where the aforementioned bilaminar profile emerges (Lewis et al., 1987).

Dopaminergic fibers have also been reported to innervate subcortical structures that are involved in processing sensory stimuli. Dopamine axons reach the LGN of the thalamus (LGN, visual nucleus) (Papadopoulos and Parnavelas, 1990). Here, D1 and D2 receptors are found in excitatory relay neurons and in inhibitory local interneurons (Albrecht et al., 1996; Zhao et al., 2002; Munsch et al., 2005). D2 receptors are also present in the thalamic medial geniculate nucleus (MGN, auditory nucleus) (Hurd et al., 2001; Chun et al., 2014) and in the ventrobasal complex (VB, somatosensory nucleus) (Govindaiah et al., 2010b).

While these first-order thalamic nuclei mainly relay sensory input to the cortex, the second-order thalamic nuclei are part of cortico–thalamo–cortical loops and could support higher brain functions operating on sensory information (Sherman, 2016). The second-order thalamus is more strongly innervated by DA neurons than its first-order counterpart, reaching the levels of highest cortical density in some nuclei (Sánchez-González et al., 2005). Thalamic DA fibers are much denser in primates than in rodents (García-Cabezas et al., 2009). Dopaminergic afferents in the thalamus stem from multiple sources including the hypothalamus, ventral mesencephalon, the PAG, and the lateral parabrachial nucleus, possibly hinting at the existence of a distinct “thalamic dopaminergic system” (Groenewegen, 1988; Sánchez-González et al., 2005). Interestingly, the densest dopaminergic projections to the thalamus are found in those second-order nuclei that are linked to frontal and limbic cortex, e.g., the mediodorsal (MD) nucleus and the midline nuclei (García-Cabezas et al., 2007). In fact, these DA projections share many anatomical features with the strong meso-prefrontal DA system (Melchitzky et al., 2006). These findings suggest that DA could modulate higher-order frontal lobe functions both at the cortical level and by controlling its associated thalamic nuclei (Varela, 2014). Finally, it has been noted that VTA axon terminals and terminals from thalamic MD neurons converge in mPFC layer 5, forming a synaptic triad as described above (Kuroda et al., 1996). Thus, dopaminergic modulation of thalamic function might also have extra-thalamic components.

The main auditory midbrain nucleus, the IC, is targeted by TH-immunoreactive nerve terminals arising from the subparafascicular thalamic nucleus (Tong et al., 2005; Nevue et al., 2015), and the IC has been shown to express D2 receptors (Weiner et al., 1991). Dopaminergic afferents to the superior colliculus, a crucial midbrain structure for oculomotor and visual processing, are sparser in comparison (Weiner et al., 1991).

Dopaminergic Modulation of Sensory Physiology

Dopamine neuron activity is classically described as being time locked to the presentation of rewarding stimuli. Phasic firing of action potentials by DA neurons especially in the medial mesencephalon communicates a reward prediction error that scales with the difference between predicted and actual reward (Schultz, 2007). These neurophysiological findings form the basis for the large number of studies that have investigated DA’s role in motivation, appetence, and reward-related learning (“motivational salience”). More recent experiments have revealed the existence of functionally distinct subgroups of DA neurons in particular in the lateral midbrain that are activated both by rewarding and aversive events (Matsumoto and Hikosaka, 2009; Matsumoto et al., 2013). This suggests that these neurons are responsive to a more general group of sensory stimuli that are behaviorally relevant and should trigger an appropriate coordinated response (“cognitive salience”). The physiological effects of DA on sensory information processing, however, are not yet well understood. Given the sparse innervation of sensory structures, comparatively few studies have addressed the role of DA in directly modulating sensory inputs (Table 6).

In rat and cat dorsal LGN, in vivo iontophoretic activation of D1 receptors produced inhibition, whereas engagement of D2 receptors resulted in excitation of extracellularly recorded relay neurons (Phillis et al., 1967; Albrecht et al., 1996; Zhao et al., 2002). Intracellular recordings in rat and mouse LGN slices, however, found that D1 receptors lead to an excitatory membrane depolarization in relay neurons (Govindaiah and Cox, 2005), whereas D2 receptors on local GABAergic interneurons produced inhibition in postsynaptic neurons (Munsch et al., 2005), in complete contrast to the in vivo results. It is currently unclear whether these diverging findings reflect dose-dependent effects, where application of small and large drug concentrations often yields opposite effects (Zhao et al., 2002), or rather result from network mechanisms that differ in the in vivo and in vitro preparation.

In primate primary visual cortex (V1), oscillatory activity (local field potentials) containing information about animated visual stimuli (movie clips) was enhanced in particular in supragranular layers following systemic administration of the DA precursor L-DOPA (Zaldivar et al., 2018). However, focal application of DA failed to induce changes in neuronal activity (Zaldivar et al., 2014), possibly reflecting the very sparse dopaminergic innervation of the occipital pole. In accordance with the notion that dopaminergic effects on visual processing are not mediated by early primary visual regions but possibly by higher-order brain areas, visually induced neuronal responses were directly modulated by DA in the monkey lateral PFC (Jacob et al., 2013). Here, iontophoretically applied DA affected two distinct neuronal populations involved in encoding behaviorally relevant visual stimuli. In putative interneurons, DA inhibited activity in form of a subtractive shift in response levels with unchanged SNR. In putative pyramidal neurons, DA increased excitability in form of a multiplication in gain and enhanced SNR through a reduction of response variability across trials (Jacob et al., 2013). By increasing the coding strength of sensory signals, DA could play a crucial role in how sensory information is represented, memorized, and interpreted in PFC (Ott et al., 2014; Jacob et al., 2016).

Acting on cognitive brain centers, DA might influence visual cortical processing (Arsenault et al., 2013) by long-range interactions originating, e.g., in frontal cortex. Support for this hypothesis comes from exploring DA’s modulatory influence on PFC-guided allocation of visual attention in the macaque monkey (Noudoost and Moore, 2011). D1R were blocked by local antagonist injections into sites of the frontal eye fields (FEFs) that represented the same region of visual space (the “response field”) as simultaneously recorded neurons in visual cortex area V4. Prefrontal D1R antagonism caused the animals to saccade more frequently toward FEF response field targets, meaning this part of the visual field had grasped their attention. The response properties of V4 neurons were changed in a way that is consistent with a multiplicative increase in gain: first, there was an enhancement in the magnitude of responses to visual stimulation; second, the visual responses became more selective to stimulus orientation; third, the visual responses became less variable across trials (Noudoost and Moore, 2011). Thus, prefrontal top-down control over visual cortical neurons during visual attention is under the influence of D1 receptors.

In the auditory system, both inhibitory and – less frequently – excitatory responses in IC neurons were observed after local iontophoretic application of DA in awake mice (Gittelman et al., 2013). The importance of subcortical DA for auditory information processing was underscored by showing that overexpressed MGN D2 receptors in a schizophrenia mouse model reduce the efficiency of synaptic transmission of excitatory thalamocortical afferents in auditory cortex (Chun et al., 2014). These changes were accompanied by behavioral deficits in auditory perception (acoustic startle response). Because thalamocortical afferents in visual or somatosensory cortex were not affected, studying this mouse model might help to provide a neuronal mechanism that links dopaminergic dysfunction to the generation of auditory hallucinations in schizophrenia (Chun et al., 2014). Auditory processing is modulated by cortical DA receptors as well. Systemic administration of D1 receptor antagonists or local injections directly into auditory cortex of gerbils impaired discrimination learning of acoustic stimuli, while D1 receptor agonists improved the animals’ performance (Schicknick et al., 2012; Happel et al., 2014).

Finally, the representation of somatosensory information is also strengthened by DA: in vivo depletion of DA in mouse striatum worsened the laterality coding of whisker deflections in medium spiny neurons, i.e., the projection neurons of this structure, indicating that tactile acuity requires dopaminergic input (Ketzef et al., 2017). Intracellular recordings in rat VB thalamic slices showed that DA increases neuronal excitability in two different ways: activation of D1 receptors leads to membrane depolarization, whereas D2 receptors facilitate action potential discharge (Govindaiah et al., 2010b). In contrast, in rat S1, iontophoretic DA application produced inhibitory effects on neuronal firing (Bassant et al., 1990).

Putting It All Together: Monoaminergic Neuromodulation of Sensory Processing

The discussed studies provide compelling evidence that the representation and processing of sensory information is heavily regulated by the brain’s monoamine transmitters. Despite their widespread cortical and subcortical targeting, the monoaminergic systems are by no means blurry, brain-wide modulators of neuronal activity. They send regionally and laminar-specific projections, which may allow them to control both feed-forward and feed-back influences (Cumming and Nienborg, 2016) on sensory signaling by distinct mechanisms. These regional and laminar differences are particularly pronounced in the macaque brain (Figure 1).

The indolamine serotonin has prominent projections to the primary sensory areas and innervates all cortical layers including the thalamo-cortical input layer 4. Serotonin is well suited to regulate the sensory input stages by acting in these primary sensory areas and in the first-order thalamic relay nuclei. Despite some degree of variability between studies on the serotonergic modulation of sensory processing, the emerging pattern is that it dampens neuronal responses and reduces gain. The reduction in gain may reduce the salience of a sensory stimulus (Seillier et al., 2017). Alternatively, if it only affects the spontaneous but not the stimulus-driven response (Lottem et al., 2016), it may increase a neuron’s SNR and hence effectively increase stimulus salience. Probing the serotonergic modulation of sensory processing during perceptually driven behavior may resolve this seeming discrepancy. In general, however, the experimental data show that serotonin directly modulates sensory processing as early as the feed-forward sensory input stage.

In contrast to serotonin the catecholamine DA has a pronounced fronto-occipital gradient (Figure 1), is less abundant in sensory cortices, particularly sparse in the primary visual cortex, and only weakly active in granular layers. This suggests that dopaminergic effects on sensory processing are not mediated primarily by local modulation of early sensory input stages (e.g., Zaldivar et al., 2014) but instead by modulating long-range recurrent cortico-cortical and cortico-bulbar interactions originating in the strongly innervated supragranular and infragranular layers, respectively, e.g., of the frontal lobe cognitive control centers (Lewis et al., 1987; Noudoost and Moore, 2011; Jacob et al., 2013). Its modulatory effects stem from a variable and complex combination of inhibition and excitation in the targeted circuits. The net result is likely an increase in SNR, which is based both on additive operations, e.g., predominant suppression of responses to non-preferred stimuli (“sculpting inhibition”) (Vijayraghavan et al., 2007), and on multiplicative operations, e.g., increase in gain and response reliability (reduction of trial-to-trial variability) (Noudoost and Moore, 2011; Jacob et al., 2013). Thus, the role of DA could primarily be to adapt the read-out of sensory circuits to best serve task demands and behavioral goals.

The catecholamine NA, conversely, may play a role in between these two extremes. It has a less pronounced fronto-occipital gradient than DA and, like serotonin, substantial projections to the primary sensory cortices, including the primary visual cortex. But in contrast to serotonin, the innervation of the granular layers is relatively sparse (Figure 1). The modulatory effects of NA on sensory processing are diverse. This variability may reflect adaptable modulation depending on the behavioral state of the animal, in line with the notion of optimizing the neuronal gain for behavior (Aston-Jones and Cohen, 2005).

Taken together, the current literature argues for a prominent complementarity in sensory neuromodulation by monoamines. This complementarity is prominent anatomically (Figure 1B), resulting in both direct bottom-up and indirect top-down control over sensory signaling by the indolamine serotonin and the catecholamines NA and DA, respectively (Papadopoulos and Parnavelas, 1991). One of the main challenges will now be to dissect the individual contributions of the anatomically and functionally separable monoamine subsystems in shaping how sensory information is represented, processed, and evaluated by the brain’s sensory, cognitive, and motivational networks (Figure 1A). We believe that key to such insights will be the combination of increased specificity and precision when targeting these neuromodulatory systems with well characterized behavior (Krakauer et al., 2017).

References

• 1

  AlbrechtD.QuäschlingU.ZippelU.DavidowaH. (1996). Effects of dopamine on neurons of the lateral geniculate nucleus: an iontophoretic study.Synapse2370–78. 10.1002/(SICI)1098-2396(199606)23:2<70::AID-SYN2>3.0.CO;2-D

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 2

  Armstrong-JamesM.FoxK. (1983). Effects of ionophoresed noradrenaline on the spontaneous activity of neurones in rat primary somatosensory cortex.J. Physiol.335427–447. 10.1113/jphysiol.1983.sp014542

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 3

  ArsenaultJ. T.NelissenK.JarrayaB.VanduffelW. (2013). Dopaminergic reward signals selectively decrease fMRI activity in primate visual cortex.Neuron771174–1186. 10.1016/j.neuron.2013.01.008

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 4

  Aston-JonesG.CohenJ. D. (2005). Adaptive gain and the role of the locus coeruleus-norepinephrine system in optimal performance.J. Comp. Neurol.49399–110. 10.1002/cne.20723

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 5

  BassantM. H.EnnouriK.LamourY. (1990). Effects of iontophoretically applied monoamines on somatosensory cortical neurons of unanesthetized rats.Neuroscience39431–439. 10.1016/0306-4522(90)90279-D

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 6

  BeaudetA.DescarriesL. (1976). Quantitative data on serotonin nerve terminals in adult rat neocortex.Brain Res.111301–309. 10.1016/0006-8993(76)90775-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 7

  BentivoglioM.MorelliM. (2005). “Chapter I The organization and circuits of mesencephalic dopaminergic neurons and the distribution of dopamine receptors in the brain,” inDopamine: Handbook of Chemical NeuroanalVol. 21edsDunnettS. B.BentivoglioM.BjorklundA.HokfeltT. (Amsterdam: Elsevier), 1–107. 10.1016/S0924-8196(05)80005-3

  • CrossRef
  • Google Scholar

• 8

  BergerB.GasparP.VerneyC. (1991). Dopaminergic innervation of the cerebral cortex: unexpected differences between rodents and primates.Trends Neurosci.1421–27. 10.1016/0166-2236(91)90179-X

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 9

  BergerB.TrottierS.VerneyC.GasparP.AlvarezC. (1988). Regional and laminar distribution of the dopamine and serotonin innervation in the macaque cerebral cortex: a radioautographic study.J. Comp. Neurol.27399–119. 10.1002/cne.902730109

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 10

  BerridgeC. W.WaterhouseB. D. (2003). The locus coeruleus-noradrenergic system: modulation of behavioral state and state-dependent cognitive processes.Brain Res. Brain Res. Rev.4233–84. 10.1016/S0165-0173(03)00143-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 11

  BouretS.SaraS. J. (2002). Locus coeruleus activation modulates firing rate and temporal organization of odour-induced single-cell responses in rat piriform cortex.Eur. J. Neurosci.162371–2382. 10.1046/j.1460-9568.2002.02413.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 12

  BouretS.SaraS. J. (2005). Network reset: a simplified overarching theory of locus coeruleus noradrenaline function.Trends Neurosci.28574–582. 10.1016/j.tins.2005.09.002

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 13

  BoysonS. J.McGonigleP.MolinoffP. B. (1986). Quantitative autoradiographic localization of the D1 and D2 subtypes of dopamine receptors in rat brain.J. Neurosci.63177–3188. 10.1523/JNEUROSCI.06-11-03177.1986

  • CrossRef
  • Google Scholar

• 14

  BrownR. M.CraneA. M.GoldmanP. S. (1979). Regional distribution of monoamines in the cerebral cortex and subcortical structures of the rhesus monkey: concentrations and in vivo synthesis rates.Brain Res.168133–150. 10.1016/0006-8993(79)90132-X

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 15

  CalladoL. F.StamfordJ. A. (2000). Spatiotemporal interaction of alpha(2) autoreceptors and noradrenaline transporters in the rat locus coeruleus: implications for volume transmission.J. Neurochem.742350–2358. 10.1046/j.1471-4159.2000.0742350.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 16

  CampbellM. J.LewisD. A.FooteS. L.MorrisonJ. H. (1987). Distribution of choline acetyltransferase-, serotonin-, dopamine-beta-hydroxylase-, tyrosine hydroxylase-immunoreactive fibers in monkey primary auditory cortex.J. Comp. Neurol.261209–220. 10.1002/cne.902610204

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 17

  ChandlerD. J.GaoW. J.WaterhouseB. D. (2014). Heterogeneous organization of the locus coeruleus projections to prefrontal and motor cortices.Proc. Natl. Acad. Sci. U.S.A.1116816–6821. 10.1073/pnas.1320827111

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 18

  ChandlerD. J.LamperskiC. S.WaterhouseB. D. (2013). Identification and distribution of projections from monoaminergic and cholinergic nuclei to functionally differentiated subregions of prefrontal cortex.Brain Res.152238–58. 10.1016/j.brainres.2013.04.057

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 19

  ChuY.KompolitiK.CochranE. J.MufsonE. J.KordowerJ. H. (2002). Age-related decreases in Nurr1 immunoreactivity in the human substantia nigra.J. Comp. Neurol.450203–214. 10.1002/cne.10261

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 20

  ChunS.WestmorelandJ. J.BayazitovI. T.EddinsD.PaniA. K.SmeyneR. J.et al (2014). Specific disruption of thalamic inputs to the auditory cortex in schizophrenia models.Science3441178–1182. 10.1126/science.1253895

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 21

  CiliaxB. J.HeilmanC.DemchyshynL. L.PristupaZ. B.InceE.HerschS. M.et al (1995). The dopamine transporter: immunochemical characterization and localization in brain.J. Neurosci.15(3 Pt 1), 1714–1723. 10.1523/JNEUROSCI.15-03-01714.1995

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 22

  CohenJ. Y.AmorosoM. W.UchidaN. (2015). Serotonergic neurons signal reward and punishment on multiple timescales.eLife4:e06346. 10.7554/eLife.06346

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 23

  ConstantinopleC. M.BrunoR. M. (2011). Effects and mechanisms of wakefulness on local cortical networks.Neuron691061–1068. 10.1016/j.neuron.2011.02.040

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 24

  CostaV. D.KakaliosL. C.AverbeckB. B. (2016). Blocking serotonin but not dopamine reuptake alters neural processing during perceptual decision making.Behav. Neurosci.130461–468. 10.1037/bne0000162

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 25

  CummingB. G.NienborgH. (2016). Feedforward and feedback sources of choice probability in neural population responses.Curr. Opin. Neurobiol.37126–132. 10.1016/j.conb.2016.01.009

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 26

  DahlströmA.FuxeK. (1964). Localization of monoamines in the lower brain stem.Experientia20398–399. 10.1007/BF02147990

  • CrossRef
  • Google Scholar

• 27

  DavisM.StrachanD. I.KassE. (1980). Excitatory and inhibitory effects of serotonin on sensorimotor reactivity measured with acoustic startle.Science209521–523. 10.1126/science.7394520

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 28

  DayanP.HuysQ. (2015). Serotonin’s many meanings elude simple theories.eLife4:e07390. 10.7554/eLife.07390

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 29

  de LimaA. D.BloomF. E.MorrisonJ. H. (1988). Synaptic organization of serotonin-immunoreactive fibers in primary visual cortex of the macaque monkey.J. Comp. Neurol.274280–294. 10.1002/cne.902740211

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 30

  DeFelipeJ.ArellanoJ. I.GómezA.AzmitiaE. C.MuñozA. (2001). Pyramidal cell axons show a local specialization for GABA and 5-HT inputs in monkey and human cerebral cortex.J. Comp. Neurol.433148–155. 10.1002/cne.1132

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 31

  DeFelipeJ.HendryS. H.HashikawaT.JonesE. G. (1991). Synaptic relationships of serotonin-immunoreactive terminal baskets on GABA neurons in the cat auditory cortex.Cereb. Cortex1117–133. 10.1093/cercor/1.2.117

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 32

  DeFelipeJ.JonesE. G. (1988). A light and electron microscopic study of serotonin-immunoreactive fibers and terminals in the monkey sensory-motor cortex.Exp. Brain Res.71171–182. 10.1007/BF00247532

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 33

  DescarriesL.LemayB.DoucetG.BergerB. (1987). Regional and laminar density of the dopamine innervation in adult rat cerebral cortex.Neuroscience21807–824. 10.1016/0306-4522(87)90038-8

  • CrossRef
  • Google Scholar

• 34

  DescarriesL.RiadM.ParentM. (2010). “Ultrastructure of the serotonin innervation in the mammalian central nervous system,” inHandbook of the Behavioral Neurobiology of Serotonin, edsMuellerC. P.JacobsB. L. (London: Academic Press), 82–119.

  • Google Scholar

• 35

  DevilbissD. M.WaterhouseB. D. (2011). Phasic and tonic patterns of locus coeruleus output differentially modulate sensory network function in the awake rat.J. Neurophysiol.10569–87. 10.1152/jn.00445.2010

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 36

  DevotoP.FloreG.LonguG.PiraL.GessaG. L. (2003). Origin of extracellular dopamine from dopamine and noradrenaline neurons in the medial prefrontal and occipital cortex.Synapse50200–205. 10.1002/syn.10264

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 37

  DevotoP.FloreG.PaniL.GessaG. L. (2001). Evidence for co-release of noradrenaline and dopamine from noradrenergic neurons in the cerebral cortex.Mol. Psychiatry6657–664. 10.1038/sj.mp.4000904

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 38

  DevotoP.FloreG.SabaP.FàM.GessaG. L. (2005). Stimulation of the locus coeruleus elicits noradrenaline and dopamine release in the medial prefrontal and parietal cortex.J. Neurochem.92368–374. 10.1111/j.1471-4159.2004.02866.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 39

  DoriI.DinopoulosA.BlueM. E.ParnavelasJ. G. (1996). Regional differences in the ontogeny of the serotonergic projection to the cerebral cortex.Exp. Neurol.1381–14. 10.1006/exnr.1996.0041

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 40

  DoriI. E.DinopoulosA.ParnavelasJ. G. (1998). The development of the synaptic organization of the serotonergic system differs in brain areas with different functions.Exp. Neurol.154113–125. 10.1006/exnr.1998.6937

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 41

  DotyR. W. (1983). Nongeniculate afferents to striate cortex in macaques.J. Comp. Neurol.218159–173. 10.1002/cne.902180204

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 42

  DuguéG. P.LörinczM. L.LottemE.AuderoE.MatiasS.CorreiaP. A.et al (2014). Optogenetic recruitment of dorsal raphe serotonergic neurons acutely decreases mechanosensory responsivity in behaving mice.PLoS One9:e105941. 10.1371/journal.pone.0105941

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 43

  EbertU.OstwaldJ. (1992). Serotonin modulates auditory information processing in the cochlear nucleus of the rat.Neurosci. Lett.14551–54. 10.1016/0304-3940(92)90201-H

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 44

  EckerA. S.BerensP.CottonR. J.SubramaniyanM.DenfieldG. H.CadwellC. R.et al (2014). State dependence of noise correlations in macaque primary visual cortex.Neuron82235–248. 10.1016/j.neuron.2014.02.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 45

  EmborgM. E.MaS. Y.MufsonE. J.LeveyA. I.TaylorM. D.BrownW. D.et al (1998). Age-related declines in nigral neuronal function correlate with motor impairments in rhesus monkeys.J. Comp. Neurol.401253–265. 10.1002/(SICI)1096-9861(19981116)401:2<253::AID-CNE7>3.0.CO;2-X

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 46

  FonsecaM. S.MurakamiM.MainenZ. F. (2015). Activation of dorsal raphe serotonergic neurons promotes waiting but is not reinforcing.Curr. Biol.25306–315. 10.1016/j.cub.2014.12.002

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 47

  FooteS. L.FreedmanR.OliverA. P. (1975). Effects of putative neurotransmitters on neuronal activity in monkey auditory cortex.Brain Res.86229–242. 10.1016/0006-8993(75)90699-X

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 48

  FooteS. L.MorrisonJ. H. (1987). Extrathalamic modulation of cortical function.Annu. Rev. Neurosci.1067–95. 10.1146/annurev.ne.10.030187.000435

  • CrossRef
  • Google Scholar

• 49

  FrazãoR.PinatoL.da SilvaA. V.BrittoL. R.OliveiraJ. A.NogueiraM. I. (2008). Evidence of reciprocal connections between the dorsal raphe nucleus and the retina in the monkey Cebus apella.Neurosci. Lett.430119–123. 10.1016/j.neulet.2007.10.032

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 50

  FujimiyaM.KimuraH.MaedaT. (1986). Postnatal development of serotonin nerve fibers in the somatosensory cortex of mice studied by immunohistochemistry.J. Comp. Neurol.246191–201. 10.1002/cne.902460205

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 51

  FusterJ. (2015). The Prefrontal Cortex, 5th Edn. Cambridge, MA: Academic Press.

  • Google Scholar

• 52

  FuxeK. (1965). Evidence for the existence of monoamine neurons in the central nervous system. IV. Distribution of monoamine nerve terminals in the central nervous system.Acta Physiol. Scand. Suppl.247:37. 10.1007/BF00337069

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 53

  FuxeK.Borroto-EscuelaD. O. (2016). Volume transmission and receptor-receptor interactions in heteroreceptor complexes: understanding the role of new concepts for brain communication.Neural Regen. Res.111220–1223. 10.4103/1673-5374.189168

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 54

  García-CabezasM. A.Martínez-SánchezP.Sánchez-GonzálezM. A.GarzónM.CavadaC. (2009). Dopamine innervation in the thalamus: monkey versus rat.Cereb. Cortex19424–434. 10.1093/cercor/bhn093

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 55

  García-CabezasM. A.RicoB.Sánchez-GonzálezM. A.CavadaC. (2007). Distribution of the dopamine innervation in the macaque and human thalamus.Neuroimage34965–984. 10.1016/j.neuroimage.2006.07.032

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 56

  GermanD. C.ManayeK. F. (1993). Midbrain dopaminergic neurons (nuclei A8, A9, and A10): three-dimensional reconstruction in the rat.J. Comp. Neurol.331297–309. 10.1002/cne.903310302

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 57

  GittelmanJ. X.PerkelD. J.PortforsC. V. (2013). Dopamine modulates auditory responses in the inferior colliculus in a heterogeneous manner.J. Assoc. Res. Otolaryngol.14719–729. 10.1007/s10162-013-0405-0

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 58

  Goldman-RakicP. S.LeranthC.WilliamsS. M.MonsN.GeffardM. (1989). Dopamine synaptic complex with pyramidal neurons in primate cerebral cortex.Proc. Natl. Acad. Sci. U.S.A.869015–9019. 10.1073/pnas.86.22.9015

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 59

  GovindaiahG.CoxC. L. (2005). Excitatory actions of dopamine via D1-like receptors in the rat lateral geniculate nucleus.J. Neurophysiol.943708–3718. 10.1152/jn.00583.2005

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 60

  GovindaiahG.WangY.CoxC. L. (2010a). Dopamine enhances the excitability of somatosensory thalamocortical neurons.Neuroscience170981–991. 10.1016/j.neuroscience.2010.08.043

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 61

  GovindaiahG.WangT.GilletteM. U.CrandallS. R.CoxC. L. (2010b). Regulation of inhibitory synapses by presynaptic D₄ dopamine receptors in thalamus.J. Neurophysiol.1042757–2765. 10.1152/jn.00361.2010

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 62

  GroenewegenH. J. (1988). Organization of the afferent connections of the mediodorsal thalamic nucleus in the rat, related to the mediodorsal-prefrontal topography.Neuroscience24379–431. 10.1016/0306-4522(88)90339-9

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 63

  GrzannaR.MolliverM. E. (1980). The locus coeruleus in the rat: an immunohistochemical delineation.Neuroscience521–40. 10.1016/0306-4522(80)90068-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 64

  HappelM. F. K.DelianoM.HandschuhJ.OhlF. W. (2014). Dopamine-modulated recurrent corticoefferent feedback in primary sensory cortex promotes detection of behaviorally relevant stimuli.J. Neurosci.341234–1247. 10.1523/JNEUROSCI.1990-13.2014

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 65

  HarrisK. D.ThieleA. (2011). Cortical state and attention.Nat. Rev. Neurosci.12509–523. 10.1038/nrn3084

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 66

  HornungJ. P. (2010). “The neuroanatomy of the serotonergic system,” inHandbook of the Behavioral Neurobiology of Serotonin, edsMuellerC. P.JacobsB. L. (London: Academic Press), 68–81.

  • Google Scholar

• 67

  HuntleyG. W.MorrisonJ. H.PrikhozhanA.SealfonS. C. (1992). Localization of multiple dopamine receptor subtype mRNAs in human and monkey motor cortex and striatum.Brain Res. Mol. Brain Res.15181–188. 10.1016/0169-328X(92)90107-M

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 68

  HurdY. L.SuzukiM.SedvallG. C. (2001). D1 and D2 dopamine receptor mRNA expression in whole hemisphere sections of the human brain.J. Chem. Neuroanat.22127–137. 10.1016/S0891-0618(01)00122-3

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 69

  HurleyL. M.DevilbissD. M.WaterhouseB. D. (2004). A matter of focus: monoaminergic modulation of stimulus coding in mammalian sensory networks.Curr. Opin. Neurobiol.14488–495. 10.1016/j.conb.2004.06.007

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 70

  HurleyL. M.PollakG. D. (1999). Serotonin differentially modulates responses to tones and frequency-modulated sweeps in the inferior colliculus.J. Neurosci.198071–8082. 10.1523/JNEUROSCI.19-18-08071.1999

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 71

  HurleyL. M.PollakG. D. (2005). Serotonin shifts first-spike latencies of inferior colliculus neurons.J. Neurosci.257876–7886. 10.1523/JNEUROSCI.1178-05.2005

  • CrossRef
  • Google Scholar

• 72

  IshimuraK.TakeuchiY.FujiwaraK.TominagaM.YoshiokaH.SawadaT. (1988). Quantitative analysis of the distribution of serotonin-immunoreactive cell bodies in the mouse brain.Neurosci. Lett.91265–270. 10.1016/0304-3940(88)90691-X

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 73

  JacobS. N.OttT.NiederA. (2013). Dopamine regulates two classes of primate prefrontal neurons that represent sensory signals.J. Neurosci.3313724–13734. 10.1523/JNEUROSCI.0210-13.2013

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 74

  JacobS. N.StalterM.NiederA. (2016). Cell-type-specific modulation of targets and distractors by dopamine D1 receptors in primate prefrontal cortex.Nat. Commun.7:13218. 10.1038/ncomms13218

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 75

  JacobowitzD. M.MacLeanP. D. (1978). A brainstem atlas of catecholaminergic neurons and serotonergic perikarya in a pygmy primate (Cebuella pygmaea).J. Comp. Neurol.177397–416. 10.1002/cne.901770304

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 76

  JonesB. E.HalarisA. E.McIlhanyM.MooreR. Y. (1977). Ascending projections of the locus coeruleus in the rat. I. Axonal transport in central noradrenaline neurons.Brain Res.1271–21. 10.1016/0006-8993(77)90377-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 77

  KasamatsuT.HeggelundP. (1982). Single cell responses in cat visual cortex to visual stimulation during iontophoresis of noradrenaline.Exp. Brain Res.45317–327. 10.1007/BF01208591

  • CrossRef
  • Google Scholar

• 78

  KayamaY.NegiT.SugitaniM.IwamaK. (1982). Effects of locus coeruleus stimulation on neuronal activities of dorsal lateral geniculate nucleus and perigeniculate reticular nucleus of the rat.Neuroscience7655–666. 10.1016/0306-4522(82)90071-9

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 79

  KehrW.LindqvistM.CarlssonA. (1976). Distribution of dopamine in the rat cerebral cortex.J. Neural Transm.38173–180. 10.1007/BF01249437

  • CrossRef
  • Google Scholar

• 80

  KetzefM.SpigolonG.JohanssonY.Bonito-OlivaA.FisoneG.SilberbergG. (2017). Dopamine depletion impairs bilateral sensory processing in the striatum in a pathway-dependent manner.Neuron94855–865. 10.1016/j.neuron.2017.05.004

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 81

  KimJ. H.JungA. H.JeongD.ChoiI.KimK.ShinS.et al (2016). Selectivity of neuromodulatory projections from the basal forebrain and locus ceruleus to primary sensory cortices.J. Neurosci.365314–5327. 10.1523/JNEUROSCI.4333-15.2016

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 82

  KlepperA.HerbertH. (1991). Distribution and origin of noradrenergic and serotonergic fibers in the cochlear nucleus and inferior colliculus of the rat.Brain Res.557190–201. 10.1016/0006-8993(91)90134-H

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 83

  KosofskyB. E.MolliverM. E.MorrisonJ. H.FooteS. L. (1984). The serotonin and norepinephrine innervation of primary visual cortex in the cynomolgus monkey (Macaca fascicularis).J. Comp. Neurol.230168–178. 10.1002/cne.902300203

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 84

  KösslM.VaterM. (1989). Noradrenaline enhances temporal auditory contrast and neuronal timing precision in the cochlear nucleus of the mustached bat.J. Neurosci.94169–4178. 10.1523/JNEUROSCI.09-12-04169.1989

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 85

  KrakauerJ. W.GhazanfarA. A.Gomez-MarinA.MacIverM. A.PoeppelD. (2017). Neuroscience needs behavior: correcting a reductionist bias.Neuron93480–490. 10.1016/j.neuron.2016.12.041

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 86

  KurodaM.MurakamiK.IgarashiH.OkadaA. (1996). The convergence of axon terminals from the mediodorsal thalamic nucleus and ventral tegmental area on pyramidal cells in layer V of the rat prelimbic cortex.Eur. J. Neurosci.81340–1349. 10.1111/j.1460-9568.1996.tb01596.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 87

  LammelS.HetzelA.HäckelO.JonesI.LissB.RoeperJ. (2008). Unique properties of mesoprefrontal neurons within a dual mesocorticolimbic dopamine system.Neuron57760–773. 10.1016/j.neuron.2008.01.022

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 88

  LammelS.SteinbergE. E.FöldyC.WallN. R.BeierK.LuoL.et al (2015). Diversity of transgenic mouse models for selective targeting of midbrain dopamine neurons.Neuron85429–438. 10.1016/j.neuron.2014.12.036

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 89

  LamourY.RivotJ. P.PointisD.Ory-LavolleeL. (1983). Laminar distribution of serotonergic innervation in rat somatosensory cortex, as determined by in vivo electrochemical detection.Brain Res.259163–166. 10.1016/0006-8993(83)91082-X

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 90

  LeschK. P.WaiderJ. (2012). Serotonin in the modulation of neural plasticity and networks: implications for neurodevelopmental disorders.Neuron76175–191. 10.1016/j.neuron.2012.09.013

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 91

  LewisD. A.CampbellM. J.FooteS. L.GoldsteinM.MorrisonJ. H. (1987). The distribution of tyrosine hydroxylase-immunoreactive fibers in primate neocortex is widespread but regionally specific.J. Neurosci.7279–290. 10.1523/JNEUROSCI.07-01-00279.1987

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 92

  LidowM. S.Goldman-RakicP. S.GallagerD. W.RakicP. (1991). Distribution of dopaminergic receptors in the primate cerebral cortex: quantitative autoradiographic analysis using [3H]raclopride, [3H]spiperone and [3H]SCH23390.Neuroscience40657–671. 10.1016/0306-4522(91)90003-7

  • CrossRef
  • Google Scholar

• 93

  LidowM. S.WangF.CaoY.Goldman-RakicP. S. (1998). Layer V neurons bear the majority of mRNAs encoding the five distinct dopamine receptor subtypes in the primate prefrontal cortex.Synapse2810–20. 10.1002/(SICI)1098-2396(199801)28:1<10::AID-SYN2>3.0.CO;2-F

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 94

  LottemE.BanerjeeD.VertechiP.SarraD.LohuisM. O.MainenZ. F. (2018). Activation of serotonin neurons promotes active persistence in a probabilistic foraging task.Nat. Commun.9:1000. 10.1038/s41467-018-03438-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 95

  LottemE.LörinczM. L.MainenZ. F. (2016). Optogenetic activation of dorsal raphe serotonin neurons rapidly inhibits spontaneous but not odor-evoked activity in olfactory cortex.J. Neurosci.367–18. 10.1523/JNEUROSCI.3008-15.2016

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 96

  LoughlinS. E.FallonJ. H. (1984). Substantia nigra and ventral tegmental area projections to cortex: topography and collateralization.Neuroscience11425–435. 10.1016/0306-4522(84)90034-4

  • CrossRef
  • Google Scholar

• 97

  LoughlinS. E.FooteS. L.BloomF. E. (1986). Efferent projections of nucleus locus coeruleus: topographic organization of cells of origin demonstrated by three-dimensional reconstruction.Neuroscience18291–306. 10.1016/0306-4522(86)90155-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 98

  ManellaL. C.PetersenN.LinsterC. (2017). Stimulation of the locus ceruleus modulates signal-to-noise ratio in the olfactory bulb.J. Neurosci.3711605–11615. 10.1523/JNEUROSCI.2026-17.2017

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 99

  ManuntaY.EdelineJ. M. (1997). Effects of noradrenaline on frequency tuning of rat auditory cortex neurons.Eur. J. Neurosci.9833–847. 10.1111/j.1460-9568.1997.tb01433.x

  • CrossRef
  • Google Scholar

• 100

  MatsumotoM.HikosakaO. (2009). Two types of dopamine neuron distinctly convey positive and negative motivational signals.Nature459837–841. 10.1038/nature08028

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 101

  MatsumotoM.MatsumotoM.TakadaM.TakadaM. (2013). Distinct representations of cognitive and motivational signals in midbrain dopamine neurons.Neuron791011–1024. 10.1016/j.neuron.2013.07.002

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 102

  McLeanJ.WaterhouseB. D. (1994). Noradrenergic modulation of cat area 17 neuronal responses to moving visual stimuli.Brain Res.66783–97. 10.1016/0006-8993(94)91716-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 103

  McLeanJ. H.ShipleyM. T. (1987). Serotonergic afferents to the rat olfactory bulb: I. Origins and laminar specificity of serotonergic inputs in the adult rat.J. Neurosci.73016–3028. 10.1523/JNEUROSCI.07-10-03016.1987

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 104

  McLeanJ. H.ShipleyM. T.NickellW. T.Aston-JonesG.ReyherC. K. (1989). Chemoanatomical organization of the noradrenergic input from locus coeruleus to the olfactory bulb of the adult rat.J. Comp. Neurol.285339–349. 10.1002/cne.902850305

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 105

  MelchitzkyD. S.EricksonS. L.LewisD. A. (2006). Dopamine innervation of the monkey mediodorsal thalamus: location of projection neurons and ultrastructural characteristics of axon terminals.Neuroscience1431021–1030. 10.1016/j.neuroscience.2006.08.056

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 106

  MengodG.CortesR.VilaroM. T.HoyerD. (2010). “Distribution of 5-HT receptors in the central nervous system,” inHandbook of the Behavioral Neurobiology of Serotonin, edsMuellerC. P.JacobsB. L. (London: Academic Press), 140–155.

  • Google Scholar

• 107

  MissaleC.NashS. R.RobinsonS. W.JaberM.CaronM. G. (1998). Dopamine receptors: from structure to function.Physiol. Rev.78189–225. 10.1152/physrev.1998.78.1.189

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 108

  MiyazakiK. W.MiyazakiK.TanakaK. F.YamanakaA.TakahashiA.TabuchiS.et al (2014). Optogenetic activation of dorsal raphe serotonin neurons enhances patience for future rewards.Curr. Biol.242033–2040. 10.1016/j.cub.2014.07.041

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 109

  MooreR. Y.BloomF. E. (1979). Central catecholamine neuron systems: anatomy and physiology of the norepinephrine and epinephrine systems.Annu. Rev. Neurosci.2113–168. 10.1146/annurev.ne.02.030179.000553

  • CrossRef
  • Google Scholar

• 110

  MorrisonJ. H.FooteS. L. (1986). Noradrenergic and serotoninergic innervation of cortical, thalamic, and tectal visual structures in Old and New World monkeys.J. Comp. Neurol.243117–138. 10.1002/cne.902430110

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 111

  MorrisonJ. H.FooteS. L.MolliverM. E.BloomF. E.LidovH. G. (1982a). Noradrenergic and serotonergic fibers innervate complementary layers in monkey primary visual cortex: an immunohistochemical study.Proc. Natl. Acad. Sci. U.S.A.792401–2405.

  • Pubmed Abstract
  • Google Scholar

• 112

  MorrisonJ. H.FooteS. L.O’ConnorD.BloomF. E. (1982b). Laminar, tangential and regional organization of the noradrenergic innervation of monkey cortex: dopamine-beta-hydroxylase immunohistochemistry.Brain Res. Bull.9309–319.

  • Pubmed Abstract
  • Google Scholar

• 113

  MullerA.JosephV.SlesingerP. A.KleinfeldD. (2014). Cell-based reporters reveal in vivo dynamics of dopamine and norepinephrine release in murine cortex.Nat. Methods111245–1252. 10.1038/nmeth.3151

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 114

  MunschT.YanagawaY.ObataK.PapeH.-C. (2005). Dopaminergic control of local interneuron activity in the thalamus.Eur. J. Neurosci.21290–294. 10.1111/j.1460-9568.2004.03842.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 115

  NelsonE. L.LiangC. L.SintonC. M.GermanD. C. (1996). Midbrain dopaminergic neurons in the mouse: computer-assisted mapping.J. Comp. Neurol.369361–371. 10.1002/(SICI)1096-9861(19960603)369:3<361::AID-CNE3>3.0.CO;2-3

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 116

  NevesR. M.van KeulenS.YangM.LogothetisN. K.EschenkoO. (2018). Locus coeruleus phasic discharge is essential for stimulus-induced gamma oscillations in the prefrontal cortex.J. Neurophysiol.119904–920. 10.1152/jn.00552.2017

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 117

  NevueA. A.EldeC. J.PerkelD. J.PortforsC. V. (2015). Dopaminergic input to the inferior colliculus in mice.Front. Neuroanat.9:168. 10.3389/fnana.2015.00168

  • CrossRef
  • Google Scholar

• 118

  NiellC. M.StrykerM. P. (2010). Modulation of visual responses by behavioral state in mouse visual cortex.Neuron65472–479. 10.1016/j.neuron.2010.01.033

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 119

  NoudoostB.MooreT. (2011). Control of visual cortical signals by prefrontal dopamine.Nature474372–375. 10.1038/nature09995

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 120

  O’HanlonJ. F. (1965). Adrenaline and noradrenaline: relation to performance in a visual vigilance task.Science150507–509. 10.1126/science.150.3695.507

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 121

  OttT.JacobS. N.NiederA. (2014). Dopamine receptors differentially enhance rule coding in primate prefrontal cortex neurons.Neuron841317–1328. 10.1016/j.neuron.2014.11.012

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 122

  PapadopoulosG. C.ParnavelasJ. G. (1990). Distribution and synaptic organization of dopaminergic axons in the lateral geniculate nucleus of the rat.J. Comp. Neurol.294356–361. 10.1002/cne.902940305

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 123

  PapadopoulosG. C.ParnavelasJ. G. (1991). Monoamine systems in the cerebral cortex: evidence for anatomical specificity.Prog. Neurobiol.36195–200. 10.1016/0301-0082(91)90030-5

  • CrossRef
  • Google Scholar

• 124

  PapadopoulosG. C.ParnavelasJ. G.BuijsR. M. (1989). Light and electron microscopic immunocytochemical analysis of the noradrenaline innervation of the rat visual cortex.J. Neurocytol.181–10. 10.1007/BF01188418

  • CrossRef
  • Google Scholar

• 125

  PaspalasC. D.PapadopoulosG. C. (2001). Serotoninergic afferents preferentially innervate distinct subclasses of peptidergic interneurons in the rat visual cortex.Brain Res.891158–167. 10.1016/S0006-8993(00)03193-0

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 126

  PetzoldG. C.HagiwaraA.MurthyV. N. (2009). Serotonergic modulation of odor input to the mammalian olfactory bulb.Nat. Neurosci.12784–791. 10.1038/nn.2335

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 127

  PhillipsonO. T.KilpatrickI. C.JonesM. W. (1987). Dopaminergic innervation of the primary visual cortex in the rat, and some correlations with human cortex.Brain Res. Bull.18621–633. 10.1016/0361-9230(87)90132-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 128

  PhillisJ. W.TeběcisA. K. (1967). The responses of thalamic neurons to iontophoretically applied monoamines.J. Physiol.192715–745. 10.1113/jphysiol.1967.sp008327

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 129

  PhillisJ. W.TeběcisA. K.YorkD. H. (1967). The inhibitory action of monoamines on lateral geniculate neurones.J. Physiol.190563–581. 10.1113/jphysiol.1967.sp008228

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 130

  PolackP. O.FriedmanJ.GolshaniP. (2013). Cellular mechanisms of brain state-dependent gain modulation in visual cortex.Nat. Neurosci.161331–1339. 10.1038/nn.3464

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 131

  Pollak DorocicI.FürthD.XuanY.JohanssonY.PozziL.SilberbergG.et al (2014). A whole-brain atlas of inputs to serotonergic neurons of the dorsal and median raphe nuclei.Neuron83663–678. 10.1016/j.neuron.2014.07.002

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 132

  RabinowitzN. C.GorisR. L.CohenM.SimoncelliE. (2015). Attention stabilizes the shared gain of V4 populations.eLife4:e08998. 10.7554/eLife.08998

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 133

  RamosB. P.ArnstenA. F. (2007). Adrenergic pharmacology and cognition: focus on the prefrontal cortex.Pharmacol. Ther.113523–536. 10.1016/j.pharmthera.2006.11.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 134

  RanadeS.PiH. J.KepecsA. (2014). Neuroscience: waiting for serotonin.Curr. Biol.24R803–R805. 10.1016/j.cub.2014.07.024

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 135

  RanadeS. P.MainenZ. F. (2009). Transient firing of dorsal raphe neurons encodes diverse and specific sensory, motor, and reward events.J. Neurophysiol.1023026–3037. 10.1152/jn.00507.2009

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 136

  RauchA.RainerG.LogothetisN. K. (2008). The effect of a serotonin-induced dissociation between spiking and perisynaptic activity on BOLD functional MRI.Proc. Natl. Acad. Sci. U.S.A.1056759–6764. 10.1073/pnas.0800312105

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 137

  ReimerJ.FroudarakisE.CadwellC. R.YatsenkoD.DenfieldG. H.ToliasA. S. (2014). Pupil fluctuations track fast switching of cortical states during quiet wakefulness.Neuron84355–362. 10.1016/j.neuron.2014.09.033

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 138

  ReimerJ.McGinleyM. J.LiuY.RodenkirchC.WangQ.McCormickD. A.et al (2016). Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex.Nat. Commun.7:13289. 10.1038/ncomms13289

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 139

  RiceM. E.CraggS. J. (2008). Dopamine spillover after quantal release: rethinking dopamine transmission in the nigrostriatal pathway.Brain Res. Rev.58303–313. 10.1016/j.brainresrev.2008.02.004

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 140

  RogawskiM. A.AghajanianG. K. (1980). Modulation of lateral geniculate neurone excitability by noradrenaline microiontophoresis or locus coeruleus stimulation.Nature287731–734. 10.1038/287731a0

  • CrossRef
  • Google Scholar

• 141

  RudyB.FishellG.LeeS.Hjerling-LefflerJ. (2011). Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons.Dev. Neurobiol.7145–61. 10.1002/dneu.20853

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 142

  SafaaiH.NevesR.EschenkoO.LogothetisN. K.PanzeriS. (2015). Modeling the effect of locus coeruleus firing on cortical state dynamics and single-trial sensory processing.Proc. Natl. Acad. Sci. U.S.A.11212834–12839. 10.1073/pnas.1516539112

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 143

  Sánchez-GonzálezM. A.García-CabezasM. A.RicoB.CavadaC. (2005). The primate thalamus is a key target for brain dopamine.J. Neurosci.256076–6083. 10.1523/JNEUROSCI.0968-05.2005

  • CrossRef
  • Google Scholar

• 144

  SantanaN.MengodG.ArtigasF. (2009). Quantitative analysis of the expression of dopamine D1 and D2 receptors in pyramidal and GABAergic neurons of the rat prefrontal cortex.Cereb. Cortex19849–860. 10.1093/cercor/bhn134

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 145

  SaraS. J.BouretS. (2012). Orienting and reorienting: the locus coeruleus mediates cognition through arousal.Neuron76130–141. 10.1016/j.neuron.2012.09.011

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 146

  SarterM.ParikhV.HoweW. M. (2009). Phasic acetylcholine release and the volume transmission hypothesis: time to move on.Nat. Rev. Neurosci.10383–390. 10.1038/nrn2635

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 147

  SatoH.FoxK.DawN. W. (1989). Effect of electrical stimulation of locus coeruleus on the activity of neurons in the cat visual cortex.J. Neurophysiol.62946–958. 10.1152/jn.1989.62.4.946

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 148

  SchicknickH.ReichenbachN.SmallaK.-H.ScheichH.GundelfingerE. D.TischmeyerW. (2012). Dopamine modulates memory consolidation of discrimination learning in the auditory cortex.Eur. J. Neurosci.35763–774. 10.1111/j.1460-9568.2012.07994.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 149

  SchicknickH.SchottB. H.BudingerE.SmallaK.-H.RiedelA.SeidenbecherC. I.et al (2008). Dopaminergic modulation of auditory cortex-dependent memory consolidation through mTOR.Cereb. Cortex182646–2658. 10.1093/cercor/bhn026

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 150

  SchnyderH.KünzleH. (1984). Is there a retinopetal system in the rat.Exp. Brain Res.56502–508. 10.1007/BF00237991

  • CrossRef
  • Google Scholar

• 151

  SchölvinckM. L.SaleemA. B.BenucciA.HarrisK. D.CarandiniM. (2015). Cortical state determines global variability and correlations in visual cortex.J. Neurosci.35170–178. 10.1523/JNEUROSCI.4994-13.2015

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 152

  SchultzW. (2007). Multiple dopamine functions at different time courses.Annu. Rev. Neurosci.30259–288. 10.1146/annurev.neuro.28.061604.135722

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 153

  SeillierL.LorenzC.KawaguchiK.OttT.NiederA.PourriahiP.et al (2017). Serotonin decreases the gain of visual responses in awake macaque V1.J. Neurosci.3711390–11405. 10.1523/JNEUROSCI.1339-17.2017

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 154

  ShermanS. M. (2016). Thalamus plays a central role in ongoing cortical functioning.Nat. Neurosci.19533–541. 10.1038/nn.4269

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 155

  SmileyJ. F.LeveyA. I.CiliaxB. J.Goldman-RakicP. S. (1994). D1 dopamine receptor immunoreactivity in human and monkey cerebral cortex: predominant and extrasynaptic localization in dendritic spines.Proc. Natl. Acad. Sci. U.S.A.915720–5724. 10.1073/pnas.91.12.5720

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 156

  SoubrieP. (1986). Reconciling the role of central serotonin neurons in human and animal behavior.Behav. Brain Sci.9319–335. 10.1017/S0140525X00022871

  • CrossRef
  • Google Scholar

• 157

  SulzerD.CraggS. J.RiceM. E. (2016). Striatal dopamine neurotransmission: regulation of release and uptake.Basal Ganglia6123–148. 10.1016/j.baga.2016.02.001

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 158

  TakeuchiT.DuszkiewiczA. J.SonnebornA.SpoonerP. A.YamasakiM.WatanabeM.et al (2016). Locus coeruleus and dopaminergic consolidation of everyday memory.Nature537357–362. 10.1038/nature19325

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 159

  TakeuchiY.KimuraH.SanoY. (1982). Immunohistochemical demonstration of serotonin nerve fibers in the olfactory bulb of the rat, cat and monkey.Histochemistry75461–471.

  • Pubmed Abstract
  • Google Scholar

• 160

  TakeuchiY.SanoY. (1984). Serotonin nerve fibers in the primary visual cortex of the monkey. Quantitative and immunoelectronmicroscopical analysis.Anat. Embryol.1691–8. 10.1007/BF00300581

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 161

  TiggesJ.TiggesM.CrossN. A.McBrideR. L.LetbetterW. D.AnschelS. (1982). Subcortical structures projecting to visual cortical areas in squirrel monkey.J. Comp. Neurol.20929–40. 10.1002/cne.902090104

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 162

  TongL.AltschulerR. A.HoltA. G. (2005). Tyrosine hydroxylase in rat auditory midbrain: distribution and changes following deafness.Hear. Res.20628–41. 10.1016/j.heares.2005.03.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 163

  UematsuA.TanB. Z.YcuE. A.CuevasJ. S.KoivumaaJ.JunyentF.et al (2017). Modular organization of the brainstem noradrenaline system coordinates opposing learning states.Nat. Neurosci.201602–1611. 10.1038/nn.4642

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 164

  VarelaC. (2014). Thalamic neuromodulation and its implications for executive networks.Front. Neural Circuits8:69. 10.3389/fncir.2014.00069

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 165

  VertesR. P.LinleyS. B.HooverW. B. (2010). Pattern of distribution of serotonergic fibers to the thalamus of the rat.Brain Struct. Funct.2151–28. 10.1007/s00429-010-0249-x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 166

  VijayraghavanS.WangM.BirnbaumS. G.von WilliamsG.ArnstenA. F. T. (2007). Inverted-U dopamine D1 receptor actions on prefrontal neurons engaged in working memory.Nat. Neurosci.10376–384. 10.1038/nn1846

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 167

  VillarM. J.VitaleM. L.HökfeltT.VerhofstadA. A. (1988). Dorsal raphe serotoninergic branching neurons projecting both to the lateral geniculate body and superior colliculus: a combined retrograde tracing-immunohistochemical study in the rat.J. Comp. Neurol.277126–140. 10.1002/cne.902770109

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 168

  VincentS. L.KhanY.BenesF. M. (1993). Cellular distribution of dopamine D1 and D2 receptors in rat medial prefrontal cortex.J. Neurosci.132551–2564. 10.1523/JNEUROSCI.13-06-02551.1993

  • CrossRef
  • Google Scholar

• 169

  WatakabeA.KomatsuY.SadakaneO.ShimegiS.TakahataT.HigoN.et al (2009). Enriched expression of serotonin 1B and 2A receptor genes in macaque visual cortex and their bidirectional modulatory effects on neuronal responses.Cereb. Cortex191915–1928. 10.1093/cercor/bhn219

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 170

  WaterhouseB. D.AziziS. A.BurneR. A.WoodwardD. J. (1990). Modulation of rat cortical area 17 neuronal responses to moving visual stimuli during norepinephrine and serotonin microiontophoresis.Brain Res.514276–292. 10.1016/0006-8993(90)91422-D

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 171

  WaterhouseB. D.LinC. S.BurneR. A.WoodwardD. J. (1983). The distribution of neocortical projection neurons in the locus coeruleus.J. Comp. Neurol.217418–431. 10.1002/cne.902170406

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 172

  WaterhouseB. D.MoisesH. C.WoodwardD. J. (1980). Noradrenergic modulation of somatosensory cortical neuronal responses to iontophoretically applied putative neurotransmitters.Exp. Neurol.6930–49. 10.1016/0014-4886(80)90141-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 173

  WaterhouseB. D.MoisesH. C.WoodwardD. J. (1986). Interaction of serotonin with somatosensory cortical neuronal responses to afferent synaptic inputs and putative neurotransmitters.Brain Res. Bull.17507–518. 10.1016/0361-9230(86)90218-2

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 174

  WaterhouseB. D.MoisesH. C.WoodwardD. J. (1998). Phasic activation of the locus coeruleus enhances responses of primary sensory cortical neurons to peripheral receptive field stimulation.Brain Res.79033–44. 10.1016/S0006-8993(98)00117-6

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 175

  WaterhouseB. D.WoodwardD. J. (1980). Interaction of norepinephrine with cerebrocortical activity evoked by stimulation of somatosensory afferent pathways in the rat.Exp. Neurol.6711–34. 10.1016/0014-4886(80)90159-4

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 176

  WeinerD. M.LeveyA. I.SunaharaR. K.NiznikH. B.O’DowdB. F.SeemanP.et al (1991). D1 and D2 dopamine receptor mRNA in rat brain.Proc. Natl. Acad. Sci. U.S.A.881859–1863. 10.1073/pnas.88.5.1859

  • CrossRef
  • Google Scholar

• 177

  WilliamsS. M.Goldman-RakicP. S. (1998). Widespread origin of the primate mesofrontal dopamine system.Cereb. Cortex8321–345. 10.1093/cercor/8.4.321

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 178

  WilsonM. A.MolliverM. E. (1991a). The organization of serotonergic projections to cerebral cortex in primates: regional distribution of axon terminals.Neuroscience44537–553.

  • Pubmed Abstract
  • Google Scholar

• 179

  WilsonM. A.MolliverM. E. (1991b). The organization of serotonergic projections to cerebral cortex in primates: retrograde transport studies.Neuroscience44555–570.

  • Pubmed Abstract
  • Google Scholar

• 180

  ZaldivarD.GoenseJ.LoweS. C.LogothetisN. K.PanzeriS. (2018). Dopamine is signaled by mid-frequency oscillations and boosts output layers visual information in visual cortex.Curr. Biol.28224.e5–235.e5. 10.1016/j.cub.2017.12.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 181

  ZaldivarD.RauchA.WhittingstallK.LogothetisN. K.GoenseJ. (2014). Dopamine-induced dissociation of BOLD and neural activity in macaque visual cortex.Curr. Biol.242805–2811. 10.1016/j.cub.2014.10.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 182

  ZhaoY.KerscherN.EyselU.FunkeK. (2002). D1 and D2 receptor-mediated dopaminergic modulation of visual responses in cat dorsal lateral geniculate nucleus.J. Physiol.539(Pt 1), 223–238.

  • Pubmed Abstract
  • Google Scholar