Mesoscopic-scale functional networks in the primate amygdala

Comparative basolateral amygdala connectomics reveals dissociable single-neuron projection patterns to frontal cortex in macaques and mice

Basolateral amygdala (BLA) is a key hub for affect in the brain,1,2,3 and dysfunction within this area contributes to a host of psychiatric disorders.4,5 BLA is extensively and reciprocally interconnected with frontal cortex,6,7,8,9 and some aspects of its function are evolutionarily conserved across rodents, anthropoid primates, and humans.10 Neuron density in BLA is substantially lower in primates compared to murine rodents,11 and frontal cortex (FC) is dramatically expanded in primates, particularly the more anterior granular and dysgranular areas.12,13,14 Yet, how these anatomical differences influence the projection patterns of single BLA neurons to frontal cortex across rodents and primates is unknown. Using a barcoded connectomic approach, we assessed the single BLA neuron connections to frontal cortex in mice and macaques. We found that BLA neurons are more likely to project to multiple distinct parts of FC in mice than in macaques. Further, while single BLA neuron projections to nucleus accumbens were similarly organized in mice and macaques, BLA-FC connections differed substantially. Notably, BLA connections to subcallosal anterior cingulate cortex (scACC) in macaques were least likely to branch to other medial frontal cortex areas compared to perigenual ACC (pgACC). This pattern of connections was reversed in the mouse homologues of these areas, infralimbic and prelimbic cortex (IL and PL), mirroring functional differences between rodents and non-human primates. Taken together, these results indicate that BLA connections to FC are not linearly scaled from mice to macaques and instead the organization of single-neuron BLA connections is distinct between these species.

Detection of latent brain states from baseline neural activity in the amygdala

The amygdala responds to a large variety of socially and emotionally salient environmental and interoceptive stimuli. The context in which these stimuli occur determines their social and emotional significance. In canonical neurophysiological studies, the fast-paced succession of stimuli and events induce phasic changes in neural activity. During inter-trial intervals neural activity is expected to return to a stable and relatively featureless baseline. Context, such as the presence of a social partner, or the similarity of trials in a blocked design, induces brain states that can transcend the fast-paced succession of stimuli and can be recovered from the baseline firing rate of neurons. Indeed, the baseline firing rates of neurons in the amygdala change between blocks of trials of gentle grooming touch, delivered by a trusted social partner, and non-social airflow stimuli, delivered by a computer-controlled air valve. In this experimental paradigm, the presence of the groomer alone was sufficient to induce small but significant changes in baseline firing rates. Here, we examine local field potentials (LFP) recorded during these baseline periods to determine whether context was encoded by network dynamics that emerge in the local field potentials from the activity of large ensembles of neurons. We found that machine learning techniques can reliably decode social vs. non-social context from spectrograms of baseline local field potentials. Notably, decoding accuracy improved significantly with access to broad-band information. No significant differences were detected between the nuclei of the amygdala that receive direct or indirect inputs from areas of the prefrontal cortex known to coordinate flexible, context-dependent behaviors. The lack of nuclear specificity suggests that context-related synaptic inputs arise from a shared source, possibly interoceptive inputs that signal the sympathetic- vs. parasympathetic-dominated states characterizing non-social and social blocks, respectively.

A method for chronic and semi-chronic microelectrode array implantation in deep brain structures using image guided neuronavigation

BACKGROUND

Accurate targeting of brain structures for in-vivo electrophysiological recordings is essential for basic as well as clinical neuroscience research. Although methodologies for precise targeting and recording from the cortical surface are abundant, such protocols are scarce for deep brain structures.

NEW METHOD

We have incorporated stable fiducial markers within a custom cranial cap for improved image-guided neuronavigation targeting of subcortical structures in macaque monkeys. Anchor bolt chambers allowed for a minimally invasive entrance into the brain for chronic recordings. A 3D-printed microdrive allowed for semi-chronic applications.

RESULTS

We achieved an average Euclidean targeting error of 1.6 mm and a radial error of 1.2 mm over three implantations in two animals. Chronic and semi-chronic implantations allowed for recording of extracellular neuronal activity, with single-neuron activity examples shown from one macaque monkey.

COMPARISON WITH EXISTING METHOD(S)

Traditional stereotactic methods ignore individual anatomical variability. Our targeting approach allows for a flexible, subject-specific surgical plan with targeting errors lower than what is reported in humans, and equal to or lower than animal models using similar methods. Utilizing an anchor bolt as a chamber reduced the craniotomy size needed for electrode implantation, compared to conventional large access chambers which are prone to infection. Installation of an in-house, 3D-printed, screw-to-mount mechanical microdrive is in contrast to existing semi-chronic methods requiring fabrication, assembly, and installation of complex parts.

CONCLUSIONS

Leveraging commercially available tools for implantation, our protocol decreases the risk of infection from open craniotomies, and improves the accuracy of chronic electrode implantations targeting deep brain structures in large animal models.

Saccade-related neural communication in the human medial temporal lobe is modulated by the social relevance of stimuli

Humans predominantly explore their environment by moving their eyes. To optimally communicate and process visual information, neural activity needs to be coordinated with the execution of eye movements. We investigated the coordination between visual exploration and interareal neural communication by analyzing local field potentials and single neuron activity in patients with epilepsy. We demonstrated that during the free viewing of images, neural communication between the human amygdala and hippocampus is coordinated with the execution of eye movements. The strength and direction of neural communication and hippocampal saccade-related phase alignment were strongest for fixations that landed on human faces. Our results argue that the state of the human medial temporal lobe network is selectively coordinated with motor behavior. Interareal neural communication was facilitated for social stimuli as indexed by the category of the attended information.

Large-Scale and Multiscale Networks in the Rodent Brain during Novelty Exploration

Neural activity is coordinated across multiple spatial and temporal scales, and these patterns of coordination are implicated in both healthy and impaired cognitive operations. However, empirical cross-scale investigations are relatively infrequent, because of limited data availability and to the difficulty of analyzing rich multivariate datasets. Here, we applied frequency-resolved multivariate source-separation analyses to characterize a large-scale dataset comprising spiking and local field potential (LFP) activity recorded simultaneously in three brain regions (prefrontal cortex, parietal cortex, hippocampus) in freely-moving mice. We identified a constellation of multidimensional, inter-regional networks across a range of frequencies (2-200 Hz). These networks were reproducible within animals across different recording sessions, but varied across different animals, suggesting individual variability in network architecture. The theta band (∼4-10 Hz) networks had several prominent features, including roughly equal contribution from all regions and strong inter-network synchronization. Overall, these findings demonstrate a multidimensional landscape of large-scale functional activations of cortical networks operating across multiple spatial, spectral, and temporal scales during open-field exploration.

Beta2 Oscillations in Hippocampal-Cortical Circuits During Novelty Detection

Novelty detection is a core feature of behavioral adaptation and involves cascades of neuronal responses-from initial evaluation of the stimulus to the encoding of new representations-resulting in the behavioral ability to respond to unexpected inputs. In the past decade, a new important novelty detection feature, beta2 (~20-30 Hz) oscillations, has been described in the hippocampus (HC). However, the interactions between beta2 and the hippocampal network are unknown, as well as the role-or even the presence-of beta2 in other areas involved with novelty detection. In this work, we combined multisite local field potential (LFP) recordings with novelty-related behavioral tasks in mice to describe the oscillatory dynamics associated with novelty detection in the CA1 region of the HC, parietal cortex, and mid-prefrontal cortex. We found that transient beta2 power increases were observed only during interaction with novel contexts and objects, but not with familiar contexts and objects. Also, robust theta-gamma phase-amplitude coupling was observed during the exploration of novel environments. Surprisingly, bursts of beta2 power had strong coupling with the phase of delta-range oscillations. Finally, the parietal and mid-frontal cortices had strong coherence with the HC in both theta and beta2. These results highlight the importance of beta2 oscillations in a larger hippocampal-cortical circuit, suggesting that beta2 plays a role in the mechanism for detecting and modulating behavioral adaptation to novelty.