Ventral striatal gamma oscillations are highly variable from trial to trial, and are dominated by behavioural state, and only weakly influenced by outcome value

Dynamics Learning Rate Bias in Pigeons: Insights from Reinforcement Learning and Neural Correlates

Research in reinforcement learning indicates that animals respond differently to positive and negative reward prediction errors, which can be calculated by assuming learning rate bias. Many studies have shown that humans and other animals have learning rate bias during learning, but it is unclear whether and how the bias changes throughout the entire learning process. Here, we recorded the behavior data and the local field potentials (LFPs) in the striatum of five pigeons performing a probabilistic learning task. Reinforcement learning models with and without learning rate biases were used to dynamically fit the pigeons' choice behavior and estimate the option values. Furthemore, the correlation between the striatal LFPs power and the model-estimated option values was explored. We found that the pigeons' learning rate bias shifted from negative to positive during the learning process, and the striatal Gamma (31 to 80 Hz) power correlated with the option values modulated by dynamic learning rate bias. In conclusion, our results support the hypothesis that pigeons employ a dynamic learning strategy in the learning process from both behavioral and neural aspects, providing valuable insights into reinforcement learning mechanisms of non-human animals.

High-Frequency Local Field Potential Oscillations May Modulate Aggressive Behaviors in Mice

Aggressive behavior is one of congenital social behaviors in many species, which could be promoted by social neglect or isolation in the early stages of life. Many brain regions including the medial prefrontal cortex (mPFC), medial amygdala (MeA) and ventromedial hypothalamus (VMH) are demonstrated to relate to aggressive behavior; however, the dynamic patterns of neural activities during the occurrence of this behavior remain unclear. In this study, 21-day-old male CD-1 mice were reared in social isolation conditions and cohousing conditions for two weeks. Aggressive behaviors of each subject were estimated by the resident–intruder test. Simultaneously, the local field potentials of mPFC, MeA and VMH were recorded for exploring differences in the relative power spectra of different oscillations when aggressive behaviors occurred. The results showed that the following: (1) Compared with the cohousing mice, the socially isolated mice exhibited more aggression. (2) Regardless of “time condition” (pre-, during- and post- attack), the relative power spectra of beta band in the cohousing mice were significantly greater than those in the socially isolated mice, and inversely, the relative power spectra of gamma band in the cohousing mice were significantly smaller than those in the socially isolated mice. (3) The bilateral mPFC exhibited significantly smaller beta power spectra but greater gamma power spectra compared with other brain areas regardless of rearing patterns. (4) For the right VMH of the socially isolated mice, the relative power spectra of the gamma band during attacks were significantly greater than those before attack. These results suggest that aggressive behaviors in mice could be shaped by rearing patterns and that high-frequency oscillations (beta and gamma bands) may engage in mediating aggressive behaviors in mice.

Reward-related dynamical coupling between basolateral amygdala and nucleus accumbens

Recognizing reward-related stimuli is crucial for survival. Neuronal projections from the basolateral amygdala (BLA) to the nucleus accumbens (NAc) play an important role in processing reward-related cues. Previous studies revealed synchronization between distant brain regions in reward-sensitive neurocircuits; however, whether the NAc synchronizes with the BLA is unknown. Here, we recorded local field potentials simultaneously from the BLA and NAc of rats during social preference tests and an appetitive conditioning test in which explicit stimuli were associated with food. BLA-NAc coherence in the theta band (5-8 Hz) increased in response to food-associated cues. Meanwhile, the modulatory strength of theta-high gamma (50-110 Hz) phase-amplitude cross-frequency coupling (PAC) in the NAc decreased. Importantly, both of these neuromodulations disappeared upon extinction. In contrast, both theta and gamma power oscillations in each region increased in the presence of social conspecifics or contexts associated with conspecifics, but coherence did not change. To potentially disrupt behavior and associated neural activity, a subgroup of rats was exposed prenatally to valproic acid (VPA), which has been shown to disrupt transcriptome and excitatory/inhibitory balance in the amygdala. VPA-exposed rats demonstrated impulsive-like behavior, but VPA did not affect BLA-NAc coherence. These findings reveal changes in BLA-NAc coherence in response to select reward-related stimuli (i.e., food-predictive cues); the differences between the tasks used here could shed light onto the functional nature of BLA-NAc coherence and are discussed.

Persistent coding of outcome-predictive cue features in the rat nucleus accumbens

The nucleus accumbens (NAc) is important for learning from feedback, and for biasing and invigorating behaviour in response to cues that predict motivationally relevant outcomes. NAc encodes outcome-related cue features such as the magnitude and identity of reward. However, little is known about how features of cues themselves are encoded. We designed a decision making task where rats learned multiple sets of outcome-predictive cues, and recorded single-unit activity in the NAc during performance. We found that coding of cue identity and location occurred alongside coding of expected outcome. Furthermore, this coding persisted both during a delay period, after the rat made a decision and was waiting for an outcome, and after the outcome was revealed. Encoding of cue features in the NAc may enable contextual modulation of on-going behaviour, and provide an eligibility trace of outcome-predictive stimuli for updating stimulus-outcome associations to inform future behaviour.

Basal forebrain contributes to default mode network regulation

The default mode network (DMN) is a collection of cortical brain regions that is active during states of rest or quiet wakefulness in humans and other mammalian species. A pertinent characteristic of the DMN is a suppression of local field potential gamma activity during cognitive task performance as well as during engagement with external sensory stimuli. Conversely, gamma activity is elevated in the DMN during rest. Here, we document that the rat basal forebrain (BF) exhibits the same pattern of responses, namely pronounced gamma oscillations during quiet wakefulness in the home cage and suppression of this activity during active exploration of an unfamiliar environment. We show that gamma oscillations are localized to the BF and that gamma-band activity in the BF has a directional influence on a hub of the rat DMN, the anterior cingulate cortex, during DMN-dominated brain states. The BF is well known as an ascending, activating, neuromodulatory system involved in wake-sleep regulation, memory formation, and regulation of sensory information processing. Our findings suggest a hitherto undocumented role of the BF as a subcortical node of the DMN, which we speculate may be important for switching between internally and externally directed brain states. We discuss potential BF projection circuits that could underlie its role in DMN regulation and highlight that certain BF nuclei may provide potential target regions for up- or down-regulation of DMN activity that might prove useful for treatment of DMN dysfunction in conditions such as epilepsy or major depressive disorder.

Gamma Oscillations in the Rat Ventral Striatum Originate in the Piriform Cortex

Local field potentials (LFPs) recorded from the human and rodent ventral striatum (vStr) exhibit prominent, behaviorally relevant gamma-band oscillations. These oscillations are related to local spiking activity and transiently synchronize with anatomically related areas, suggesting a possible role in organizing vStr activity. However, the origin of vStr gamma is unknown. We recorded vStr gamma oscillations across a 1.4 mm² grid spanned by 64 recording electrodes as male rats rested and foraged for rewards, revealing a highly consistent power gradient originating in the adjacent piriform cortex. Phase differences across the vStr were consistently small (<15°) and current source density analysis further confirmed the absence of local sink-source pairs in the vStr. Reversible occlusions of the ipsilateral (but not contralateral) nostril, known to abolish gamma oscillations in the piriform cortex, strongly reduced vStr gamma power and the occurrence of transient gamma-band events. These results imply that local circuitry is not a major contributor to gamma oscillations in the vStr LFP and that piriform cortex is an important driver of gamma-band oscillations in the vStr and associated limbic areas.SIGNIFICANCE STATEMENT The ventral striatum (vStr) is an area of anatomical convergence in circuits underlying motivated behavior, but it remains unclear how its inputs from different sources interact. A major proposal about how neural circuits may switch dynamically between convergent inputs is through temporal organization reflected in local field potential (LFP) oscillations. Our results show that, in the rat, the mechanisms controlling gamma-band oscillations in the vStr LFP are primarily located in the in the adjacent piriform cortex rather than in the vStr itself, providing a novel interpretation of previous rodent work on gamma oscillations in the vStr and related circuits and an important consideration for future work seeking to use oscillations in these areas as biomarkers for behavioral and neurological disorders.

Memories of Opiate Withdrawal Emotional States Correlate with Specific Gamma Oscillations in the Nucleus Accumbens

Affective memories associated with the negative emotional state experienced during opiate withdrawal are central in maintaining drug taking, seeking, and relapse. Nucleus accumbens (NAC) is a key structure for both acute withdrawal and withdrawal memories reactivation, but the NAC neuron coding properties underpinning the expression of these memories remain largely unknown. Here we aimed at deciphering the role of NAC neurons in the encoding and retrieval of opiate withdrawal memory. Chronic single neuron and local field potentials recordings were performed in morphine-dependent rats and placebo controls. Animals were subjected to an unbiased conditioned placed aversion protocol with one compartment (CS+) paired with naloxone-precipitated withdrawal, a second compartment with saline injection (CS-), and a third being neutral (no pairing). After conditioning, animals displayed a typical place aversion for CS+ and developed a preference for CS- characteristic of safety learning. We found that distinct NAC neurons code for CS+ or CS-. Both populations also displayed highly specific oscillatory dynamics, CS+ and CS- neurons, respectively, following 80 Hz (G80) and 60 Hz (G60) local field potential gamma rhythms. Finally, we found that the balance between G60 and G80 rhythms strongly correlated both with the ongoing behavior of the animal and the strength of the conditioning. We demonstrate here that the aversive and preferred environments are underpinned by distinct groups of NAC neurons as well as specific oscillatory dynamics. This suggest that G60/G80 interplay-established through the conditioning process-serves as a robust and versatile mechanism for a fine coding of the environment emotional weight.

Optimizing for generalization in the decoding of internally generated activity in the hippocampus

The decoding of a sensory or motor variable from neural activity benefits from a known ground truth against which decoding performance can be compared. In contrast, the decoding of covert, cognitive neural activity, such as occurs in memory recall or planning, typically cannot be compared to a known ground truth. As a result, it is unclear how decoders of such internally generated activity should be configured in practice. We suggest that if the true code for covert activity is unknown, decoders should be optimized for generalization performance using cross-validation. Using ensemble recording data from hippocampal place cells, we show that this cross-validation approach results in different decoding error, different optimal decoding parameters, and different distributions of error across the decoded variable space. In addition, we show that a minor modification to the commonly used Bayesian decoding procedure, which enables the use of spike density functions, results in substantially lower decoding errors. These results have implications for the interpretation of covert neural activity, and suggest easy-to-implement changes to commonly used procedures across domains, with applications to hippocampal place cells in particular. © 2017 Wiley Periodicals, Inc.

Gamma band directional interactions between basal forebrain and visual cortex during wake and sleep states

The basal forebrain (BF) is an important regulator of cortical excitability and responsivity to sensory stimuli, and plays a major role in wake-sleep regulation. While the impact of BF on cortical EEG or LFP signals has been extensively documented, surprisingly little is known about LFP activity within BF. Based on bilateral recordings from rats in their home cage, we describe endogenous LFP oscillations in the BF during quiet wakefulness, rapid eye movement (REM) and slow wave sleep (SWS) states. Using coherence and Granger causality methods, we characterize directional influences between BF and visual cortex (VC) during each of these states. We observed pronounced BF gamma activity particularly during wakefulness, as well as to a lesser extent during SWS and REM. During wakefulness, this BF gamma activity exerted a directional influence on VC that was associated with cortical excitation. During SWS but not REM, there was also a robust directional gamma band influence of BF on VC. In all three states, directional influence in the gamma band was only present in BF to VC direction and tended to be regulated specifically within each brain hemisphere. Locality of gamma band LFPs to the BF was confirmed by demonstration of phase locking of local spiking activity to the gamma cycle. We report novel aspects of endogenous BF LFP oscillations and their relationship to cortical LFP signals during sleep and wakefulness. We link our findings to known aspects of GABAergic BF networks that likely underlie gamma band LFP activations, and show that the Granger causality analyses can faithfully recapitulate many known attributes of these networks.

Low- and high-gamma oscillations deviate in opposite directions from zero-phase synchrony in the limbic corticostriatal loop

The loop structure of cortico-striatal anatomy in principle enables both descending (cortico-striatal) and ascending (striato-cortical) influences, but the factors that regulate the flow of information in these loops are not known. We report that low- and high-gamma oscillations (∼50 and ∼80 Hz, respectively) in the local field potential of freely moving rats are highly synchronous between the infralimbic region of the medial prefrontal cortex (mPFC) and the ventral striatum (vStr). Strikingly, high-gamma oscillations in mPFC preceded those in vStr, whereas low-gamma oscillations in mPFC lagged those in vStr, with short (∼1 ms) time lags. These systematic deviations from zero-phase synchrony were consistent across measures based on amplitude cross-correlation and phase slopes and were robustly maintained between behavioral states and different individual subjects. Furthermore, low- and high-gamma oscillations were associated with distinct ensemble spiking patterns in vStr, even when controlling for overt behavioral differences and slow changes in neural activity. These results imply that neural activity in vStr and mPFC is tightly coupled at the gamma timescale and raise the intriguing possibility that frequency-specific deviations from this coupling may signal transient leader-follower switches.