Behavioral Neuroscience publications

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.

Dopamine (DA) is a central monoamine neurotransmitter involved in many physiological and pathological processes. A longstanding yet largely unmet goal is to measure DA changes reliably and specifically with high spatiotemporal precision, particularly in animals executing complex behaviors. Here we report the development of novel genetically-encoded GPCR-Activation-Based-DA (GRAB DA ) sensors that enable these measurements. In response to extracellular DA rises, GRAB DA sensors exhibit large fluorescence increases (ΔF/F 0 ∼90%) with sub-second kinetics, nanomolar to sub-micromolar affinities, and excellent molecular specificity. Importantly, GRABDA sensors can resolve a single-electrical-stimulus evoked DA release in mouse brain slices, and detect endogenous DA release in the intact brains of flies, fish, and mice. In freely-behaving mice, GRABDA sensors readily report optogenetically-elicited nigrostriatal DA release and depict dynamic mesoaccumbens DA changes during Pavlovian conditioning or during sexual behaviors. Thus, GRAB DA sensors enable spatiotemporal precise measurements of DA dynamics in a variety of model organisms while exhibiting complex behaviors.

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.

The subthalamic nucleus (STN) is hypothesized to play a central role in the rapid stopping of movement in reaction to a stop signal. Single-unit recording evidence for such a role is sparse, however, and it remains uncertain how that role relates to the disparate functions described for anatomic subdivisions of the STN. Here we address that gap in knowledge using non-human primates and a task that distinguishes reactive and proactive action inhibition, switching and skeletomotor functions. We found that specific subsets of STN neurons have activity consistent with causal roles in reactive action stopping or switching. Importantly, these neurons were strictly segregated to a ventromedial region of STN. Neurons in other subdivisions encoded task dimensions such as movement per se and proactive control. We propose that the involvement of STN in reactive control is restricted to its ventromedial portion, further implicating this STN subdivision in impulse control disorders.

To better understand how a stream of sensory data is transformed into a percept, we examined neuronal activity in vibrissal sensory cortex, vS1, together with vibrissal motor cortex, vM1 (a frontal cortex target of vS1), while rats compared the intensity of two vibrations separated by an interstimulus delay. Vibrations were "noisy," constructed by stringing together over time a sequence of velocity values sampled from a normal distribution; each vibration's mean speed was proportional to the width of the normal distribution. Durations of both stimulus 1 and stimulus 2 could vary from 100 to 600 ms. Psychometric curves reveal that rats overestimated the longer-duration stimulus-thus, perceived intensity of a vibration grew over the course of hundreds of milliseconds even while the sensory input remained, on average, stationary. Human subjects demonstrated the identical perceptual phenomenon, indicating that the underlying mechanisms of temporal integration generalize across species. The time dependence of the percept allowed us to ask to what extent neurons encoded the ongoing stimulus stream versus the animal's percept. We demonstrate that vS1 firing correlated with the local features of the vibration, whereas vM1 firing correlated with the percept: the final vM1 population state varied, as did the rat's behavior, according to both stimulus speed and stimulus duration. Moreover, vM1 populations appeared to participate in the trace of the percept of stimulus 1 as the rat awaited stimulus 2. In conclusion, the transformation of sensory data into the percept appears to involve the integration and storage of vS1 signals by vM1.

Impaired motivation is present in a variety of neurological disorders, suggesting that decreased motivation is caused by broad dysfunction of the nervous system across a variety of circuits. Based on evidence that impaired motivation is a major symptom in the early stages of Huntington’s disease, when dopamine receptor type 2-expressing striatal medium spiny neurons (D2-MSNs) are particularly affected, we hypothesize that degeneration of these neurons would be a key node regulating motivational status. Using a progressive, time-controllable, diphtheria toxin-mediated cell ablation/dysfunction technique, we find that loss-of-function of D2-MSNs within ventrolateral striatum (VLS) is sufficient to reduce goal-directed behaviours without impairing reward preference or spontaneous behaviour. Moreover, optogenetic inhibition and ablation of VLS D2-MSNs causes, respectively, transient and chronic reductions of goal-directed behaviours. Our data demonstrate that the circuitry containing VLS D2-MSNs control motivated behaviours and that VLS D2-MSN loss-of-function is a possible cause of motivation deficits in neurodegenerative diseases.

The pulvinar complex is interconnected extensively with brain regions involved in spatial processing and eye movement control. Recent inactivation studies have shown that the dorsal pulvinar (dPul) plays a role in saccade target selection; however, it remains unknown whether it exerts effects on visual processing or at planning/execution stages. We used electrical microstimulation of the dPul while monkeys performed saccade tasks toward instructed and freely chosen targets. Timing of stimulation was varied, starting before, at, or after onset of target(s). Stimulation affected saccade properties and target selection in a time-dependent manner. Stimulation starting before but overlapping with target onset shortened saccadic reaction times (RTs) for ipsiversive (to the stimulation site) target locations, whereas stimulation starting at and after target onset caused systematic delays for both ipsiversive and contraversive locations. Similarly, stimulation starting before the onset of bilateral targets increased ipsiversive target choices, whereas stimulation after target onset increased contraversive choices. Properties of dPul neurons and stimulation effects were consistent with an overall contraversive drive, with varying outcomes contingent upon behavioral demands. RT and choice effects were largely congruent in the visually-guided task, but stimulation during memory-guided saccades, while influencing RTs and errors, did not affect choice behavior. Together, these results show that the dPul plays a primary role in action planning as opposed to visual processing, that it exerts its strongest influence on spatial choices when decision and action are temporally close, and that this choice effect can be dissociated from motor effects on saccade initiation and execution. SIGNIFICANCE STATEMENT Despite a recent surge of interest, the core function of the pulvinar, the largest thalamic complex in primates, remains elusive. This understanding is crucial given the central role of the pulvinar in current theories of integrative brain functions supporting cognition and goal-directed behaviors, but electrophysiological and causal interference studies of dorsal pulvinar (dPul) are rare. Building on our previous studies that pharmacologically suppressed dPul activity for several hours, here we used transient electrical microstimulation at different periods while monkeys performed instructed and choice eye movement tasks, to determine time-specific contributions of pulvinar to saccade generation and decision making. We show that stimulation effects depend on timing and behavioral state and that effects on choices can be dissociated from motor effects.

The objective of this study was to demonstrate the efficacy of acute inactivation of brain areas by cooling in the behaving ferret and to demonstrate that cooling auditory cortex produced a localisation deficit that was specific to auditory stimuli. The effect of cooling on neural activity was measured in anesthetized ferret cortex. The behavioural effect of cooling was determined in a benchmark sound localisation task in which inactivation of primary auditory cortex (A1) is known to impair performance. Cooling strongly suppressed the spontaneous and stimulus-evoked firing rates of cortical neurons when the cooling loop was held at temperatures below 10°C, and this suppression was reversed when the cortical temperature recovered. Cooling of ferret auditory cortex during behavioural testing impaired sound localisation performance, with unilateral cooling producing selective deficits in the hemifield contralateral to cooling, and bilateral cooling producing deficits on both sides of space. The deficit in sound localisation induced by inactivation of A1 was not caused by motivational or locomotor changes since inactivation of A1 did not affect localisation of visual stimuli in the same context.

Persistent activity has been reported in many brain areas and is hypothesized to mediate working memory and emotional brain states and to rely upon network or biophysical feedback. Here, we demonstrate a novel mechanism by which persistent neuronal activity can be generated without feedback, relying instead on the slow removal of Na+ from neurons following bursts of activity. We show that mitral cells in the accessory olfactory bulb (AOB), which plays a major role in mammalian social behavior, may respond to a brief sensory stimulation with persistent firing. By combining electrical recordings, Ca2+ and Na+ imaging, and realistic computational modeling, we explored the mechanisms underlying the persistent activity in AOB mitral cells. We found that the exceptionally slow inward current that underlies this activity is governed by prolonged dynamics of intracellular Na+ ([Na+]i), which affects neuronal electrical activity via several pathways. Specifically, elevated dendritic [Na+]i reverses the Na+-Ca2+ exchanger activity, thus modifying the [Ca2+]i set-point. This process, which relies on ubiquitous membrane mechanisms, is likely to play a role in other neuronal types in various brain regions.

Despite many prior studies demonstrating offline behavioral gains in motor skills after sleep, the underlying neural mechanisms remain poorly understood. To investigate the neurophysiological basis for offline gains, we performed single-unit recordings in motor cortex as rats learned a skilled upper-limb task. We found that sleep improved movement speed with preservation of accuracy. These offline improvements were linked to both replay of task-related ensembles during non-rapid eye movement (NREM) sleep and temporal shifts that more tightly bound motor cortical ensembles to movements; such offline gains and temporal shifts were not evident with sleep restriction. Interestingly, replay was linked to the coincidence of slow-wave events and bursts of spindle activity. Neurons that experienced the most consistent replay also underwent the most significant temporal shift and binding to the motor task. Significantly, replay and the associated performance gains after sleep only occurred when animals first learned the skill; continued practice during later stages of learning (i.e., after motor kinematics had stabilized) did not show evidence of replay. Our results highlight how replay of synchronous neural activity during sleep mediates large-scale neural plasticity and stabilizes kinematics during early motor learning.

Acute seizures after a severe brain insult can often lead to epilepsy and cognitive impairment. Aberrant hippocampal neurogenesis follows the insult but the role of adult-generated neurons in the development of chronic seizures or associated cognitive deficits remains to be determined. Here we show that the ablation of adult neurogenesis before pilocarpine-induced acute seizures in mice leads to a reduction in chronic seizure frequency. We also show that ablation of neurogenesis normalizes epilepsy-associated cognitive deficits. Remarkably, the effect of ablating adult neurogenesis before acute seizures is long lasting as it suppresses chronic seizure frequency for nearly 1 year. These findings establish a key role of neurogenesis in chronic seizure development and associated memory impairment and suggest that targeting aberrant hippocampal neurogenesis may reduce recurrent seizures and restore cognitive function following a pro-epileptic brain insult.

The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns.

Fast-scan cyclic voltammetry (FSCV) is often used to measure real-time dopamine (DA) concentrations in awake, behaving rodents. Extending this technique to work in monkeys would provide a platform for advanced behavioral studies and a primate model for preclinical research. The present study demonstrates the feasibility of DA recordings in two awake monkeys (Macaca mulatta) using a mixture of techniques adapted from rodent, primate and brain slice work. We developed a long carbon fiber electrode to operate in the larger primate brain. This electrode was lowered into the striatum each day using a recording chamber and a detachable micromanipulator system. A manipulator also moved one or more tungsten stimulating electrodes into either the nearby striatum or the ventral tegmental area/substantia nigra pars compacta (VTA/SNc). We developed an electrical stimulation controller to reduce artifacts during electrical stimulation. We also introduce a stimulation-based methodology for estimating distances between electrodes in the brain. Dopamine responses within the striatum were evoked by either stimulation of the striatum near the FSCV electrode, or stimulation within the VTA/SNc. Unexpected juice rewards also evoked dopamine responses in the ventral striatum. Thus, we demonstrate that robust dopamine responses can be recorded from awake, behaving primates with FSCV. In addition, we describe how a stimulation technique borrowed from the neuroprosthetics field can activate the distributed monkey midbrain dopamine system in a way that mimics rodent VTA stimulation.

Brain-Machine Interfaces (BMIs) can be used to restore function in people living with paralysis. Current BMIs require extensive calibration that increase the set-up times and external inputs for decoder training that may be difficult to produce in paralyzed individuals. Both these factors have presented challenges in transitioning the technology from research environments to activities of daily living (ADL). For BMIs to be seamlessly used in ADL, these issues should be handled with minimal external input thus reducing the need for a technician/caregiver to calibrate the system. Reinforcement Learning (RL) based BMIs are a good tool to be used when there is no external training signal and can provide an adaptive modality to train BMI decoders. However, RL based BMIs are sensitive to the feedback provided to adapt the BMI. In actor-critic BMIs, this feedback is provided by the critic and the overall system performance is limited by the critic accuracy. In this work, we developed an adaptive BMI that could handle inaccuracies in the critic feedback in an effort to produce more accurate RL based BMIs. We developed a confidence measure, which indicated how appropriate the feedback is for updating the decoding parameters of the actor. The results show that with the new update formulation, the critic accuracy is no longer a limiting factor for the overall performance. We tested and validated the system onthree different data sets: synthetic data generated by an Izhikevich neural spiking model, synthetic data with a Gaussian noise distribution, and data collected from a non-human primate engaged in a reaching task. All results indicated that the system with the critic confidence built in always outperformed the system without the critic confidence. Results of this study suggest the potential application of the technique in developing an autonomous BMI that does not need an external signal for training or extensive calibration.

Improving performance in motor skill acquisition is proposed to be supported by tuning of neural networks. To address this issue we investigated changes of phase-amplitude cross-frequency coupling (paCFC) in neuronal networks during motor performance improvement. We recorded intracranially from subdural electrodes (electrocorticogram; ECoG) from 6 patients who learned 3 distinct motor tasks requiring coordination of finger movements with an external cue (serial response task, auditory motor coordination task, go/no-go). Performance improved in all subjects and all tasks during the first block and plateaued in subsequent blocks. Performance improvement was paralled by increasing neural changes in the trial-to-trial paCFC between theta ([Formula: see text]; 4-8 Hz) phase and high gamma (HG; 80-180 Hz) amplitude. Electrodes showing this covariation pattern (Pearson's r ranging up to .45) were located contralateral to the limb performing the task and were observed predominantly in motor brain regions. We observed stable paCFC when task performance asymptoted. Our results indicate that motor performance improvement is accompanied by adjustments in the dynamics and topology of neuronal network interactions in the [Formula: see text] and HG range. The location of the involved electrodes suggests that oscillatory dynamics in motor cortices support performance improvement with practice.

Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.