Valence coding in amygdala circuits

Abstract

The neural mechanisms underlying emotional valence are at the interface between perception and action, integrating inputs from the external environment with past experiences to guide the behavior of an organism. Depending on the positive or negative valence assigned to an environmental stimulus, the organism will approach or avoid the source of the stimulus. Multiple convergent studies have demonstrated that the amygdala complex is a critical node of the circuits assigning valence. Here we examine the current progress in identifying valence coding properties of neural populations in different nuclei of the amygdala, based on their activity, connectivity, and gene expression profile.

Figure 1

The amygdala complex and genetically identified populations. (a) Atlas of horizontal and coronal sections of the adult mouse brain highlighting the different nuclei of the amygdala. (b) Schematic of the different amygdala nuclei and identified genetic markers.

Figure 2

Valence coding and population biases. (a) Definition of nine classes of neurons depending on their response to stimuli of positive and negative valence [^●●]. In this classification neurons responding to both stimuli in a similar way (excitation or inhibition to both stimuli) do not encode valence. (b) Alternative classification of units including the amplitude of the response. In this case, neurons responding to both stimuli in a similar way also encode valence as they exhibit a stronger response to one valence [^●●,21]. (c) Multidimensional definition of neurons encoding valence. (d) Each line represents a neuronal population and every dot corresponds to a single neuron. A single feature defines populations with valence coding biases, and combining multiple features could potentially reveal valence selective populations.

Figure 3

Circuit diagram illustrating valence biases in BLA and CeA. (a) Optogenetic activation of three projection-defined BLA populations induces defensive behaviors [52,53,56] and activation of the last population induces appetitive behaviors [52,57,58] (b) Intra-amygdala circuit diagram of genetic populations in the anterior (a) and posterior (p) BLA, and CeA. Anterior BLA Rspo2+ and posterior BLA Ppp1r1b+ neurons drive opposite behavioral responses and reciprocally inhibit each other [^●●]. Rspo2+ neurons innervate CeC PKCδ⁺ neurons driving a defensive response. CeC PKCδ⁺ neurons inhibit CeL PKCδ⁺ neurons and Tac2+ CeM neurons, which mediate appetitive responses. Ppp1r1b+ neurons innervate all CeA neurons driving appetitive responses. CeC and CeL PKCδ⁺ neurons antagonize each other [^●●] (c) Recordings of BLA neurons defined by their projection have revealed coding biases for learned positive and negative valence. Although collateralization has been described at a population level, the relationship between collateralization pattern and valence coding at a single neuron level remains unknown.