We investigated locus coeruleus (LC) modulation of thalamic feature selectivity through reverse correlation analysis of single-unit recordings from different stages of the rat vibrissa pathway. LC activation increased feature selectivity, drastically improving thalamic information transmission. We found this improvement was dependent on both local activation of α-adrenergic receptors and modulation of T-type calcium channels in the thalamus and was not due to LC modulation of trigeminothalamic feedforward or corticothalamic feedback inputs. Tonic spikes with LC stimulation carried 3-times the information than did tonic spikes without LC stimulation. Modelling confirmed norepinephrine (NE) regulation of intrathalamic circuit dynamics led to the improved information transmission. Behavioral data demonstrated that LC activation increased the perceptual performance of animals performing tactile discrimination tasks through LC-NE optimization of thalamic sensory processing. These results suggest a new sub-dimension within the tonic mode in which brain state can optimize thalamic sensory processing through modulation of intrathalamic circuit dynamics.

In decision‐making tasks, neural circuits involved in different aspects of information processing may activate the central arousal system, likely through their interconnection with brainstem arousal nuclei, collectively contributing to the observed pupil‐linked phasic arousal. However, the individual components of the phasic arousal associated with different elements of information processing and their effects on behavior remain little known. In this study, we used machine learning techniques to decompose pupil‐linked phasic arousal evoked by different components of information processing in rats performing a Go/No‐Go perceptual decision‐making task. We found that phasic arousal evoked by stimulus encoding was larger for the Go stimulus than the No‐Go stimulus. For each session, the separation between distributions of phasic arousal evoked by the Go and by the No‐Go stimulus was predictive of perceptual performance. The separation between distributions of decision‐formation‐evoked arousal on correct and incorrect trials was correlated with decision criterion but not perceptual performance. When a Go stimulus was presented, the action of go was primarily determined by the phasic arousal evoked by stimulus encoding. On the contrary, when a No‐Go stimulus was presented, the action of go was determined by phasic arousal elicited by both stimulus encoding and decision formation. Drift diffusion modeling revealed that the four model parameters were better accounted for when phasic arousal elicited by both stimulus encoding and decision formation was considered. These results suggest that the interplay between phasic arousal evoked by both stimulus encoding and decision formation has important functional consequences on forming behavioral choice in perceptual decision‐making.

In this review, we provide a brief overview of several of the most thoroughly researched pathogenic hypotheses for Alzheimer's disease (AD) and assess their clinical impact to-date. We focus specifically on recent research into the role of the locus coeruleus norepinephrine (LC-NE) system, in both AD pathogenesis and symptom exacerbation, as well as the potential to use advanced neural stimulation techniques as a novel therapeutic option in the earliest stages of neuropathology.

Objective. Vagus nerve stimulation (VNS) has been FDA-approved as a long-term, therapeutic treatment for multiple disorders, including pharmacoresistant epilepsy and depression. Here we elucidate the short-term effects of VNS on sensory processing. Approach. We employed an information theoretic approach to examine the effects of VNS on thalamocortical transmission of sensory-related information along the somatosensory pathway. Main results. We found that VNS enhanced the selectivity of the response of thalamic neurons to specific kinetic features in the stimuli, resulting in a significant increase in the efficiency and rate of stimulus-related information conveyed by thalamic spikes. VNS-induced improvements in thalamic sensory processing coincided with a decrease in thalamic burst firing. Importantly, we found VNS-induced enhancement of sensory processing had a rapid onset and offset, completely disappearing one minute after cessation of VNS. The timescales of these effects indicate against an underlying mechanism involving long-term neuroplasticity. We found several patterns of VNS (tonic, standard duty-cycle, and fast duty-cycle) all induced similar improvements in sensory processing. Under closer inspection we noticed that due to the fast timescale of VNS effects on sensory processing, standard duty-cycle VNS induced a fluctuating sensory processing state which may be sub-optimal for perceptual behavior. Fast duty-cycle VNS and continuous, tonic VNS induced quantitatively similar improvements in thalamic information transmission as standard duty-cycle VNS without inducing a fluctuating thalamic state. Further, we found the strength of VNS-induced improvements in sensory processing increased monotonically with amplitude and frequency of VNS. Significance. These results demonstrate, for the first time, the feasibility of utilizing specific patterns of VNS to rapidly improve sensory processing and confirm fast duty-cycle and tonic patterns as optimal for this purpose, while showing standard duty-cycle VNS causes non-optimal fluctuations in thalamic state.

Objective. Reorienting is central to how humans direct attention to different stimuli in their environment. Previous studies typically employ well-controlled paradigms with limited eye and head movements to study the neural and physiological processes underlying attention reorienting. Here, we aim to better understand the relationship between gaze and attention reorienting using a naturalistic virtual reality (VR)-based target detection paradigm. Approach. Subjects were navigated through a city and instructed to count the number of targets that appeared on the street. Subjects performed the task in a fixed condition with no head movement and in a free condition where head movements were allowed. Electroencephalography (EEG), gaze and pupil data were collected. To investigate how neural and physiological reorienting signals are distributed across different gaze events, we used hierarchical discriminant component analysis (HDCA) to identify EEG and pupil-based discriminating components. Mixedeffects general linear models (GLM) were used to determine the correlation between these discriminating components and the different gaze events time. HDCA was also used to combine EEG, pupil and dwell time signals to classify reorienting events. Main results. In both EEG and pupil, dwell time contributes most significantly to the reorienting signals. However, when dwell times were orthogonalized against other gaze events, the distributions of the reorienting signals were different across the two modalities, with EEG reorienting signals leading that of the pupil reorienting signals. We also found that the hybrid classifier that integrates EEG, pupil and dwell time features detects the reorienting signals in both the fixed (AUC = 0.79) and the free (AUC = 0.77) condition. Significance. We show that the neural and ocular reorienting signals are distributed differently across gaze events when a subject is immersed in VR, but nevertheless can be captured and integrated to classify target vs. distractor objects to which the human subject orients.

1Brain-machine interfaces (BMIs) for reaching have enjoyed continued performance 2improvements. Yet there remains significant need for locomotor BMIs (e.g., for wheelchair 3 control), which could potentially benefit a much larger patient population. Fewer studies have 4 addressed this need, and the most effective approach remains undetermined. Here, we develop 5 a locomotor BMI based on cortical activity as monkeys cycle a hand-held pedal to progress 6 along a virtual track. Unlike most reach-based BMIs, we did not directly map neural states to 7 commanded velocity or position. Instead, we leveraged features of the neural population 8 response that were robust during rhythmic cycling. These included an overall shift in neural 9 state when moving, and rotational trajectories with direction-specific paths. We used nonlinear 10 means to infer kinematics from these features. Online BMI-control success rates approached 11 those during manual control. Our results illustrate that different use-cases can require very 12 different approaches to guiding a prosthetic via neural activity. 13 14 Brain-machine interfaces (BMIs) interpret neural activity and provide control signals to external 15 devices such as computers and prosthetic limbs. Intracortical BMIs for reach-like tasks have 16 proved successful in primates and human clinical trials 1-8 . More widespread use appears 17imminent. Yet at the same time, there exist non-reach-like movements whose restoration is 18 valuable to patients. For example, many patients could benefit from a BMI that controls 19 locomotion through their environment (e.g., movement of a wheelchair). Recent work has 20 demonstrated that this is feasible 9,10 . While locomotor BMIs can be guided by reach-inspired 21 decoding approaches, other viable strategies exist and remain unexplored. For example, it may 22A decoder that leveraged these dominant features provided excellent online control of virtual 71 locomotion. Success rates and acquisition times were very close to those achieved under manual 72 control. Almost no training or adaptation time was needed; the low-latency and accuracy of the 73 decoder were such that monkeys appeared to barely notice transitions from manual control to 74 BMI control. These results demonstrate the feasibility of BMI locomotion based on rhythmic 75 neural activity. More broadly, they establish that opportunistic decode strategies can work well 76 in non-reach-based scenarios, but that new applications require novel decode approaches that 77 respect the dominant structure of neural activity. 78 79 80 5 Results 81Behavior 82We trained two monkeys (G and E) to rotate a hand-held pedal to move through a virtual 83 environment (Fig. 1). All motion was along a linear track -no steering was necessary. 84Consistent with this, a single pedal was cycled with the right arm only. Our goal when 85 decoding was to reconstruct the virtual motion produced by that single pedal. On each trial, a 86 target appeared in the distance. To acquire that target, monkeys produced virtual ve...

The noradrenergic and cholinergic modulation of functionally distinct regions of the brain has become one of the primary organizational principles behind understanding the contribution of each system to the diversity of neural computation in the central nervous system. Decades of work has shown that a diverse family of receptors, stratified across different brain regions, and circuit-specific afferent and efferent projections play a critical role in helping such widespread neuromodulatory systems obtain substantial heterogeneity in neural information processing. This review briefly discusses the anatomical layout of both the noradrenergic and cholinergic systems, as well as the types and distributions of relevant receptors for each system. Previous work characterizing the direct and indirect interaction between these two systems is discussed, especially in the context of higher order cognitive functions such as attention, learning, and the decision-making process. Though a substantial amount of work has been done to characterize the role of each neuromodulator, a cohesive understanding of the region-specific cooperation of these two systems is not yet fully realized. For the field to progress, new experiments will need to be conducted that capitalize on the modular subdivisions of the brain and systematically explore the role of norepinephrine and acetylcholine in each of these subunits and across the full range of receptors expressed in different cell types in these regions.

Perceptual decision making is a dynamic cognitive process and is shaped by many factors, including behavioral state, reward contingency, and sensory environment. To understand the extent to which adaptive behavior in decision making is dependent upon pupil-linked arousal, we trained head-fixed rats to perform perceptual decision making tasks and systematically manipulated the probability of Go and No-go stimuli while simultaneously measuring their pupil size in the tasks. Our data demonstrated that the animals adaptively modified their behavior in response to the changes in the sensory environment. The response probability to both Go and No-go stimuli decreased as the probability of the Go stimulus being presented decreased. Analyses within the signal detection theory framework showed that while the perceptual sensitivity of the animals was invariant, their decision criterion increased as the probability of the Go stimulus decreased. Simulation results indicated that the adaptive increase in the decision criterion will increase possible water rewards during the task. Moreover, the adaptive decision making is dependent upon pupil-linked arousal as the increase in the decision criterion was the largest during low pupil-linked arousal periods. Taken together, our results demonstrated that the rats were able to adjust their decision making to maximize rewards in the tasks, and that adaptive behavior in perceptual decision making is dependent upon pupil-linked arousal.