Oscillatory correlates of threat imminence during virtual navigation.

The Predatory Imminence Continuum Theory proposes that defensive behaviors depend on the proximity of a threat. While the neural mechanisms underlying this proposal are well studied in animal models, it remains poorly understood in humans. To address this issue, we recorded EEG from 24 (15 female) young adults engaged in a first-person virtual reality Risk-Reward interaction task. On each trial, participants were placed in a virtual room and presented with either a threat or reward conditioned stimulus (CS) in the same room location (proximal) or different room location (distal). Behaviorally, all participants learned to avoid the threat-CS, with most using the optimal behavior to actively avoid the proximal threat-CS (88% accuracy) and passively avoid the distal threat-CS (69% accuracy). Similarly, participants learned to actively approach the distal reward-CS (82% accuracy) and to remain passive to the proximal reward-CS (72% accuracy). At an electrophysiological level, we observed a general increase in theta power (4-8 Hz) over the right posterior channel P8 across all conditions, with the proximal threat-CS evoking the largest theta response. By contrast, distal cues induced two bursts of gamma (30-60 Hz) power over midline-parietal channel Pz (200 msec post-cue) and right frontal channel Fp2 (300 msec post-cue). Interestingly, the first burst of gamma power was sensitive to the distal threat-CS and the second burst at channel Fp2 was sensitive to the distal reward-CS. Together, these findings demonstrate that oscillatory processes differentiate between the spatial proximity information during threat and reward encoding, likely optimizing the selection of the appropriate behavioral response.

Approaches to characterizing oscillatory burst detection algorithms for electrophysiological recordings.

BACKGROUND: Cognitive processes are associated with fast oscillations of the local field potential and electroencephalogram. There is a growing interest in targeting them because these are disrupted by aging and disease. This has proven challenging because they often occur as short-lasting bursts. Moreover, they are obscured by broad-band aperiodic activity reflecting other neural processes. These attributes have made it exceedingly difficult to develop analytical tools for estimating the reliability of detection methods. NEW METHOD: To address this challenge, we developed an open-source toolkit with four processing steps, that can be tailored to specific brain states and individuals. First, the power spectrum is decomposed into periodic and aperiodic components, each of whose properties are estimated. Second, the properties of the transient oscillatory bursts that contribute to the periodic component are derived and optimized to account for contamination from the aperiodic component. Third, using the burst properties and aperiodic power spectrum, surrogate neural signals are synthesized that match the observed signal's spectrotemporal properties. Lastly, oscillatory burst detection algorithms run on the surrogate signals are subjected to a receiver operating characteristic analysis, providing insight into their performance. RESULTS: The characterization algorithm extracted features of oscillatory bursts across multiple frequency bands and brain regions, allowing for recording-specific evaluation of detection performance. For our dataset, the optimal detection threshold for gamma bursts was found to be lower than the one commonly used. COMPARISON WITH EXISTING METHODS: Existing methods characterize the power spectrum, while ours evaluates the detection of oscillatory bursts. CONCLUSIONS: This pipeline facilitates the evaluation of thresholds for detection algorithms from individual recordings.

The amygdala mediates the facilitating influence of emotions on memory through multiple interacting mechanisms.

Emotionally arousing experiences are better remembered than neutral ones, highlighting that memory consolidation differentially promotes retention of experiences depending on their survival value. This paper reviews evidence indicating that the basolateral amygdala (BLA) mediates the facilitating influence of emotions on memory through multiple mechanisms. Emotionally arousing events, in part by triggering the release of stress hormones, cause a long-lasting enhancement in the firing rate and synchrony of BLA neurons. BLA oscillations, particularly gamma, play an important role in synchronizing the activity of BLA neurons. In addition, BLA synapses are endowed with a unique property, an elevated post-synaptic expression of NMDA receptors. As a result, the synchronized gamma-related recruitment of BLA neurons facilitates synaptic plasticity at other inputs converging on the same target neurons. Given that emotional experiences are spontaneously remembered during wake and sleep, and that REM sleep is favorable to the consolidation of emotional memories, we propose a synthesis for the various lines of evidence mentioned above: gamma-related synchronized firing of BLA cells potentiates synapses between cortical neurons that were recruited during an emotional experience, either by tagging these cells for subsequent reactivation or by enhancing the effects of reactivation itself.

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 with optogenetic methods and whole cell recordings in vitro. Optogenetic stimulation of CMT and PVT axons elicited glutamatergic excitatory postsynaptic potentials (EPSPs) or excitatory postsynaptic currents (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. Although 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 feedforward 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.NEW & NOTEWORTHY Midline thalamic (MTh) nuclei contribute major projections to the basolateral amygdala (BL). Similarities between the responsiveness of MTh and BL neurons suggest that MTh neurons exert a significant influence over BL activity. Using optogenetic techniques, we show that MTh inputs mainly contact principal BL neurons such that when MTh neurons fire, little feedforward inhibition counters their excitatory influence over principal cells. Thus, MTh inputs may be major determinants of BL activity.

Gamma oscillations in the basolateral amygdala: localization, microcircuitry, and behavioral correlates.

The lateral (LA) and basolateral (BL) nuclei of the amygdala regulate emotional behaviors. Despite their dissimilar extrinsic connectivity, they are often combined, perhaps because their cellular composition is similar to that of the cerebral cortex, including excitatory principal cells reciprocally connected with fast-spiking interneurons (FSIs). In the cortex, this microcircuitry produces gamma oscillations that support information processing and behavior. We tested whether this was similarly the case in the rat (males) LA and BL using extracellular recordings, biophysical modeling, and behavioral conditioning. During periods of environmental assessment, both nuclei exhibited gamma oscillations that stopped upon initiation of active behaviors. Yet, BL exhibited more robust spontaneous gamma oscillations than LA. The greater propensity of BL to generate gamma resulted from several microcircuit differences, especially the proportion of FSIs and their interconnections with principal cells. Furthermore, gamma in BL but not LA regulated the efficacy of excitatory synaptic transmission between connected neurons. Together, these results suggest fundamental differences in how LA and BL operate. Most likely, gamma in LA is externally driven whereas in BL, it can also arise spontaneously to support ruminative processing and the evaluation of complex situations.SIGNIFICANCE STATEMENT:The basolateral amygdala (BLA) participates in the production and regulation of emotional behaviors. It is thought to perform this using feedforward circuits that enhance stimuli that gain emotional significance and directs them to valence-appropriate downstream effectors. This perspective overlooks the fact that its microcircuitry is recurrent and potentially capable of generating oscillations in the gamma band (50-80 Hz), which synchronize spiking activity and modulate communication between neurons. This study found that BLA gamma supports both these processes, is associated with periods of action selection and environmental assessment irrespective of valence, and differs between BLA subnuclei in a manner consistent with their heretofore unknown microcircuit differences. Thus, it provides new mechanisms for BLA to support emotional behaviors.

Inferring Morphology of a Neuron from In Vivo LFP Data.

We propose a computational pipeline that uses biophysical modeling and sequential neural posterior estimation algorithm to infer the position and morphology of single neurons using multi-electrode in vivo extracellular voltage recordings. In this inverse modeling scheme, we designed a generic biophysical single neuron model with stylized morphology that had adjustable parameters for the dimensions of the soma, basal and apical dendrites, and their location and orientations relative to the multi-electrode probe. Preliminary results indicate that the proposed methodology can infer up to eight neuronal parameters well. We highlight the issues involved in the development of the novel pipeline and areas for further improvement.

Model neocortical microcircuit supports beta and gamma rhythms.

Gamma and beta rhythms in neocortical circuits are thought to be caused by distinct subcircuits involving different type of interneurons. However, it is not clear how these distinct but inter-linked intrinsic circuits interact with afferent drive to engender the two rhythms. We report a biophysical computational model to investigate the hypothesis that tonic and phasic drive might engender beta and gamma oscillations, respectively, in a neocortical circuit.

Different Multidimensional Representations across the Amygdalo-Prefrontal Network during an Approach-Avoidance Task.

The prelimbic (PL) area and basolateral amygdala (lateral [LA] and basolateral [BL] nuclei) have closely related functions and similar extrinsic connectivity. Reasoning that the computational advantage of such redundancy should be reflected in differences in how these structures represent information, we compared the coding properties of PL and amygdala neurons during a task that requires rats to produce different conditioned defensive or appetitive behaviors. Rather than unambiguous regional differences in the identities of the variables encoded, we found gradients in how the same variables are represented. Whereas PL and BL neurons represented many different parameters through minor variations in firing rates, LA cells coded fewer task features with stronger changes in activity. At the population level, whereas valence could be easily distinguished from amygdala activity, PL neurons could distinguish both valence and trial identity as well as or better than amygdala neurons. Thus, PL has greater representational capacity.

Space, Time, and Fear: Survival Computations along Defensive Circuits.

Naturalistic observations show that decisions to avoid or escape predators occur at different spatiotemporal scales and that they are supported by different computations and neural circuits. At their extremes, proximal threats are addressed by a limited repertoire of reflexive and myopic actions, reflecting reduced decision and state spaces and model-free (MF) architectures. Conversely, distal threats allow increased information processing supported by model-based (MB) operations, including affective prospection, replay, and planning. However, MF and MB computations are often intertwined, and under conditions of safety the foundations for future effective reactive execution can be laid through MB instruction of MF control. Together, these computations are associated with distinct population codes embedded within a distributed defensive circuitry whose goal is to determine and realize the best policy.

Advancing functional connectivity research from association to causation.

Cognition and behavior emerge from brain network interactions, such that investigating causal interactions should be central to the study of brain function. Approaches that characterize statistical associations among neural time series-functional connectivity (FC) methods-are likely a good starting point for estimating brain network interactions. Yet only a subset of FC methods ('effective connectivity') is explicitly designed to infer causal interactions from statistical associations. Here we incorporate best practices from diverse areas of FC research to illustrate how FC methods can be refined to improve inferences about neural mechanisms, with properties of causal neural interactions as a common ontology to facilitate cumulative progress across FC approaches. We further demonstrate how the most common FC measures (correlation and coherence) reduce the set of likely causal models, facilitating causal inferences despite major limitations. Alternative FC measures are suggested to immediately start improving causal inferences beyond these common FC measures.

Closed-loop control of gamma oscillations in the amygdala demonstrates their role in spatial memory consolidation.

Gamma is a ubiquitous brain rhythm hypothesized to support cognitive, perceptual, and mnemonic functions by coordinating neuronal interactions. While much correlational evidence supports this hypothesis, direct experimental tests have been lacking. Since gamma occurs as brief bursts of varying frequencies and durations, most existing approaches to manipulate gamma are either too slow, delivered irrespective of the rhythm's presence, not spectrally specific, or unsuitable for bidirectional modulation. Here, we overcome these limitations with an approach that accurately detects and modulates endogenous gamma oscillations, using closed-loop signal processing and optogenetic stimulation. We first show that the rat basolateral amygdala (BLA) exhibits prominent gamma oscillations during the consolidation of contextual memories. We then boost or diminish gamma during consolidation, in turn enhancing or impairing subsequent memory strength. Overall, our study establishes the role of gamma oscillations in memory consolidation and introduces a versatile method for studying fast network rhythms in vivo.

Embracing Complexity in Defensive Networks.

The neural basis of defensive behaviors continues to attract much interest, not only because they are important for survival but also because their dysregulation may be at the origin of anxiety disorders. Recently, a dominant approach in the field has been the optogenetic manipulation of specific circuits or cell types within these circuits to dissect their role in different defensive behaviors. While the usefulness of optogenetics is unquestionable, we argue that this method, as currently applied, fosters an atomistic conceptualization of defensive behaviors, which hinders progress in understanding the integrated responses of nervous systems to threats. Instead, we advocate for a holistic approach to the problem, including observational study of natural behaviors and their neuronal correlates at multiple sites, coupled to the use of optogenetics, not to globally turn on or off neurons of interest, but to manipulate specific activity patterns hypothesized to regulate defensive behaviors.

Basolateral amygdala neurons are activated during threat expectation.

Fear conditioning studies have led to the view that the amygdala contains neurons that signal threat and in turn elicit defensive behaviors through their brain stem and hypothalamic targets. In agreement with this model, a prior unit-recording study in rats performing a seminaturalistic foraging task revealed that many lateral amygdala (LA) neurons are predator responsive. In contrast, our previous study emphasized that most basolateral (BL) amygdala neurons are inhibited at proximity of the predator. However, the two studies used different methods to analyze unit activity, complicating comparisons between them. By applying the same method to the sample of BL neurons we recorded previously, the present study revealed that most principal cells are inhibited by the predator and only 4.5% are activated. Moreover, two-thirds of these cells were also activated by nonthreatening stimuli. In fact, fitting unit activity with a generalized linear model revealed that the only task variables associated with a prevalent positive modulation of BL activity were expectation of the predator's presence and whether the prior trial had been a failure or success. At odds with the threat-coding model of the amygdala, actual confrontation with the predator was usually associated with a widespread inhibition of principal BL neurons. NEW & NOTEWORTHY The basolateral amygdala (BL) is thought to contain neurons that signal threat, in turn eliciting defensive behaviors. In contrast, the present study reports that very few principal BL cells are responsive to threats and that most of them are also activated by nonthreatening stimuli. Yet, expectation of the threat's presence was associated with a prevalent positive modulation of BL activity; actual confrontation with the threat was associated with a widespread inhibition.

Gamma Oscillations in the Basolateral Amygdala: Biophysical Mechanisms and Computational Consequences.

The basolateral nucleus of the amygdala (BL) is thought to support numerous emotional behaviors through specific microcircuits. These are often thought to be comprised of feedforward networks of principal cells (PNs) and interneurons. Neither well-understood nor often considered are recurrent and feedback connections, which likely engender oscillatory dynamics within BL. Indeed, oscillations in the gamma frequency range (40 - 100 Hz) are known to occur in the BL, and yet their origin and effect on local circuits remains unknown. To address this, we constructed a biophysically and anatomically detailed model of the rat BL and its local field potential (LFP) based on the physiological and anatomical literature, along with in vivo and in vitro data we collected on the activities of neurons within the rat BL. Remarkably, the model produced intermittent gamma oscillations (∼50 - 70 Hz) whose properties matched those recorded in vivo, including their entrainment of spiking. BL gamma-band oscillations were generated by the intrinsic circuitry, depending upon reciprocal interactions between PNs and fast-spiking interneurons (FSIs), while connections within these cell types affected the rhythm's frequency. The model allowed us to conduct experimentally impossible tests to characterize the synaptic and spatial properties of gamma. The entrainment of individual neurons to gamma depended on the number of afferent connections they received, and gamma bursts were spatially restricted in the BL. Importantly, the gamma rhythm synchronized PNs and mediated competition between ensembles. Together, these results indicate that the recurrent connectivity of BL expands its computational and communication repertoire.

Classification of Brainwaves Using Convolutional Neural Network.

Classification of brainwaves in recordings is of considerable interest to neuroscience and medical communities. Classification techniques used presently depend on the extraction of low-level features from the recordings, which in turn affects the classification performance. To alleviate this problem, this paper proposes an end-to-end approach using Convolutional Neural Network (CNN) which has been shown to detect complex patterns in a signal by exploiting its spatiotemporal nature. The present study uses time and frequency axes for the classification using synthesized Local Field Potential (LFP) data. The results are analyzed and compared with the FFT technique. In all the results, the CNN outperforms the FFT by a significant margin especially when the noise level is high. This study also sheds light on certain signal characteristics affecting network performance.

Multi-dimensional Coding by Basolateral Amygdala Neurons.

Conditioned appetitive and aversive responses (CRs) are thought to result from the activation of specific subsets of valence-coding basolateral amygdala (BLA) neurons. Under this model, the responses of BLA cells to conditioned stimuli (CSs) and the activity that drives CRs are closely related. We tested the strength of this correlation using a task where rats could emit different CRs in response to the same CSs. At odds with this model, the CS responses and CR-related activity of individual BLA cells were separable. Moreover, while the incidence of valence-coding cells did not exceed chance, at the population level there was similarity between valence coding for CSs and CRs. In fact, both lateral and basolateral neurons concurrently encoded multiple task features and behaviors. Thus, conditioned emotional behaviors may not depend on the recruitment of single cells that explicitly encode individual task variables but from multiplexed representations distributed across the BLA.

Vigilance-Associated Gamma Oscillations Coordinate the Ensemble Activity of Basolateral Amygdala Neurons.

Principal basolateral amygdala (BL) neurons profoundly influence motivated behaviors, yet few of them are activated by emotionally valenced stimuli. Here, we show that a likely explanation for this paradox is the synchronizing influence of the high-gamma rhythm. High-gamma (75-95 Hz) entrained BL firing more strongly than all other rhythms. It was most pronounced during states of increased vigilance, when rats were apprehensive. Relative to behavioral states, high-gamma produced minor changes in firing rates yet dramatic increases in synchrony. Moreover, connected pairs of cells showed similarly high levels of entrainment and synchronization. Unexpectedly, prefrontal- and accumbens-projecting cells, respectively, showed high and low entrainment by high-gamma, indicating that this rhythm differentially synchronizes the activity of BL neurons projecting to specific sites. Overall, our findings suggest that individual BL neurons encode information not only by changing their firing rates, but also by synchronizing their collective activity, amplifying their impact on target structures.

Common oscillatory mechanisms across multiple memory systems.

The cortex, hippocampus, and striatum support dissociable forms of memory. While each of these regions contains specialized circuitry supporting their respective functions, all structure their activities across time with delta, theta, and gamma rhythms. We review how these oscillations are generated and how they coordinate distinct memory systems during encoding, consolidation, and retrieval. First, gamma oscillations occur in all regions and coordinate local spiking, compressing it into short population bursts. Second, gamma oscillations are modulated by delta and theta oscillations. Third, oscillatory dynamics in these memory systems can operate in either a 'slow' or 'fast' mode. The slow mode happens during slow-wave sleep (SWS) and is characterized by large irregular activity in the hippocampus and delta oscillations in cortical and striatal circuits. The fast mode occurs during active waking and REM and is characterized by theta oscillations in the hippocampus and its targets, along with gamma oscillations in the rest of cortex. In waking, the fast mode is associated with the efficacious encoding and retrieval of declarative and procedural memories. Theta and gamma oscillations have the similar relationships with encoding and retrieval across multiple forms of memory and brain regions, despite regional differences in microcircuitry and information content. Differences in the oscillatory coordination of memory systems during sleep might explain why the consolidation of some forms of memory is sensitive to SWS, while others depend on REM. In particular, theta oscillations appear to support the consolidation of certain types of procedural memories during REM, while delta oscillations during SWS seem to promote declarative and procedural memories.

Intra- and interregional cortical interactions related to sharp-wave ripples and dentate spikes.

The hippocampus generates population events termed sharp-wave ripples (SWRs) and dentate spikes (DSs). While little is known about DSs, SWR-related hippocampal discharges during sleep are thought to replay prior waking activity, reactivating the cortical networks that encoded the initial experience. During slow-wave sleep, such reactivations likely occur during up-states, when most cortical neurons are depolarized. However, most studies have examined the relationship between SWRs and up-states measured in single neocortical regions. As a result, it is currently unclear whether SWRs are associated with particular patterns of widely distributed cortical activity. Additionally, no such investigation has been carried out for DSs. The present study addressed these questions by recording SWRs and DSs from the dorsal hippocampus simultaneously with prefrontal, sensory (visual and auditory), perirhinal, and entorhinal cortices in naturally sleeping rats. We found that SWRs and DSs were associated with up-states in all cortical regions. Up-states coinciding with DSs and SWRs exhibited increased unit activity, power in the gamma band, and intraregional gamma coherence. Unexpectedly, interregional gamma coherence rose much more strongly in relation to DSs than to SWRs. Whereas the increase in gamma coherence was time locked to DSs, that seen in relation to SWRs was not. These observations suggest that SWRs are related to the strength of up-state activation within individual regions throughout the neocortex but not so much to gamma coherence between different regions. Perhaps more importantly, DSs coincided with stronger periods of interregional gamma coherence, suggesting that they play a more important role than previously assumed. NEW & NOTEWORTHY: Off-line cortico-hippocampal interactions are thought to support memory consolidation. We surveyed the relationship between hippocampal sharp-wave ripples (SWRs) and dentate spikes (DSs) with up-states across multiple cortical regions. SWRs and DSs were associated with increased cortical gamma oscillations. Interregional gamma coherence rose much more strongly in relation to DSs than to SWRs. Moreover, it was time locked to DSs but not SWRs. These results have important implications for current theories of systems memory consolidation during sleep.

Basolateral amygdala nucleus responses to appetitive conditioned stimuli correlate with variations in conditioned behaviour.

In the lateral amygdala (LA), training-induced increases in neuronal responsiveness to conditioned stimuli (CSs) reflect potentiated sensory responses that drive conditioned behaviours (CRs) via LA's targets. The basolateral nucleus of the amygdala (BL) receives LA inputs and projects to various subcortical sites that can drive aversive and appetitive CRs. Consistent with this, BL neurons also develop increased responses to CSs that predict rewarding or aversive outcomes. This increased BL activity is thought to reflect the potentiated sensory responses of LA neurons. Here we contrast the CS-related activity of BL neurons when rats produced the expected CR or not, to show that cells activated by appetitive CSs mainly encode behavioural output, not CS identity. The strong dependence of BL activity on behaviour irrespective of CS identity suggests that feedforward connectivity from LA to BL can be overridden by other BL inputs.