Methylphenidate, but not citalopram, decreases impulsive choice in rats performing a temporal discounting task.

Introduction: Drugs targeting monoamine systems remain the most common treatment for disorders with impulse control impairments. There is a body of literature suggesting that drugs affecting serotonin reuptake and dopamine reuptake can modulate distinct aspects of impulsivity - though such tests are often performed using distinct behavioral tasks prohibiting easy comparisons. Methods: Here, we directly compare pharmacologic agents that affect dopamine (methylphenidate) vs serotonin (citalopram) manipulations on choice impulsivity in a temporal discounting task where rats could choose between a small, immediate reward or a large reward delayed at either 2 or 10s. In control conditions, rats preferred the large reward at a small (2s) delay and discounted the large reward at a long (10s) delay. Results: Methylphenidate, a dopamine transport inhibitor that blocks reuptake of dopamine, dose-dependently increased large reward preference in the long delay (10s) block. Citalopram, a selective serotonin reuptake inhibitor, had no effect on temporal discounting behavior. Impulsive behavior on the temporal discounting task was at least partially mediated by the nucleus accumbens shell. Bilateral lesions to the nucleus accumbens shell reduced choice impulsivity during the long delay (10s) block. Following lesions, methylphenidate did not impact impulsivity. Discussion: Our results suggest that striatal dopaminergic systems modulate choice impulsivity via actions within the nucleus accumbens shell, whereas serotonin systems may regulate different aspects of behavioral inhibition/impulsivity.

Behavioral Interventions Can Improve Brain Injury-Induced Deficits in Behavioral Flexibility and Impulsivity Linked to Impaired Reward-Feedback Beta Oscillations.

Traumatic brain injury (TBI) affects a large population, resulting in severe cognitive impairments. Although cognitive rehabilitation is an accepted treatment for some deficits, studies in patients are limited in ability to probe physiological and behavioral mechanisms. Therefore, animal models are needed to optimize strategies. Frontal TBI in a rat model results in robust and replicable cognitive deficits, making this an ideal candidate for investigating various behavioral interventions. In this study, we report three distinct frontal TBI experiments assessing behavior well into the chronic post-injury period using male Long-Evans rats. First, we evaluated the impact of frontal injury on local field potentials recorded simultaneously from 12 brain regions during a probabilistic reversal learning (PbR) task. Next, a set of rats were tested on a similar PbR task or an impulsivity task (differential reinforcement of low-rate behavior [DRL]) and half received salient cues associated with reinforcement contingencies to encourage engagement in the target behavior. After intervention on the PbR task, brains were stained for markers of activity. On the DRL task, cue relevance was decoupled from outcomes to determine if beneficial effects persisted on impulsive behavior. TBI decreased the ability to detect reinforced outcomes; this was evident in task performance and reward-feedback signals occurring at beta frequencies in lateral orbitofrontal cortex (OFC) and associated frontostriatal regions. The behavioral intervention improved flexibility and increased OFC activity. Intervention also reduced impulsivity, even after cues were decoupled, which was partially mediated by improvements in timing behavior. The current study established a platform to begin investigating cognitive rehabilitation in rats and identified a strong role for dysfunctional OFC signaling in probabilistic learning after frontal TBI.

A generalized reinforcement learning based deep neural network agent model for diverse cognitive constructs.

Human cognition is characterized by a wide range of capabilities including goal-oriented selective attention, distractor suppression, decision making, response inhibition, and working memory. Much research has focused on studying these individual components of cognition in isolation, whereas in several translational applications for cognitive impairment, multiple cognitive functions are altered in a given individual. Hence it is important to study multiple cognitive abilities in the same subject or, in computational terms, model them using a single model. To this end, we propose a unified, reinforcement learning-based agent model comprising of systems for representation, memory, value computation and exploration. We successfully modeled the aforementioned cognitive tasks and show how individual performance can be mapped to model meta-parameters. This model has the potential to serve as a proxy for cognitively impaired conditions, and can be used as a clinical testbench on which therapeutic interventions can be simulated first before delivering to human subjects.

Theta Burst Stimulation Is Not Inferior to High-Frequency Repetitive Transcranial Magnetic Stimulation in Reducing Symptoms of Posttraumatic Stress Disorder in Veterans With Depression: A Retrospective Case Series.

OBJECTIVES: Two commonly used forms of repetitive transcranial magnetic stimulation (rTMS) were recently shown to be equivalent for the treatment of depression: high-frequency stimulation (10 Hz), a protocol that lasts between 19 and 38 minutes, and intermittent theta burst stimulation (iTBS), a protocol that can be delivered in just three minutes. However, it is unclear whether iTBS treatment offers the same benefits as those of standard 10-Hz rTMS for comorbid symptoms such as those seen in posttraumatic stress disorder (PTSD). MATERIALS AND METHODS: In this retrospective case series, we analyzed treatment outcomes in veterans from the Veterans Affairs San Diego Healthcare System who received 10-Hz (n = 47) or iTBS (n = 51)-rTMS treatments for treatment-resistant depression between February 2018 and June 2022. We compared outcomes between these two stimulation protocols in symptoms of depression (using changes in the Patient Health Questionnaire-9 [PHQ-9]) and PTSD (using changes in the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, or Patient Checklist [PCL]-5). RESULTS: There was an imbalance of sex between groups (p < 0.05). After controlling for sex, we found no significant difference by stimulation protocol for depression (PHQ-9, F [1,94] = 0.16, p = 0.69, eta-squared = 0.002), confirming the original study previously noted. We also showed no difference by stimulation protocol of changes in PTSD symptoms (PCL-5, F [1,94] = 3.46, p = 0.067, eta-squared = 0.036). The iTBS group showed a decrease from 41.9 ± 4.4 to 25.1 ± 4.9 (a difference of 16.8 points) on the PCL-5 scale whereas the 10-Hz group showed a decrease from 43.6 ± 2.9 to 35.2 ± 3.2 on this scale (a difference of 8.4 points). Follow-up analyses restricting the sample in various ways did not meaningfully change these results (no follow-up analyses showed that there was a significant difference between stimulation protocols). CONCLUSIONS: Although limited by small sample size, nonblind, and pseudorandomized assignment, our data suggest that iTBS is similar to 10-Hz stimulation in inducing reductions in PTSD symptoms and depression in military veterans.

Modulation of ventromedial orbitofrontal cortical glutamatergic activity affects the explore-exploit balance and influences value-based decision-making.

The balance between exploration and exploitation is essential for decision-making. The present study investigated the role of ventromedial orbitofrontal cortex (vmOFC) glutamate neurons in mediating value-based decision-making by first using optogenetics to manipulate vmOFC glutamate activity in rats during a probabilistic reversal learning (PRL) task. Rats that received vmOFC activation during informative feedback completed fewer reversals and exhibited reduced reward sensitivity relative to rats. Analysis with a Q-learning computational model revealed that increased vmOFC activity did not affect the learning rate but instead promoted maladaptive exploration. By contrast, vmOFC inhibition increased the number of completed reversals and increased exploitative behavior. In a separate group of animals, calcium activity of vmOFC glutamate neurons was recorded using fiber photometry. Complementing our results above, we found that suppression of vmOFC activity during the latter part of rewarded trials was associated with improved PRL performance, greater win-stay responding and selecting the correct choice on the next trial. These data demonstrate that excessive vmOFC activity during reward feedback disrupted value-based decision-making by increasing the maladaptive exploration of lower-valued options. Our findings support the premise that pharmacological interventions that normalize aberrant vmOFC glutamate activity during reward feedback processing may attenuate deficits in value-based decision-making.

Recovery of consolidation after sleep following stroke-interaction of slow waves, spindles, and GABA.

Sleep is known to promote recovery after stroke. Yet it remains unclear how stroke affects neural processing during sleep. Using an experimental stroke model in rats along with electrophysiological monitoring of neural firing and sleep microarchitecture, here we show that sleep processing is altered by stroke. We find that the precise coupling of spindles to global slow oscillations (SOs), a phenomenon that is known to be important for memory consolidation, is disrupted by a pathological increase in "isolated" local delta waves. The transition from this pathological to a physiological state-with increased spindle coupling to SO-is associated with sustained performance gains during recovery. Interestingly, post-injury sleep could be pushed toward a physiological state via a pharmacological reduction of tonic γ-aminobutyric acid (GABA). Together, our results suggest that sleep processing after stroke is impaired due to an increase in delta waves and that its restoration can be important for recovery.

Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs.

Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. Next, we provide an overview of the application, rationale, and therapeutic aspects of CLNM for clinical purposes. Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.

Coupling between motor cortex and striatum increases during sleep over long-term skill learning.

The strength of cortical connectivity to the striatum influences the balance between behavioral variability and stability. Learning to consistently produce a skilled action requires plasticity in corticostriatal connectivity associated with repeated training of the action. However, it remains unknown whether such corticostriatal plasticity occurs during training itself or 'offline' during time away from training, such as sleep. Here, we monitor the corticostriatal network throughout long-term skill learning in rats and find that non-rapid-eye-movement (NREM) sleep is a relevant period for corticostriatal plasticity. We first show that the offline activation of striatal NMDA receptors is required for skill learning. We then show that corticostriatal functional connectivity increases offline, coupled to emerging consistent skilled movements, and coupled cross-area neural dynamics. We then identify NREM sleep spindles as uniquely poised to mediate corticostriatal plasticity, through interactions with slow oscillations. Our results provide evidence that sleep shapes cross-area coupling required for skill learning.

Electrophysiological Correlates of Rodent Default-Mode Network Suppression Revealed by Large-Scale Local Field Potential Recordings.

The default-mode network (DMN) in humans consists of a set of brain regions that, as measured with functional magnetic resonance imaging (fMRI), show both intrinsic correlations with each other and suppression during externally oriented tasks. Resting-state fMRI studies have previously identified similar patterns of intrinsic correlations in overlapping brain regions in rodents (A29C/posterior cingulate cortex, parietal cortex, and medial temporal lobe structures). However, due to challenges with performing rodent behavior in an MRI machine, it is still unclear whether activity in rodent DMN regions are suppressed during externally oriented visual tasks. Using distributed local field potential measurements in rats, we have discovered that activity in DMN brain regions noted above show task-related suppression during an externally oriented visual task at alpha and low beta-frequencies. Interestingly, this suppression (particularly in posterior cingulate cortex) was linked with improved performance on the task. Using electroencephalography recordings from a similar task in humans, we identified a similar suppression of activity in posterior cingulate cortex at alpha/low beta-frequencies. Thus, we have identified a common electrophysiological marker of DMN suppression in both rodents and humans. This observation paves the way for future studies using rodents to probe circuit-level functioning of DMN function. SIGNIFICANCE: Here we show that alpha/beta frequency oscillations in rats show key features of DMN activity, including intrinsic correlations between DMN brain regions, task-related suppression, and interference with attention/decision-making. We found similar task-related suppression at alpha/low beta-frequencies of DMN activity in humans.

Emergent modular neural control drives coordinated motor actions.

A remarkable feature of motor control is the ability to coordinate movements across distinct body parts into a consistent, skilled action. To reach and grasp an object, 'gross' arm and 'fine' dexterous movements must be coordinated as a single action. How the nervous system achieves this coordination is currently unknown. One possibility is that, with training, gross and fine movements are co-optimized to produce a coordinated action; alternatively, gross and fine movements may be modularly refined to function together. To address this question, we recorded neural activity in the primary motor cortex and dorsolateral striatum during reach-to-grasp skill learning in rats. During learning, the refinement of fine and gross movements was behaviorally and neurally dissociable. Furthermore, inactivation of the primary motor cortex and dorsolateral striatum had distinct effects on skilled fine and gross movements. Our results indicate that skilled movement coordination is achieved through emergent modular neural control.

Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke.

Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; <4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation.

Neural reactivations during sleep determine network credit assignment.

A fundamental goal of motor learning is to establish the neural patterns that produce a desired behavioral outcome. It remains unclear how and when the nervous system solves this 'credit assignment' problem. Using neuroprosthetic learning, in which we could control the causal relationship between neurons and behavior, we found that sleep-dependent processing was required for credit assignment and the establishment of task-related functional connectivity reflecting the casual neuron-behavior relationship. Notably, we observed a strong link between the microstructure of sleep reactivations and credit assignment, with downscaling of non-causal activity. Decoupling of spiking to slow oscillations using optogenetic methods eliminated rescaling. Thus, our results suggest that coordinated firing during sleep is essential for establishing sparse activation patterns that reflect the causal neuron-behavior relationship.

Sleep-Dependent Reactivation of Ensembles in Motor Cortex Promotes Skill Consolidation.

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.

Robust neuroprosthetic control from the stroke perilesional cortex.

Intracortical brain-machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the development of intracortical BMIs has focused on subjects with largely intact cortical structures, such as those with spinal cord injury. Although the stroke perilesional cortex (PLC) has been hypothesized as a potential site for a BMI, it remains unclear whether the injured motor cortical network can support neuroprosthetic control directly. Using chronic electrophysiological recordings in a rat stroke model, we demonstrate here the PLC's capacity for neuroprosthetic control and physiological plasticity. We initially found that the perilesional network demonstrated abnormally increased slow oscillations that also modulated neural firing. Despite these striking abnormalities, neurons in the perilesional network could be modulated volitionally to learn neuroprosthetic control. The rate of learning was surprisingly similar regardless of the electrode distance from the stroke site and was not significantly different from intact animals. Moreover, neurons achieved similar task-related modulation and, as an ensemble, formed cell assemblies with learning. Such control was even achieved in animals with poor motor recovery, suggesting that neuroprosthetic control is possible even in the absence of motor recovery. Interestingly, achieving successful control also reduced locking to abnormal oscillations significantly. Our results thus suggest that, despite the disrupted connectivity in the PLC, it may serve as an effective target for neuroprosthetic control in those with poor motor recovery after stroke.

An automated behavioral box to assess forelimb function in rats.

BACKGROUND: Rodent forelimb reaching behaviors are commonly assessed using a single-pellet reach-to-grasp task. While the task is widely recognized as a very sensitive measure of distal limb function, it is also known to be very labor-intensive, both for initial training and the daily assessment of function. NEW METHOD: Using components developed by open-source electronics platforms, we have designed and tested a low-cost automated behavioral box to measure forelimb function in rats. Our apparatus, made primarily of acrylic, was equipped with multiple sensors to control the duration and difficulty of the task, detect reach outcomes, and dispense pellets. Our control software, developed in MATLAB, was also used to control a camera in order to capture and process video during reaches. Importantly, such processing could monitor task performance in near real-time. RESULTS: We further demonstrate that the automated apparatus can be used to expedite skill acquisition, thereby increasing throughput as well as facilitating studies of early versus late motor learning. The setup is also readily compatible with chronic electrophysiological monitoring. COMPARISON WITH EXISTING METHODS: Compared to a previous version of this task, our setup provides a more efficient method to train and test rodents for studies of motor learning and recovery of function after stroke. The unbiased delivery of behavioral cues and outcomes also facilitates electrophysiological studies. CONCLUSIONS: In summary, our automated behavioral box will allow high-throughput and efficient monitoring of rat forelimb function in both healthy and injured animals.

Cholinergic systems are essential for late-stage maturation and refinement of motor cortical circuits.

Previous studies reported that early postnatal cholinergic lesions severely perturb early cortical development, impairing neuronal cortical migration and the formation of cortical dendrites and synapses. These severe effects of early postnatal cholinergic lesions preclude our ability to understand the contribution of cholinergic systems to the later-stage maturation of topographic cortical representations. To study cholinergic mechanisms contributing to the later maturation of motor cortical circuits, we first characterized the temporal course of cortical motor map development and maturation in rats. In this study, we focused our attention on the maturation of cortical motor representations after postnatal day 25 (PND 25), a time after neuronal migration has been accomplished and cortical volume has reached adult size. We found significant maturation of cortical motor representations after this time, including both an expansion of forelimb representations in motor cortex and a shift from proximal to distal forelimb representations to an extent unexplainable by simple volume enlargement of the neocortex. Specific cholinergic lesions placed at PND 24 impaired enlargement of distal forelimb representations in particular and markedly reduced the ability to learn skilled motor tasks as adults. These results identify a novel and essential role for cholinergic systems in the late refinement and maturation of cortical circuits. Dysfunctions in this system may constitute a mechanism of late-onset neurodevelopmental disorders such as Rett syndrome and schizophrenia.

Reactivation of emergent task-related ensembles during slow-wave sleep after neuroprosthetic learning.

Brain-machine interfaces can allow neural control over assistive devices. They also provide an important platform for studying neural plasticity. Recent studies have suggested that optimal engagement of learning is essential for robust neuroprosthetic control. However, little is known about the neural processes that may consolidate a neuroprosthetic skill. On the basis of the growing body of evidence linking slow-wave activity (SWA) during sleep to consolidation, we examined whether there is 'offline' processing after neuroprosthetic learning. Using a rodent model, we found that, after successful learning, task-related units specifically experienced increased locking and coherency to SWA during sleep. Moreover, spike-spike coherence among these units was substantially enhanced. These changes were not present with poor skill acquisition or after control awake periods, demonstrating the specificity of our observations to learning. Notably, the time spent in SWA predicted the performance gains. Thus, SWA appears to be involved in offline processing after neuroprosthetic learning.

The role of spatial attention in the selection of real and illusory objects.

Selective attention may be flexibly directed toward particular locations in the visual field (spatial attention) or to entire object configurations (object-based attention). A key question is whether spatial attention plays a direct role in the selection of objects, perhaps by spreading its facilitatory influence throughout the boundaries of an object. We studied the relationship between spatial and object-based attention in a design in which subjects attended to brief offsets of one corner of a real or illusory square form. Object-selective attention was indexed by differences in event-related potential (ERP) amplitudes and blood oxygen level-dependent (BOLD) activations to unattended corner offsets in conditions in which the objects were intact versus fragmented or absent. This design ensured that object-based attention effects were not an artifact of attention being guided by simple directional cues such as parallel lines, which may have occurred in previous studies. Both space-based and object-based attention were associated with enhanced negative ERPs (N1 component at 140-180 ms) that were colocalized with BOLD activations in lateral occipital cortex (LOC). These results provide physiological evidence that directing spatial attention to one part of an object (whether real or illusory) facilitates the processing of the entire object at the level of the LOC and thus contributes directly to object-based selective attention.