Sensory-thresholded switch of neural firing states in a computational model of the ventromedial hypothalamus

The mouse ventromedial hypothalamus (VMH) is both necessary and sufficient for defensive responses to predator and social threats. Defensive behaviors typically involve cautious approach toward potentially threatening stimuli aimed at obtaining information about the risk involved, followed by sudden avoidance and flight behavior to escape harm. In vivo neural recording studies in mice have identified two major populations of VMH neurons that either increase their firing activity as the animal approaches the threat (called Assessment+ cells) or increase their activity as the animal flees the threat (called Flight+ cells). Interestingly, Assessment+ and Flight+ cells abruptly decrease and increase their firing activity, respectively, at the decision point for flight, creating an escape-related “switch” in functional state. This suggests that the activity of the two cell types in VMH is coordinated and could result from local circuit interactions. Here, we used computational modelling to test if a local inhibitory feedback circuit could give rise to key features of the neural activity seen in VMH during the approach-to-flight transition. Starting from a simple dual-population inhibitory feedback circuit receiving repeated trains of monotonically increasing sensory input to mimic approach to threat, we tested the requirement for balanced sensory input, balanced feedback, short-term synaptic plasticity, rebound excitation, and inhibitory feedback exclusivity to reproduce an abrupt, sensory-thresholded reciprocal firing change that resembles Assessment+ and Flight+ cell activity seen in vivo. Our work demonstrates that a relatively simple local circuit architecture is sufficient for the emergence of firing patterns similar to those seen in vivo and suggests that a reiterative process of experimental and computational work may be a fruitful avenue for better understanding the functional organization of mammalian instinctive behaviors at the circuit level.

Optogenetic study of central medial and paraventricular thalamic projections to the basolateral amygdala

The central medial (CMT) and paraventricular (PVT) thalamic nuclei project strongly to the basolateral amygdala (BL). Similarities between the responsiveness of CMT, PVT, and BL neurons suggest that these nuclei strongly influence BL activity. Supporting this possibility, an electron microscopic study reported that in contrast with other extrinsic afferents, CMT and PVT axon terminals form very few synapses with BL interneurons. However, since limited sampling is a concern in electron microscopic studies, the present investigation was undertaken to compare the impact of CMT and PVT thalamic inputs on principal and local-circuit BL neurons using optogenetic methods and whole-cell recordings in vitro. Optogenetic stimulation of CMT and PVT axons elicited glutamatergic EPSPs or EPSCs in principal cells and interneurons, but they generally had a longer latency in interneurons. Moreover, after blockade of polysynaptic interactions with tetrodotoxin (TTX), a lower proportion of interneurons (50%) than principal cells (90%) remained responsive to CMT and PVT inputs. While the presence of TTX-resistant responses in some interneurons indicates that CMT and PVT inputs directly contact some local-circuit cells, their lower incidence and amplitude after TTX suggest that CMT and PVT inputs form fewer synapses with them than with principal BL cells. Together, these results indicate that CMT and PVT inputs mainly contact principal BL neurons such that when CMT or PVT neurons fire, limited feed-forward inhibition counters their excitatory influence over principal BL cells. However, CMT and PVT axons can also recruit interneurons indirectly, via the activation of principal cells, thereby generating feedback inhibition.

Local circuit allowing hypothalamic control of hippocampal area CA2 activity and consequences for CA1

The hippocampus is critical for memory formation. The hypothalamic supramammillary nucleus (SuM) sends long-range projections to hippocampal area CA2. While the SuM-CA2 connection is critical for social memory, how this input acts on the local circuit is unknown. Using mice, we found that SuM axon stimulation elicited mixed excitatory and inhibitory responses in area CA2 pyramidal neurons (PNs). Parvalbumin-expressing basket cells were largely responsible for the feedforward inhibitory drive of SuM over area CA2. Inhibition recruited by the SuM input onto CA2 PNs increased the precision of action potential firing both in conditions of low and high cholinergic tone. Furthermore, SuM stimulation in area CA2 modulated CA1 activity, indicating that synchronized CA2 output drives a pulsed inhibition in area CA1. Hence, the network revealed here lays basis for understanding how SuM activity directly acts on the local hippocampal circuit to allow social memory encoding.

Cellular connectomes as arbiters of local circuit models in the cerebral cortex

With the availability of cellular-resolution connectivity maps, connectomes, from the mammalian nervous system, it is in question how informative such massive connectomic data can be for the distinction of local circuit models in the mammalian cerebral cortex. Here, we investigated whether cellular-resolution connectomic data can in principle allow model discrimination for local circuit modules in layer 4 of mouse primary somatosensory cortex. We used approximate Bayesian model selection based on a set of simple connectome statistics to compute the posterior probability over proposed models given a to-be-measured connectome. We find that the distinction of the investigated local cortical models is faithfully possible based on purely structural connectomic data with an accuracy of more than 90%, and that such distinction is stable against substantial errors in the connectome measurement. Furthermore, mapping a fraction of only 10% of the local connectome is sufficient for connectome-based model distinction under realistic experimental constraints. Together, these results show for a concrete local circuit example that connectomic data allows model selection in the cerebral cortex and define the experimental strategy for obtaining such connectomic data.

Anatomical and Functional Gradients Shape Dynamic Functional Connectivity in the Human Brain

Large-scale biophysical circuit models can provide mechanistic insights into the fundamental micro-scale and macro-scale properties of brain organization that shape complex patterns of spontaneous brain activity. By allowing local synaptic properties to vary across brain regions, recent large-scale circuit models have demonstrated better fit to empirical observations, such as inter-regional synchrony averaged over several minutes, i.e. static functional connectivity (FC). However, most previous models do not capture how inter-regional synchrony patterns vary over timescales of seconds, i.e., time-varying FC dynamics. Here we developed a spatially-heterogeneous large-scale dynamical circuit model that allowed for variation in local circuit properties across the human cortex. We showed that parameterizing local circuit properties with both anatomical and functional gradients was necessary for generating realistic static and dynamical properties of resting-state fMRI activity. Furthermore, empirical and simulated FC dynamics demonstrated remarkably similar sharp transitions in FC patterns, suggesting the existence of multiple attractors. We found that time-varying regional fMRI amplitude tracked multi-stability in FC dynamics. Causal manipulation of the large-scale circuit model suggested that sensory-motor regions were a driver of FC dynamics. Finally, the spatial distribution of sensory-motor drivers matched the principal gradient of gene expression that encompassed certain interneuron classes, suggesting that heterogeneity in excitation-inhibition balance might shape multi-stability in FC dynamics.

Dual color mesoscopic imaging reveals spatiotemporally heterogeneous coordination of cholinergic and neocortical activity

Acetylcholine (ACh) is associated with the modulation of brain activity linked to arousal, attention, and emotional valence. We performed dual-color mesoscopic imaging of ACh and calcium across the neocortex of awake mice to investigate the spatiotemporal dynamics of cholinergic signaling and their relationship to cortical output. We find distinct movement-defined behavioral states are represented in spatially heterogeneous cholinergic networks that are differentially coupled to fluctuations in local circuit activity.

Local circuit allowing hypothalamic control of hippocampal area CA2 activity and consequences for CA1

The hippocampus is critical for memory formation. The hypothalamic supramammillary nucleus (SuM) sends long-range projections to hippocampal area CA2. While the SuM-CA2 connection is critical for social memory, how this input acts on the local circuit is unknown. We found that SuM axon stimulation elicited mixed excitatory and inhibitory responses in area CA2 pyramidal neurons (PNs). We found that parvalbumin-expressing basket cells as responsible for the feedforward inhibitory drive of SuM over area CA2. Inhibition recruited by the SuM input onto CA2 PNs increased the precision of action potential firing both in conditions of low and high cholinergic tone. Furthermore, SuM stimulation in area CA2 modulates CA1 activity, indicating that synchronized CA2 output drives a pulsed inhibition in area CA1. Hence, the network revealed here lays basis for understanding how SuM activity directly acts on the local hippocampal circuit to allow social memory encoding.