Projection from the Amygdala to the Thalamic Reticular Nucleus Amplifies Cortical Sound Responses

Aizenberg, Mark; Rolón‐Martínez, Solymar; Pham, Tuan D.; Rao, Winnie; Haas, Julie S.; Geffen, Maria N.

doi:10.1016/j.celrep.2019.10.036

Cited by 7 publications

(6 citation statements)

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“…A mechanism of TRN-based modification of thalamic synchrony to activate the cortex has been proposed previously [49] and is consistent with the finding that synchronized populations of thalamic neurons are required to optimally activate the cortex [25] and that the TRN is at the heart of a prefrontal cortex-based mechanism to shape cortical activation under changing cognitive demands [50][51][52]. Further, the TRN receives inputs from basal forebrain, amygdala and non-reciprocally linked regions of the thalamus [53][54][55][56][57][58][59][60][61], forming an assortment of inputs to potentially modulate TRN, and ultimately select cortical circuits for activation. Given the putative role of the TRN in the selection of thalamic, and therefore cortical circuits during sensory perception, one would predict that disruption of TRN activity could lead to uncontrolled release of patterns of cortical activity.…”

Section: Discussionsupporting

confidence: 76%

Corticothalamic gating of population auditory thalamocortical transmission in mouse

Ibrahim

Murphy

Yudintsev

et al. 2021

eLife

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The mechanisms that govern thalamocortical transmission are poorly understood. Recent data have shown that sensory stimuli elicit activity in ensembles of cortical neurons that recapitulate stereotyped spontaneous activity patterns. Here, we elucidate a possible mechanism by which gating of patterned population cortical activity occurs. In this study, sensory-evoked all-or-none cortical population responses were observed in the mouse auditory cortex in vivo and similar stochastic cortical responses were observed in a colliculo-thalamocortical brain slice preparation. Cortical responses were associated with decreases in auditory thalamic synaptic inhibition and increases in thalamic synchrony. Silencing of corticothalamic neurons in layer 6 (but not layer 5) or the thalamic reticular nucleus linearized the cortical responses, suggesting that layer 6 corticothalamic feedback via the thalamic reticular nucleus was responsible for gating stochastic cortical population responses. These data implicate a corticothalamic-thalamic reticular nucleus circuit that modifies thalamic neuronal synchronization to recruit populations of cortical neurons for sensory representations.

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Section: Discussionsupporting

confidence: 76%

Corticothalamic gating of population auditory thalamocortical transmission in mouse

Ibrahim

Murphy

Yudintsev

et al. 2021

eLife

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“…The first is the Emotional Exaggeration Hypothesis, which proposes that an effect of expectation on conscious perception is exaggerated for emotional stimuli (i.e., we "see what we expect to see" even more so if what we expect is dangerous). This may arise from amplification of affective sensory processing (Cornwell et al, 2017) via modulatory connections from amygdala to primary sensory cortices (Aizenberg et al, 2019;Chen et al, 2014), or a gain in amplitude due to increased precision of affective priors (Otten et al, 2017). In support of this hypothesis, previous studies have found neural activity evoked by surprise is larger and earlier for affective than neutral stimuli ( Vogel et al, 2015;Chen et al, 2017;Kovarski et al, 2017).…”

Section: Introductionmentioning

confidence: 77%

Surprising Threats Accelerate Conscious Perception

McFadyen

Tsuchiya

Mattingley

et al. 2022

Front. Behav. Neurosci.

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The folk psychological notion that “we see what we expect to see” is supported by evidence that we become consciously aware of visual stimuli that match our prior expectations more quickly than stimuli that violate our expectations. Similarly, “we see what we want to see,” such that more biologically-relevant stimuli are also prioritised for conscious perception. How, then, is perception shaped by biologically-relevant stimuli that we did not expect? Here, we conducted two experiments using breaking continuous flash suppression (bCFS) to investigate how prior expectations modulated response times to neutral and fearful faces. In both experiments, we found that prior expectations for neutral faces hastened responses, whereas the opposite was true for fearful faces. This interaction between emotional expression and prior expectations was driven predominantly by participants with higher trait anxiety. Electroencephalography (EEG) data collected in Experiment 2 revealed an interaction evident in the earliest stages of sensory encoding, suggesting prediction errors expedite sensory encoding of fearful faces. These findings support a survival hypothesis, where biologically-relevant fearful stimuli are prioritised for conscious access even more so when unexpected, especially for people with high trait anxiety.

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“…The model proposes that either MGB or AC or a combination of both can induce auditory fear memory through the strengthening of connections in the amygdala. We propose that feedback from auditory cortex to the MGB contributes to discrimination of perceptually similar pure tone stimuli during DFC by controlling stimulus discrimination in the MGB, this may or may not be a direct projection neuroanatomically 35,37,38 . Future studies need to explore the role of the MGB and specific projections between AC, MGB and BLA in fear learning and memory.…”

Section: Discussionmentioning

confidence: 99%

Neuronal activity in sensory cortex predicts the specificity of learning

Wood

Angeloni

Oxman

et al. 2020

Preprint

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Learning to avoid dangerous signals while preserving normal behavioral responses to safe stimuli is essential for everyday behavior and survival. Like other forms of learning, fear learning has a high level of inter-subject variability. Following an identical fear conditioning protocol, different subjects exhibit a range of fear specificity. Under high specificity, subjects specialize fear to only the paired (dangerous) stimulus, whereas under low specificity, subjects generalize fear to other (safe) sensory stimuli. Pathological fear generalization underlies emotional disorders, such as post-traumatic stress disorder. Despite decades of work, the neuronal basis that determines fear specificity level remains unknown. We identified the neuronal code that underlies variability in fear specificity. We performed longitudinal imaging of activity of neuronal ensembles in the auditory cortex of mice prior to and after the mice were subjected to differential fear conditioning. The neuronal code in the auditory cortex prior to learning predicted the level of specificity following fear learning across subjects. After fear learning, population neuronal responses were reorganized: the responses to the safe stimulus decreased, whereas the responses to the dangerous stimulus remained the same, rather than decreasing as in pseudo-conditioned subjects. The magnitude of these changes, however, did not correlate with learning specificity, suggesting that they did not reflect the fear memory. Together, our results identify a new, temporally restricted, function for cortical activity in associative learning. These results reconcile seemingly conflicting previous findings and provide for a neuronal code for determining individual patterns in learning. Results Experimental setupWhereas AC is involved in auditory fear conditioning, its role in the specificity of fear learning remains controversial. To establish the relationship between sound-evoked activity in the primary auditory cortex and differential fear conditioning (DFC), we recorded simultaneous neural activity from hundreds of neurons. We tracked the same neurons before and after DFC, using two-photon imaging of a virally expressed fluorescent calcium probe (GCaMP6 (Chen et al., 2013), Fig. 1). Longitudinal imaging of neuronal activity in large ensembles of neurons in AC before and after conditioning allowed us to compare the representation of the CS stimuli before and after learning ( Fig. 2A).We conditioned mice by exposure to a sequence of 10 repeats of two tones, one of which coterminated with a foot-shock (CS+, 15 kHz), and one which did not (CS-, 11.4kHz). Pseudo-conditioned mice were presented with the same stimuli (CS, 11.4 kHz and 15 kHz), but the foot-shock occurred during periods of silence between the stimuli (Fig. 2B). We measured recall of the fear memory by presenting the same stimuli to the mouse in a different context and measuring the % of time the mouse froze (Fig. 2C). Learning specificity was defined as a difference between freezing to CS+ and CS-during me...

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Projection from the Amygdala to the Thalamic Reticular Nucleus Amplifies Cortical Sound Responses

Cited by 7 publications

References 0 publications

Corticothalamic gating of population auditory thalamocortical transmission in mouse

Corticothalamic gating of population auditory thalamocortical transmission in mouse

Surprising Threats Accelerate Conscious Perception

Neuronal activity in sensory cortex predicts the specificity of learning

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