Beta2 oscillations (23-30 Hz) in the mouse hippocampus during novel object recognition.

The oscillatory activity of hippocampal neuronal networks is believed to play a role in memory acquisition and consolidation. Particular focus has been given to characterising theta (4-12 Hz), gamma (40-100 Hz) and ripple (150-250 Hz) oscillations. Beyond these well-described network states, few studies have investigated hippocampal beta2 (23-30 Hz) activity in vivo and its link to behaviour. A previous sudy showed that the exploration of novel environments may lead to the appearance of beta2 oscillations in the mouse hippocampus. In the present study we characterised hippocampal beta2 oscillations in mice during an object recognition task. We found prominent bursts of beta2 oscillations in the beginning of novel exploration sessions (four new objects), which could be readily observed by spectral analysis and visual inspection of local field potentials. Beta2 modulated hippocampal but not neocortical neurons and its power decreased along the session. We also found increased beta2 power in the beginning of a second exploration session performed 24 h later in a slightly modified environment (two new, two familiar objects), but to a lesser extent than in the first session. However, the increase in beta2 power in the second exploration session became similar to the first session when we pharmacologically impaired object recognition in a new set of experiments performed 1 week later. Our results suggest that hippocampal beta2 activity is associated with a dynamic network state tuned for novelty detection and which may allow new learning to occur.

Neurophysiological alterations in mice and humans carrying mutations in APP and PSEN1 genes.

BACKGROUND: Studies in animal models of Alzheimer's disease (AD) have provided valuable insights into the molecular and cellular processes underlying neuronal network dysfunction. Whether and how AD-related neurophysiological alterations translate between mice and humans remains however uncertain. METHODS: We characterized neurophysiological alterations in mice and humans carrying AD mutations in the APP and/or PSEN1 genes, focusing on early pre-symptomatic changes. Longitudinal local field potential recordings were performed in APP/PS1 mice and cross-sectional magnetoencephalography recordings in human APP and/or PSEN1 mutation carriers. All recordings were acquired in the left frontal cortex, parietal cortex, and hippocampus. Spectral power and functional connectivity were analyzed and compared with wildtype control mice and healthy age-matched human subjects. RESULTS: APP/PS1 mice showed increased absolute power, especially at higher frequencies (beta and gamma) and predominantly between 3 and 6 moa. Relative power showed an overall shift from lower to higher frequencies over almost the entire recording period and across all three brain regions. Human mutation carriers, on the other hand, did not show changes in power except for an increase in relative theta power in the hippocampus. Mouse parietal cortex and hippocampal power spectra showed a characteristic peak at around 8 Hz which was not significantly altered in transgenic mice. Human power spectra showed a characteristic peak at around 9 Hz, the frequency of which was significantly reduced in mutation carriers. Significant alterations in functional connectivity were detected in theta, alpha, beta, and gamma frequency bands, but the exact frequency range and direction of change differed for APP/PS1 mice and human mutation carriers. CONCLUSIONS: Both mice and humans carrying APP and/or PSEN1 mutations show abnormal neurophysiological activity, but several measures do not translate one-to-one between species. Alterations in absolute and relative power in mice should be interpreted with care and may be due to overexpression of amyloid in combination with the absence of tau pathology and cholinergic degeneration. Future studies should explore whether changes in brain activity in other AD mouse models, for instance, those also including tau pathology, provide better translation to the human AD continuum.

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.

Characterizing neural phase-space trajectories via Principal Louvain Clustering.

BACKGROUND: With the growing size and richness of neuroscience datasets in terms of dimension, volume, and resolution, identifying spatiotemporal patterns in those datasets is increasingly important. Multivariate dimension-reduction methods are particularly adept at addressing these challenges. NEW METHOD: In this paper, we propose a novel method, which we refer to as Principal Louvain Clustering (PLC), to identify clusters in a low-dimensional data subspace, based on time-varying trajectories of spectral dynamics across multisite local field potential (LFP) recordings in awake behaving mice. Data were recorded from prefrontal cortex, hippocampus, and parietal cortex in eleven mice while they explored novel and familiar environments. RESULTS: PLC-identified subspaces and clusters showed high consistency across animals, and were modulated by the animals' ongoing behavior. CONCLUSIONS: PLC adds to an important growing literature on methods for characterizing dynamics in high-dimensional datasets, using a smaller number of parameters. The method is also applicable to other kinds of datasets, such as EEG or MEG.

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.

Structural Degradation in Midcingulate Cortex Is Associated with Pathological Aggression in Mice.

Pathological aggression is a debilitating feature of many neuropsychiatric disorders, and cingulate cortex is one of the brain areas centrally implicated in its control. Here we explore the specific role of midcingulate cortex (MCC) in the development of pathological aggression. To this end, we investigated the structural and functional degeneration of MCC in the BALB/cJ strain, a mouse model for pathological aggression. Compared to control animals from the BALB/cByJ strain, BALB/cJ mice expressed consistently heightened levels of aggression, as assessed by the resident-intruder test. At the same time, immunohistochemistry demonstrated stark structural degradation in the MCC of aggressive BALB/cJ mice: Decreased neuron density and widespread neuron death were accompanied by increased microglia and astroglia concentrations and reactive astrogliosis. cFos staining indicated that this degradation had functional consequences: MCC activity did not differ between BALB/cJ and BALB/cByJ mice at baseline, but unlike BALB/cByJ mice, BALB/cJ mice failed to activate MCC during resident-intruder encounters. This suggests that structural and functional impairments of MCC, triggered by neuronal degeneration, may be one of the drivers of pathological aggression in mice, highlighting MCC as a potential key area for pathologies of aggression in humans.

A central role for anterior cingulate cortex in the control of pathological aggression.

Controlling aggression is a crucial skill in social species like rodents and humans and has been associated with anterior cingulate cortex (ACC). Here, we directly link the failed regulation of aggression in BALB/cJ mice to ACC hypofunction. We first show that ACC in BALB/cJ mice is structurally degraded: neuron density is decreased, with pervasive neuron death and reactive astroglia. Gene-set enrichment analysis suggested that this process is driven by neuronal degeneration, which then triggers toxic astrogliosis. cFos expression across ACC indicated functional consequences: during aggressive encounters, ACC was engaged in control mice, but not BALB/cJ mice. Chemogenetically activating ACC during aggressive encounters drastically suppressed pathological aggression but left species-typical aggression intact. The network effects of our chemogenetic perturbation suggest that this behavioral rescue is mediated by suppression of amygdala and hypothalamus and activation of mediodorsal thalamus. Together, these findings highlight the central role of ACC in curbing pathological aggression.

Low-cost and versatile electrodes for extracellular chronic recordings in rodents.

Electrophysiological data are used to investigate fundamental properties of brain function, its relation to cognition, and its dysfunction in diseases. The development of reliable and open-source systems for electrophysiological data acquisition is decreasing the total cost of constructing and operating an electrophysiology laboratory, and facilitates low-cost methods to extract and analyze the data (Siegle et al., 2017). Here we detail our method of building custom-designed low-cost electrodes. These electrodes can be customized and manufactured by any researcher to address a broad set of research questions, further decreasing the final cost of an implanted animal. Finally, we present data showing such an electrode has a good signal quality to record LFP.

Gradient of Parvalbumin- and Somatostatin-Expressing Interneurons Across Cingulate Cortex Is Differentially Linked to Aggression and Sociability in BALB/cJ Mice.

Successfully navigating social interactions requires the precise and balanced integration of social and environmental cues. When such flexible information integration fails, maladaptive behavioral patterns arise, including excessive aggression, empathy deficits, and social withdrawal, as seen in disorders such as conduct disorder and autism spectrum disorder. One of the main hubs for the context-dependent regulation of behavior is cingulate cortex, specifically anterior cingulate cortex (ACC) and midcingulate cortex (MCC). While volumetric abnormalities of ACC and MCC have been demonstrated in patients, little is known about the exact structural changes responsible for the dysregulation of behaviors such as aggression and social withdrawal. Here, we demonstrate that the distribution of parvalbumin (PV) and somatostatin (SOM) interneurons across ACC and MCC differentially predicts aggression and social withdrawal in BALB/cJ mice. BALB/cJ mice were phenotyped for their social behavior (three-chamber task) and aggression (resident-intruder task) compared to control (BALB/cByJ) mice. In line with previous studies, BALB/cJ mice behaved more aggressively than controls. The three-chamber task revealed two sub-groups of highly-sociable versus less-sociable BALB/cJ mice. Highly-sociable BALB/cJ mice were as aggressive as the less-sociable group-in fact, they committed more acts of socially acceptable aggression (threats and harmless bites). PV and SOM immunostaining revealed that a lack of specificity in the distribution of SOM and PV interneurons across cingulate cortex coincided with social withdrawal: both control mice and highly-sociable BALB/cJ mice showed a differential distribution of PV and SOM interneurons across the sub-areas of cingulate cortex, while for less-sociable BALB/cJ mice, the distributions were near-flat. In contrast, both highly-sociable and less-sociable BALB/cJ mice had a decreased concentration of PV interneurons in MCC compared to controls, which was therefore linked to aggressive behavior. Together, these results suggest that the dynamic balance of excitatory and inhibitory activity across ACC and MCC shapes both social and aggressive behavior.

OLMα2 Cells Bidirectionally Modulate Learning.

Inhibitory interneurons participate in mnemonic processes. However, defined roles for identified interneuron populations are scarce. A subpopulation of oriens lacunosum-moleculare (OLM) interneurons genetically defined by the expression of the nicotinic receptor α2 subunit has been shown to gate information carried by either the temporoammonic pathway or Schaffer collaterals in vitro. Here we set out to determine whether selective modulation of OLMα2 cells in the intermediate CA1 affects learning and memory in vivo. Our data show that intermediate OLMα2 cells can either enhance (upon their inhibition) or impair (upon their activation) object memory encoding in freely moving mice, thus exerting bidirectional control. Moreover, we find that OLMα2 cell activation inhibits fear-related memories and that OLMα2 cells respond differently to nicotine in the dorsoventral axis. These results suggest that intermediate OLMα2 cells are an important component in the CA1 microcircuit regulating learning and memory processes. VIDEO ABSTRACT.

Object recognition impairment and rescue by a dopamine D2 antagonist in hyperdopaminergic mice.

Genetically-modified mice without the dopamine transporter (DAT) are hyperdopaminergic, and serve as models for studies of addiction, mania and hyperactive disorders. Here we investigated the capacity for object recognition in mildly hyperdopaminergic mice heterozygous for DAT (DAT +/-), with synaptic dopaminergic levels situated between those shown by DAT -/- homozygous and wild-type (WT) mice. We used a classical dopamine D2 antagonist, haloperidol, to modulate the levels of dopaminergic transmission in a dose-dependent manner, before or after exploring novel objects. In comparison with WT mice, DAT +/- mice showed a deficit in object recognition upon subsequent testing 24h later. This deficit was compensated by a single 0.05mg/kg haloperidol injection 30min before training. In all mice, a 0.3mg/kg haloperidol injected immediately after training impaired object recognition. The results indicate that a mild enhancement of dopaminergic levels can be detrimental to object recognition, and that this deficit can be rescued by a low dose of a D2 dopamine receptor antagonist. This suggests that novel object recognition is optimal at intermediate levels of D2 receptor activity.

Mouse activity across time scales: fractal scenarios.

In this work we devise a classification of mouse activity patterns based on accelerometer data using Detrended Fluctuation Analysis. We use two characteristic mouse behavioural states as benchmarks in this study: waking in free activity and slowwave sleep (SWS). In both situations we find roughly the same pattern: for short time intervals we observe high correlation in activity--a typical 1/f complex pattern--while for large time intervals there is anti-correlation. High correlation of short intervals (0.01 s to 2 s: waking state and 0.01 s to 0.1 s: SWS) is related to highly coordinated muscle activity. In the waking state we associate high correlation both to muscle activity and to mouse stereotyped movements (grooming, waking, etc.). On the other side, the observed anti-correlation over large time scales (30 s to 300 s: waking state and 0.3 s to 5 s: SWS) during SWS appears related to a feedback autonomic response. The transition from correlated regime at short scales to an anti-correlated regime at large scales during SWS is given by the respiratory cycle interval, while during the waking state this transition occurs at the time scale corresponding to the duration of the stereotyped mouse movements. Furthermore, we find that the waking state is characterized by longer time scales than SWS and by a softer transition from correlation to anticorrelation. Moreover, this soft transition in the waking state encompass a behavioural time scale window that gives rise to a multifractal pattern. We believe that the observed multifractality in mouse activity is formed by the integration of several stereotyped movements each one with a characteristic time correlation. Finally, we compare scaling properties of body acceleration fluctuation time series during sleep and wake periods for healthy mice. Interestingly, differences between sleep and wake in the scaling exponents are comparable to previous works regarding human heartbeat. Complementarily, the nature of these sleep-wake dynamics could lead to a better understanding of neuroautonomic regulation mechanisms.