Behavioral Neuroscience publications

The ability to detect deviations from expected sensory input is fundamental for adaptive behavior. We recorded electrocorticographic activity from the auditory (AC) and prefrontal (PFC) cortices of behaving macaques during an auditory oddball task to probe the cortical dynamics of predictive processing. Repetition of standard stimuli evoked suppression and facilitation in AC and strong low-frequency (2 Hz) enhancement in PFC, accompanied by bidirectional delta-band GC-defined interactions indicative of a shared predictive state. Deviant stimuli triggered earlier AC responses followed by PFC activation and increased GC-defined directed interactions across theta, alpha, and conventional gamma bands. Behavioral engagement amplified both repetition-related and deviance-related ECoG responses, strengthening cortical network coordination. Together, these findings reveal behaviorally gated auditory–prefrontal dynamics that are consistent with hierarchical predictive-processing accounts, while also allowing for contributions from repetition-, novelty-, and salience-related mechanisms.

Foraging in the wild requires coordinated switching of critical functions, including goal-oriented navigation and context-appropriate action selection. Nevertheless, few studies have examined how different functions are represented in the brain during naturalistic foraging. To address this question, we recorded multiple single-unit activities from the medial prefrontal cortex (mPFC) of rats seeking a sucrose reward in the presence of an unpredictable attack posed by a robotic predator (Lobsterbot). Simultaneously recorded ensemble activities from neurons were analyzed in reference to various behavioral indices as the animal moved freely across the foraging area (F) between the nest (N) and the goal (E) area. An artificial neural network, trained with simultaneously recorded neural activity, estimated the rat’s current distance from the Lobsterbot. The accuracy of distance estimation was the highest in the middle F-zone in which the dominant behavior was active navigation. The spatial encoding persisted in the N-zone when non-navigational behaviors such as grooming, rearing, and sniffing were excluded. In contrast, the accuracy decreased as the animal approached the E-zone, when the activity of the same neuronal ensembles was more correlated with events related to dynamic decision-making between food procurement and Lobsterbot evasion. A population-wide analysis confirmed highly heterogeneous encoding by the region. To further assess the decision-related activity in the E-zone, a naive Bayesian classifier was trained to predict the success and failure of avoidance behavior. The classifier predicted the avoidance outcome as much as 6 s before the head withdrawal. In addition, two sub-populations of recorded units with distinct temporal dynamics contributed differently to the prediction. These findings suggest that an overlapping population of mPFC neurons may switch between two heterogeneous modes, encoding relevant locations for goal-directed navigation or an imminent situational challenge.

The hippocampus (HPC) supports spatial working memory (SWM) through its interactions with the prefrontal cortex (PFC). However, it is not clear whether and how the dorsal (dHPC) and ventral (vHPC) poles of the HPC make distinct contributions to SWM and whether they differentially influence the PFC. To address this question, we optogenetically silenced the dHPC or the vHPC while simultaneously recording from the PFC of mice performing a SWM task. We found that whereas both HPC subregions were necessary during the encoding phase of the task, only the dHPC was necessary during the choice phase. Unexpectedly, silencing of either subregion did not affect PFC neurons’ ability to represent the animal’s position, but did alter how it was represented. In contrast, only silencing of the vHPC affected their coding of spatial goals. These results thus reveal distinct contributions of the dorsal and ventral HPC poles to SWM and the coding of behaviorally relevant spatial information by PFC neurons.

Alcohol use disorder (AUD) is a chronic relapsing brain disorder characterized by an impaired ability to stop or control alcohol consumption despite adverse social, occupational, or health consequences. AUD affects nearly one-third of adults at some point during their lives, with an associated cost of approximately $249 billion annually in the U.S. alone. The effects of alcohol consumption are expected to increase significantly during the COVID-19 pandemic, with alcohol sales increasing by approximately 54%, potentially exacerbating health concerns and risk-taking behaviors. Unfortunately, existing pharmacological and behavioral therapies for AUD are associated with poor success rates, with approximately 40% of individuals relapsing within three years of treatment.Pre-clinical studies have shown that chronic alcohol consumption leads to significant changes in synaptic function within the dorsal medial striatum (DMS), one of the brain regions associated with AUD and responsible for mediating goal-directed behavior. Specifically, chronic alcohol consumption has been associated with hyperactivity of dopamine receptor 1 (D1) medium spiny neurons (MSN) and hypoactivity of dopamine receptor 2 (D1) MSNs within the DMS. Optogenetic, chemogenetic, and transgenic approaches have demonstrated that reducing the D1/D2 MSN signaling imbalance decreases alcohol self-administration in rodent models of AUD.Here, we present an electrical stimulation approach that uses ultra-low (≤ 1 Hz) frequency (ULF) spike-timing-dependent plasticity (STDP) in mouse models of AUD to reduce DMS D1/D2 MSN signaling imbalances by stimulating D1-MSN afferents into the GPi and ACC glutamatergic projections to the DMS in a time-locked stimulation sequence. Our data suggest that GPi/ACC ULF-STDP selectively decreases DMS D1-MSN hyperactivity leading to reduced alcohol consumption without evoking undesired affective behaviors using electrical stimulation rather than approaches requiring genetic modification. This work represents a step towards fulfilling the unmet need for a reliable method of treating severe AUD through cell-type-specific control with clinically available neuromodulation tools.

The value associated with reward is sensitive to external factors, such as the time between the choice and reward delivery as classically manipulated in temporal discounting tasks. Subjective preference for two reward options is dependent on objective variables of reward magnitude and reward delay. Single neuron correlates of reward value have been observed in regions, including ventral striatum, orbital, and medial prefrontal cortex. Brain imaging studies show cortico-striatal-limbic network activity related to subjective preferences. To explore how oscillatory dynamics represent reward processing across brain regions, we measured local field potentials of rats performing a temporal discounting task. Our goal was to use a data-driven approach to identify an electrophysiological marker that correlates with reward preference. We found that reward-locked oscillations at beta frequencies signaled the magnitude of reward and decayed with longer temporal delays. Electrodes in orbitofrontal/medial prefrontal cortex, anterior insula, ventral striatum, and amygdala individually increased power and were functionally connected at beta frequencies during reward outcome. Beta power during reward outcome correlated with subjective value as defined by a computational model fit to the discounting behavior. These data suggest that cortico-striatal beta oscillations are a reward signal correlated, which may represent subjective value and hold potential to serve as a biomarker and potential therapeutic target.

The common marmoset has emerged as a key model in neuroscience. Marmosets are small in size, show great potential for genetic modification and exhibit complex behaviors. Thus, it is necessary to develop technology that enables monitoring and manipulation of the underlying neural circuits. Here, we describe a novel approach to record and optogenetically manipulate neural activity in awake, behaving marmosets. Our design utilizes a light-weight, 3D printed titanium chamber that can house several high-density silicon probes for semi-chronic recordings, while enabling simultaneous optogenetic stimulation. We demonstrate the application of our method in male marmosets by recording multi- and single-unit data from areas V1 and V6 with 192 channels simultaneously, and show that optogenetic activation of excitatory neurons in area V6 can influence behavior in a detection task. This method may enable future studies to investigate the neural basis of perception and behavior in the marmoset.

Systems consolidation—a process for long-term memory stabilization—has been hypothesized to occur in two stages 1–4 . Whereas new memories require the hippocampus 5–9 , they become integrated into cortical networks over time 10–12 , making them independent of the hippocampus. How hippocampal–cortical dialogue precisely evolves during this and how cortical representations change in concert is unknown. Here, we use a skill learning task 13,14 to monitor the dynamics of cross-area coupling during non-rapid eye movement sleep along with changes in primary motor cortex (M1) representational stability. Our results indicate that precise cross-area coupling between hippocampus, prefrontal cortex and M1 can demarcate two distinct stages of processing. We specifically find that each animal demonstrates a sharp increase in prefrontal cortex and M1 sleep slow oscillation coupling with stabilization of performance. This sharp increase then predicts a drop in hippocampal sharp-wave ripple (SWR)–M1 slow oscillation coupling—suggesting feedback to inform hippocampal disengagement and transition to a second stage. Notably, the first stage shows significant increases in hippocampal SWR–M1 slow oscillation coupling in the post-training sleep and is closely associated with rapid learning and variability of the M1 low-dimensional manifold. Strikingly, even after consolidation, inducing new manifold exploration by changing task parameters re-engages hippocampal–M1 coupling. We thus find evidence for dynamic hippocampal–cortical dialogue associated with manifold exploration during learning and adaptation.

Sharp wave/ripples/high frequency events (HFEs) are transient bursts of depolarization in hippocampal subregions CA3 and CA1 that occur during rest and pauses in behavior. Previous studies have reported that CA1 ripples in aged rats have lower frequency than those detected in young animals. While CA1 ripples are thought to be driven by CA3, HFEs in CA3 have not been examined in aged animals. The current study obtained simultaneous recordings from CA1 and CA3 in young and aged rats to examine sharp wave/ripples/HFEs in relation to age. While CA1 ripple frequency was reduced with age, there were no age differences in the frequency of CA3 HFEs, although power and length were lower in old animals. While there was a proportion of CA1 ripples that co-occurred with a CA3 HFE, none of the age-related differences in CA1 ripples could be explained by alterations in CA3 HFE characteristics. These findings suggest that age differences in CA1 are not due to altered CA3 activity, but instead reflect distinct mechanisms of ripple generation with age.

The marmoset has emerged as a promising primate model system, in particular for visual neuroscience. Many common experimental paradigms rely on head fixation and an extended period of eye fixation during the presentation of salient visual stimuli. Both of these behavioral requirements can be challenging for marmosets. Here, we present two methodological developments, each addressing one of these difficulties. First, we show that it is possible to use a standard eye-tracking system without head fixation to assess visual behavior in the marmoset. Eye-tracking quality from head-free animals is sufficient to obtain precise psychometric functions from a visual acuity task. Second, we introduce a novel method for efficient receptive field (RF) mapping that does not rely on moving stimuli but uses fast flashing annuli and wedges. We present data recorded during head-fixation in areas V1 and V6 and show that RF locations are readily obtained within a short period of recording time. Thus, the methodological advancements presented in this work will contribute to establish the marmoset as a valuable model in neuroscience.

Background Electrical stimulation of residual afferent nerve fibers can evoke sensations from a missing limb after amputation, and bionic arms endowed with artificial sensory feedback have been shown to confer functional and psychological benefits. Here we explore the extent to which artificial sensations can be discriminated based on location, quality, and intensity. Methods We implanted Utah Slanted Electrode Arrays (USEAs) in the arm nerves of three transradial amputees and delivered electrical stimulation via different electrodes and frequencies to produce sensations on the missing hand with various locations, qualities, and intensities. Participants performed blind discrimination trials to discriminate among these artificial sensations. Results Participants successfully discriminated cutaneous and proprioceptive sensations ranging in location, quality and intensity. Performance was significantly greater than chance for all discrimination tasks, including discrimination among up to ten different cutaneous location-intensity combinations (15/30 successes, p < 0.0001) and seven different proprioceptive location-intensity combinations (21/40 successes, p < 0.0001). Variations in the site of stimulation within the nerve, via electrode selection, enabled discrimination among up to five locations and qualities (35/35 successes, p < 0.0001). Variations in the stimulation frequency enabled discrimination among four different intensities at the same location (13/20 successes, p < 0.0005). One participant also discriminated among individual stimulation of two different USEA electrodes, simultaneous stimulation on both electrodes, and interleaved stimulation on both electrodes (20/24 successes, p < 0.0001). Conclusion Electrode location, stimulation frequency, and stimulation pattern can be modulated to evoke functionally discriminable sensations with a range of locations, qualities, and intensities. This rich source of artificial sensory feedback may enhance functional performance and embodiment of bionic arms endowed with a sense of touch.

A major frontier in neuroscience is to find neural correlates of perception, learning, decision making, and a variety of other types of behavior. In the last decades, modern devices allow simultaneous recordings of different operant responses and the electrical activity of large neuronal populations. However, the commercially available instruments for studying operant conditioning are expensive, and the design of low-cost chambers has emerged as an appealing alternative to resource-limited laboratories engaged in animal behavior. In this article, we provide a full description of a platform that records the operant behavior and synchronizes it with the electrophysiological activity. The programming of this platform is open source, flexible, and adaptable to a wide range of operant conditioning tasks. We also show results of operant conditioning experiments with freely moving rats with simultaneous electrophysiological recordings.

As we navigate in space, external landmarks and internal information guide our movement. Circuit and synaptic mechanisms that integrate these cues with head-direction (HD) signals remain, however, unclear. We identify an excitatory synaptic projection from the presubiculum (PreS) and the multisensory-associative retrosplenial cortex (RSC) to the anterodorsal thalamic reticular nucleus (TRN), so far classically implied in gating sensory information flow. In vitro, projections to TRN involve AMPA/NMDA-type glutamate receptors that initiate TRN cell burst discharge and feedforward inhibition of anterior thalamic nuclei. In vivo, chemogenetic anterodorsal TRN inhibition modulates PreS/RSC-induced anterior thalamic firing dynamics, broadens the tuning of thalamic HD cells, and leads to preferential use of allo- over egocentric search strategies in the Morris water maze. TRN-dependent thalamic inhibition is thus an integral part of limbic navigational circuits wherein it coordinates external sensory and internal HD signals to regulate the choice of search strategies during spatial navigation.

Tactile working memory engages a broad network of cortical regions in primates. To assess whether the conclusions drawn from primates apply to rodents, we examined the vibrissal primary somatosensory cortex (vS1) and the prelimbic cortex (PL) in a delayed comparison task. Rats compared the speeds of two vibrissal vibrations, stimulus1 and stimulus2, separated by a delay of 2 s. Neuronal firing rates in vS1 and PL encode both stimuli in real time. Across the delay, the stimulus1 representation declines more precipitously in vS1 than in PL. Theta-band local field potential (LFP) coherence between vS1 and PL peaks at trial onset and remains elevated during the interstimulus interval; simultaneously, vS1 spikes become phase locked to PL LFP. Phase locking is stronger on correct (versus error) trials. Tactile working memory in rats appears to be mediated by a posterior (vS1) to anterior (PL) flow of information, with performance facilitated through coherent LFP oscillation.

Background Primate distal forelimb behaviors are commonly assessed using reach-to-grasp tasks. While these tasks are widely recognized as sensitive assays for forelimb function, they often require experimenter input, lack precise temporal cues for physiological monitoring, and can be expensive. New Method Using components developed by open-source electronics platforms, we have designed and tested a low-cost system to measure distal forelimb function in non-human primates. Our system is inexpensive; it is made primarily of acrylic and 3D printed plastic parts. Our control software, developed in MATLAB, was also used to control two cameras in order to capture and process video during behavior. The system was equipped with sensors, motors and microcontrollers to control the timing of the task and facilitate synchronization between behavior and neurophysiology with high temporal precision. Results We demonstrate that this system can be used to monitor motor recovery after stroke and investigate neurophysiological correlates of motor control. Comparison with Existing Methods Compared to a previous version of this task, our setup reduces experimenter input while providing unbiased delivery of behavioral cues and behavioral measurements with the temporal precision necessary for electrophysiological studies. Conclusions In summary, our system will allow unbiased monitoring of forelimb function in both healthy and injured animals that is compatible with electrophysiological studies.

To better understand how object recognition can be triggered independently of the sensory channel through which information is acquired, we devised a task in which rats judged the orientation of a raised, black and white grating. They learned to recognize two categories of orientation: 0° ± 45° ("horizontal") and 90° ± 45° ("vertical"). Each trial required a visual (V), a tactile (T), or a visual-tactile (VT) discrimination; VT performance was better than that predicted by optimal linear combination of V and T signals, indicating synergy between sensory channels. We examined posterior parietal cortex (PPC) and uncovered key neuronal correlates of the behavioral findings: PPC carried both graded information about object orientation and categorical information about the rat's upcoming choice; single neurons exhibited identical responses under the three modality conditions. Finally, a linear classifier of neuronal population firing replicated the behavioral findings. Taken together, these findings suggest that PPC is involved in the supramodal processing of shape.