Cortico-thalamo-cortical interactions modulate electrically evoked EEG responses in mice.

Perturbational complexity analysis predicts the presence of consciousness in volunteers and patients by stimulating the brain with brief pulses, recording EEG responses, and computing their spatiotemporal complexity. We examined the underlying neural circuits in mice by directly stimulating cortex while recording with EEG and Neuropixels probes during wakefulness and isoflurane anesthesia. When mice are awake, stimulation of deep cortical layers reliably evokes locally a brief pulse of excitation, followed by a biphasic sequence of 120 ms profound off period and a rebound excitation. A similar pattern, partially attributed to burst spiking, is seen in thalamic nuclei and is associated with a pronounced late component in the evoked EEG. We infer that cortico-thalamo-cortical interactions drive the long-lasting evoked EEG signals elicited by deep cortical stimulation during the awake state. The cortical and thalamic off period and rebound excitation, and the late component in the EEG, are reduced during running and absent during anesthesia.

Temporally restricted dopaminergic control of reward-conditioned movements.

Midbrain dopamine (DA) neurons encode both reward- and movement-related events and are implicated in disorders of reward processing as well as movement. Consequently, disentangling the contribution of DA neurons in reinforcing versus generating movements is challenging and has led to lasting controversy. In this study, we dissociated these functions by parametrically varying the timing of optogenetic manipulations in a Pavlovian conditioning task and examining the influence on anticipatory licking before reward delivery. Inhibiting both ventral tegmental area and substantia nigra pars compacta DA neurons in the post-reward period had a significantly greater behavioral effect than inhibition in the pre-reward period of the task. Furthermore, the contribution of DA neurons to behavior decreased linearly as a function of elapsed time after reward. Together, the results indicate a temporally restricted role of DA neurons primarily related to reinforcing stimulus-reward associations and suggest that directly generating movements is a comparatively less important function.

Gain Modulation by Corticostriatal and Thalamostriatal Input Signals during Reward-Conditioned Behavior.

The cortex and thalamus send excitatory projections to the striatum, but little is known about how these inputs, either individually or collectively, regulate striatal dynamics during behavior. The lateral striatum receives overlapping input from the secondary motor cortex (M2), an area involved in licking, and the parafascicular thalamic nucleus (PF). Using neural recordings, together with optogenetic terminal inhibition, we examine the contribution of M2 and PF projections on medium spiny projection neuron (MSN) activity as mice performed an anticipatory licking task. Each input has a similar contribution to striatal activity. By comparing how suppressing single or multiple projections altered striatal activity, we find that cortical and thalamic input signals modulate MSN gain and that this effect is more pronounced in a temporally specific period of the task following the cue presentation. These results demonstrate that cortical and thalamic inputs synergistically regulate striatal output during reward-conditioned behavior.

Selective Modulation of Orbitofrontal Network Activity during Negative Occasion Setting.

Discrete cues can gain powerful control over behavior to help an animal anticipate and cope with upcoming events. This is important in conditions where understanding the relationship between complex stimuli provides a means to resolving situational ambiguity. However, it is unclear how cortical circuits generate and maintain these signals that conditionally regulate behavior. To address this, we established a Pavlovian serial feature-negative conditioning paradigm, where male mice are trained on a trial in which a conditioned stimulus (CS) is presented alone and followed by reward, or a feature-negative trial in which the CS is preceded by a feature cue indicating there is no reward. Mice learn to respond with anticipatory licking to a solitary CS, but significantly suppress their responding to the same cue during feature-negative trials. We show that the feature cue forms a selective association with its paired CS, because the ability of the feature to transfer its suppressive properties to a separately rewarded cue is limited. Next, to examine the underlying neural dynamics, we conduct recordings in the orbitofrontal cortex (OFC). We find that the feature cue significantly and selectively inhibits CS-evoked activity. Finally, we find that the feature triggers a distinct OFC network state during the delay period between the feature and CS, establishing a potential link between the feature and future events. Together, our findings suggest that OFC dynamics are modulated by the feature cue and its associated conditioned stimulus in a manner consistent with an occasion setting model.SIGNIFICANCE STATEMENT The ability of patterned cues to form an inhibitory relationship with ambiguously rewarded outcomes has been appreciated since early studies on learning and memory. However, it was often assumed that these cues, despite their hierarchical nature, still made direct associative links with neural rewarding events. This model was significantly challenged, largely by the work of Holland and colleagues, who demonstrated that under certain conditions cues can inherit occasion setting properties whereby they modulate the ability of a paired cue to elicit its conditioned response. Here we provide some of the first evidence that the activity of a cortical circuit is selectively modulated by such cues, thereby providing insight into the mechanisms of higher order learning.

Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.

Telling time is fundamental to many forms of learning and behavior, including the anticipation of rewarding events. Although the neural mechanisms underlying timing remain unknown, computational models have proposed that the brain represents time in the dynamics of neural networks. Consistent with this hypothesis, changing patterns of neural activity dynamically in a number of brain areas-including the striatum and cortex-has been shown to encode elapsed time. To date, however, no studies have explicitly quantified and contrasted how well different areas encode time by recording large numbers of units simultaneously from more than one area. Here, we performed large-scale extracellular recordings in the striatum and orbitofrontal cortex of mice that learned the temporal relationship between a stimulus and a reward and reported their response with anticipatory licking. We used a machine-learning algorithm to quantify how well populations of neurons encoded elapsed time from stimulus onset. Both the striatal and cortical networks encoded time, but the striatal network outperformed the orbitofrontal cortex, a finding replicated both in simultaneously and nonsimultaneously recorded corticostriatal datasets. The striatal network was also more reliable in predicting when the animals would lick up to ∼1 s before the actual lick occurred. Our results are consistent with the hypothesis that temporal information is encoded in a widely distributed manner throughout multiple brain areas, but that the striatum may have a privileged role in timing because it has a more accurate "clock" as it integrates information across multiple cortical areas. SIGNIFICANCE STATEMENT: The neural representation of time is thought to be distributed across multiple functionally specialized brain structures, including the striatum and cortex. However, until now, the neural code for time has not been compared quantitatively between these areas. Here, we performed large-scale recordings in the striatum and orbitofrontal cortex of mice trained on a stimulus-reward association task involving a delay period and used a machine-learning algorithm to quantify how well populations of simultaneously recorded neurons encoded elapsed time from stimulus onset. We found that, although both areas encoded time, the striatum consistently outperformed the orbitofrontal cortex. These results suggest that the striatum may refine the code for time by integrating information from multiple inputs.

Frontostriatal Circuit Dynamics Correlate with Cocaine Cue-Evoked Behavioral Arousal during Early Abstinence.

It is thought that frontostriatal circuits play an important role in mediating conditioned behavioral responses to environmental stimuli that were previously encountered during drug administration. However, the neural correlates of conditioned responses to drug-associated cues are not well understood at the level of large populations of simultaneously recorded neurons, or at the level of local field potential (LFP) synchrony in the frontostriatal network. Here we introduce a behavioral assay of conditioned arousal to cocaine cues involving pupillometry in awake head-restrained mice. After just 24 h of drug abstinence, brief exposures to olfactory stimuli previously paired with cocaine injections led to a transient dilation of the pupil, which was greater than the dilation effect to neutral cues. In contrast, there was no cue-selective change in locomotion, as measured by the rotation of a circular treadmill. The behavioral assay was combined with simultaneous recordings from dozens of electrophysiologically identified units in the medial prefrontal cortex (mPFC) and ventral striatum (VS). We found significant relationships between cocaine cue-evoked pupil dilation and the proportion of inhibited principal cells in the mPFC and VS. Additionally, LFP coherence analysis revealed a significant correlation between pupillary response and synchrony in the 25-45 Hz frequency band. Together, these results show that pupil dilation is sensitive to drug-associated cues during acute stages of abstinence, and that individual animal differences in this behavioral arousal response can be explained by two complementary measures of frontostriatal network activity.

Brain activity mapping at multiple scales with silicon microprobes containing 1,024 electrodes.

The coordinated activity of neural ensembles across multiple interconnected regions has been challenging to study in the mammalian brain with cellular resolution using conventional recording tools. For instance, neural systems regulating learned behaviors often encompass multiple distinct structures that span the brain. To address this challenge we developed a three-dimensional (3D) silicon microprobe capable of simultaneously measuring extracellular spike and local field potential activity from 1,024 electrodes. The microprobe geometry can be precisely configured during assembly to target virtually any combination of four spatially distinct neuroanatomical planes. Here we report on the operation of such a device built for high-throughput monitoring of neural signals in the orbitofrontal cortex and several nuclei in the basal ganglia. We perform analysis on systems-level dynamics and correlations during periods of conditioned behavioral responding and rest, demonstrating the technology's ability to reveal functional organization at multiple scales in parallel in the mouse brain.