Mesoscopic-scale functional networks in the primate amygdala

Morrow, Jeremiah K; Cohen, Michael X; Gothard, Katalin M.

doi:10.7554/elife.57341

Cited by 10 publications

(5 citation statements)

References 60 publications

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“…This results in a single time series from each region, which was subjected to further analyses. We and others have shown that this method increases signal-to-noise characteristics while reducing computational costs and multiple-comparisons issues, and is more accurate than other sources separation methods such as principal components analysis and independent components analysis in M/EEG and LFP data (Haufe et al, 2014 ; de Cheveigné and Arzounian, 2015 ; Cohen, 2017a ; Morrow et al, 2020 ). An advantage of generalized eigendecomposition over independent components analysis is that it optimizes the spatial filter for narrowband activity, which was a primary goal here.…”

Section: Methodsmentioning

confidence: 91%

Beta2 Oscillations in Hippocampal-Cortical Circuits During Novelty Detection

França

Borgesius

Souza

et al. 2021

Front. Syst. Neurosci.

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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.

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Section: Methodsmentioning

confidence: 91%

Beta2 Oscillations in Hippocampal-Cortical Circuits During Novelty Detection

França

Borgesius

Souza

et al. 2021

Front. Syst. Neurosci.

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show abstract

“…Our classifiers are trained on data obtained from different subject and sessions when the linear probes recorded neural activity from different nuclear subdivisions of the amygdala. In fact, the classifiers do not generalize when applied to data obtained from other sessions, which was expected based previous work that mapped dissociable functions to different mesoscale subregions of the amygdala (Morrow et al, 2019). For the purpose of this paper, our (non-generalizable) approach was sufficient to conclude that contextual information is present in baseline LFP.…”

Section: Discussionmentioning

confidence: 72%

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

Aucoin,

Lin,

Gothard

2024

Preprint

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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.

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“…While less is known about interactions within the MTL, our data indicate that a similar mechanism might be used to coordinate information flow between the amygdala and hippocampus. The non-human primate amygdala contains multiple putative subnetworks indexed by distinct neural coactivity patterns that are characterized by different dominant frequencies in 0- to 20-Hz range ( 61 ).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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Mesoscopic-scale functional networks in the primate amygdala

Cited by 10 publications

References 60 publications

Beta2 Oscillations in Hippocampal-Cortical Circuits During Novelty Detection

Beta2 Oscillations in Hippocampal-Cortical Circuits During Novelty Detection

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

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

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