The role of the basolateral amygdala in the perception of faces in natural contexts

Hortensius, Ruud; Terburg, David; Morgan, Barak; Stein, Dan J.; Honk, Jack van; Gelder, Béatrice de

doi:10.1098/rstb.2015.0376

Cited by 26 publications

(23 citation statements)

References 89 publications

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“…BLA connections to primary visual cortex are reported in primates 61,62 although, to our knowledge, not in mice. The relevance of these connections are apparent in the context of primate 63,64 and human 65 studies showing BLA involvement in the processing of facial expressions; however, they may also be relevant in rodents.…”

Section: Blaam Neurons and Visual And Spatial Informationmentioning

confidence: 98%

Connectivity characterization of the mouse basolateral amygdalar complex

Hintiryan

Bowman

Johnson

et al. 2019

Preprint

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The basolateral amygdalar complex (BLA) is implicated in behavioral processing ranging from fear acquisition to addiction. Newer methods like optogenetics have enabled the association of circuitspecific functionality to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. In this work, we applied computational analysis techniques to the results of our circuittracing experiments to create a foundational, comprehensive, multiscale connectivity atlas of the mouse BLA. The analyses identified three domains within the classically defined anterior BLA (BLAa) that house target-specific projection neurons with distinguishable cell body and dendritic morphologies. Further, we identify brain-wide targets of projection neurons located in the three BLAa domains as well as in the posterior BLA (BLAp), ventral BLA (BLAv), lateral (LA), and posterior basomedial (BMAp) nuclei. Projection neurons that provide input to each nucleus are also identifed. Functional characterization of some projection-defined BLA neurons were demonstrated via optogenetic and recording experiments. Hypotheses relating function to connection-defined BLA cell types are proposed. rACAd, Anterior cingulate cortical area, dorsal part, rostral region cACAd, Anterior cingulate cortical area, dorsal part, caudal region ACAv, Anterior cingulate cortical area, ventral part rACAv, Anterior cingulate cortical area, ventral part, rostral region cACAv, Anterior cingulate cortical area, ventral part, caudal region ACB, Nucleus accumbens AD, Anterodorsal nucleus of the thalamus ADP, Anterodorsal preoptic nucleus of the hypothalamus AHN, Anterior hypothalamic nucleus AI, Agranular insular cortical area AId, Agranular insular cortical area, dorsal part AIv, Agranular insular cortical area, ventral part AIv, Agranular insular cortical area, posterior part AM, Anteromedial nucleus of the thalamus AMd, Anteromedial nucleus of the thalamus, dorsal part AMv, Anteromedial nucleus of the thalamus, ventral part AON, Anterior olfactory nucleus AONm, Anterior olfactory nucleus, medial part AONpv, Anterior olfactory nucleus, posteroventral part ARH, Arcuate hypothalamic nucleus AUD, Auditory cortical area AUDd, Dorsal auditory cortical area AUDp, Primary auditory cortical area AUDv, Ventral auditory cortical area AV, Anteroventral nucleus of the thalamus AVP, Anteroventral preoptic nucleus AVPV, Anteroventral periventricular nucleus bic, Brachium of the inferior colliculus BLA, Basolateral amygdalar complex BLAa, Basolateral amygdalar nucleus, anterior part BLA.am, Basolateral amydalar nucleus, anterior part, medial domain BLA.al, Basolateral amydalar nucleus, anterior part, lateral domain BLA.ac, Basolateral amydalar nucleus, anterior part, caudal domain BLAp, Basolateral amygdalar nucleus, posterior part BLAv, Basolateral amygdalar nucleus, ventral part BMA, Basomedial amygdalar nucleus BMAa, Basomedial amygdalar nucleus, anterior part BMAp, Basomedial...

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Section: Blaam Neurons and Visual And Spatial Informationmentioning

confidence: 98%

Connectivity characterization of the mouse basolateral amygdalar complex

Hintiryan

Bowman

Johnson

et al. 2019

Preprint

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“…In humans, the amygdala as a whole is thought to play a key role in emotional and social cognitive processes (e.g. Adolphs et al, 2005, Kliemann et al 2012, Hortensius et al, 2016), and accordingly, its dysfunction is implicated in psychopathologies, such as mood disorders (Phillips et al, 2003; Siegle et al, 2002), anxiety disorders (Birbaumer et al, 1998; Rauch et al, 2003), and developmental disorders (Baron-Cohen et al, 2000; Dziobek et al, 2010). Additionally, several post mortem studies have shown that the amygdala is a common site for neurofibrillary tangles and senile plaques in mild cognitive impairment (Merkesbery, 2010) and Alzheimer’s disease (Yilmazer-Hanke, 1998) as well as Lewy bodies (Kotzbauer et al, 2011, Fujishiro et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas

et al. 2017

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The amygdala is composed of multiple nuclei with unique functions and connections in the limbic system and to the rest of the brain. However, standard in vivo neuroimaging tools to automatically delineate the amygdala into its multiple nuclei are still rare. By scanning postmortem specimens at high resolution (100–150μm) at 7T field strength (n = 10), we were able to visualize and label nine amygdala nuclei (anterior amygdaloid, cortico-amygdaloid transition area; basal, lateral, accessory basal, central, cortical medial, paralaminar nuclei). We created an atlas from these labels using a recently developed atlas building algorithm based on Bayesian inference. This atlas, which will be released as part of FreeSurfer, can be used to automatically segment nine amygdala nuclei from a standard resolution structural MR image. We applied this atlas to two publicly available datasets (ADNI and ABIDE) with standard resolution T1 data, used individual volumetric data of the amygdala nuclei as the measure and found that our atlas i) discriminates between Alzheimer’s disease participants and age-matched control participants with 84% accuracy (AUC=0.915), and ii) discriminates between individuals with autism and age-, sex- and IQ-matched neurotypically developed control participants with 59.5% accuracy (AUC=0.59). For both datasets, the new ex vivo atlas significantly outperformed (all p < .05) estimations of the whole amygdala derived from the segmentation in FreeSurfer 5.1 (ADNI: 75%, ABIDE: 54% accuracy), as well as classification based on whole amygdala volume (using the sum of all amygdala nuclei volumes; ADNI: 81%, ABIDE: 55% accuracy). This new atlas and the segmentation tools that utilize it will provide neuroimaging researchers with the ability to explore the function and connectivity of the human amygdala nuclei with unprecedented detail in healthy adults as well as those with neurodevelopmental and neurodegenerative disorders.

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“…Application of this technique is relatively easy and does not require considerable load of effort or time. Thus, it has been extensively used in research on the role of the amygdala subregions in facial emotion perception (Hurlemann et al 2008, Barbour et al 2010, Hortensius et al 2016, auditory stimulation with pleasant and unpleasant music excerpts (Ball et al 2007) and emotional voices (Frühholz and Grandjean 2013) or perceiving social cues (Freeman et al 2014). However, as critically pointed by Prévost and colleagues (2011), the probabilistic maps might not be applicable for the studies with younger sample than the one used in the study by Amunts and colleagues due to extensive age-related changes in structure of the brain.…”

Section: Parcellation Of the Amygdalamentioning

confidence: 99%

Functional organization of the human amygdala in appetitive learning

Kolada¹,

Bielski²,

Falkiewicz³

et al. 2017

Acta Neurobiologiae Experimentalis

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The amygdala is a small subcortical structure located bilaterally in medial temporal lobes. It is a key region for emotional processes and some forms of associative learning. In particular, the role of the amygdala in processing of negative emotions and aversive learning has been shown in numerous studies. However, involvement of this structure in processing of positive affect and appetitive learning is not fully understood. Previous experiments in animals are not consistent. While some authors implicate only the centromedial part of the amygdala in appetitive learning, the others suggest contribution of both centromedial and basolateral subregions. Although from the evolutionary perspective appetitive learning is equally important as aversive learning, research on the role of the human amygdala and its subregions in appetitive learning is undertaken relatively rarely and the results are not conclusive. Therefore, the aim of this review is twofold: to summarize the current knowledge in this field and to indicate and discuss the factors, which might affect the observed level of the amygdala activity during appetitive learning in humans.

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The role of the basolateral amygdala in the perception of faces in natural contexts

Cited by 26 publications

References 89 publications

Connectivity characterization of the mouse basolateral amygdalar complex

Connectivity characterization of the mouse basolateral amygdalar complex

High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas

Functional organization of the human amygdala in appetitive learning

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