Abstract
The basal forebrain (BF) contains major projections to the cerebral cortex, and plays a well-documented role in arousal, attention, decision-making, and in modulating cortical activity. BF neuronal degeneration is an early event in Alzheimer’s disease (AD) and dementias, and occurs in normal cognitive aging. While the BF is best known for its population of cortically projecting cholinergic neurons, the region is anatomically and neurochemically diverse, and also contains prominent populations of non-cholinergic projection neurons. In recent years, increasing attention has been dedicated to these non-cholinergic BF neurons in order to better understand how non-cholinergic BF circuits control cortical processing and behavioral performance. In this review, we focus on a unique population of putative non-cholinergic BF neurons that encodes the motivational salience of stimuli with a robust ensemble bursting response. We review recent studies that describe the specific physiological and functional characteristics of these BF salience-encoding neurons in behaving animals. These studies support the unifying hypothesis whereby BF salience-encoding neurons act as a gain modulation mechanism of the decision-making process to enhance cortical processing of behaviorally relevant stimuli, and thereby facilitate faster and more precise behavioral responses. This function of BF salience-encoding neurons represents a critical component in determining which incoming stimuli warrant an animal’s attention, and is therefore a fundamental and early requirement of behavioral flexibility.
Introduction
The mammalian basal forebrain (BF) is one of the most prominent cortically projecting neuromodulatory systems, with dense projections throughout the entire cerebral cortex, including prefrontal cortical areas (Gritti et al., ; Henny and Jones, ; Zaborszky et al., ). BF is an important structure implicated in attention, arousal, and in the control of cortical activity and plasticity (Everitt and Robbins, ; Wenk, ; Kilgard and Merzenich, ; Weinberger, ; Froemke et al., ). BF neuronal degeneration often occurs as an early event in Alzheimer’s disease (AD; Whitehouse et al., ; Grothe et al., ) and some forms of dementia (Cummings and Benson, ; Grothe et al., ). BF impairment has been implicated in normal cognitive aging (Gallagher and Colombo, ). In recent years, deep brain stimulation of BF targets has emerged as a potential novel therapy to alleviate dementia-related cognitive impairments (Freund et al., ; Hescham et al., ; Salma et al., ). Because of BF’s important role in normal cognitive functioning and in age-related diseases, understanding BF circuitry is therefore an important topic in neuroscience.
Despite the historical focus of BF studies on its cholinergic neurons, recent studies have begun to reveal the heterogeneity of neuronal dynamics and the functional significance of different non-cholinergic elements in the BF (a brief review in Lin et al., 2015). In this review, we focus on a specific population of putative non-cholinergic neurons in the BF that have been extensively studied in recent years (Lin et al., ; Lin and Nicolelis, ; Avila and Lin, ,; Nguyen and Lin, ). These studies highlight the functional significance of this group of putative non-cholinergic BF neurons in the decision making process via the encoding of motivational salience, which supports a fundamental aspect of behavioral flexibility.
In the first part of this article (Section 1), we discuss how the anatomical and neurochemical complexity of the BF extends far beyond the cholinergic neurons that have historically been the focus of study. In Section 2, we review recent studies that identify a unique population of putative non-cholinergic BF neurons that encodes the motivational salience of stimuli with a robust bursting response and discuss their neurochemical identity. In Section 3, we review previous BF single unit studies in behaving animals and suggest that this group of salience-encoding BF neurons have been widely described but interpreted under different circuit identities. In Section 4, we review the key features of salience-encoding BF neurons that have been revealed by recent studies. Finally, in Section 5, we propose a unifying hypothesis about the functional significance and neurochemical identity of BF salience-encoding neurons. We propose that these salience-encoding BF neurons serve as a gain-modulation mechanism to augment cortical processing of behaviorally relevant stimuli, and to modulate the speed of the decision process that enables flexible and adaptive behavior.
Section 1: BF is a Neurochemically and Anatomically Complex Region
BF has traditionally been defined by the presence of cortically projecting magnocellular cholinergic neurons that provide most of the cholinergic input to the cerebral cortex (Meynert, ; Mesulam et al., ). The cortically-projecting cholinergic neurons do not reside in a single well-defined nucleus, but rather are distributed throughout a collection of brain regions that extend along both the anterior-posterior and dorso-ventral axes with a complex geometry (Figure 1; Gritti et al., ; Zaborszky et al., ). The regions containing cholinergic neurons can be broadly divided into two major divisions: an anterior division projecting to the hippocampus, that includes the medial septum and vertical band of Broca, and a posterior division projecting to the cerebral cortex and amygdala, that includes the substantia innominata (SI), the horizontal diagonal band of Broca (HDB), the magnocellular preoptic area (MCPO), and the nucleus basalis of Meynert (NBM; Meynert, ; Mesulam et al., ; Gritti et al., ; Zaborszky et al., ). Cortically-projecting neurons in the posterior BF division are also found throughout the posterior ventral pallidum (VP; Gritti et al., ; Zaborszky et al., ). The anterior division is commonly referred to as the medial septum, while the posterior division is commonly referred to as the BF. The current review focuses on the posterior division only and adopts this narrower definition of the term BF.
Figure 1
Despite the historical focus of BF studies on its cholinergic neurons, neuroanatomical studies in the last two decades have made it clear that BF contains more than just cholinergic neurons and is instead a neurochemically heterogeneous region. In addition to cholinergic neurons, the BF contains an equally prominent number of GABAergic and glutamatergic cortically projecting neurons that are spatially intermixed with cholinergic neurons and co-distributed throughout the BF (Figure 1; Freund and Gulyás,
The complex geometry of the BF also intersects at different subregions with several other macrosystems, such as the ventral-striatopallidal system and the extended amygdala, that have input-output connectivity patterns distinct from that of the BF (Gritti et al.,
Section 2: BF Bursting Neurons Represent a Unique Population of Putative Non-Cholinergic BF Neurons
Recent studies have identified a unique population of BF neurons that forms a physiologically and functionally homogenous ensemble, and that has been referred to as BF bursting neurons or salience-encoding BF neurons in the literature (Lin et al.,
Figure 2

A unique population of non-cholinergic BF neurons. (A) Example firing rate trace of a BF bursting neuron overlaid on wake-sleep coding for the different arousal states [wake (WK); slow-wave sleep (SWS); REM sleep (REM)] and binned at 1 s (black) or 20 s (orange). (B) Average firing rates of BF bursting neurons. Left, BF tonic neurons (BFTNs, red), later identified to be BF bursting neurons or salience-encoding neurons (Lin and Nicolelis,
Multiple lines of indirect evidence suggest that BF bursting neurons do not match the known properties of BF cholinergic neurons. First, the constant firing rates in BF bursting neurons across different arousal states (Figures 2A,B) stands in contrast to BF cholinergic neurons whose firing rates are significantly higher during waking and REM sleep compared to slow-wave sleep (SWS; Lee et al.,
In addition to the corticopetal cholinergic neurons, BF contains prominent populations of GABAergic and glutamatergic cortically projecting cells (Gritti et al.,
Section 3: Differing Interpretations of BF Salience-Encoding Neurons in the Literature
Perhaps the most distinct and best-characterized property of BF bursting neurons is their ability to encode the motivational salience of primary reinforcers and reinforcer-predictive cues using phasic bursting responses. In the rodent BF, Lin and colleagues have demonstrated that BF bursting neurons respond to both primary reward (water or a sucrose solution; Figure 3A; Lin and Nicolelis,
Figure 3

Salience-encoding BF neurons have been widely reported in both non-human primates and rodents. (A) Rodent salience-encoding BF neurons show robust bursting responses to both primary reward (sucrose) and punishment (quinine). Top panels, each row represents the peri-stimulus time histogram (PSTH) of one neuron. Middle panels indicate the presence of significant excitatory (red) or inhibitory (blue) responses. Bottom panels show population PSTHs of all salience-encoding BF neurons. (B) Rodent salience-encoding neurons show robust bursting responses to motivationally salient cues that predict rewards (Ts and Ls) and punishment (Tq) when animals made correct behavioral responses (Go vs. Nogo). Ts = tone predicting sucrose; Tq = tone predicting quinine; Ls = light predicting sucrose. Conventions are the same as in (A). (C) The characteristic firing patterns differ between rhesus monkey BF structures (Border and NBM) and the globus pallidus (GP). Example 3.5 s traces from these regions reveal that neurons recorded in the nucleus basilis of Meynert (NBM) and the medullary lamina (border) have steady, regular tonic discharge patterns, in contrast to neurons in neighboring GP segments (external, GPe, and internal, GPi). (D) An example rhesus monkey BF neuron in the border region whose activity is not modulated by movement, but responds with bursts of action potentials to rewards. Action potential traces (top) are aligned with movement traces (bottom), with the first segment during rest (A; flat movement trace) and the second segment during push-pull arm movements (B; movement indicated in the bottom trace). Note how the border unit does not respond to the arm movements, but does burst to each presentation of a juice reward (R). (E) An example rhesus monkey NBM neuron responds with graded bursting responses to rewards, as well as to an aversive stimulus (air puff). (F) An example rhesus monkey NBM neuron shows robust bursting responses to the onset of stimuli instructing either a go response or a nogo response in order to receive reward. (G) An example neuron recorded in the rat caudal VP region shows robust bursting responses to a tone that predicts a sucrose pellet and instructs a go response (top; CS+1), a different tone that predicts no reward and instructs a nogo response (middle; CS−), and to the sound of the feeder that delivers a sucrose pellet (bottom; CS+2) as well as to the delivery of the pellet reward itself (UCS). (H) Normalized firing rates of all BF neurons recorded in a behavioral task, each neuron (y-axis) normalized to its maximum response across all phases of the task (x axis). While different sub-populations of BF neurons respond to all phases of a behavioral task, there is a clear overrepresentation of neurons that respond rapidly and robustly to the reward-predictive stimulus (first black line, green arrow). (A,B) were adapted from Lin and Nicolelis (
The phasic bursting responses of BF neurons to motivationally salient stimuli have in fact been widely described in both non-human primate and in rodent BF literatures. In non-human primates, DeLong first described in 1971 (DeLong,
More recent studies in the rodent BF have identified similar response patterns as the non-human primate BF bursting neurons (Tindell et al.,
It is important to note that salience-encoding BF neurons are also influenced by hedonic valence. For example, subsequent to the initial phasic bursting response to both CS+ and CS− in a Go/Nogo task that encodes motivational salience, Lin and Nicolelis (
The prevalence of salience-encoding neurons in the BF literature shows that this is a prominent neuronal population widely present in both rodents and non-human primates. Despite their prevalence, BF salience-encoding neurons have often been interpreted very differently in the literature as either the BF cholinergic neurons (Wilson and Rolls,
In this context, the unique contributions of Lin and colleagues are the identification of salience-encoding neurons as a physiologically and functionally homogeneous neuronal population in the BF, which highlights the importance in distinguishing BF salience-encoding neurons from the other neurons in this region. More importantly, Lin and colleagues suggest that these neurons are non-cholinergic BF neurons that project to the cerebral cortex (Lin et al.,
Section 4: Key Features of the BF Salience-Encoding Neurons in the Decision-Making Process
In this section, we highlight several key features of BF bursting neurons and describe how BF bursting activity quantitatively modulates behavioral responses and cortical processing. These features are instrumental in understanding the functional significance of BF bursting neurons in the decision-making process.
The first key property of BF salience-encoding neurons is that their bursting responses to sensory stimuli are not innate, but are instead acquired through associative learning (Lin and Nicolelis,
Figure 4

Key features of BF salience-encoding bursting neurons in the decision-making process. (A) BF bursting responses to motivationally salient cues are acquired through associative learning. Left: behavioral responses to auditory cues that rats have learned to associate with sucrose (Ts) and quinine (Tq), and the lack of behavioral response to a novel light cue that would subsequently come to predict sucrose (Ls). Right: BF bursting responses are present only for the previously learned cues (Ts and Tq), but not for the perceptually salient, but motivationally not salient, novel Ls cue. Conventions for this figure are the same as in Figure 3A. (B) BF bursting response is tightly coupled with successful behavioral response to motivationally salient cues. Left: all-or-none bursting responses of an example BF neuron to tone onsets in successful (Hit) or unsuccessful (Miss) trials in a near-threshold auditory detection task, with trials sorted by sound intensity levels (dB). BF bursting responses are always present in Hit trials, regardless of the sound intensity of the stimulus. Top right: population PSTHs for BF neurons to tones for Hit (shades of red) or Miss (black) trials. Note that, although the bursting response is present in all Hit trials, the amplitude of the burst is graded based on the detectability of the tone, and associated with overall response latencies (right bottom). (C) BF bursting amplitude is coupled with decision speed. Left: bursting responses of an example BF neuron to stimuli predicting a large (S-Large, green) or small reward (S-Small, red), sorted by reaction time (RT, blue). Note the larger amplitude bursting responses and faster RTs to S-Large vs. S-Small stimuli. Right: significant correlation between BF bursting amplitude modulation and RT modulation, each calculated as a ratio between S-Large and S-Small trials. (D) BF bursting responses to motivationally salient cues enhance cortical processing by generating a frontal cortex event related potential (ERP) in an auditory oddball task. Top panel: the amplitudes of the frontal cortex ERP during the oddball task are graded with motivational salience, as they are higher for motivationally salient tones (Odd-Hit and Odd-Miss) than for the standard tone that does not require a response Bottom panel: both the amplitude and timing of the BF busting response scale with the simultaneously recorded frontal ERP in the top panel. (A,B) are adapted from Lin and Nicolelis (
The second key property of BF salience-encoding neurons is that the bursting response is tightly coupled with the success of behavioral responses to motivationally salient cues. In a near-threshold auditory detection task, BF neurons displayed phasic bursting responses to tones when animals made correct behavioral responses (Hit; Figure 4B), even when tones were presented at or below detection level threshold. In contrast, when animals failed to respond to the tone, BF neurons were not activated (Miss; Figure 4B; Lin and Nicolelis,
The third key property of BF bursting neurons is that the strength of the BF motivational salience signal is quantitatively coupled with faster and more precise decision speeds. To determine the quantitative relationship between the BF salience signal and decision speed, Avila and Lin (
The fourth key property is that the BF bursting response enhances cortical processing at least in part by generating an event-related potential (ERP) response in the frontal cortex (Figure 4D; Nguyen and Lin,
Section 5: Hypothesis
Based on studies reviewed above, we propose a unifying hypothesis that the BF salience-encoding neurons serve as a signal amplifying, or gain-modulation, mechanism for motivationally salient cues (Figure 5A). The hypothesis includes three key components: (1) A unique population of putative non-cholinergic BF neurons encodes the motivational salience of stimuli with a phasic bursting response (Lin et al.,
Figure 5

Hypothesis: BF salience-encoding neurons act as a gain modulation signal to enhance cortical processing and the speed of decision-making. (A) Our working hypothesis contains three key components: first, a unique population of non-cholinergic BF neurons encodes the motivational salience of stimuli using a phasic bursting response. Second, BF motivational salience is rapidly broadcasted to the cerebral cortex to enhance cortical processing. Third, this modulation results in faster and more precise decision speed. (B) The role of BF motivational salience signal in the decision making process. Simple decision-making is commonly modeled as a drift-diffusion process or a linear rise to threshold process where activity accumulates toward a decision threshold. We propose that the amplitude of the BF motivational salience signal serves as a gain modulation mechanism that controls the rate of activity accumulation in the decision unit. Stronger BF motivational salience signal (green) increases the rate of activity accumulation relative to weaker BF bursting (blue), and in turn, increases decision speed and generates a faster RT distribution. On the other hand, the absence of BF motivational salience signal (red) translates into the decision unit never reaching the decision threshold, and in turn, leads to no behavioral response (absence of red RT distribution).
This hypothesis addresses a fundamental question in neuroscience: how the brain filters meaningful from meaningless stimuli to execute responses only to stimuli that are behaviorally relevant. Animals are constantly faced with a barrage of incoming sensory stimuli; however, most of the stimuli are not motivationally salient, do not carry any behavioral consequence, and need not be responded to. For the subset of stimuli that are motivationally salient, which may or may not be perceptually salient, the brain must require an internal gain modulation mechanism to amplify their processing and ensure correct and efficient behavioral responses. Such is the main behavioral function of this unique population of non-cholinergic BF bursting neurons, to serve as a fast and powerful gain modulation mechanism to facilitate behavioral responses to environmental stimuli, and that operates based on the motivational, but not perceptual, salience of the stimuli.
This gain-modulation hypothesis can also be conceptualized in a decision model (Figure 5B). Simple decision making processes have been commonly modeled as activity accumulation in a hypothetical decision unit, such as the drift-diffusion model or the linear rise to threshold model (Ratcliff and Rouder,
The specific cortical mechanisms that underlie the transference of the BF motivational salience signal into a rapid and precise behavioral response remain to be determined, and should be the focus of future experiments. However, the ability of BF bursting neurons to rapidly enhance cortical activity and decision speed are consistent with a disinhibition mechanism mediated by GABAergic BF cortically projecting neurons. Anatomical data show that corticopetal GABAergic neurons preferentially innervate inhibitory interneurons in the neocortex (Freund and Gulyás,
The BF’s ability to encode the motivational salience of a stimulus is a critical component in determining whether or not to attend to incoming sensory information, and is therefore a fundamental and early requirement of adaptive and flexible behavior. Indeed, animals can flexibly respond to the same stimulus depending on its associated motivational salience. The associated motivational salience can be dynamically adjusted through associative learning and rapidly reversed by extinction (Lin and Nicolelis,
Funding
This work was supported by the Intramural Research Program of the National Institute on Aging, National Institutes of Health.
Statements
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1
AlonsoA.KhatebA.FortP.JonesB. E.MühlethalerM. (1996). Differential oscillatory properties of cholinergic and noncholinergic nucleus basalis neurons in guinea pig brain slice. Eur. J. Neurosci.8, 169–182. 10.1111/j.1460-9568.1996.tb01178.x
2
Aston-JonesG.ShaverR.DinanT. G. (1985). Nucleus basalis neurons exhibit axonal branching with decreased impulse conduction velocity in rat cerebrocortex. Brain Res.325, 271–285. 10.1016/0006-8993(85)90323-3
3
AvilaI.LinS.-C. (2014a). Motivational salience signal in the basal forebrain is coupled with faster and more precise decision speed. PLoS Biol.12:e1001811. 10.1371/journal.pbio.1001811
4
AvilaI.LinS.-C. (2014b). Distinct neuronal populations in the basal forebrain encode motivational salience and movement. Front. Behav. Neurosci.8:421. 10.3389/fnbeh.2014.00421
5
BerntsonG. G.ShafiR.SarterM. (2002). Specific contributions of the basal forebrain corticopetal cholinergic system to electroencephalographic activity and sleep/waking behaviour. Eur. J. Neurosci. 16, 2453–2461. 10.1046/j.1460-9568.2002.02310.x
6
CummingsJ. L.BensonD. F. (1984). Subcortical dementia: review of an emerging concept. Arch. Neurol.41, 874–879. 10.1001/archneur.1984.04050190080019
7
DeLongM. R. (1971). Activity of pallidal neurons during movement. J. Neurophysiol.34, 414–427.
8
DunnettS. B.EverittB. J.RobbinsT. W. (1991). The basal forebrain-cortical cholinergic system: interpreting the functional consequences of excitotoxic lesions. Trends Neurosci.14, 494–501. 10.1016/0166-2236(91)90061-X
9
DykesR. W. (1997). Mechanisms controlling neuronal plasticity in somatosensory cortex. Can. J. Physiol. Pharmacol.75, 535–545. 10.1139/y97-089
10
EverittB. J.RobbinsT. W. (1997). Central cholinergic systems and cognition. Annu. Rev. Psychol.48, 649–684. 10.1146/annurev.psych.48.1.649
11
FreundT. F.GulyásA. I. (1991). GABAergic interneurons containing calbindin D28K or somatostatin are major targets of GABAergic basal forebrain afferents in the rat neocortex. J. Comp. Neurol.314, 187–199. 10.1002/cne.903140117
12
FreundH.-J.KuhnJ.LenartzD.MaiJ. K.SchnellT.KlosterkoetterJ.et al. (2009). Cognitive functions in a patient with parkinson-dementia syndrome undergoing deep brain stimulation. Arch. Neurol.66, 781–785. 10.1001/archneurol.2009.102
13
FreundT. F.MeskenaitetV. (1992). gamma-aminobutyric acid-containing basal forebrain neurons innervate inhibitory interneurons in the neocortex. Proc. Natl. Acad. Sci. U S A89, 738–742. 10.1073/pnas.89.2.738
14
FroemkeR. C.MerzenichM. M.SchreinerC. E. (2007). A synaptic memory trace for cortical receptive field plasticity. Nature450, 425–429. 10.1038/nature06289
15
FurutaT.KoyanoK.TomiokaR.YanagawaY.KanekoT. (2004). GABAergic basal forebrain neurons that express receptor for neurokinin b and send axons to the cerebral cortex. J. Comp. Neurol.473, 43–58. 10.1002/cne.20087
16
GallagherM.ColomboP. J. (1995). Ageing: the cholinergic hypothesis of cognitive decline. Curr. Opin. Neurobiol.5, 161–168. 10.1016/0959-4388(95)80022-0
17
GrittiI.HennyP.GalloniF.MainvilleL.MariottiM.JonesB. E. (2006). Stereological estimates of the basal forebrain cell population in the rat, including neurons containing choline acetyltransferase, glutamic acid decarboxylase or phosphate-activated glutaminase and colocalizing vesicular glutamate transporters. Neuroscience143, 1051–1064. 10.1016/j.neuroscience.2006.09.024
18
GrittiI.MainvilleL.JonesB. E. (1993). Codistribution of GABA- with acetylcholine-synthesizing neurons in the basal forebrain of the rat. J. Comp. Neurol.329, 438–457. 10.1002/cne.903290403
19
GrittiI.MainvilleL.ManciaM.JonesB. E. (1997). GABAergic and other noncholinergic basal forebrain neurons, together with cholinergic neurons, project to the mesocortex and isocortex in the rat. J. Comp. Neurol.383, 163–177. 10.1002/(sici)1096-9861(19970630)383:2<163::aid-cne4>3.0.co;2-z
20
GrotheM.HeinsenH.TeipelS. J. (2012). Atrophy of the cholinergic basal forebrain over the adult age range and in early stages of Alzheimer’s disease. Biol. Psychiatry71, 805–813. 10.1016/j.biopsych.2011.06.019
21
HangyaB.RanadeS. P.LorencM.KepecsA. (2015). Central cholinergic neurons are rapidly recruited by reinforcement feedback. Cell162, 1155–1168. 10.1016/j.cell.2015.07.057
22
HeimerL. (2000). Basal forebrain in the context of schizophrenia. Brain Res. Brain Res. Rev.31, 205–235. 10.1016/s0165-0173(99)00039-9
23
HennyP.JonesB. E. (2008). Projections from basal forebrain to prefrontal cortex comprise cholinergic, GABAergic and glutamatergic inputs to pyramidal cells or interneurons. Eur. J. Neurosci.27, 654–670. 10.1111/j.1460-9568.2008.06029.x
24
HermanstyneT. O.KihiraY.MisonoK.DeitchlerA.YanagawaY.MisonouH. (2010). Immunolocalization of the voltage-gated potassium channel Kv2.2 in GABAergic neurons in the basal forebrain of rats and mice. J. Comp. Neurol.518, 4298–4310. 10.1002/cne.22457
25
HeschamS.LimL. W.JahanshahiA.BloklandA.TemelY. (2013). Deep brain stimulation in dementia-related disorders. Neurosci. Biobehav. Rev.37, 2666–2675. 10.1016/j.neubiorev.2013.09.002
26
HurE. E.ZaborszkyL. (2005). Vglut2 afferents to the medial prefrontal and primary somatosensory cortices: a combined retrograde tracing in situ hybridization. J. Comp. Neurol.483, 351–373. 10.1002/cne.20444
27
KilgardM. P.MerzenichM. M. (1998). Cortical map reorganization enabled by nucleus basalis activity. Science279, 1714–1718. 10.1126/science.279.5357.1714
28
KimT.ThankachanS.McKennaJ. T.McNallyJ. M.YangC.ChoiJ. H.et al. (2015). Cortically projecting basal forebrain parvalbumin neurons regulate cortical gamma band oscillations. Proc. Natl. Acad. Sci. U S A112, 3535–3540. 10.1073/pnas.1413625112
29
LeeM. G.HassaniO. K.AlonsoA.JonesB. E. (2005). Cholinergic basal forebrain neurons burst with theta during waking and paradoxical sleep. J. Neurosci.25, 4365–4369. 10.1523/jneurosci.0178-05.2005
30
LinS.-C.BrownR. E.Hussain ShulerM. G.PetersenC. C. H.KepecsA. (2015). Optogenetic dissection of the basal forebrain neuromodulatory control of cortical activation, plasticity, and cognition. J. Neurosci. (in press).
31
LinS.-C.GervasoniD.NicolelisM. A. L. (2006). Fast modulation of prefrontal cortex activity by basal forebrain noncholinergic neuronal ensembles. J. Neurophysiol.96, 3209–3219. 10.1152/jn.00524.2006
32
LinS.-C.NicolelisM. A. L. (2008). Neuronal ensemble bursting in the basal forebrain encodes salience irrespective of valence. Neuron59, 138–149. 10.1016/j.neuron.2008.04.031
33
McKennaJ. T.YangC.FranciosiS.WinstonS.AbarrK. K.RigbyM. S.et al. (2013). Distribution and intrinsic membrane properties of basal forebrain GABAergic and parvalbumin neurons in the mouse. J. Comp. Neurol.521, 1225–1250. 10.1002/cne.23290
34
MesulamM. M.MufsonE. J.LeveyA. I.WainerB. H. (1983). Cholinergic innervation of cortex by the basal forebrain: cytochemistry and cortical connections of the septal area, diagonal band nuclei, nucleus basalis (substantia innominata) and hypothalamus in the rhesus monkey. J. Comp. Neurol.214, 170–197. 10.1002/cne.902140206
35
MeynertT. H. (1872). “The brain of mammals,” in Man Histology, ed. StrickerS. (New York: Wm. Wood & Co.), 650–766.
36
MuirJ. L.PageK. J.SirinathsinghjiD. J.RobbinsT. W.EverittB. J. (1993). Excitotoxic lesions of basal forebrain cholinergic neurons: effects on learning, memory and attention. Behav. Brain Res.57, 123–131. 10.1016/0166-4328(93)90128-D
37
NguyenD. P.LinS.-C. (2014). A frontal cortex event-related potential driven by the basal forebrain. eLife3:e02148. 10.7554/elife.02148
38
PageK. J.EverittB. J.RobbinsT. W.MarstonH. M.WilkinsonL. S. (1991). Dissociable effects on spatial maze and passive avoidance acquisition and retention following AMPA- and ibotenic acid-induced excitotoxic lesions of the basal forebrain in rats: differential dependence on cholinergic neuronal loss. Neuroscience43, 457–472. 10.1016/0306-4522(91)90308-B
39
RatcliffR. (2001). Putting noise into neurophysiological models of simple decision making. Nat. Neurosci.4, 336–337. 10.1038/85956
40
RatcliffR.RouderJ. N. (1998). Modeling response times for two-choice decisions. Psychol. Sci.9, 347–356. 10.1111/1467-9280.00067
41
ReddiB. A.CarpenterR. H. (2000). The influence of urgency on decision time. Nat. Neurosci.3, 827–830. 10.1038/77739
42
ReinerP. B.SembaK.FibigerH. C.McGreerE. G. (1987). Physiological evidence for subpopulations of cortically projecting basal forebrain neurons in the anesthetized rat. Neuroscience20, 629–636. 10.1016/0306-4522(87)90115-1
43
RichardsonR. T.DeLongM. R. (1991). Electrophysiological studies of the functions of the nucleus basalis in primates. Adv. Exp. Med. Biol.295, 233–252. 10.1007/978-1-4757-0145-6_12
44
SalmaA.VasilakisM.TracyP. T. (2014). Deep brain stimulation for cognitive disorders: insights into targeting nucleus basalis of meynert in alzheimer dementia. World Neurosurg.81, e4–e5. 10.1016/j.wneu.2013.08.011
45
SarterM.BrunoJ. P. (2002). The neglected constituent of the basal forebrain corticopetal projection system: GABAergic projections. Eur. J. Neurosci.15, 1867–1873. 10.1046/j.1460-9568.2002.02004.x
46
SmithK. S.BerridgeK. C.AldridgeJ. W. (2011). Disentangling pleasure from incentive salience and learning signals in brain reward circuitry. Proc. Natl. Acad. Sci. U S A108, E255–E264. 10.1073/pnas.1101920108
47
TindellA. J.BerridgeK. C.ZhangJ.PeciñaS.AldridgeJ. W. (2005). Ventral pallidal neurons code incentive motivation: amplification by mesolimbic sensitization and amphetamine. Eur. J. Neurosci.22, 2617–2634. 10.1111/j.1460-9568.2005.04411.x
48
TindellA. J.SmithK. S.BerridgeK. C.AldridgeJ. W. (2009). Dynamic computation of incentive salience: ‘wanting’ what was never ‘liked’. J. Neurosci.29, 12220–12228. 10.1523/JNEUROSCI.2499-09.2009
49
TindellA. J.SmithK. S.PeciñaS.BerridgeK. C.AldridgeJ. W. (2006). Ventral pallidum firing codes hedonic reward: when a bad taste turns good. J. Neurophysiol.96, 2399–2409. 10.1152/jn.00576.2006
50
TingleyD.AlexanderA. S.KolbuS.de SaV. R.ChibaA. A.NitzD. W. (2014). Task-phase-specific dynamics of basal forebrain neuronal ensembles. Front. Sys. Neurosci.8:174. 10.3389/fnsys.2014.00174
51
WeinbergerN. M. (2003). The nucleus basalis and memory codes: auditory cortical plasticity and the induction of specific, associative behavioral memory. Neurobiol. Learn. Mem.80, 268–284. 10.1016/s1074-7427(03)00072-8
52
WenkG. L. (1997). The nucleus basalis magnocellularis cholinergic system: one hundred years of progress. Neurobiol. Learn. Mem.67, 85–95. 10.1006/nlme.1996.3757
53
WenkG.StoehrJ.QuintanaG.MobleyS.WileyR. (1994). Behavioral, biochemical, histological, and electrophysiological effects of 192 IgG-saporin injections into the basal forebrain of rats. J. Neurosci.14, 5986–5995.
54
WhitehouseP. J.PriceD. L.StrubleR. G.ClarkA. W.CoyleJ. T.DeLongM. R. (1982). Alzheimer’s disease and senile dementia: loss of neurons in the basal forebrain. Science215, 1237–1239. 10.1126/science.7058341
55
WilsonF. A.RollsE. T. (1990). Learning and memory is reflected in the responses of reinforcement-related neurons in the primate basal forebrain. J. Neurosci.10, 1254–1267.
56
ZaborszkyL.CsordasA.MoscaK.KimJ.GielowM. R.VadaszC.et al. (2015). Neurons in the basal forebrain project to the cortex in a complex topographic organization that reflects corticocortical connectivity patterns: an experimental study based on retrograde tracing and 3D reconstruction. Cereb. Cortex25, 118–137. 10.1093/cercor/bht210
57
ZhangH.LinS.-C.NicolelisM. A. L. (2011). A distinctive subpopulation of medial septal slow-firing neurons promote hippocampal activation and theta oscillations. J. Neurophysiol.106, 2749–2763. 10.1152/jn.00267.2011
Summary
Keywords
nucleus basalis, behavioral flexibility, attention, decision making, rat, gain modulation
Citation
Raver SM and Lin S-C (2015) Basal forebrain motivational salience signal enhances cortical processing and decision speed. Front. Behav. Neurosci. 9:277. doi: 10.3389/fnbeh.2015.00277
Received
28 August 2015
Accepted
28 September 2015
Published
12 October 2015
Volume
9 - 2015
Edited by
Gregory B. Bissonette, University of Maryland, USA
Reviewed by
David A. Leopold, National Institutes of Health, USA; Benjamin Hayden, University of Rochester, USA
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Copyright
© 2015 Raver and Lin.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Shih-Chieh Lin shih-chieh.lin@nih.gov
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