The concept of the high road (cortical) and low road (subcortical) visual pathways for processing fear in primates. On the high road, visual information from retinal ganglion cells is relayed to the visual cortex via the lateral geniculate nucleus, a brain area in the thalamus. Visual information is processed through several areas of the cortex before it's sent to the amygdala, whereupon autonomic and endocrine mediators of fear are engaged. On the low road, visual information is sent first to the superior colliculus in the midbrain before being relayed to the amygdala via the pulvinar nucleus. Adapted from Pessoa and Adolphs (2010). LGN, lateral geniculate nucleus; SC, superior colliculus; TE, inferior temporal cortex; TEO, inferior temporal cortex; V, visual cortex.

The concept of the high road (cortical) and low road (subcortical) visual pathways for processing fear in primates. On the high road, visual information from retinal ganglion cells is relayed to the visual cortex via the lateral geniculate nucleus, a brain area in the thalamus. Visual information is processed through several areas of the cortex before it's sent to the amygdala, whereupon autonomic and endocrine mediators of fear are engaged. On the low road, visual information is sent first to the superior colliculus in the midbrain before being relayed to the amygdala via the pulvinar nucleus. Adapted from Pessoa and Adolphs (2010). LGN, lateral geniculate nucleus; SC, superior colliculus; TE, inferior temporal cortex; TEO, inferior temporal cortex; V, visual cortex.

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Although there is general agreement that the central nucleus of the amygdala (CeA) is critical for triggering the neuroendocrine response to visual threats, there is uncertainty about the role of subcortical visual pathways in this process. Primates in general appear to depend less on subcortical visual pathways than other mammals. Yet, imaging stu...

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... While the information flows from the Retina to HPA, there is no direct link between them. Fear stimulus of the retina causes trigerring of the HPA (response region) mediated by the activity of intermediate brain nuclei in a specific sequence of activation through two merging pathways (Pessoa and Adolphs, 2010;Bertini et al., 2013;Carr, 2015). A causal model relates the cause and effect, rather than recording correlation in the data and allows the investigator to answer a variety of queries such as associational queries (e.g., having observed activity in LGN, what activity can we expect in CeA?), abductive queries (e.g., what are highly plausible explanations for active CeA during fear stimulus?), and interventional queries (e.g., what will happen to the causal pathways if there is an ablation of VC?). ...
... Left: Literature describes two routes for fear stimulus propagation from Retina to HPA: Retina → LGN → VC → CeA → PVN → HPA (cortical route) and Retina →SC → P → CeA → PVN → HPA (subcortical route). Right: It is demonstrated that even if there is intervention by ablation or lesion in the striate cortex of VC, thereby blindness, yet fear response to visual stimuli ("blindsight") is yielded through the subcortical route (Morris et al., 1999;Carr, 2015). a causal relationship that holds between pairs of variables. ...
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Representation of brain network interactions is fundamental to the translation of neural structure to brain function. As such, methodologies for mapping neural interactions into structural models, i.e., inference of functional connectome from neural recordings, are key for the study of brain networks. While multiple approaches have been proposed for functional connectomics based on statistical associations between neural activity, association does not necessarily incorporate causation. Additional approaches have been proposed to incorporate aspects of causality to turn functional connectomes into causal functional connectomes, however, these methodologies typically focus on specific aspects of causality. This warrants a systematic statistical framework for causal functional connectomics that defines the foundations of common aspects of causality. Such a framework can assist in contrasting existing approaches and to guide development of further causal methodologies. In this work, we develop such a statistical guide. In particular, we consolidate the notions of associations and representations of neural interaction, i.e., types of neural connectomics, and then describe causal modeling in the statistics literature. We particularly focus on the introduction of directed Markov graphical models as a framework through which we define the Directed Markov Property—an essential criterion for examining the causality of proposed functional connectomes. We demonstrate how based on these notions, a comparative study of several existing approaches for finding causal functional connectivity from neural activity can be conducted. We proceed by providing an outlook ahead regarding the additional properties that future approaches could include to thoroughly address causality.
... In the context of neuroscience, causality is a major factor. For example, in fear perception in the human brain, the causal relationships Right: It is demonstrated that even if there is intervention by ablation or lesion in the striate cortex of VC, thereby blindness, yet fear response to visual stimuli ("blindsight") is yielded through the subcortical route [53,56]. ...
... While the information flows from the Retina to HPA, there is no direct link between them. Fear stimulus of the retina causes trigerring of the HPA (response region) mediated by the activity of intermediate brain nuclei in a specific sequence of activation through two merging pathways [53][54][55]. ...
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Representation of brain network interactions is fundamental to the translation of neural structure to brain function. As such, methodologies for mapping neural interactions into structural models, i.e., inference of functional connectome from neural recordings, are key for the study of brain networks. While multiple approaches have been proposed for functional connectomics based on statistical associations between neural activity, association does not necessarily incorporate causation. Additional approaches have been proposed to incorporate aspects of causality to turn functional connectomes into causal functional connectomes, however, these methodologies typically focus on specific aspects of causality. This warrants a systematic statistical framework for causal functional connectomics that defines the foundations of common aspects of causality. Such a framework can assist in contrasting existing approaches and to guide development of further causal methodologies. In this work, we develop such a statistical guide. In particular, we consolidate the notions of associations and representations of neural interaction, i.e., types of neural connectomics, and then describe causal modeling in the statistics literature. We particularly focus on the introduction of directed Markov graphical models as a framework through which we define the Directed Markov Property -- an essential criterion for examining the causality of proposed functional connectomes. We demonstrate how based on these notions, a comparative study of several existing approaches for finding causal functional connectivity from neural activity can be conducted. We proceed by providing an outlook ahead regarding the additional properties that future approaches could include to thoroughly address causality.
... Neonatal stress in mammals causes stable, long term alterations in the morphology of CRF neurons in brain areas involved with neuroendocrine and behavioral responses to stress (i.e., PVN, amygdala, bed nucleus of the stria terminalis -BNST, hippocampus, locus coeruleus) (Buschdorf and Meaney, 2016;Meaney, 2001). Comparative studies support that the functions of limbic structures in the stress response are conserved in tetrapods (Carr, 2015;Daviu et al., 2019;Yao and Denver, 2007;Yao et al., 2004Yao et al., , 2008aYao et al., , 2008b. The amygdala and BNST play central roles in fear and anxiety-related behaviors (Herman et al., 2005;Morgane et al., 2005;Schafe et al., 2005;Schulkin et al., 2005), and also influence neuroendocrine and autonomic functions (Herman et al., 2005;Morgane et al., 2005). ...
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The environment experienced by developing organisms can shape the timing and character of developmental processes, generating different phenotypes from the same genotype, each with different probabilities of survival and performance as adults. Chordates have two basic modes of development, indirect and direct. Species with indirect development, which includes most fishes and amphibians, have a complex life cycle with a free-swimming larva that is typically a growth stage, followed by a metamorphosis into the juvenile frog. Species with direct development, which is an evolutionarily derived developmental mode, develop directly from embryo to the juvenile without an intervening larval stage. Among the best studied species with complex life cycles are the amphibians, especially the anurans (frogs and toads). Amphibian tadpoles are exposed to diverse biotic and abiotic factors in their developmental habitat. They have extensive capacity for developmental plasticity, which can lead to the expression of different, adaptive morphologies as tadpoles (polyphenism), variation in the timing of and size at metamorphosis, and carry-over effects on the phenotype of the juvenile/adult. The neuroendocrine stress axis plays a pivotal role in mediating environmental effects on amphibian development. Before initiating metamorphosis, if tadpoles are exposed to predators they upregulate production of the stress hormone corticosterone (CORT), which acts directly on the tail to cause it to grow, thereby increasing escape performance. When tadpoles reach a minimum body size to initiate metamorphosis they can vary the timing of transformation in relation to growth opportunity or mortality risk in the larval habitat. They do this by modulating the production of thyroid hormone (TH), the primary inducer of metamorphosis, and CORT, which synergizes with TH to promote tissue transformation. Hypophysiotropic neurons that release the stress neurohormone corticotropin-releasing factor (CRF) are activated in response to environmental stress (e.g., pond drying, food restriction, etc.), and CRF accelerates metamorphosis by directly inducing secretion of pituitary thyrotropin and corticotropin, thereby increasing secretion of TH and CORT. Although activation of the neuroendocrine stress axis promotes immediate survival in a deteriorating larval habitat, costs may be incurred such as reduced tadpole growth and size at metamorphosis. Small size at transformation can impair performance of the adult, reducing probability of survival in the terrestrial habitat, or fecundity. Furthermore, elevations in CORT in the tadpole caused by environmental stressors cause long term, stable changes in neuroendocrine function, behavior and physiology of the adult, which can affect fitness. Comparative studies show that the roles of stress hormones in developmental plasticity are conserved across vertebrate taxa including humans.
... Accumulating evidence from animal experiments and neuroimaging studies has suggested sensory inputs reach the amygdala via two neural pathways: a subcortical 'low road' and a cortical 'high road' pathway. The low road pathway is thought to be fast and mainly involves subcortical brain regions such as the amygdala, superior colliculus, basal ganglia, and pulvinar ( Carr, 2015b ;Liddell et al., 2005 ;Pessoa and Adolphs, 2010 b). In contrast, the high road pathway is relatively slow and involves sensory and higher cortices ( Carr, 2015b ;Hariri et al., 2003 a;Williams et al., 2006 ). ...
... The low road pathway is thought to be fast and mainly involves subcortical brain regions such as the amygdala, superior colliculus, basal ganglia, and pulvinar ( Carr, 2015b ;Liddell et al., 2005 ;Pessoa and Adolphs, 2010 b). In contrast, the high road pathway is relatively slow and involves sensory and higher cortices ( Carr, 2015b ;Hariri et al., 2003 a;Williams et al., 2006 ). However, the activation patterns of brain regions in such two pathways for fear processing manifested by the neuroimaging technique have not been quantitatively scrutinized and summarized. ...
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Processing of fear is of crucial importance for human survival and it can generally occur at explicit and implicit conditions. It is worth noting that explicit and implicit fear processing produces different behavioral and neurophysiological outcomes. The present study capitalizes on the Activation Likelihood Estimation (ALE) method of meta-analysis to identify: (a) the “core” network of fear processing in healthy individuals; (b) common and specific neural activations associated with explicit and implicit processing of fear. Following PRISMA guidelines, a total of 92 fMRI and PET studies were included in the meta-analysis. The overall analysis show that the core fear network comprises the amygdala, pulvinar, and fronto-occipital regions. Both implicit and explicit fear processing activated amygdala, declive, fusiform gyrus, and middle frontal gyrus, suggesting that these two types of fear processing share a common neural substrate. Explicit fear processing elicited more activations at the pulvinar and parahippocampal gyrus, suggesting visual attention/orientation and contextual association play important roles during explicit fear processing. In contrast, implicit fear processing elicited more activations at the cerebellum-amygdala-cortical pathway, indicating an ‘alarm’ system underlying implicit fear processing. These findings have shed light on the neural mechanism underlying fear processing at different levels of awareness.
... As increasing complexity gave way to more sophisticated systems, a rich inventory of tasks could be performed, such as threat evaluation, decision making, coordinated physical responses, and advanced forms of learning. Evolution tends to build sophisticated processes out of and on top of simpler ones, and so the neural circuits associated with threat detection and avoidance lie in deep brain regions with many direct connections between sensory inputs and motor outputs that avoid passageway through the cerebral cortex (Carr, 2015). Functionally, this means that fear can be triggered without conscious input. ...
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This paper argues that specific phobia is an ideal kind of psychiatric disorder because it bears the marks of a mature medical diagnosis and is amenable to causal explanation. A new and ambitious program of 'causal revolution' has recently emerged in psychiatry that hopes to refurnish our taxonomies by discovering the underlying biological and psychological causes that create and maintain mental illness. I show that the sort of causal story envisioned by the program is a mechanistic property cluster (MPC) structure, which involves a causal mechanism that explains the co-occurrence of a disorder's signs and symptoms (Kendler, Zachar & Craver, 2011). I then build a model of fear in humans and sketch a novel account of specific phobia as a configuration of the fear system in thrall to deregulated network dynamics such as hysteresis, tipping points, and feedback loops. Specific phobia has an MPC structure. I close by reflecting on whether we can reasonably expect other mental disorders to fit an MPC mold, and thus lend themselves to future causal validation. This paper shows that specific phobia holds a unique place in our picture of mental disorder that has so far been missed. It is an ideal kind of psychopathology.
... The amygdala and other subcortical structures, such as the thalamus, provide examples of structures that are highly conserved across evolution 11 , and this allows informative comparisons between the human brain and the more accessible and manipulable brains of other species. Although rodents rely strongly on auditory and tactile stimuli, they also demonstrate freezing and escape behaviour to looming visual stimuli 12 (as do humans 13 ). ...
Article
The very earliest stages of sensory processing have the potential to alter how we perceive and respond to our environment. These initial processing circuits can incorporate subcortical regions, such as the thalamus and brainstem nuclei, which mediate complex interactions with the brain’s cortical processing hierarchy. These subcortical pathways, many of which we share with other animals, are not merely vestigial but appear to function as ‘shortcuts’ that ensure processing efficiency and preservation of vital life-preserving functions, such as harm avoidance, adaptive social interactions and efficient decision-making. Here, we propose that functional interactions between these higher-order and lower-order brain areas contribute to atypical sensory and cognitive processing that characterizes numerous neuropsychiatric disorders.
... On the low road, the superior colliculus directly mediates stimulus 27 responses in the amygdala. For threatening stimuli, the processing of stimuli may be 28 expedited, to allow for a rapid preparation of adaptive responses including physiological 29 changes, with amygdala at the apex of such processing (Morris, Öhman et al. 1999, Carr 2015 McFadyen, Mermillod et al. 2017). bioRxiv preprint In this study, we employed a conceptual hierarchy of complimentary methods and models to 1 study responses and interactions between the TP and the amygdala. ...
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The temporal pole (TP) is an associative cortical region required for complex cognitive functions such as social and emotional cognition. However, functional mapping of the TP with functional magnetic resonance imaging is technically challenging and thus understanding of its interaction with other key emotional circuitry, such as the amygdala, remain elusive. We exploited the unique advantages of stereo-electroencephalography (SEEG) to assess the responses of the TP and the amygdala during the perception of emotionally salient stimuli of pictures, music and movies. These stimuli consistently elicited high gamma responses (70-140 Hz) in both the TP and the amygdala, accompanied by functional connectivity in the low frequency range (2-12 Hz). Computational analyses suggested the TP driving this effect in the theta-alpha frequency range and which was modulated by the emotional salience of the stimuli. Of note, cross-frequency analysis indicated the phase of theta-alpha oscillations in the TP modulated the amplitude of high gamma activity in the amygdala. These results were reproducible with three types of stimuli including naturalistic stimuli suggesting a hierarchical influence of the TP over the amygdala in non-threatening stimuli.
... The SC, one of the subcortical visual areas, is phylogenetically old and might support innate visual recognition in vertebrates (Sewards and Sewards, 2002;Carr, 2015). Accumulating evidence from human neuropsychological studies suggests the existence of the subcortical face processing pathway, which consists of the SC, pulvinar, and amygdala (Tamietto and de Gelder, 2010;Rafal et al., 2015). ...
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Human babies respond preferentially to faces or face-like images. It has been proposed that an innate and rapid face detection system is present at birth before the cortical visual pathway is developed in many species, including primates. However, in primates, the visual area responsible for this process is yet to be unraveled. We hypothesized that the superior colliculus (SC) that receives direct and indirect retinal visual inputs may serve as an innate rapid face-detection system in primates. To test this hypothesis, we examined the responsiveness of monkey SC neurons to first-order information of faces required for face detection (basic spatial layout of facial features including eyes, nose, and mouth), by analyzing neuronal responses to line drawing images of: (1) face-like patterns with contours and properly placed facial features; (2) non-face patterns including face contours only; and (3) nonface random patterns with contours and randomly placed face features. Here, we show that SC neurons respond stronger and faster to upright and inverted face-like patterns compared to the responses to nonface patterns, regardless of contrast polarity and contour shapes. Furthermore, SC neurons with central receptive fields (RFs) were more selective to face-like patterns. In addition, the population activity of SC neurons with central RFs can discriminate face-like patterns from nonface patterns as early as 50 ms after the stimulus onset. Our results provide strong neurophysiological evidence for the involvement of the primate SC in face detection and suggest the existence of a broadly tuned template for face detection in the subcortical visual pathway.
... To respond to a threat, some animals can integrate incoming multiple modes of sensory stimuli. For example, many vertebrate animals integrate visual (reviewed by Carr, 2015), auditory (reviewed by May, 2006), and vibrational (lateral line in frogs, Hiramoto and Cline, 2009;whiskers in rats, Castro-Alamancos and Favero, 2016) stimuli before responding to a predator. Similarly most animals must integrate multiple modes of sensory stimuli to successfully capture live prey. ...
... In both rodents and primates, the SC connects with the periaqueductal gray (PAG), inferior colliculus, amygdala, and hypothalamus to form the brain's 'aversion system' (Brandao et al., 1999, Brandao et al., 2003Coimbra et al., 2006;Maior et al., 2012). As part of this central defense system, the SC not only elicits aversive behavior but activates the sympathetic nervous system response to an aversive stimulus or threat (Keay et al., 1988Iigaya et al., 2012;Carr, 2015). ...
... Across vertebrate species, the SC and the OT, the evolutionary homolog of the SC, possess numerous neuropeptides that may potentially modulate predator avoidance (Carr, 2015) and help to integrate information about eating vs. fleeing behavior. Neuropeptide Y (NPY) in the OT can suppress food intake when a predator is present (Schwippert and Ewert, 1995;Schwippert et al., 1998;Funke and Ewert, 2006), and recent work from our laboratory suggests a role for NPY2R receptors, in superficial layers of the OT, mediating predator avoidance behavior in frogs (Islam et al., 2019). ...
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Animals in the wild must balance food intake with vigilance for predators in order to survive. The optic tectum plays an important role in the integration of external (predators) and internal (energy status) cues related to predator defense and prey capture. However, the role of neuromodulators involved in tectal sensorimotor processing is poorly studied. Recently we showed that tectal CRFR1 receptor activation decreases food intake in the South African clawed frog, Xenopus laevis, suggesting that CRF may modulate food intake/predator avoidance tradeoffs. Here we use a behavioral assay modeling food intake and predator avoidance to test the role of CRFR1 receptors and energy status in this tradeoff. We tested the predictions that 1) administering the CRFR1 antagonist NBI-27914 via the optic tecta will increase food intake and feeding-related behaviors in the presence of a predator, and 2) that prior food deprivation, which lowers tectal CRF content, will increase food intake and feeding-related behaviors in the presence of a predator. Pre-treatment with NBI-27914 did not prevent predator-induced reductions in food intake. Predator exposure altered feeding-related behaviors in a predictable manner. Pretreatment with NBI-27914 reduced the response of certain behaviors to a predator but also altered behaviors irrelevant of predator presence. Although 1-wk of food deprivation altered some non-feeding behaviors related to energy conservation strategy, food intake in the presence of a predator was not altered by prior food deprivation. Collectively, our data support a role for tectal CRFR1 in modulating discrete behavioral responses during predator avoidance/foraging tradeoffs.
... According to tracing experiments in weakly electric fish, rainbow trout, carp, and goldfish, this diencephalic structure receives projections from the tectum and establishes connections with the dorsal pallium, which in turn closes the loop by sending axons to the tectum (brown in Fig. 4.5) (Echteler and Saidel, 1981;Luiten, 1981;Demski, 2003Demski, , 2013Folgueira et al., 2004;Ito, 2005, 2008;Northcutt, 2006;Yamamoto et al., 2007;Giassi et al., 2012aGiassi et al., , 2012b. These connections are reminiscent of the visual pathway involved in the visual escape responses triggered by looms in mice (Mueller, 2012;Zhao et al., 2014;Carr, 2015;Wei et al., 2015;Yuan and Sus, 2015;Perathoner et al., 2016;Pereira and Moita, 2016;Shang et al., 2018;Zhou et al., 2019) and that may be important in the processing of threatening visual stimuli in humans (McFadyen et al., 2017). Given the similarities to the amygdala's connectivity in mammals, it is tempting to think that the Dm may play a similar role in fish. ...
Chapter
Visual escape behavior is important for survival, and elements of this behavior are conserved from insects to humans. Because it needs to be robust and rapid, but also open to modulation, it is an excellent system in which to study visual processing and sensorimotor gating. Recent studies, especially in the transparent larvae of the zebrafish model system, have begun to shed light on the intricacies of visual escape circuitry, and in this chapter, we will review this progress. First, we will explore the essential properties of loom stimuli, including their movement, edges, and luminance changes, and will discuss how these stimulus properties, alone or in combination, can contribute to eliciting startle behavior. Next, we will describe the escape behavior itself, including the sequence of kinematic events that carries the animal away from the perceived threat and the various forms that this behavior can take depending on the stimulus and context. We will then provide an in-depth review of the core circuitry that lies between the stimulus and response, beginning with the retinal and thalamic projections that carry loom-relevant information to the tectum. We will also discuss how this information is likely to be processed in the tectum and the visuomotor projections to premotor cells in the hindbrain, including the well-known Mauthner neurons. Finally, we will describe ways in which context, such as alertness or hunger, can alter an animal's responses to threatening visual stimuli and the ways in which specific brain regions may detect these conditions and impinge on the core escape circuit to modulate behavior. We will conclude with perspectives on the important outstanding questions about visual escape circuits and specific experiments that might help in addressing them.