
==== Front
Curr Neuropharmacol
Curr Neuropharmacol
CN
Current Neuropharmacology
1570-159X
1875-6190
Bentham Science Publishers

37653629
CN-22-1497
10.2174/1570159X21666230831163052
Medicine, Neurology, Pharmacology, Neuroscience
Implicit Selective Attention: The Role of the Mesencephalic-basal Ganglia System
Esposito Matteo 1
Palermo Sara 12
Nahi Ylenia Camassa 1
Tamietto Marco 13
Celeghin Alessia 1*
1 Department of Psychology, University of Torino, Via Verdi 10, 10124, Turin;
2 Neuroradiology Unit, Department of Diagnostic and Technology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy;
3 Department of Medical and Clinical Psychology, and CoRPS - Center of Research on Psychology in Somatic Diseases, Tilburg University, PO Box 90153, 5000 LE Tilburg, The Netherlands
* Address correspondence to this author at the Department of Psychology, University of Torino, Via Verdi 10, 10124, Turin, Itlay; Tel: +39 011 6703057; E-mail: alessia.celeghin@unito.it
31 8 2023
2024
22 9 14971512
13 3 2023
13 4 2023
13 4 2023
© 2024 The Author(s). Published by Bentham Science Publishers
2024
The Author(s)
https://creativecommons.org/licenses/by/4.0/ © 2024 The Author(s). Published by Bentham Science Publishers. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode.
The ability of the brain to recognize and orient attention to relevant stimuli appearing in the visual field is highlighted by a tuning process, which involves modulating the early visual system by both cortical and subcortical brain areas. Selective attention is coordinated not only by the output of stimulus-based saliency maps but is also influenced by top-down cognitive factors, such as internal states, goals, or previous experiences. The basal ganglia system plays a key role in implicitly modulating the underlying mechanisms of selective attention, favouring the formation and maintenance of implicit sensory-motor memories that are capable of automatically modifying the output of priority maps in sensory-motor structures of the midbrain, such as the superior colliculus. The article presents an overview of the recent literature outlining the crucial contribution of several subcortical structures to the processing of different sources of salient stimuli. In detail, we will focus on how the mesencephalic-basal ganglia closed loops contribute to implicitly addressing and modulating selective attention to prioritized stimuli. We conclude by discussing implicit behavioural responses observed in clinical populations in which awareness is compromised at some level. Implicit (emergent) awareness in clinical conditions that can be accompanied by manifest anosognosic symptomatology (i.e., hemiplegia) or involving abnormal conscious processing of visual information (i.e., unilateral spatial neglect and blindsight) represents interesting neurocognitive “test cases” for inferences about mesencephalic-basal ganglia closed-loops involvement in the formation of implicit sensory-motor memories.

Keywords

Basal ganglia
superior colliculus
selective attention
implicit memories
blindsight
neglect
hemiplegia
anosognosia
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pmc1 INTRODUCTION

By tuning ourselves to the outside world, we may ensure that the information that matters to us the most reaches our awareness and directs our actions. The ability of the brain to recognize and highlight the most important areas of the visual field to allocate a finite amount of attentional resources is highlighted by this tuning process, which involves modulation of the visual system by both cortical and subcortical brain areas.

Selective attention is the ability to prioritize the processing of some stimuli while ignoring others. It is generally accepted that it operates by enhancing the most relevant location in space. This enhancement is first coded as a stimulus-based saliency map [1-3], which reflects a two-dimensional topographic representation of a space combining several low-level feature maps, and operates through competition, establishing the most attractive point in the space that then guides the attentional focus [4]. Selective attention is coordinated not only by the output of stimulus-based saliency maps but is also influenced by top-down cognitive factors, such as internal states, goals, or previous experiences. Together, these cognitive factors create an internal motivational saliency map that, interacting with stimulus-based saliency maps, forms a priority map that guides eye movements and/or shifts of attention [5, 6].

If perceptually salient and/or emotional stimuli can automatically capture our attention through the involvement of subcortical regions, such as the Superior Colliculus (SC), the Pulvinar (Pulv) and the Amygdala (Amg), our cognitive system can also select stimuli based on more abstract information through the mediation of frontal and parietal areas, like the frontal eye fields (FEF) and the lateral intraparietal area (LIP).

The relatively fast preattentive processing promoted by the SC-Pulv-Amg circuit is capable of detecting value-based visual stimuli (i.e., salience) and implementing rough responses, while FEF and LIP integrate bottom-up signals with cognitive and motivational top-down factors and then modulate the neural activity of SC and related visual cortices. In fact, the SC, FEF, and LIP are highly interconnected, with SC encoding both stimulus-based saliency maps and priority maps, while the FEF and LIP preferentially computing priority maps [6].

Past literature has mainly focused on the role of this vast cortical and subcortical network in dynamically modulating the activity in visual cortices. However, other mechanisms can also intervene in modulating selective attention, revising the stimuli values according to individual history and, as a result, revising the priority maps formed in the SC [7]. Indeed, we can implicitly learn to act and react to certain stimuli by attending to the predictability and frequency of objects and events [8] or their reward value [9]. Statistical incidental learning, namely, the extraction of regularities in the learning process not guided by a task or planned, represents one of those mechanisms.

Statistical incidental learning of the spatial distribution of the targets influences selective attention, as demonstrated by experiments on gaze patterns, which favoured regions of space where targets were more frequently presented [10]. This approach can drive feature-based as well as spatial attention [11], and it is empowered when associated with semantic [12, 13], effective, and reward [14-17] meanings.

Indeed, when spatial and temporal resources are limited, the association with emotional arousal, both positive and negative, prioritizes attention [18-21], as well as reward-associated stimuli [17]. Reward-biased attention is context-dependent, meaning that attentional capture depends on whether a stimulus feature has been previously rewarded in the same circumstances [22]. Moreover, different regions of space gain priority differently after learning, suggesting that the priority maps had been reshaped to favor sites with a history of receiving higher rewards.

The basal ganglia (BG) system plays a key part in these implicitly learnt modulation mechanisms of selective attention, including many striatal sensorimotor neurons where the stable (long-term) values of visual stimuli, learned via experience, are preserved [7]. These striatal neurons receive early visual input from and reproject to SC, thereby forming closed loops through which SC activity is modulated in a rapid and automatic way [23, 24].

In this article, we will focus on how subcortical areas and these striatum-collicular closed loops contribute to implicitly addressing and modulating selective attention, emphasizing how these processes can operate without explicit awareness.

2 FROM GAZE CONTROL TO SELECTIVE ATTENTION: THE ROLE OF THE SUPERIOR COLLICULUS

The SC is a layered structure situated on the roof (tectum) of the midbrain that is crucially involved in the orientation of the gaze and head; Fig. (1) shows the anatomical subdivision of SC. The SC’s layers are commonly organized into two divisions, a dorsally located visuosensory division (superficial layers) and a centrally located motor division (deep layers) [25]. The primary inputs to the superficial layers come from the retina and striate and extrastriate cortices [26], whereas the most conspicuous outputs target the posterior thalamus, primarily the lateral geniculate nucleus and the Pulv [27, 28]. The superficial visuosensory layers also project to the deep layers of SC, which instead are both multimodal and premotor. The deep layers receive inputs virtually from the entire brain and send descending efferents to brainstem nuclei and ascending outputs to anterior thalamic nuclei that supply BG and a host of cortical regions [29, 30]. Extensive literature covering multiple species highlights that SC is capable in itself of identifying biologically salient stimuli and implementing the approach and escape behaviours (i.e., prey capture and predator avoidance) [29, 30].

The role of SC in attention has been investigated in tasks that involve gaze control, target selection, and selective attention [31-34]. Research on build-up neurons in the SC of monkeys performing a saccadic eye movement task confirms that presaccadic activation is modulated by increasing the probability of target localization [35]. Moreover, within the deep layers of SC, there are neurons specialized in orienting the focus of attention, regardless of corresponding eye movements towards selected stimuli [36, 37], proving the crucial role of SC in selective attention. SC is also involved in the causal control of selective attention, as demonstrated by electrical microstimulation [38] or reversible inactivation of monkeys’ SC, which results in neglect-like deficits [39].

A prominent feature of SC is the presence of organized maps: superficially, a visual space map, ventrally a saccadic eye movement space map, and more recently, saliency and priority maps distributed among the different layers of the SC [32, 40]. As indicated previously, the stimulus-based saliency map computes visually conspicuous points based on low-level visual features, such as brightness, color, oriented edges and motion. All these low-level visual features are rooted in local circuits, especially in the superficial layers of the SC [32-34, 41-43]. Importantly, the superficial layers of the SC process saliency before the visual cortices, thus suggesting an ancestral mechanism that can be locally managed by this mesencephalic structure [34]. The stimulus-based saliency map output can then follow two main routes; the first one to the deep layers of SC, which in turn can implement raw responses through their direct projections to the motoneurons of the brain stem [44]; the second one to the cortical areas, where it is integrated with top-down cognitive factors, forming a priority map [6], whose output is ultimately feedbacked to the deep layers of the SC [33]. In fact, in primates, the ascending input from the superficial layers of SC through the Pulv reaches cortical areas involved in spatial attention, such as the LIP or FEF [45-47], with both areas sending direct descending projections to the deep layers of the SC. Further, the FEF is also interconnected with the dorsolateral prefrontal cortex (dlPFC), which is crucially involved in supporting deliberate shifts of attention, especially when subjects must keep in mind specific abstract rules [48, 49]. Therefore, if, on the one hand, the superficial layers of SC are capable of (autonomously) detecting potentially relevant stimuli, elaborating their value (i.e., their salience), and implementing fast responses [33, 34, 44], the attentional cortical network can, on the other hand, always modulate collicular activity, modifying the priority map output in the deep layers [33] (Fig. 2).

Collicular signals can also reach the BG [23, 24]. Mounting evidence (in both humans and non-humans) highlights the role of this mesencephalic-BG network in selective attention, notably in automatically modifying the priority map output in the deep layers of the SC [7, 50], providing, moreover, new perspectives on the effect of reward on attention. Indeed, until recently, the reward was believed to influence attention indirectly by modulating task-related motivation. However, it now appears to operate directly by modifying the stimuli value (i.e., their salience), even when the stimulus is physically inconspicuous or irrelevant to the task [51].

3 THE MESENCEPHALIC-BASAL GANGLIA ARCHITECTURE

The BG system is one of the most significant components of the vertebrate brain involved in modulating neural activity of cognitive, affective and motor functions. Concerning selective attention, many studies have highlighted its crucial involvement in suppressing distractors stimuli [52-55], regulating attention-related visual changes in visual cortices [56, 57], and supporting shifts of attention [58, 59].

The BG system is characterized by parallel closed loops (topographically organized), each performing a different function [60]. In fact, there are three main anatomo-functional subdivisions within the BG system, determined by the specific cortical inputs to the striatum: (i) the dorsolateral and posterior putamen, and the dorsolateral rim of the body and of the tail of the caudate are sensorimotor territories; (ii) the anterior part of the putamen, most of the head of the caudate, and the middle parts of the body and of the tail of the caudate are associative territories; (iii) the ventral portions of the putamen and of the caudate are limbic territories [61, 62]. The most prominent example of the BG closed-loops configuration is the cortico-basal architecture. However, several animal studies (including primate models) have reported that the BG is also interconnected with SC, forming parallel closed loops similar to those with the cortex [23, 24]. These have the same general intrinsic organization, albeit in the first case, the thalamic nuclei transmit output signals, whereas in the second case, the input signals [23, 24] (Fig. 3).

The mesencephalic-BG architecture includes ancient brain structures, such as the SC, and two main closed loops are identifiable within this subcortical system. The first closed-loop originates from the superficial layers of the SC (Fig. 4a) that project to the Pulv and to the posterior lateral nucleus of the thalamus. The information then reaches the lateral territories of the body and tail of the caudate and the dorsolateral putamen, providing early visual input to the BG system. The second closed-loop (Fig. 4b), instead, originates from the deep layers of SC that send axons to the intralaminar nuclei of the thalamus, which, in turn, project to all territories of the striatum. In both loops, neuronal information is retransmitted from the striatum to SC, mainly through the substantia nigra pars reticulata (SNpr), closing the loop [23, 24]. The SC also sends ascending projections to the substantia nigra pars compacta (SNpc), thus providing dopaminergic input to the striatum [63-65].

These two mesencephalic-BG closed loops probably process different information [23]. In fact, the superficial visuosensory layers of the SC mainly project to the sensorimotor territories of the striatum. In contrast, the deep layers, which contain multimodal and premotor neurons [25], project to all the striatal territories. Therefore, the mesencephalic-BG closed-loops that originate from the superficial layers of the SC are mainly sensorimotor, whereas those that originate from the deep layers of SC are motor, associative, limbic, and multimodal [23, 24, 50].

The two mesencephalic-BG loops just described focus on collicular inputs to the striatum. However, the deep layers of SC can also provide early signal input to the BG system through its direct projections to the subthalamic nucleus (STN) [66, 67]. The evolutionary significance of this pathway is probably to stop ongoing activity in the presence of unexpected salient stimuli [24, 50], similar to the functional role of the cortico-subthalamic pathway [68, 69]. In humans, in fact, the STN exhibits an early increase in activity after the onset of an unexpected stimulus [70, 71]. Further, studies on rodents showed that STN activation interrupts behavior, and blocking the STN blunts the interruptive effect of unexpected stimuli [72].

4 THE STRIATAL MODULATION OF THE SUPERIOR COLLICULUS

Practice can modulate selective attention [8], making us faster at detecting target stimuli and suppressing the interfering effect of distractors [73-75]. Interesting data collected in humans refer to a gradual reduction of attention-related activity in FEF and inferior parietal sulcus (IPS) [76], thus suggesting a transition to a less resource-dependent level of processing. Despite it having been long known, on the one hand, that SC is widely implicated in several attentional functions, such as stimuli salience processing or shifts of attention regulation [36] and, on the other hand, that the BG system is crucially implicated in translating goal-directed behaviours into well-learned responses [77, 78], the possibility that the mesencephalic-BG closed-loops may play a primary role in implicit learning phenomena observed in selective attention has been put forth only recently [50, 79].

Several recent studies on non-human primates have investigated as to which specific striatal territories concur in modulating SC activity during the selection of visual stimuli, highlighting two main configurations of striatal neurons (Fig. 1): a first group located in the head of the caudate and involved in the selection of stimuli based on flexible (short-term) abstract rules, and a second group instead located in the posterior putamen and the tail of the caudate and involved in the selection of stimuli based on their stable (long-term) values acquired through repeated individual experience [7, 80, 81]. The head of the caudate seems to play a crucial role in modulating SC activity in situations where the relevance of stimuli changes frequently, thus requiring strategy switching [81, 82]. In fact, chemical and electrical inactivation of this striatal portion leads to a loss in selecting visual stimuli based on reward-related short-term information, sparing the selection of stimuli whose reward-related value has already been consolidated. On the contrary, inactivating the tail of the caudate results in opposite effects, suggesting that this subpopulation of striatal neurons is instead crucially involved in regulating shifts of attention towards stimuli that are historically relevant [81, 83].

In non-human primates, neurons that process stable (long-term) value of visual stimuli acquired through individual experience were found in the caudate tail, as well as in the posterior portions of the putamen (Put), globus pallidus externus (GPe), SNpr, and SNpc [84-88]. The implicitly learned relevance of stimuli, therefore, seems to be encoded along all the intrinsic circuits of the BG that receive visual input from the superficial (visuosensory) layers of the SC Notably, these posterior circuits mainly contain sensorimotor neurons [61, 62], as reported above. The head of the caudate instead receives collicular input only from the deep layers and is highly interconnected with several cortical areas involved in selective attention, such as the dlPFC, FEF and LIP. Therefore, it has been proposed that one possible role of the mesencephalic-BG closed-loops in selective visuospatial attention may be to extract regularity to create sensory-motor memories [50, 89]. Importantly, neurons involved in processing stable (long-term) values of stimuli acquired through experience and capable of triggering automatic shifts of attention towards previously rewarded visual stimuli have been recently found also in the human striatum [90], thus suggesting a neural mechanism conserved across species. The evolutionary value of this mechanism lies in the possibility of making this cortical process automatic and flexible. Once sensorimotor memories are formed and settled in the sensorimotor mesencephalic-BG closed-loops, early visual input from the superficial layers of SC can recruit a rapid automatic modulation of the output of the priority maps located within the deep layers of SC, thus reducing cognitive load without losing the possibility of responding in an adaptive way [50].

We implicitly learn from experience that in certain situations, some stimuli may be relevant, whereas others tend not to be, albeit salient from an evolutionary standpoint [73, 91, 92]. This implicitly acquired automatic selection of visual stimuli seems to be managed by the sensorimotor mesencephalic-BG closed-loops [50, 80].

5 THE CONTRIBUTION OF THE AMYGDALA TO SELECTIVE ATTENTION: THE AUTOMATIC CODING OF CONTEXTUAL CUES.

The Amg prioritizes processing emotional or salient signals from the environment through reentrant projections to sensory cortices [93-96]. An Amg response can be triggered through a “double way” of information processing: a fast “low road” from the thalamus to the Amg and a slow “high road” from the thalamus to the neocortex and then to the Amg [97-100]. The low road is the one through which the signal is processed faster, but also in less detail. It is a pathway that allows us to activate our bodies quickly in order to respond promptly to a threat. The high road is slower, but also more precise and systematic, allowing for a cautious and thoughtful assessment of the potentially adverse stimulus [97-100].

As introduced before, the SC, Pulv, and Amg have been identified as nodes of a primate subcortical route to the Amg that bypasses the cortex and participates in the fast and coarse elaboration of evolutionary emotional stimuli [96, 101]. They consistently coactivate in healthy adults [101-104], as well as in cortically blind patients [105-107], when presented with emotional stimuli, such as angry or fearful faces [108]. Further, investigations on sensory unawareness have shown consistently that unseen emotional stimuli elicit activity in the Amg, often along with activity in the SC and Pulv [93, 101, 109-121].

Studies on animals have demonstrated that both the superficial and deep layers of SC are connected predominantly to the inferior and anterior Pulv [122-125], with the inferior Pulv receiving fibers and re-projecting to the basolateral (BLA) nucleus of the Amg [45, 108, 126-133]. For the Pulv-Amg pathway, the greatest number of fibers terminate in the inferior Pulv and in the left BLA or right centromedial amygdala (CeA) [108]. Moreover, Amg sends axons to the BG, including the tail of the caudate, the GPe and the SNpr [134-138]. Through these projections (Fig. 5), the Amg can modulate SC; in fact, in monkeys, chemical inhibition of CeA neurons suppresses saccadic eye movements, whereas optical stimulation of the CeA neurons or of the axon terminals in the SNpr facilitates them [139].

Recent evidence suggests that a primary role of the primate Amg is to modulate selective attention by processing emotional cues [139, 140]. Maeda and colleagues found within the Amg of non-human primates, especially in the CeA, neurons that are activated differentially by the emotional context, based on the specific valence acquired through experience. They found neurons selectively sensitive to the dangerous-safe dimension, selectively sensitive to the rich-poor dimension, and sensitive to both dimensions. Importantly, the activity of these neurons occurred early (about 100 ms after the scene appearance) and it was negatively correlated with the reaction time of shifts of attention towards stimuli previously rewarded [140]. Due to the anatomical connectivity between Amg and BG, information on object value and context is probably integrated at the level of the mesencephalic-BG network output [139, 140]. In other words, the Amg, mostly the CeA, contributes to attentional selection by encoding whether a specific context is potentially dangerous or safe, rich or poor, based on previous individual experiences [140]. As a matter of fact, signals from the Amg are integrated with the BG outputs, probably in the SNpr [139], thus allowing an automatic selection of the stimuli that takes into account both the specific values of objects and the context in which they are present.

6 IS AWARENESS NECESSARY FOR THE FORMATION OF IMPLICIT SENSORY-MOTOR MEMORIES?

The above data show that one of the main roles of the BG system in selective attention is to automate the resource-dependent attentional processing managed by the cortex and to form sensorimotor memories that are capable of fast modulating the priority map output in the deep layers of the SC [50]. An open question is whether awareness is necessary for the formation and/or retrieval of these memories. In this regard, clues can be gained from some clinical conditions, such as blindsight (BS), unilateral spatial neglect (USN) and anosognosia for hemiplegia (AHP).

These clinical populations seem to suggest that alterations in the attentional networks support the dysfunction of the metacognitive-executive system but still allow the formation of implicit memories [141]. Importantly for our purposes, there is a strong association between lack of or reduced awareness and brain lesions involving cortical and subcortical structures [142, 143]. Considering that lesions in these areas are often associated with disturbances related to visuospatial processing, online monitoring of information, and retrieval of bodily and autobiographical memories, the role of BG and SC appears consistent with the wide variability of symptoms observed in anosognosia or abnormalities in conscious information processing [144].

6.1 The Blindsight Phenomenon

BS is a clinical condition in which patients with a lesion to the primary visual cortex (V1) manifest implicit (i.e., without subjective awareness) residual visual abilities [145-147]. Specifically, they retain sensitivity within their visual field, including recognition and spatial localization of stimuli, pointing, grasping, discrimination of orientation, shape, form and wavelength, encoding of direction and speed of movement, obstacle avoidance, and discrimination of facial and bodily expressions [106, 146, 148-151]. The direct pathway from SC to the inferior Pulv appears to be involved, at least in part, in mediating those residual visual abilities in patients with damage to V1 [152]. Indeed, ablation of the SC or reversible inactivation of the connection between SC and the Pulv impairs residual vision after a V1 lesion [153, 154] and leads to impaired saccades or target attainment in the blind field of monkeys with V1 lesions [153]. Thus, stimuli in the blind field may recruit spatial attention in the early phase of visual information processing. This suggests that the appearance of secondary reinforcing visual cues could intervene in the acquisition of novel instrumental behavior. Recently, Kato and colleagues found that the monkeys’ability to discover the location of the target zone was retained when the conditioned stimuli were subsequently presented in the lesion-affected visual field [154]. This finding strongly suggests that early visual input from the superficial layers of SC can still recruit sensorimotor memories stored in the striatum, despite cortical damage and lack of visual awareness.

6.2 The Unilateral Spatial Neglect

The USN is a neurological disorder in which, as a result of brain damage mainly in the right parietal lobe, patients show deficits in spatial attention orientation and spatial representations in the contralesional visual hemifield. Despite their inability to consciously detect the contralesional stimuli, patients with USN can still process and respond to perceptual and semantic features of the neglected stimuli without being aware of it [155-158]. Notably, contralesional stimuli that are perceptually or biologically salient may overcome inattention symptoms [159-163], as well as previously fear-conditioned stimuli [164]. Therefore, the early (rapid) sensory processing managed by the SC-Pulv-Amg route still occurs. Further, a similar effect has also been observed with rewarded stimuli [165], and USN patients would appear to be as sensitive as healthy individuals to the distribution of targets even in the neglected field, responding more quickly when targets appear in the most likely region than when targets appear in the least likely region [166]. This last phenomenon of optimization of visual processes is achieved by contextual cueing, which interplays selective attention and implicit learning [167]. As a robust memory for visual context that exists to guide spatial attention, contextual cueing has been shown to direct spatial attention towards embedded targets when there is a high degree of regularity between targets and distractor context in visual search tasks [168, 169]. Rather than being conscious or intentional, this contextual knowledge is acquired implicitly [8]. The observed facilitation may occur during perceptual encoding of the input as a result of contextual cueing that automatically redirects the saccadic eye movements necessary for target discrimination [166]. In other words, it could be managed locally by the sensorimotor mesencephalic-BG closed-loops that originate from the superficial layers of SC and by the CeA neurons that encode contextual cues [139, 140], as argued above.

6.3 Anosognosia for Hemiplegia

AHP is a neurological condition in which patients neither perceive nor record their paralysis. However, despite their lack of awareness, they often adjust their behavioral performance over time unknowingly [170], suggesting “implicit awareness” of motor impairment. AHP might paradoxically be accompanied by cognitive understanding or representation of signs and deficits, yet not explicitly expressed: in such cases, hemiplegic patients may demonstrate implicit sensory-motor formation by their actions or expressions [170, 171]. For example, Nardone and colleagues (2007) tested a group of AHP patients using an attentional-capture paradigm with hemiplegia-associated words as distractors and demonstrated that AHP patients are still prone to the effect of implicit learning of selective attention: patients displayed significantly higher latencies than healthy subjects when target stimuli were presented with emotionally threatening distractors (i.e., hemiplegia-associated words), but not when the distractors were emotionally neutral (i.e., when they did not refer to the acquired hemiplegia) [171]. Evidence of this interference (increased latency) could be traced back to implicit associations recently learned during daily living.

Those findings suggest that the mesencephalic-BG closed-loops can still operate, frequently prioritizing relevant stimuli and automatically implementing adaptive responses.

OUTSTANDING QUESTIONS AND INTERIM CONCLUSION

A growing body of evidence implicates specific brain circuits in humans' introspective and conscious experiences of visual stimuli [172]. In response to recurrent sensorimotor patterns of perception and action, emotional and cognitive structures and processes emerge. It is through sensorimotor coupling between organisms and their environments that endogenous dynamic patterns of neural activity are formed and that ever-new sensorimotor memories are formed.

The role of the BG in forming sensorimotor memories is increasingly being demonstrated as a primary feature of this system since one of its core functions is to extract regularity from the external environment [50]. This neural mechanism appears to be ancient; in fact, the effects of implicit learning on selective attention have been observed in birds, amphibians, reptiles, and fish [79], other than in mammals [7], and the neural structures sustaining this mechanism are evolutionary and shared among all species. Learning to prioritise frequently relevant stimuli, ignoring those that, although originally salient, become irrelevant, and using environmental cues to predict whether a given situation could be potentially dangerous or rich, are all behaviours that can significantly increase the survival odds. The evolutionary advantage of the mesencephalic-BG system could therefore be traced to the possibility of automatizing these functions, making the selection of relevant stimuli and the implementation of related responses faster. Therefore, evolution seems to have exploited a subcortical-cortical mechanism to automate even attention-related fronto-parietal activity.

A subcortical mechanism that detects potentially environmentally threatening stimuli by using the collicular-pulvinar-amygdala network [173] is likely to serve as a mediator for covert attentional orientation [174] and automatic raw processing of value-based stimuli [43, 107], ensuring survival and adaptation to the external environment. The mesencephalic-BG system contributes to selection processes by automatizing the top-down modulation of priority map outputs in the deep layers of SC through the formation of sensorimotor memories, which, once formed and stored in the sensorimotor striatum, can be automatically recruited by early input from the SC [50]. This advantage also seems maintained in clinical populations characterised by focal cortical lesions and preserved subcortical areas and manifesting a lack of awareness of specific behavioural responses, such as in the AHP. In such a case, implicit awareness of motor dysfunctions could originate from a dissociation between attentional, executive and mnemonic components [175]. Studies on AHP or BS and USN, which are not an all-or-nothing phenomenon but have partial and fluctuating trigger-tie responses, demonstrate implicit learning and consequent manifest behaviours [175]. Attention, therefore, has been paid to the relationship between anosognosia and hemiplegia [176-178], anosognosia and neglect [179-181], and anosognosia and blindsight [182]. These disorders may occur simultaneously, and a partially common underlying process has been hypothesised [144].

As a result of several studies analyzing reduced awareness of sensory, motor, and cognitive impairments, it has become increasingly apparent that abnormal conscious processing of information can be caused by disruptions of several cognitive mechanisms and anatomical networks [144]. The three conditions may all be affected, though in different ways, by inadequate neuromodulation between the SC, BG, subthalamic nuclei, and higher-order cortices and may paradoxically maintain signs of coarse understanding or representation of simple attention-guided behaviours. This “emergent awareness” based on implicit learning allows AHP patients to recognize their deficits when they have been asked to perform an action and realise their errors [183], or they must attempt dangerous actions [184], while influencing the manifest behaviour in patients with USN or BS, given that selective attention and error processing mechanisms are intrinsically automatic [185]. As a result, ecological behaviour depends on access to a plurality of information sources (such as proprioception, visual attention and motor attention), which are simultaneously engaged at explicit and implicit levels. Sensorimotor memories are usually consolidated in the light of action- and self-monitoring proper functioning. In the case of impairment, varying degrees and types of awareness dysfunction may occur [141, 144, 175]. Those inferences prove to be robust beyond the heterogeneity of the neuropsychological measures used to evaluate implicit sensory-motor memories or awareness and the variation in the amount of information available in the three pathological models (for example, USN has a much longer tradition of implicit memory evaluation than AHP). The neural underpinnings of implicit sensory-motor memory and implicit (emergent) awareness remain to be clearly disambiguated. Therefore, new functional neuroimaging studies involving implicit learning tasks that underline the role of selective attention in subjects with different levels of impaired awareness (or abnormal conscious processing of information) are needed.

There is still a question as to how explicit and implicit levels are integrated. Of particular interest will be studies on how mesencephalic-BG closed-loops intervene and support other subcortical-cortical networks to allow the aware subjective experience [186]. In particular, new research is needed to explore the association between implicit sensory-motor memory impairment and the disruption of brain regions involved in selective attention and awareness. The clinical implications of this future research are considerable. Reduced awareness leads to high noncompliance rates during the first 4 years after diagnosis [187] and poor prognosis and rehabilitation [188]. By contrast, the proper mesencephalic-BG closed-loop function could facilitate sensory-motor memories and, consequently, treatment options, both acute and post-acute, pharmaceutical and non-pharmaceutical. By mobilizing the dopaminergic system, BG supports the reinforcement of positive outcomes, which promotes a success-driven learning system that limits decay after learning [189]. As a result of the dopaminergic input from the substantia nigra and spatial information through the cortico-striatal connections, reward expectations modulate striatal projection neurons' activity [190]. This modulates the inhibitory output of the BG, which directs attention toward rewarded items [190]. Considering that dopamine accumulates gradually and lasts for long periods [191], it may facilitate the formation of long-term sensory-motor memories that contribute to proper behaviors in daily living. Finally, implicit (emergent) awareness may facilitate rehabilitation and recovery as patients may exhibit an inclination to take part in the therapeutic process to tackle neurological dysfunctions because of the well-functioning of circuits we have described.

ACKNOWLEDGEMENTS

Declared none.

LIST OF ABBREVIATIONS

Amg Amygdala

BG Basal Ganglia

FEF Frontal Eye Fields

GPe Globus Pallidus Externus

IPS Inferior Parietal Sulcus

Pulv Pulvinar

SC Superior Colliculus

SNpc Substantia Nigra Pars Compacta

SNpr Substantia Nigra Pars Reticulata

USN Unilateral Spatial Neglect

CONSENT FOR PUBLICATION

Not applicable.

FUNDING

ME and AC are supported by a grant from the CRT Foundation to AC; YCN and MT are supported by an ERC Consolidator grant (prot. 772953) to MT and by a PRIN grant from the Italian MUR (grant no. 2017TBA4KS) to MT.

CONFLICT OF INTEREST

The authors declare no conflict of interest, financial or otherwise.

Fig. (1) The anatomical subdivision of the primate striatum, pulvinar, amygdala, and superior colliculus. (a) The striatum is formed by the caudate nucleus and putamen nucleus. The caudate nucleus is, in turn, divisible in the head, body and tail of the caudate; (b) The pulvinar complex comprises several subnuclei: the pulvinar inferior centro-lateral, PIcl; pulvinar inferior centro-medial, PIcm; pulvinar inferior medial, PIm; pulvinar inferior posterior, PIp; pulvinar lateral dorso-medial, PLdm; pulvinar lateral ventro-lateral, PLvl; pulvinar medial, PM; (c) the cytoarchitecture of the amygdala includes several subnuclei: the lateral nucleus, (La); the basolateral nucleus (BL); the basomedial nucleus (BM); The paralaminar nucleus (PL); the ventral cortical nucleus, (VCo); the amygdalopiriform transition area (APir); the central nucleus, (Ce); the anterior amygdaloid area, (AAA); the medial nucleus, (Me); (d) The superior colliculus is composed of six layers: the stratum sonale (SZ); the stratum griseum superficiale (SGS); stratum opticum (SO); stratum griseum intermediate (SGI); and stratum griseum profundum (SGP). Not indicated in the figure, but part of SC also involves the stratum album intermediate (SAI) and the stratum album profundum (SAP).

Fig. (2) The main collicular human networks involved in selective attention. Through the pulvinar, collicular signals can reach the frontal eye fields (purple arrows), the amygdala (black arrows), and the striatum (blue arrows). All these brain areas, in turn, send descending projections to the superior colliculus, modulating its activity and regulating eye movements and shifts of attention. AMG = amygdala; FEF = frontal eye fields; LIP = lateral intraparietal area; Pulv = pulvinar; SC = superior colliculus; SNpr = substantia nigra pars reticulata.

Fig. (3) The basal ganglia architecture. The neuronal signal is transmitted from the striatum to the output nuclei of BG through the direct and indirect pathways. In the direct pathway, the striatum sends axons to the GPi and the SNpr, whereas in the indirect pathway, the signal, before targeting the GPi and the SNpr, passes first through the GPe and then through the STN. All striatal territories project to both the GPi and the GPe, while also receiving axons from the SNpc. Finally, in the hyper-direct pathway, signals from the cortex or the tectum can directly recruit the STN, thus bypassing the striatum. (a) The cortico-basal architecture; (b) The mesencephalic-basal architecture. The glutamatergic structures and projections are indicated in blue. The GABAergic structures and projections are shown in orange; and the dopaminergic structures and projections are demonstrated in red; GPe = globus pallidus externus; GPi = globus pallidus internus; SNpc = substantia nigra pars compacta; SNpr = substantia nigra pars reticulata; STN = subthalamic nucleus; Pulv = Pulvinar; PL = posterior-lateral nucleus; VA = ventral-anterior nucleus; VL = ventral-lateral nucleus.

Fig. (4) The two main closed loops of the mesencephalic-BG system. (a) The closed loop originates from the superficial layers of the superior colliculus. (b) The closed loop originates from the deep layers of the superior colliculus. The glutamatergic structures and projections are indicated in blue; and the GABAergic structures and projections are shown in orange; Pulv = Pulvinar; PL = posterior lateral nucleus; SNpr = substantia nigra pars reticulata.

Fig. (5) The role of the amygdala in implicit selective attention. Early visual input from the superficial layers of the superior colliculus can recruit the activity of the neurons in the centromedial amygdala that encode the contextual clues based on the specific valence acquired through individual experience. At the same time, early collicular input can also recruit the sensorimotor memories stored in the sensorimotor striatum, which instead encodes the object's values. The two pieces of information are probably integrated within the substantia nigra pars reticolata, which can, therefore (automatically) modulate the priority map output in the superior colliculus, taking into account both the specific object values and the context in which they are present. The glutamatergic structures and projections are shown in blue, and the GABAergic structures and projections are indicated in orange. BLA = Basolateral nucleus of amygdala; CeA = Centromedial amygdala; Pulv = Pulvinar; SNpr = substantia nigra pars reticulata.
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REFERENCES

1 Itti L. Koch C. A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Res. 2000 40 10-12 1489 1506 10.1016/S0042-6989(99)00163-7 10788654
2 Itti L. Koch C. Feature combination strategies for saliency-based visual attention systems. J. Electron. Imaging 2001 10 1 161 169 10.1117/1.1333677
3 Itti L. Koch C. Computational modelling of visual attention. Nat. Rev. Neurosci. 2001 2 3 194 203 10.1038/35058500 11256080
4 Lee D.K. Itti L. Koch C. Braun J. Attention activates winner-take-all competition among visual filters. Nat. Neurosci. 1999 2 4 375 381 10.1038/7286 10204546
5 Fecteau J. Munoz D. Salience, relevance, and firing: A priority map for target selection. Trends Cogn. Sci. 2006 10 8 382 390 10.1016/j.tics.2006.06.011 16843702
6 Klink P.C. Jentgens P. Lorteije J.A.M. Priority maps explain the roles of value, attention, and salience in goal-oriented behavior. J. Neurosci. 2014 34 42 13867 13869 10.1523/JNEUROSCI.3249-14.2014 25319682
7 Kim A.J. Anderson B.A. How does threat modulate the motivational effects of reward on attention? Exp. Psychol. 2021 68 3 165 172 10.1027/1618-3169/a000521 34711076
8 Todd R.M. Manaligod M.G.M. Implicit guidance of attention: The priority state space framework. Cortex 2018 102 121 138 10.1016/j.cortex.2017.08.001 28863855
9 Joshua M. Adler A. Mitelman R. Vaadia E. Bergman H. Midbrain dopaminergic neurons and striatal cholinergic interneurons encode the difference between reward and aversive events at different epochs of probabilistic classical conditioning trials. J. Neurosci. 2008 28 45 11673 11684 10.1523/JNEUROSCI.3839-08.2008 18987203
10 Jiang Y.V. Won B.Y. Swallow K.M. First saccadic eye movement reveals persistent attentional guidance by implicit learning. J. Exp. Psychol. Hum. Percept. Perform. 2014 40 3 1161 1173 10.1037/a0035961 24512610
11 Zhao J. Al-Aidroos N. Turk-Browne N.B. Attention is spontaneously biased toward regularities. Psychol. Sci. 2013 24 5 667 677 10.1177/0956797612460407 23558552
12 Shomstein S. Gottlieb J. Spatial and non-spatial aspects of visual attention: Interactive cognitive mechanisms and neural underpinnings. Neuropsychologia 2016 92 9 19 10.1016/j.neuropsychologia.2016.05.021 27256592
13 Shomstein S. Behrmann M. Cortical systems mediating visual attention to both objects and spatial locations. Proc. Natl. Acad. Sci. USA 2006 103 30 11387 11392 10.1073/pnas.0601813103 16840559
14 Chelazzi L. Perlato A. Santandrea E. Della Libera C. Rewards teach visual selective attention. Vision Res. 2013 85 58 72 10.1016/j.visres.2012.12.005 23262054
15 Chelazzi L. E to inova, J.; Calletti, R.; Lo Gerfo, E.; Sani, I.; Della Libera, C.; Santandrea, E. Altering spatial priority maps via reward-based learning. J. Neurosci. 2014 34 25 8594 8604 10.1523/JNEUROSCI.0277-14.2014 24948813
16 Anderson B.A. Laurent P.A. Yantis S. Learned value magnifies salience-based attentional capture. PLoS One 2011 6 11 e27926 10.1371/journal.pone.0027926 22132170
17 Raymond J.E. O’Brien J.L. Selective visual attention and motivation: The consequences of value learning in an attentional blink task. Psychol. Sci. 2009 20 8 981 988 10.1111/j.1467-9280.2009.02391.x 19549080
18 Markovic J. Anderson A.K. Todd R.M. Tuning to the significant: Neural and genetic processes underlying affective enhancement of visual perception and memory. Behav. Brain Res. 2014 259 229 241 10.1016/j.bbr.2013.11.018 24269973
19 Mather M. Sutherland M.R. Arousal-biased competition in perception and memory. Perspect. Psychol. Sci. 2011 6 2 114 133 10.1177/1745691611400234 21660127
20 Todd R.M. Cunningham W.A. Anderson A.K. Thompson E. Affect-biased attention as emotion regulation. Trends Cogn. Sci. 2012 16 7 365 372 10.1016/j.tics.2012.06.003 22717469
21 Vuilleumier P. Affective and motivational control of vision. Curr. Opin. Neurol. 2015 28 1 29 35 10.1097/WCO.0000000000000159 25490197
22 Anderson B.A. Value-driven attentional priority is context specific. Psychon. Bull. Rev. 2015 22 3 750 756 10.3758/s13423-014-0724-0 25199468
23 McHaffie J. Stanford T. Stein B. Coizet V. Redgrave P. Subcortical loops through the basal ganglia. Trends Neurosci. 2005 28 8 401 407 10.1016/j.tins.2005.06.006 15982753
24 Redgrave P. Coizet V. Comoli E. McHaffie J.G. Leriche M. Vautrelle N. Hayes L.M. Overton P. Interactions between the midbrain superior colliculus and the basal ganglia. Front. Neuroanat. 2010 4 4 10.3389/fnana.2010.00132 20428509
25 May P.J. The mammalian superior colliculus: Laminar structure and connections. Prog. Brain Res. 2006 151 321 378 10.1016/S0079-6123(05)51011-2 16221594
26 Schiller P.H. Sandell J.H. Interactions between visually and electrically elicited saccades before and after superior colliculus and frontal eye field ablations in the rhesus monkey. Exp. Brain Res. 1983 49 3 381 392 10.1007/BF00238780 6641836
27 Albano J.E. Norton T.T. Hall W.C. Laminar origin of projections from the superficial layers of the superior colliculus in the tree shrew, Tupaia glis. Brain Res. 1979 173 1 1 11 10.1016/0006-8993(79)91090-4 90538
28 Harting J.K. Huerta M.F. Hashikawa T. van Lieshout D.P. Projection of the mammalian superior colliculus upon the dorsal lateral geniculate nucleus: Organization of tectogeniculate pathways in nineteen species. J. Comp. Neurol. 1991 304 2 275 306 10.1002/cne.903040210 1707899
29 Basso M.A. Bickford M.E. Cang J. Unraveling circuits of visual perception and cognition through the superior colliculus. Neuron 2021 109 6 918 937 10.1016/j.neuron.2021.01.013 33548173
30 Isa T. Marquez-Legorreta E. Grillner S. Scott E.K. The tectum/superior colliculus as the vertebrate solution for spatial sensory integration and action. Curr. Biol. 2021 31 11 R741 R762 10.1016/j.cub.2021.04.001 34102128
31 Chen C.Y. Hafed Z.M. Orientation and contrast tuning properties and temporal flicker fusion characteristics of primate superior colliculus neurons. Front. Neural Circuits 2018 12 58 10.3389/fncir.2018.00058 30087598
32 Veale R. Hafed Z.M. Yoshida M. How is visual salience computed in the brain? Insights from behaviour, neurobiology and modelling. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2017 372 1714 20160113 10.1098/rstb.2016.0113 28044023
33 White B.J. Berg D.J. Kan J.Y. Marino R.A. Itti L. Munoz D.P. Superior colliculus neurons encode a visual saliency map during free viewing of natural dynamic video. Nat. Commun. 2017 8 1 14263 10.1038/ncomms14263 28117340
34 White B.J. Kan J.Y. Levy R. Itti L. Munoz D.P. Superior colliculus encodes visual saliency before the primary visual cortex. Proc. Natl. Acad. Sci. USA 2017 114 35 9451 9456 10.1073/pnas.1701003114 28808026
35 Basso M.A. Wurtz R.H. Modulation of neuronal activity in superior colliculus by changes in target probability. J. Neurosci. 1998 18 18 7519 7534 10.1523/JNEUROSCI.18-18-07519.1998 9736670
36 Krauzlis R.J. Lovejoy L.P. Zénon A. Superior colliculus and visual spatial attention. Annu. Rev. Neurosci. 2013 36 1 165 182 10.1146/annurev-neuro-062012-170249 23682659
37 Kustov A.A. Lee Robinson D. Shared neural control of attentional shifts and eye movements. Nature 1996 384 6604 74 77 10.1038/384074a0 8900281
38 Müller J.R. Philiastides M.G. Newsome W.T. Microstimulation of the superior colliculus focuses attention without moving the eyes. Proc. Natl. Acad. Sci. USA 2005 102 3 524 529 10.1073/pnas.0408311101 15601760
39 Lovejoy L.P. Krauzlis R.J. Changes in perceptual sensitivity related to spatial cues depends on subcortical activity. Proc. Natl. Acad. Sci. USA 2017 114 23 6122 6126 10.1073/pnas.1609711114 28533384
40 Basso M.A. May P.J. Circuits for Action and Cognition: A View from the Superior colliculus. Annu. Rev. Vis. Sci. 2017 3 1 197 226 10.1146/annurev-vision-102016-061234 28617660
41 Koch C. Ullman S. Selecting One Among the Many: A Simple Network Implementing Shifts in Selective Visual Attention. Massachusetts Inst Of Tech Cambridge Artificial Intelligence Lab 1984
42 Itti L. Koch C. Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 1998 20 11 1254 1259 10.1109/34.730558
43 Mendez C.A. Celeghin A. Diano M. Orsenigo D. Ocak B. Tamietto M. A deep neural network model of the primate superior colliculus for emotion recognition. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 2022 377 1863 20210512 10.1098/rstb.2021.0512 36126660
44 Soares S.C. Maior R.S. Isbell L.A. Tomaz C. Nishijo H. Fast detector/first responder: Interactions between the superior colliculus-pulvinar pathway and stimuli relevant to primates. Front. Neurosci. 2017 11 67 10.3389/fnins.2017.00067 28261046
45 Romanski L.M. Giguere M. Bates J.F. Goldman-Rakic P.S. Topographic organization of medial pulvinar connections with the prefrontal cortex in the rhesus monkey. J. Comp. Neurol. 1997 379 3 313 332 10.1002/(SICI)1096-9861(19970317)379:3<313::AID-CNE1>3.0.CO;2-6 9067827
46 Bisley J.W. Goldberg M.E. Attention, intention, and priority in the parietal lobe. Annu. Rev. Neurosci. 2010 33 1 1 21 10.1146/annurev-neuro-060909-152823 20192813
47 Sommer M.A. Wurtz R.H. What the brain stem tells the frontal cortex. I. Oculomotor signals sent from superior colliculus to frontal eye field via mediodorsal thalamus. J. Neurophysiol. 2004 91 3 1381 1402 10.1152/jn.00738.2003 14573558
48 Johnson J.A. Strafella A.P. Zatorre R.J. The role of the dorsolateral prefrontal cortex in bimodal divided attention: Two transcranial magnetic stimulation studies. J. Cogn. Neurosci. 2007 19 6 907 920 10.1162/jocn.2007.19.6.907 17536962
49 Loose R. Kaufmann C. Tucha O. Auer D.P. Lange K.W. Neural networks of response shifting: Influence of task speed and stimulus material. Brain Res. 2006 1090 1 146 155 10.1016/j.brainres.2006.03.039 16643867
50 Esposito M. Tamietto M. Geminiani G.C. Celeghin A. A subcortical network for implicit visuo-spatial attention: Implications for Parkinson’s Disease. Cortex 2021 141 421 435 10.1016/j.cortex.2021.05.003 34144272
51 Anderson B.A. The attention habit: how reward learning shapes attentional selection. Ann. N. Y. Acad. Sci. 2016 1369 1 24 39 10.1111/nyas.12957 26595376
52 Deijen J.B. Stoffers D. Berendse H.W. Wolters E.C. Theeuwes J. Abnormal susceptibility to distracters hinders perception in early stage Parkinson’s disease: A controlled study. BMC Neurol. 2006 6 1 43 10.1186/1471-2377-6-43 17156486
53 Lee E.Y. Cowan N. Vogel E.K. Rolan T. Valle-Inclán F. Hackley S.A. Visual working memory deficits in patients with Parkinson’s disease are due to both reduced storage capacity and impaired ability to filter out irrelevant information. Brain 2010 133 9 2677 2689 10.1093/brain/awq197 20688815
54 McNab F. Klingberg T. Prefrontal cortex and basal ganglia control access to working memory. Nat. Neurosci. 2008 11 1 103 107 10.1038/nn2024 18066057
55 Tommasi G. Fiorio M. Yelnik J. Krack P. Sala F. Schmitt E. Fraix V. Bertolasi L. Le Bas J.F. Ricciardi G.K. Fiaschi A. Theeuwes J. Pollak P. Chelazzi L. Disentangling the role of cortico-basal ganglia loops in top-down and bottom-up visual attention: An investigation of attention deficits in parkinson disease. J. Cogn. Neurosci. 2015 27 6 1215 1237 10.1162/jocn_a_00770 25514652
56 van Schouwenburg M.R. den Ouden H.E.M. Cools R. The human basal ganglia modulate frontal-posterior connectivity during attention shifting. J. Neurosci. 2010 30 29 9910 9918 10.1523/JNEUROSCI.1111-10.2010 20660273
57 van Schouwenburg M.R. den Ouden H.E.M. Cools R. Selective attentional enhancement and inhibition of fronto-posterior connectivity by the basal ganglia during attention switching. Cereb. Cortex 2015 25 6 1527 1534 10.1093/cercor/bht345 24343891
58 Ravizza S.M. Ivry R.B. Comparison of the basal ganglia and cerebellum in shifting attention. J. Cogn. Neurosci. 2001 13 3 285 297 10.1162/08989290151137340 11371307
59 Shulman G.L. Astafiev S.V. Franke D. Pope D.L.W. Snyder A.Z. McAvoy M.P. Corbetta M. Interaction of stimulus-driven reorienting and expectation in ventral and dorsal frontoparietal and basal ganglia-cortical networks. J. Neurosci. 2009 29 14 4392 4407 10.1523/JNEUROSCI.5609-08.2009 19357267
60 Alexander G.E. DeLong M.R. Strick P.L. Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu. Rev. Neurosci. 1986 9 1 357 381 10.1146/annurev.ne.09.030186.002041 3085570
61 Nakano K. Kayahara T. Tsutsumi T. Ushiro H. Neural circuits and functional organization of the striatum. J. Neurol. 2000 247 S5 Suppl. 5 V1 V15 10.1007/PL00007778 11081799
62 Postuma R.B. Dagher A. Basal ganglia functional connectivity based on a meta-analysis of 126 positron emission tomography and functional magnetic resonance imaging publications. Cereb. Cortex 2006 16 10 1508 1521 10.1093/cercor/bhj088 16373457
63 Comoli E. Coizet V. Boyes J. Bolam J.P. Canteras N.S. Quirk R.H. Overton P.G. Redgrave P. A direct projection from superior colliculus to substantia nigra for detecting salient visual events. Nat. Neurosci. 2003 6 9 974 980 10.1038/nn1113 12925855
64 May P.J. McHaffie J.G. Stanford T.R. Jiang H. Costello M.G. Coizet V. Hayes L.M. Haber S.N. Redgrave P. Tectonigral projections in the primate: A pathway for pre-attentive sensory input to midbrain dopaminergic neurons. Eur. J. Neurosci. 2009 29 3 575 587 10.1111/j.1460-9568.2008.06596.x 19175405
65 McHaffie J.G. Jiang H. May P.J. Coizet V. Overton P.G. Stein B.E. Redgrave P. A direct projection from superior colliculus to substantia nigra pars compacta in the cat. Neuroscience 2006 138 1 221 234 10.1016/j.neuroscience.2005.11.015 16361067
66 Coizet V. Graham J.H. Moss J. Bolam J.P. Savasta M. McHaffie J.G. Redgrave P. Overton P.G. Short-latency visual input to the subthalamic nucleus is provided by the midbrain superior colliculus. J. Neurosci. 2009 29 17 5701 5709 10.1523/JNEUROSCI.0247-09.2009 19403836
67 Tokuno H. Takada M. Ikai Y. Mizuno N. Direct projections from the deep layers of the superior colliculus to the subthalamic nucleus in the rat. Brain Res. 1994 639 1 156 160 10.1016/0006-8993(94)91776-0 8180831
68 Nambu A. Seven problems on the basal ganglia. Curr. Opin. Neurobiol. 2008 18 6 595 604 10.1016/j.conb.2008.11.001 19081243
69 Nambu A. Tokuno H. Takada M. Functional significance of the cortico-subthalamo-pallidal ‘hyperdirect’ pathway. Neurosci. Res. 2002 43 2 111 117 10.1016/S0168-0102(02)00027-5 12067746
70 Bočková, M.; Chládek, J.; Jurák, P.; Halámek, J.; Baláž, M.; Rektor, I. Involvement of the subthalamic nucleus and globus pallidus internus in attention. J. Neural Transm. (Vienna) 2011 118 8 1235 1245 10.1007/s00702-010-0575-4 21191623
71 Wessel J.R. Jenkinson N. Brittain J.S. Voets S.H.E.M. Aziz T.Z. Aron A.R. Surprise disrupts cognition via a fronto-basal ganglia suppressive mechanism. Nat. Commun. 2016 7 1 11195 10.1038/ncomms11195 27088156
72 Fife K.H. Gutierrez-Reed N.A. Zell V. Bailly J. Lewis C.M. Aron A.R. Hnasko T.S. Causal role for the subthalamic nucleus in interrupting behavior. eLife 2017 6 e27689 10.7554/eLife.27689 28742497
73 Failing M. Feldmann-Wüstefeld T. Wang B. Olivers C. Theeuwes J. Statistical regularities induce spatial as well as feature-specific suppression. J. Exp. Psychol. Hum. Percept. Perform. 2019 45 10 1291 1303 10.1037/xhp0000660 31157536
74 Ferrante O. Patacca A. Di Caro V. Della Libera C. Santandrea E. Chelazzi L. Altering spatial priority maps via statistical learning of target selection and distractor filtering. Cortex 2018 102 67 95 10.1016/j.cortex.2017.09.027 29096874
75 Leber A.B. Gwinn R.E. Hong Y. O’Toole R.J. Implicitly learned suppression of irrelevant spatial locations. Psychon. Bull. Rev. 2016 23 6 1873 1881 10.3758/s13423-016-1065-y 27225635
76 Mukai I. Kim D. Fukunaga M. Japee S. Marrett S. Ungerleider L.G. Activations in visual and attention-related areas predict and correlate with the degree of perceptual learning. J. Neurosci. 2007 27 42 11401 11411 10.1523/JNEUROSCI.3002-07.2007 17942734
77 Graybiel A.M. Habits, rituals, and the evaluative brain. Annu. Rev. Neurosci. 2008 31 1 359 387 10.1146/annurev.neuro.29.051605.112851 18558860
78 Redgrave P. Rodriguez M. Smith Y. Rodriguez-Oroz M.C. Lehericy S. Bergman H. Agid Y. DeLong M.R. Obeso J.A. Goal-directed and habitual control in the basal ganglia: Implications for Parkinson’s disease. Nat. Rev. Neurosci. 2010 11 11 760 772 10.1038/nrn2915 20944662
79 Krauzlis R.J. Bogadhi A.R. Herman J.P. Bollimunta A. Selective attention without a neocortex. Cortex 2018 102 161 175 10.1016/j.cortex.2017.08.026 28958417
80 Hikosaka O. Yasuda M. Nakamura K. Isoda M. Kim H.F. Terao Y. Amita H. Maeda K. Multiple neuronal circuits for variable object–action choices based on short- and long-term memories. Proc. Natl. Acad. Sci. USA 2019 116 52 26313 26320 10.1073/pnas.1902283116 31871157
81 Kim H.F. Hikosaka O. Distinct basal ganglia circuits controlling behaviors guided by flexible and stable values. Neuron 2013 79 5 1001 1010 10.1016/j.neuron.2013.06.044 23954031
82 Ragozzino M.E. Role of the striatum in learning and memory. Neurobiol. Learn. Mem. 2007 355 379
83 Yasuda M. Hikosaka O. Functional territories in primate substantia nigra pars reticulata separately signaling stable and flexible values. J. Neurophysiol. 2015 113 6 1681 1696 10.1152/jn.00674.2014 25540224
84 Anderson B.A. Laurent P.A. Yantis S. Value-driven attentional priority signals in human basal ganglia and visual cortex. Brain Res. 2014 1587 88 96 10.1016/j.brainres.2014.08.062 25171805
85 Kim H.F. Amita H. Hikosaka O. Indirect pathway of caudal basal ganglia for rejection of valueless visual objects. Neuron 2017 94 4 920 930.e3 10.1016/j.neuron.2017.04.033 28521141
86 Kunimatsu J. Maeda K. Hikosaka O. The caudal part of putamen represents the historical object value information. J. Neurosci. 2019 39 9 1709 1719 30573645
87 Yamamoto S. Kim H.F. Hikosaka O. Reward value-contingent changes of visual responses in the primate caudate tail associated with a visuomotor skill. J. Neurosci. 2013 33 27 11227 11238 10.1523/JNEUROSCI.0318-13.2013 23825426
88 Kim H.F. Ghazizadeh A. Hikosaka O. Separate groups of dopamine neurons innervate caudate head and tail encoding flexible and stable value memories. Front. Neuroanat. 2014 8 120 10.3389/fnana.2014.00120 25400553
89 Herman J.P. Arcizet F. Krauzlis R.J. Attention-related modulation of caudate neurons depends on superior colliculus activity. eLife 2020 9e53998 10.7554/eLife.53998 32940607
90 Kang J. Kim H. Hwang S.H. Han M. Lee S.H. Kim H.F. Primate ventral striatum maintains neural representations of the value of previously rewarded objects for habitual seeking. Nat. Commun. 2021 12 1 2100 10.1038/s41467-021-22335-5 33833228
91 Codispoti M. De Cesarei A. Biondi S. Ferrari V. The fate of unattended stimuli and emotional habituation: Behavioral interference and cortical changes. Cogn. Affect. Behav. Neurosci. 2016 16 6 1063 1073 10.3758/s13415-016-0453-0 27557884
92 Micucci A. Ferrari V. De Cesarei A. Codispoti M. Contextual modulation of emotional distraction: Attentional capture and motivational significance. J. Cogn. Neurosci. 2020 32 4 621 633 10.1162/jocn_a_01505 31765599
93 Diano M. Celeghin A. Bagnis A. Tamietto M. Amygdala response to emotional stimuli without awareness: Facts and interpretations. Front. Psychol. 2017 7 2029 10.3389/fpsyg.2016.02029 28119645
94 Nishijo H. Rafal R. Tamietto M. Editorial: Limbic-Brainstem roles in perception, cognition, emotion, and behavior. Front. Neurosci. 2018 12 395 10.3389/fnins.2018.00395 29946232
95 Pourtois G. Schettino A. Vuilleumier P. Brain mechanisms for emotional influences on perception and attention: What is magic and what is not. Biol. Psychol. 2013 92 3 492 512 10.1016/j.biopsycho.2012.02.007 22373657
96 Tamietto M. de Gelder B. Neural bases of the non-conscious perception of emotional signals. Nat. Rev. Neurosci. 2010 11 10 697 709 10.1038/nrn2889 20811475
97 Le Doux J. Emotional networks and motor control: a fearful view. Prog. Brain Res. 1996 107 437 446 10.1016/s0079-6123(08)61880-4 8782535
98 Phelps E.A. LeDoux J.E. Contributions of the amygdala to emotion processing: From animal models to human behavior. Neuron 2005 48 2 175 187 10.1016/j.neuron.2005.09.025 16242399
99 LeDoux J.E. Emotion circuits in the brain. Annu. Rev. Neurosci. 2000 23 1 155 184 10.1146/annurev.neuro.23.1.155 10845062
100 LeDoux J.E. Emotion, memory and the brain. Sci. Am. 1994 270 6 50 57 10.1038/scientificamerican0694-50 8023118
101 Morris J.S. Öhman A. Dolan R.J. A subcortical pathway to the right amygdala mediating “unseen” fear. Proc. Natl. Acad. Sci. USA 1999 96 4 1680 1685 10.1073/pnas.96.4.1680 9990084
102 Rafal R.D. Koller K. Bultitude J.H. Mullins P. Ward R. Mitchell A.S. Bell A.H. Connectivity between the superior colliculus and the amygdala in humans and macaque monkeys: virtual dissection with probabilistic DTI tractography. J. Neurophysiol. 2015 114 3 1947 1962 10.1152/jn.01016.2014 26224780
103 Vuilleumier P. Armony J.L. Driver J. Dolan R.J. Distinct spatial frequency sensitivities for processing faces and emotional expressions. Nat. Neurosci. 2003 6 6 624 631 10.1038/nn1057 12740580
104 Koller K. Rafal R.D. Platt A. Mitchell N.D. Orienting toward threat: Contributions of a subcortical pathway transmitting retinal afferents to the amygdala via the superior colliculus and pulvinar. Neuropsychologia 2019 128 78 86 10.1016/j.neuropsychologia.2018.01.027 29410291
105 Pegna A.J. Khateb A. Lazeyras F. Seghier M.L. Discriminating emotional faces without primary visual cortices involves the right amygdala. Nat. Neurosci. 2005 8 1 24 25 10.1038/nn1364 15592466
106 Burra N. Hervais-Adelman A. Celeghin A. de Gelder B. Pegna A.J. Affective blindsight relies on low spatial frequencies. Neuropsychologia 2019 128 44 49 10.1016/j.neuropsychologia.2017.10.009 28993236
107 de Gelder B. Tamietto M. Pegna A.J. Van den Stock J. Visual imagery influences brain responses to visual stimulation in bilateral cortical blindness. Cortex 2015 72 15 26 10.1016/j.cortex.2014.11.009 25571770
108 McFadyen J. Mattingley J.B. Garrido M.I. An afferent white matter pathway from the pulvinar to the amygdala facilitates fear recognition. eLife 2019 8e40766 10.7554/eLife.40766 30648533
109 Morris J. Friston K.J. Büchel C. Frith C.D. Young A.W. Calder A.J. Dolan R.J. A neuromodulatory role for the human amygdala in processing emotional facial expressions. Brain 1998 121 1 47 57 10.1093/brain/121.1.47 9549487
110 Whalen P.J. Rauch S.L. Etcoff N.L. McInerney S.C. Lee M.B. Jenike M.A. Masked presentations of emotional facial expressions modulate amygdala activity without explicit knowledge. J. Neurosci. 1998 18 1 411 418 10.1523/JNEUROSCI.18-01-00411.1998 9412517
111 Critchley H.D. Mathias C.J. Dolan R.J. Fear conditioning in humans: The influence of awareness and autonomic arousal on functional neuroanatomy. Neuron 2002 33 4 653 663 10.1016/S0896-6273(02)00588-3 11856537
112 Killgore W.D.S. Yurgelun-Todd D.A. Activation of the amygdala and anterior cingulate during nonconscious processing of sad versus happy faces. Neuroimage 2004 21 4 1215 1223 10.1016/j.neuroimage.2003.12.033 15050549
113 Pasley B.N. Mayes L.C. Schultz R.T. Subcortical discrimination of unperceived objects during binocular rivalry. Neuron 2004 42 1 163 172 10.1016/S0896-6273(04)00155-2 15066273
114 Williams L.M. Das P. Liddell B.J. Kemp A.H. Rennie C.J. Gordon E. Mode of functional connectivity in amygdala pathways dissociates level of awareness for signals of fear. J. Neurosci. 2006 26 36 9264 9271 10.1523/JNEUROSCI.1016-06.2006 16957082
115 Williams L.M. Liddell B.J. Rathjen J. Brown K.J. Gray J. Phillips M. Young A. Gordon E. Mapping the time course of nonconscious and conscious perception of fear: An integration of central and peripheral measures. Hum. Brain Mapp. 2004 21 2 64 74 10.1002/hbm.10154 14755594
116 Liddell B.J. Brown K.J. Kemp A.H. Barton M.J. Das P. Peduto A. Gordon E. Williams L.M. A direct brainstem-amygdala-cortical ‘alarm’ system for subliminal signals of fear. Neuroimage 2005 24 1 235 243 10.1016/j.neuroimage.2004.08.016 15588615
117 Williams L.M. Liddell B.J. Kemp A.H. Bryant R.A. Meares R.A. Peduto A.S. Gordon E. Amygdala–prefrontal dissociation of subliminal and supraliminal fear. Hum. Brain Mapp. 2006 27 8 652 661 10.1002/hbm.20208 16281289
118 Carlson J.M. Reinke K.S. Habib R. A left amygdala mediated network for rapid orienting to masked fearful faces. Neuropsychologia 2009 47 5 1386 1389 10.1016/j.neuropsychologia.2009.01.026 19428403
119 Yoon K.L. Hong S.W. Joormann J. Kang P. Perception of facial expressions of emotion during binocular rivalry. Emotion 2009 9 2 172 182 10.1037/a0014714 19348530
120 Juruena M.F. Giampietro V.P. Smith S.D. Surguladze S.A. Dalton J.A. Benson P.J. Cleare A.J. Fu C.H. Amygdala activation to masked happy facial expressions. J. Int. Neuropsychol. Soc. 2010 16 2 383 387 10.1017/S1355617709991172 19958569
121 Troiani V. Schultz R.T. Amygdala, pulvinar, and inferior parietal cortex contribute to early processing of faces without awareness. Front. Hum. Neurosci. 2013 7 241 10.3389/fnhum.2013.00241 23761748
122 Stepniewska I. Qi H-X. Kaas J.H. Projections of the superior colliculus to subdivisions of the inferior pulvinar in New World and Old World monkeys. Vis. Neurosci. 2000 17 4 529 549 10.1017/S0952523800174048 11016573
123 Benevento L.A. Standage G.P. The organization of projections of the retinorecipient and nonretinorecipient nuclei of the pretectal complex and layers of the superior colliculus to the lateral pulvinar and medial pulvinar in the macaque monkey. J. Comp. Neurol. 1983 217 3 307 336 10.1002/cne.902170307 6886056
124 Benevento L.A. Fallon J.H. The ascending projections of the superior colliculus in the rhesus monkey (Macaca mulatta). J. Comp. Neurol. 1975 160 3 339 361 10.1002/cne.901600306 1112928
125 Jacobson S. Trojanowski J.Q. Corticothalamic neurons and thalamocortical terminal fields: An investigation in rat using horseradish peroxidase and autoradiography. Brain Res. 1975 85 3 385 401 10.1016/0006-8993(75)90815-X 46175
126 Elorette C. Forcelli P.A. Saunders R.C. Malkova L. Colocalization of tectal inputs with amygdala-projecting neurons in the macaque pulvinar. Front. Neural Circuits 2018 12 91 10.3389/fncir.2018.00091 30405362
127 Locke S. The projection of the medical pulvinar of the macaque. J. Comp. Neurol. 1960 115 2 155 169 10.1002/cne.901150205 13762988
128 Jones E.G. Burton H. A projection from the medial pulvinar to the amygdala in primates. Brain Res. 1976 104 1 142 147 10.1016/0006-8993(76)90654-5 813820
129 Aggleton J.P. Burton M.J. Passingham R.E. Cortical and subcortical afferents to the amygdala of the rhesus monkey (Macaca mulatta). Brain Res. 1980 190 2 347 368 10.1016/0006-8993(80)90279-6 6768425
130 Norita M. Kawamura K. Subcortical afferents to the monkey amygdala: An HRP study. Brain Res. 1980 190 1 225 230 10.1016/0006-8993(80)91171-3 6769534
131 Stefanacci L. Amaral D.G. Topographic organization of cortical inputs to the lateral nucleus of the macaque monkey amygdala: A retrograde tracing study. J. Comp. Neurol. 2000 421 1 52 79 10.1002/(SICI)1096-9861(20000522)421:1<52::AID-CNE4>3.0.CO;2-O 10813772
132 Amaral D.G. Price J.L. Amygdalo-cortical projections in the monkey (Macaca fascicularis). J. Comp. Neurol. 1984 230 4 465 496 10.1002/cne.902300402 6520247
133 Gattass R. Soares J.G.M. Lima B. Connectivity of the Pulvinar. Adv. Anat. Embryol. Cell Biol. 2018 225 19 29 10.1007/978-3-319-70046-5_5 29116446
134 Fudge J.L. Haber S.N. The central nucleus of the amygdala projection to dopamine subpopulations in primates. Neuroscience 2000 97 3 479 494 10.1016/S0306-4522(00)00092-0 10828531
135 Griggs W.S. Kim H.F. Ghazizadeh A. Costello M.G. Wall K.M. Hikosaka O. Flexible and stable value coding areas in caudate head and tail receive anatomically distinct cortical and subcortical inputs. Front. Neuroanat. 2017 11 106 10.3389/fnana.2017.00106 29225570
136 Price J.L. Amaral D.G. An autoradiographic study of the projections of the central nucleus of the monkey amygdala. J. Neurosci. 1981 1 11 1242 1259 10.1523/JNEUROSCI.01-11-01242.1981 6171630
137 Shinonaga Y. Takada M. Mizuno N. Direct projections from the central amygdaloid nucleus to the globus pallidus and substantia nigra in the cat. Neuroscience 1992 51 3 691 703 10.1016/0306-4522(92)90308-O 1283209
138 Vankova M. Arluison M. Leviel V. Tramu G. Afferent connections of the rat substantia nigra pars lateralis with special reference to peptide-containing neurons of the amygdalo-nigral pathway. J. Chem. Neuroanat. 1992 5 1 39 50 10.1016/0891-0618(92)90032-L 1376607
139 Maeda K. Inoue K. Kunimatsu J. Takada M. Hikosaka O. Primate amygdalo-nigral pathway for boosting oculomotor action in motivating situations. iScience 2020 23 6 101194 10.1016/j.isci.2020.101194 32516719
140 Maeda K. Kunimatsu J. Hikosaka O. Amygdala activity for the modulation of goal-directed behavior in emotional contexts. PLoS Biol. 2018 16 6 e2005339 10.1371/journal.pbio.2005339 29870524
141 Mograbi D.C. Morris R.G. The developing concept of implicit awareness: A rejoinder and reply to commentaries on Mograbi and Morris. Cogn. Neurosci. 2014 5 3-4 138 142 10.1080/17588928.2014.905522 24717089
142 Starkstein S.E. Jorge R.E. Robinson R.G. The frequency, clinical correlates, and mechanism of anosognosia after stroke. Can. J. Psychiatry 2010 55 6 355 361 10.1177/070674371005500604 20540830
143 McGlynn S.M. Schacter D.L. Unawareness of deficits in neuropsychological syndromes. J. Clin. Exp. Neuropsychol. 1989 11 2 143 205 10.1080/01688638908400882 2647781
144 Prigatano G.P. The study of anosognosia. Oxford University Press 2010
145 Celeghin A. Diano M. de Gelder B. Weiskrantz L. Marzi C.A. Tamietto M. Intact hemisphere and corpus callosum compensate for visuomotor functions after early visual cortex damage. Proc. Natl. Acad. Sci. USA 2017 114 48 E10475 E10483 10.1073/pnas.1714801114 29133428
146 Celeghin A. Tamietto M. Blindsight: Functions, methods and neural substrates. Reference Module in Neuroscience and Biobehavioral Psychology 2021
147 Weiskrantz L. Warrington E.K. Sanders M.D. Marshall J. Visual capacity in the hemianopic field following a restricted occipital ablation. Brain 1974 97 1 709 728 10.1093/brain/97.1.709 4434190
148 Georgy L. Celeghin A. Marzi C.A. Tamietto M. Ptito A. The superior colliculus is sensitive to gestalt-like stimulus configuration in hemispherectomy patients. Cortex 2016 81 151 161 10.1016/j.cortex.2016.04.018 27208816
149 Celeghin A. Barabas M. Mancini F. Bendini M. Pedrotti E. Prior M. Cantagallo A. Savazzi S. Marzi C.A. Speeded manual responses to unseen visual stimuli in hemianopic patients: What kind of blindsight? Conscious. Cogn. 2015 32 6 14 10.1016/j.concog.2014.07.010 25123328
150 Celeghin A. de Gelder B. Tamietto M. From affective blindsight to emotional consciousness. Conscious. Cogn. 2015 36 414 425 10.1016/j.concog.2015.05.007 26058355
151 Celeghin A. Savazzi S. Barabas M. Bendini M. Marzi C.A. Blindsight is sensitive to stimulus numerosity and configuration: evidence from the redundant signal effect. Exp. Brain Res. 2015 233 5 1617 1623 10.1007/s00221-015-4236-6 25712088
152 Tamietto M. Morrone M.C. Visual plasticity: blindsight bridges anatomy and function in the visual system. Curr. Biol. 2016 26 2 R70 R73 10.1016/j.cub.2015.11.026 26811892
153 Kinoshita M. Kato R. Isa K. Kobayashi K. Kobayashi K. Onoe H. Isa T. Dissecting the circuit for blindsight to reveal the critical role of pulvinar and superior colliculus. Nat. Commun. 2019 10 1 135 10.1038/s41467-018-08058-0 30635570
154 Kato R. Takaura K. Ikeda T. Yoshida M. Isa T. Contribution of the retino-tectal pathway to visually guided saccades after lesion of the primary visual cortex in monkeys. Eur. J. Neurosci. 2011 33 11 1952 1960 10.1111/j.1460-9568.2011.07729.x 21645091
155 Bisiach E. Rusconi M.L. Break-down of perceptual awareness in unilateral neglect. Cortex 1990 26 4 643 649 10.1016/S0010-9452(13)80313-9 2081401
156 Làdavas E. Paladini R. Cubelli R. Implicit associative priming in a patient with left visual neglect. Neuropsychologia 1993 31 12 1307 1320 10.1016/0028-3932(93)90100-E 8127429
157 Shaqiri A. Anderson B. Priming and statistical learning in right brain damaged patients. Neuropsychologia 2013 51 13 2526 2533 10.1016/j.neuropsychologia.2013.09.024 24075841
158 Wansard M. Bartolomeo P. Vanderaspoilden V. Geurten M. Meulemans T. Can the exploration of left space be induced implicitly in unilateral neglect? Conscious. Cogn. 2015 31 115 123 10.1016/j.concog.2014.11.004 25460245
159 Brown C.R.H. The prioritisation of motivationally salient stimuli in hemi-spatial neglect may be underpinned by goal-relevance: A meta-analytic review. Cortex 2022 150 85 107 10.1016/j.cortex.2022.03.001 35381470
160 Domínguez-Borràs J. Saj A. Armony J.L. Vuilleumier P. Emotional processing and its impact on unilateral neglect and extinction. Neuropsychologia 2012 50 6 1054 1071 10.1016/j.neuropsychologia.2012.03.003 22406694
161 Tamietto M. Latini C.L. Pia L. Zettin M. Gionco M. Geminiani G. Effects of emotional face cueing on line bisection in neglect: A single case study. Neurocase 2005 11 6 399 404 10.1080/13554790500259717 16393753
162 Tamietto M. Cauda F. Celeghin A. Diano M. Costa T. Cossa F.M. Sacco K. Duca S. Geminiani G.C. de Gelder B. Once you feel it, you see it: Insula and sensory-motor contribution to visual awareness for fearful bodies in parietal neglect. Cortex 2015 62 56 72 10.1016/j.cortex.2014.10.009 25465122
163 Tamietto M. Geminiani G. Genero R. de Gelder B. Seeing fearful body language overcomes attentional deficits in patients with neglect. J. Cogn. Neurosci. 2007 19 3 445 454 10.1162/jocn.2007.19.3.445 17335393
164 Domínguez-Borràs J. Armony J.L. Maravita A. Driver J. Vuilleumier P. Partial recovery of visual extinction by pavlovian conditioning in a patient with hemispatial neglect. Cortex 2013 49 3 891 898 10.1016/j.cortex.2012.11.005 23337458
165 Lucas N. Schwartz S. Leroy R. Pavin S. Diserens K. Vuilleumier P. Gambling against neglect: Unconscious spatial biases induced by reward reinforcement in healthy people and brain-damaged patients. Cortex 2013 49 10 2616 2627 10.1016/j.cortex.2013.06.004 23969194
166 Geng J.J. Behrmann M. Probability cuing of target location facilitates visual search implicitly in normal participants and patients with hemispatial neglect. Psychol. Sci. 2002 13 6 520 525 10.1111/1467-9280.00491 12430835
167 Jiang Y. Chun M.M. Selective attention modulates implicit learning. Q. J. Exp. Psychol. A 2001 54 4 1105 1124 10.1080/713756001 11765735
168 Chun M.M. Jiang Y. Contextual cueing: implicit learning and memory of visual context guides spatial attention. Cognit. Psychol. 1998 36 1 28 71 10.1006/cogp.1998.0681 9679076
169 Hoffmann J. Kunde W. Location-specific target expectancies in visual search. J. Exp. Psychol. Hum. Percept. Perform. 1999 25 4 1127 1141 10.1037/0096-1523.25.4.1127
170 Mograbi D.C. Morris R.G. Implicit awareness in anosognosia: Clinical observations, experimental evidence, and theoretical implications. Cogn. Neurosci. 2013 4 3-4 181 197 10.1080/17588928.2013.833899 24251606
171 Nardone I.B. Ward R. Fotopoulou A. Turnbull O.H. Attention and emotion in anosognosia: evidence of implicit awareness and repression? Neurocase 2007 13 5 438 445 18781443
172 LeDoux J.E. Brown R. A higher-order theory of emotional consciousness. Proc. Natl. Acad. Sci. USA 2017 114 10 E2016 E2025 10.1073/pnas.1619316114 28202735
173 Rafee S. O’Keeffe F. O’Riordan S. Reilly R. Hutchinson M. Adult onset dystonia: A disorder of the collicular–pulvinar–amygdala network. Cortex 2021 143 282 289 10.1016/j.cortex.2021.05.010 34148640
174 Hutchinson M. Isa T. Molloy A. Kimmich O. Williams L. Molloy F. Moore H. Healy D.G. Lynch T. Walsh C. Butler J. Reilly R.B. Walsh R. O’Riordan S. Cervical dystonia: A disorder of the midbrain network for covert attentional orienting. Front. Neurol. 2014 5 54 10.3389/fneur.2014.00054 24803911
175 Palermo S. What is reduced self-awareness? An overview of interpretative models, bioethical issues and neuroimaging findings. Influences and Importance of Self-Awareness, Self-Evaluation and Self-Esteem. Thomas H.R. Nova Medicine & Health 2022 65 88
176 Gainotti G. The relations between cognitive and motivational components of anosognosia for left-sided hemiplegia and the right hemisphere dominance for emotions: A historical survey. Conscious. Cogn. 2021 94 103180 10.1016/j.concog.2021.103180 34392025
177 Pia L. Neppi-Modona M. Ricci R. Berti A. The anatomy of anosognosia for hemiplegia: A meta-analysis. Cortex 2004 40 2 367 377 10.1016/S0010-9452(08)70131-X 15156794
178 Orfei M.D. Robinson R.G. Prigatano G.P. Starkstein S. Rüsch N. Bria P. Caltagirone C. Spalletta G. Anosognosia for hemiplegia after stroke is a multifaceted phenomenon: A systematic review of the literature. Brain 2007 130 12 3075 3090 10.1093/brain/awm106 17533170
179 Berti A. Bottini G. Gandola M. Pia L. Smania N. Stracciari A. Castiglioni I. Vallar G. Paulesu E. Shared cortical anatomy for motor awareness and motor control. Science 2005 309 5733 488 491 10.1126/science.1110625 16020740
180 Kortte K. Hillis A.E. Recent advances in the understanding of neglect and anosognosia following right hemisphere stroke. Curr. Neurol. Neurosci. Rep. 2009 9 6 459 465 10.1007/s11910-009-0068-8 19818233
181 Grattan E.S. Skidmore E.R. Woodbury M.L. Examining anosognosia of neglect. OTJR (Thorofare, N.J.) 2018 38 2 113 120 10.1177/1539449217747586 29251546
182 Carota A. Bianchini F. Pizzamiglio L. Calabrese P. The “Altitudinal Anton’s syndrome”: coexistence of anosognosia, blindsight and left inattention. Behav. Neurol. 2013 26 1-2 157 163 10.1155/2013/241715 22713392
183 Moro V. Scandola M. Bulgarelli C. Avesani R. Fotopoulou A. Error-based training and emergent awareness in anosognosia for hemiplegia. Neuropsychol. Rehabil. 2015 25 4 593 616 10.1080/09602011.2014.951659 25142215
184 D’Imperio D. Bulgarelli C. Bertagnoli S. Avesani R. Moro V. Modulating anosognosia for hemiplegia: The role of dangerous actions in emergent awareness. Cortex 2017 92 187 203 10.1016/j.cortex.2017.04.009 28501758
185 Saj A. Vocat R. Vuilleumier P. On the contribution of unconscious processes to implicit anosognosia. Cogn. Neurosci. 2013 4 3-4 198 199 10.1080/17588928.2013.854760 24251607
186 Michel M. Beck D. Block N. Blumenfeld H. Brown R. Carmel D. Carrasco M. Chirimuuta M. Chun M. Cleeremans A. Dehaene S. Fleming S.M. Frith C. Haggard P. He B.J. Heyes C. Goodale M.A. Irvine L. Kawato M. Kentridge R. King J.R. Knight R.T. Kouider S. Lamme V. Lamy D. Lau H. Laureys S. LeDoux J. Lin Y.T. Liu K. Macknik S.L. Martinez-Conde S. Mashour G.A. Melloni L. Miracchi L. Mylopoulos M. Naccache L. Owen A.M. Passingham R.E. Pessoa L. Peters M.A.K. Rahnev D. Ro T. Rosenthal D. Sasaki Y. Sergent C. Solovey G. Schiff N.D. Seth A. Tallon-Baudry C. Tamietto M. Tong F. van Gaal S. Vlassova A. Watanabe T. Weisberg J. Yan K. Yoshida M. Opportunities and challenges for a maturing science of consciousness. Nat. Hum. Behav. 2019 3 2 104 107 10.1038/s41562-019-0531-8 30944453
187 Lehrer D.S. Lorenz J. Anosognosia in schizophrenia: hidden in plain sight. Innov. Clin. Neurosci. 2014 11 5-6 10 17 25152841
188 Jenkinson P.M. Preston C. Ellis S.J. Unawareness after stroke: A review and practical guide to understanding, assessing, and managing anosognosia for hemiplegia. J. Clin. Exp. Neuropsychol. 2011 33 10 1079 1093 10.1080/13803395.2011.596822 21936643
189 Wickens J.R. Reynolds J.N.J. Hyland B.I. Neural mechanisms of reward-related motor learning. Curr. Opin. Neurobiol. 2003 13 6 685 690 10.1016/j.conb.2003.10.013 14662369
190 Maier M. Ballester B.R. Verschure P.F.M.J. Principles of neurorehabilitation after stroke based on motor learning and brain plasticity mechanisms. Front. Syst. Neurosci. 2019 13 74 10.3389/fnsys.2019.00074 31920570
191 Abe M. Schambra H. Wassermann E.M. Luckenbaugh D. Schweighofer N. Cohen L.G. Reward improves long-term retention of a motor memory through induction of offline memory gains. Curr. Biol. 2011 21 7 557 562 10.1016/j.cub.2011.02.030 21419628
