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Viral vector technologies are commonly used in neuroscience research to understand and manipulate neural circuits, but successful applications of these technologies in non-human primate models have been inconsistent. An essential component to improve these technologies is an impartial and accurate assessment of the effectiveness of different viral constructs in the primate brain. We tested a diverse array of viral vectors delivered to the brain and extraocular muscles of macaques and compared three methods for histological assessment of viral-mediated fluorescent transgene expression: epifluorescence (Epi), immunofluorescence (IF), and immunohistochemistry (IHC). Importantly, IF and IHC identified a greater number of transduced neurons compared to Epi. Furthermore, IF and IHC reliably provided enhanced visualization of transgene in most cellular compartments (i.e., dendritic, axonal, and terminal fields), whereas the degree of labeling provided by Epi was inconsistent and predominantly restricted to somas and apical dendrites. Because Epi signals are unamplified (in contrast to IF and IHC), Epi likely provides a more veridical assessment for the amount of accumulated transgene and, thus, the potential to chemo- or optogenetically manipulate neuronal activity. The comparatively weak Epi signals suggest that the current generations of viral constructs, regardless of delivered transgene, are not optimized for primates. This reinforces an emerging viewpoint that viral vectors tailored for the primate brain are necessary for basic research and human gene therapy.

SummaryThe brain interprets sensory inputs to guide behavior, but behavior disrupts sensory inputs. In primates, saccadic eye movements displace visual images on the retina and yet the brain perceives visual stability, a process called active vision. We studied whether active vision is Bayesian. Humans and monkeys reported whether an image moved during saccades. We tested whether they used prior expectations to account for sensory uncertainty in a Bayesian manner. For continuous judgments, subjects were Bayesian. For categorical judgments, they were anti-Bayesian for uncertainty due to external, image noise but Bayesian for uncertainty due to internal, motor-driven noise. A discriminative learning model explained the anti-Bayesian effect. Therefore, active vision uses both Bayesian and discriminative models depending on task requirements (continuous vs. categorical) and the source of uncertainty (image noise vs. motor-driven noise), suggesting that active perceptual mechanisms are governed by the interaction of both models.

Transcranial magnetic stimulation (TMS) has become an important technique in both scientific and clinical practices, and yet our understanding of how the brain responds to TMS is still limited. Concurrent neuroimaging during TMS may bridge this gap, and emerging evidence suggests widespread that modulatory effects of TMS may be best captured through changes in functional connectivity between distributed networks, rather than local changes in cortical activity. However, the relationship between TMS stimulation parameters and evoked changes in functional connectivity is unknown. In this study, 24 healthy volunteers received concurrent TMS-fMRI while performing a dot-motion direction discrimination task. An MR-compatible coil was used to apply trains of three pulses at 10 Hz rTMS over the primary visual cortex (V1) at the onset of the dot stimuli with four levels of stimulation intensity (20%, 40%, 80%, and 120% of resting motor threshold, RMT). Behavioral results demonstrated impairment of motion discrimination at 80% RMT. FMRI results yielded three findings. First, functional connectivity between visual and non-visual areas increased as a function of rTMS intensity. Second, connectivity within the visual network was positively associated with motion accuracy, while the connectivity between visual and non-visual regions was negatively associated with motion accuracy. Lastly, we found that reductions in the similarity between functional and structural connectivity associated with increasing TMS intensity were constrained to the visual network. These findings demonstrate spatially dependent nonlinear effects of TMS intensity on brain functional connectivity that proceed beyond the site of stimulation and influence associated behavior.

The fusion of immersive virtual reality, kinematic movement tracking, and EEG offers a powerful test bed for naturalistic neuroscience research. Here, we combined these elements to investigate the neuro-behavioral mechanisms underlying precision visual–motor control as 20 participants completed a three-visit, visual–motor, coincidence-anticipation task, modeled after Olympic Trap Shooting and performed in immersive and interactive virtual reality. Analyses of the kinematic metrics demonstrated learning of more efficient movements with significantly faster hand RTs, earlier trigger response times, and higher spatial precision, leading to an average of 13% improvement in shot scores across the visits. As revealed through spectral and time-locked analyses of the EEG beta band (13–30 Hz), power measured prior to target launch and visual-evoked potential amplitudes measured immediately after the target launch correlated with subsequent reactive kinematic performance in the shooting task. Moreover, both launch-locked and shot/feedback-locked visual-evoked potentials became earlier and more negative with practice, pointing to neural mechanisms that may contribute to the development of visual–motor proficiency. Collectively, these findings illustrate EEG and kinematic biomarkers of precision motor control and changes in the neurophysiological substrates that may underlie motor learning.

In motor systems, a copy of the movement command known as corollary discharge is broadcast to other regions of the brain to warn them of the impending movement. The premise of this review is that the concept of corollary discharge may generalize in revealing ways to the brain’s cognitive systems. An oculomotor pathway from the brain stem to frontal cortex provides a well-established example of how corollary discharge is instantiated for sensorimotor processing. Building on causal evidence from inactivation of the pathway, we motivate forward models as a tool for understanding the contributions of corollary discharge to perception and movement. Finally, we extend the definition of corollary discharge to account for signals that may be used for cognitive forward models of decision making. This framework may provide new insights into signals and circuits that contribute to sequential decision processes, the breakdown of which may account for some symptoms of psychiatric disorders.

This study analyzes the light emission pattern of tapered optical fibers (TFs) across different numerical apertures (NA), core diameters, laser input powers, cone angles, and light injection angles. The results will be used to tailor optical fibers for optimal light delivery to photosensitive neuronal actuators in the non-human primate (NHP) brain.

Current knowledge of coordinated motor control of multiple muscles is derived primarily from invasive stimulation-recording techniques in animal models. Similar studies are not generally feasible in humans, so a modeling framework is needed to facilitate knowledge transfer from animal studies. We describe such a framework that uses a deep neural network model to map finite element simulation of transcranial magnetic stimulation induced electric fields (E-fields) in motor cortex to recordings of multi-muscle activation. Critically, we show that model generalization is improved when we incorporate empirically derived physiological models for E-field to neuron firing rate and low-dimensional control via muscle synergies.

Despite the widespread use of transcranial magnetic stimulation (TMS) in research and clinical care, the underlying mechanisms-of-actions that mediate modulatory effects remain poorly understood. To fill this gap, we studied dose–response functions of TMS for modulation of visual processing. Our approach combined electroencephalography (EEG) with application of single pulse TMS to visual cortex as participants performed a motion perception task. During participants’ first visit, motion coherence thresholds, 64-channel visual evoked potentials (VEPs), and TMS resting motor thresholds (RMT) were measured. In second and third visits, single pulse TMS was delivered 30 ms before the onset of motion or at the onset latency of the N2 VEP component derived from the first session. TMS was delivered at 0%, 80%, 100%, or 120% of RMT over the site of N2 peak activity, or at 120% over vertex. Behavioral results demonstrated a significant main effect of TMS timing on accuracy, with better performance when TMS was applied at N2-Onset timing versus Pre-Onset, as well as a significant interaction, indicating that 80% intensity produced higher accuracy than other conditions. TMS effects on VEPs showed reduced amplitudes in the 80% Pre-Onset condition, an increase for the 120% N2-Onset condition, and monotonic amplitude scaling with stimulation intensity. The N2 component was not affected by TMS. These findings reveal dose–response relationships between intensity and timing of TMS on visual perception and electrophysiological brain activity, generally indicating greater facilitation at stimulation intensities below RMT.

Despite the widespread use of transcranial magnetic stimulation (TMS) in research and clinical care, the dose–response relations and neurophysiological correlates of modulatory effects remain relatively unexplored. To fill this gap, we studied modulation of visual processing as a function of TMS parameters. Our approach combined electroencephalography (EEG) with application of single pulse TMS to visual cortex as participants performed a motion perception task. During each participants’ first visit, motion coherence thresholds, 64-channel visual evoked potentials (VEPs), and TMS resting motor thresholds (RMT) were measured. In second and third visits, single pulse TMS was delivered at one of two latencies, either 30 ms before the onset of motion or at the onset latency of the N2 VEP component derived from the first session. TMS was delivered at 0%, 80%, 100%, or 120% of RMT over the site of N2 peak activity, or at 120% over vertex. Behavioral results demonstrated a significant main effect of TMS timing on accuracy, with better performance when TMS was applied at the N2-Onset timing versus Pre-Onset, as well as a significant interaction, indicating that 80% intensity produced higher accuracy than other conditions at the N2-Onset. TMS effects on the P3 VEP showed reduced amplitudes in the 80% Pre-Onset condition, an increase for the 120% N2-Onset condition, and monotonic amplitude scaling with stimulation intensity. The N2 component was not affected by TMS. These findings reveal the influence of TMS intensity and timing on visual perception and electrophysiological responses, with optimal facilitation at stimulation intensities below RMT.

A deep neural network (DNN) that can reliably model muscle responses from corresponding brain stimulation has the potential to increase knowledge of coordinated motor control for numerous basic science and applied use cases. Such cases include the understanding of abnormal movement patterns due to neurological injury from stroke, and stimulation based interventions for neurological recovery such as paired associative stimulation. In this work, potential DNN models are explored and the one with the minimum squared errors is recommended for the optimal performance of the M2M-Net, a network that maps transcranial magnetic stimulation of the motor cortex to corresponding muscle responses, using: a finite element simulation, an empirical neural response profile, a convolutional autoencoder, a separate deep network mapper, and recordings of multi-muscle activation. We discuss the rationale behind the different modeling approaches and architectures, and contrast their results. Additionally, to obtain a comparative insight of the trade-off between complexity and performance analysis, we explore different techniques, including the extension of two classical information criteria for M2M-Net. Finally, we find that the model analogous to mapping the motor cortex stimulation to a combination of direct and synergistic connection to the muscles performs the best, when the neural response profile is used at the input., Comment: 6 pages, 4 figures

Critical real-life choices involve making complex decisions in the presence of potential threats, for instance, in medical or military emergencies. Effective choices require a decision maker to efficiently weigh and combine multiple sources of uncertain information. As anxiety can disrupt cognitive performance, complex decision-making under uncertainty may be particularly compromised by potential threat. One way people overcome such cognitive limitations is to “satisfice” by selectively evaluating a subset of available information to quickly identify a goodenough, feasible solution. How satisficing decision-making plays out under anxiety, however, remains elusive. Here, we examined how healthy participants solve a multi-cue probabilistic classification task under anticipatory anxiety induced via a threat-of-shock manipulation. Specifically, we investigated individual differences in information (cue) usage based on participants’ physiological responsiveness to threat, quantified by changes in skin conductance levels. In the absence of threat, all participants performed near-optimally, appropriately weighing and integrating all available cue information to guide their choices. Under threat-of-shock, however, participants who displayed high levels of anxiety employed a satisficing heuristic by ignoring the least important cue from their decision process, a strategy that uses less cognitive resources without sacrificing much accuracy. Moreover, anticipatory anxiety uncoupled the actual cue usage from explicit task knowledge. Taken together, these results suggest that, to cope with high levels of anticipatory anxiety, people satisfice by prioritizing high-value information to achieve fast and good-enough solutions.

Much of everyday behavior involves serial decision-making, in which the outcome of 1 choice affects another. An example is setting rules for oneself: choosing a behavioral rule guides appropriate choices in the future. How the brain links decisions across time is poorly understood. Neural mechanisms could be studied in monkeys, as it is known that they can select and use behavioral rules, but existing psychophysical paradigms are poorly suited for the constraints of neurophysiology. Therefore, we designed a streamlined task that requires sequential, linked decisions, and trained 2 rhesus monkeys (Macaca mulatta) to perform it. The task features trial-by-trial consistency, visual stimuli, and eye movement responses to optimize it for simultaneous electrophysiological inquiry. In the first stage of each trial, the monkeys selected a rule or a rule was provided to them. In the second stage, they used the rule to discriminate between 2 test stimuli. Our hypotheses were that they could use self-selected rules and could deliberately select rules based on reinforcement history. We found that the monkeys were as proficient at using self-selected rules as instructed rules. Their preferences for selecting rules correlated with their performance in using them, consistent with systematic, rather than random, strategies for accomplishing the task. The results confirm and extend prior findings on rule selection in monkeys and establish a viable, experimentally flexible paradigm for studying the neural basis of serial decision-making. (PsycINFO Database Record

The perception of visual motion is dependent on a set of occipitotemporal regions which are readily accessible to neuromodulation. Previous studies using paired-pulse Transcranial Magnetic Stimulation (ppTMS) have provided evidence of the capacity of this type of protocols to modulate cognitive processes. To test whether such cortical modulation can be observed in the visual system, particularly during motion perception, ppTMS was applied to the occipital cortex using both scalp-based and meta-analytic targeting coordinates. In this within-subject, sham-controlled study, fifteen subjects completed two sessions in two consecutive weeks. On the first visit, subject-specific resting motor threshold (RMT) was determined and participants performed an adaptive motion discrimination task to determine individual motion sensitivity. During the second visit, subjects performed the same task with three individualized difficulty levels as two TMS pulses were delivered respectively −150 and −50 ms prior to motion stimulus onset at 120% RMT, under the logic that the cumulative inhibitory effect of these two pulses would alter motion sensitivity as measured by the individually calibrated task. The ppTMS was delivered at one of two locations: 3 cm dorsal and 5 cm lateral to inion (scalp-based coordinate), or at the site of peak activation for “motion” according to the NeuroSynth fMRI database (meta-analytic coordinate). Sham stimulation was delivered on one-third of trials and evenly between the two targets. Analyses showed no significant active-versus-sham effects of ppTMS when stimulation was delivered to the meta-analytic (p = 0.15) or scalp-based coordinates (p = 0.17), which were separated by 29 mm on average. Additionally, there was no was significant interaction between ppTMS at either location and task difficulty level (p = 0.12 and p = 0.33, respectively). These findings fail to support the hypothesis that long-interval ppTMS recruits inhibitory processes in motion-sensitive cortex, but must be considered within the limits of the current design choices.HIGHLIGHTSLong-interval paired-pulse TMS was applied to visual cortex during a motion taskThe ppTMS was delivered according to scalp and meta-analytic coordinates, as well as shamNo effects of active-versus-sham stimulation were observed on motion task performance

When decisions must be made between uncertain options, optimal behavior depends on accurate estimations of the likelihoods of different outcomes. The contextual factors that govern whether these estimations depend on model-free learning (tracking outcomes) vs. model-based learning (learning generative stimulus distributions) are poorly understood. We studied model-free and model-based learning using serial decision-making tasks in which subjects selected a rule and then used it to flexibly act on visual stimuli. A factorial approach defined a family of behavioral models that could integrate model-free and model-based strategies to predict rule selection trial-by-trial. Bayesian model selection demonstrated that the subjects strategies varied depending on lower-level task characteristics such as the identities of the rule options. In certain conditions, subjects integrated learned stimulus distributions and tracked reward rates to guide their behavior. The results thus identify tradeoffs between model-based and model-free decision strategies, and in some cases parallel utilization, depending on task context.

Stimulus locations are detected differently by different sensory systems, but ultimately they yield similar percepts and behavioral responses. How the brain transcends initial differences to compute similar codes is unclear. We quantitatively compared the reference frames of two sensory modalities, vision and audition, across three interconnected brain areas involved in generating saccades, namely the frontal eye fields (FEF), lateral and medial parietal cortex (M/LIP), and superior colliculus (SC). We recorded from single neurons in head-restrained monkeys performing auditory- and visually-guided saccades from variable initial fixation locations, and evaluated whether their receptive fields were better described as eye-centered, head-centered, or hybrid (i.e. not anchored uniquely to head- or eye-orientation). We found a progression of reference frames across areas and across time, with considerable hybrid-ness and persistent differences between modalities during most epochs/brain regions. For both modalities, the SC was more eye-centered than the FEF, which in turn was more eye-centered than the predominantly hybrid M/LIP. In all three areas and temporal epochs from stimulus onset to movement, visual signals were more eye-centered than auditory signals. In the SC and FEF, auditory signals became more eye-centered at the time of the saccade than they were initially after stimulus onset, but only in the SC at the time of the saccade did the auditory signals become predominantly eye-centered. The results indicate that visual and auditory signals both undergo transformations, ultimately reaching the same final reference frame but via different dynamics across brain regions and time.New and NoteworthyModels for visual-auditory integration posit that visual signals are eye-centered throughout the brain, while auditory signals are converted from head-centered to eye-centered coordinates. We show instead that both modalities largely employ hybrid reference frames: neither fully head-nor eye-centered. Across three hubs of the oculomotor network (intraparietal cortex, frontal eye field and superior colliculus) visual and auditory signals evolve from hybrid to a common eye-centered format via different dynamics across brain areas and time.

Optogenetics has revolutionized neuroscience in small laboratory animals, but its effect on animal models more closely related to humans, such as non-human primates (NHPs), has been mixed. To make evidence-based decisions in primate optogenetics, the scientific community would benefit from a centralized database listing all attempts, successful and unsuccessful, of using optogenetics in the primate brain. We contacted members of the community to ask for their contributions to an open science initiative. As of this writing, 45 laboratories around the world contributed more than 1,000 injection experiments, including precise details regarding their methods and outcomes. Of those entries, more than half had not been published. The resource is free for everyone to consult and contribute to on the Open Science Framework website. Here we review some of the insights from this initial release of the database and discuss methodological considerations to improve the success of optogenetic experiments in NHPs. ispartof: NEURON vol:108 issue:6 ispartof: location:United States status: published

Background Recent genetic technologies such as opto- and chemogenetics allow for the manipulation of brain circuits with unprecedented precision. Most studies employing these techniques have been undertaken in rodents, but a more human-homologous model for studying the brain is the nonhuman primate (NHP). Optimizing viral delivery of transgenes encoding actuator proteins could revolutionize the way we study neuronal circuits in NHPs. New method rAAV2-retro, a popular new capsid variant, produces robust retrograde labeling in rodents. Whether rAAV2-retro’s highly efficient retrograde transport would translate to NHPs was unknown. Here, we characterized the anatomical distribution of labeling following injections of rAAV2-retro encoding opsins or DREADDs in the cortico-basal ganglia and oculomotor circuits of rhesus macaques. Results rAAV2-retro injections in striatum, frontal eye field, and superior colliculus produced local labeling at injection sites and robust retrograde labeling in many afferent regions. In every case, however, a few brain regions with well-established projections to the injected structure lacked retrogradely labeled cells. We also observed robust terminal field labeling in downstream structures. Comparison with existing method(s) Patterns of labeling were similar to those obtained with traditional tract-tracers, except for some afferent labeling that was noticeably absent. Conclusions rAAV2-retro promises to be useful for circuit manipulation via retrograde transduction in NHPs, but caveats were revealed by our findings. Some afferently connected regions lacked retrogradely labeled cells, showed robust axon terminal labeling, or both. This highlights the importance of anatomically characterizing rAAV2-retro’s expression in target circuits in NHPs before moving to manipulation studies.

The perception of visual motion is dependent on a set of occipitotemporal regions that are readily accessible to neuromodulation. The current study tested if paired-pulse Transcranial Magnetic Stimulation (ppTMS) could modulate motion perception by stimulating the occipital cortex as participants viewed near-threshold motion dot stimuli. In this sham-controlled study, fifteen subjects completed two sessions. On the first visit, resting motor threshold (RMT) was assessed, and participants performed an adaptive direction discrimination task to determine individual motion sensitivity. During the second visit, subjects performed the task with three difficulty levels as TMS pulses were delivered 150 and 50 ms prior to motion stimulus onset at 120% RMT, under the logic that the cumulative inhibitory effect of these pulses would alter motion sensitivity. ppTMS was delivered at one of two locations: 3 cm dorsal and 5 cm lateral to inion (scalp-based coordinate), or at the site of peak activation for “motion” according to the NeuroSynth fMRI database (meta-analytic coordinate). Sham stimulation was delivered on one-third of trials by tilting the coil 90°. Analyses showed no significant active-versus-sham effects of ppTMS when stimulation was delivered to the meta-analytic (p = 0.15) or scalp-based coordinates (p = 0.17), which were separated by 29 mm on average. Active-versus-sham stimulation differences did not interact with either stimulation location (p = 0.12) or difficulty (p = 0.33). These findings fail to support the hypothesis that long-interval ppTMS recruits inhibitory processes in motion-sensitive cortex but must be considered within the limited parameters used in this design.

Human behavior is influenced by serial decision-making: past decisions affect choices that set the context for selecting future options. A primate brain region that may be involved in linking decisions across time is the supplementary eye field (SEF), which, in addition to its well known visual responses and saccade-related activity, also signals the rules that govern flexible decisions and the outcomes of those decisions. Our hypotheses were that SEF neurons encode events during serial decision-making and link the sequential decisions with sustained activity. We recorded from neurons in the SEF of two rhesus monkeys (Macaca mulatta, one male, one female) that performed a serial decision-making task. The monkeys used saccades to select a rule that had to be applied later in the same trial to discriminate between visual stimuli. We found, first, that SEF neurons encoded the spatial parameters of saccades during rule selection but not during visual discrimination, suggesting a malleability to their movement-related tuning. Second, SEF activity linked the sequential decisions of rule selection and visual discrimination, but not continuously. Instead, rule-encoding activity appeared in a “just-in-time” manner before the visual discrimination. Third, SEF neurons encoded trial outcomes both prospectively, before decisions within a trial, and retrospectively, across multiple trials. The results thus identify neuronal correlates of rule selection and application in the SEF, including transient signals that link these sequential decisions. Its activity patterns suggest that the SEF participates in serial decision-making in a contextually dependent manner as part of a broader network. SIGNIFICANCE STATEMENT Much research has gone into studying the neurobiological basis of single, isolated decisions. An important next step is to understand how the brain links multiple decisions to generate a coherent stream of thought and behavior. We studied neural activity related to serial decision-making in an area of frontal cortex known as the supplementary eye field (SEF). Neural recordings were conducted in monkeys that performed a serial decision-making task in which they selected and applied rules. We found that SEF neurons convey signals for serial decision-making, including transient encoding of one decision at the time it is needed for the next one and longer-term representations of trial outcomes, suggesting that the region plays a role in continuity of cognition and behavior.

Immersive virtual reality (VR) systems offer flexible control of an interactive environment, along with precise position and orientation tracking of realistic movements. Immersive VR can also be used in conjunction with neurophysiological monitoring techniques, such as electroencephalography (EEG), to record neural activity as users perform complex tasks. As such, the fusion of VR, kinematic tracking, and EEG offers a powerful testbed for naturalistic neuroscience research. In this study, we combine these elements to investigate the cognitive and neural mechanisms that underlie motor skill learning during a multi-day simulated marksmanship training regimen conducted with 20 participants. On each of 3 days, participants performed 8 blocks of 60 trials in which a simulated clay pigeon was launched from behind a trap house. Participants attempted to shoot the moving target with a firearm game controller, receiving immediate positional feedback and running scores after each shot. Over the course of the 3 days that individuals practiced this protocol, shot accuracy and precision improved significantly while reaction times got significantly faster. Furthermore, results demonstrate that more negative EEG amplitudes produced over the visual cortices correlate with better shooting performance measured by accuracy, reaction times, and response times, indicating that early visual system plasticity underlies behavioral learning in this task. These findings point towards a naturalistic neuroscience approach that can be used to identify neural markers of marksmanship performance.

Real-life decision-making often involves combining multiple probabilistic sources of information under finite time and cognitive resources. To mitigate these pressures, people “satisfice”, foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and “good-enough” decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the way in which the neural encoding of cue information changes when we satisfice under time pressure. Here, we combined human functional magnetic resonance imaging (fMRI) with a probabilistic classification task to characterize neural substrates of multi-cue decision-making under low (1500 ms) and high (500 ms) time pressure. Using variational Bayesian inference, we analyzed participants’ choices to track and quantify cue usage under each experimental condition, which was then applied to model the fMRI data. Under low time pressure, participants performed near-optimally, appropriately integrating all available cues to guide choices. Both cortical (prefrontal and parietal cortex) and subcortical (hippocampal and striatal) regions encoded individual cue weights, and activity linearly tracked trial-by-trial variations in the amount of evidence and decision uncertainty. Under increased time pressure, participants adaptively shifted to using a satisficing strategy by discounting the least informative cue in their decision process. This strategic change in decision-making was associated with an increased involvement of the dopaminergic midbrain, striatum, thalamus, and cerebellum in representing and integrating cue values. We conclude that satisficing the probabilistic inference process under time pressure leads to a cortical-to-subcortical shift in the neural drivers of decisions.

We accurately perceive the visual scene despite moving our eyes ~3 times per second, an ability that requires incorporation of eye position and retinal information. We assessed how this neural computation unfolds across three interconnected structures: frontal eye fields (FEF), intraparietal cortex (LIP/MIP), and the superior colliculus (SC). Single unit activity was assessed in head-restrained monkeys performing visually-guided saccades from different initial fixations. As previously shown, the receptive fields of most LIP/MIP neurons shifted to novel positions on the retina for each eye position, and these locations were not clearly related to each other in either eye- or head-centered coordinates (hybrid coordinates). In contrast, the receptive fields of most SC neurons were stable in eye-centered coordinates. In FEF, visual signals were intermediate between those patterns: around 60% were eye-centered, whereas the remainder showed changes in receptive field location, boundaries, or responsiveness that rendered the response patterns hybrid or occasionally head-centered. These results suggest that FEF may act as a transitional step in an evolution of coordinates between LIP/MIP and SC. The persistence across cortical areas of hybrid representations that do not provide unequivocal location labels in a consistent reference frame has implications for how these representations must be read-out.New & NoteworthyHow we perceive the world as stable using mobile retinas is poorly understood. We compared the stability of visual receptive fields across different fixation positions in three visuomotor regions. Irregular changes in receptive field position were ubiquitous in intraparietal cortex, evident but less common in the frontal eye fields, and negligible in the superior colliculus (SC), where receptive fields shifted reliably across fixations. Only the SC provides a stable labelled-line code for stimuli across saccades.

Transcranial magnetic stimulation (TMS) is a widely used, noninvasive method for stimulating nervous tissue, yet its mechanisms of effect are poorly understood. Here we report novel methods for studying the influence of TMS on single neurons in the brain of alert non-human primates. We designed a TMS coil that focuses its effect near the tip of a recording electrode and recording electronics that enable direct acquisition of neuronal signals at the site of peak stimulus strength minimally perturbed by stimulation artifact in intact, awake monkeys (Macaca mulatta). We recorded action potentials within ~1 ms after 0.4 ms TMS pulses and observed changes in activity that differed significantly for active stimulation as compared to sham stimulation. The methodology is compatible with standard equipment in primate laboratories, allowing for easy implementation. Application of these new tools will facilitate the refinement of next generation TMS devices, experiments, and treatment protocols.

The spiking activity of nearby cortical neurons is correlated on both short and long time scales. Understanding this shared variability in firing patterns is critical for appreciating the representation of sensory stimuli in ensembles of neurons, the coincident influences of neurons on common targets, and the functional implications of microcircuitry. Our knowledge about neuronal correlations, however, derives largely from experiments that used different recording methods, analysis techniques, and cortical regions. Here we studied the structure of neuronal correlation in area V4 of alert macaques using recording and analysis procedures designed to match those used previously in primary visual cortex (V1), the major input to V4. We found that the spatial and temporal properties of correlations in V4 were remarkably similar to those of V1, with two notable differences: correlated variability in V4 was approximately one-third the magnitude of that in V1 and synchrony in V4 was less temporally precise than in V1. In both areas, spontaneous activity (measured during fixation while viewing a blank screen) was approximately twice as correlated as visual-evoked activity. The results provide a foundation for understanding how the structure of neuronal correlation differs among brain regions and stages in cortical processing and suggest that it is likely governed by features of neuronal circuits that are shared across the visual cortex.

Successful interaction with the world depends on accurate perception of the timing of external events. Neurons at early stages of the primate visual system represent time-varying stimuli with high precision. However, it is unknown whether this temporal fidelity is maintained in the prefrontal cortex, where changes in neuronal activity generally correlate with changes in perception. One reason to suspect that it is not maintained is that humans experience surprisingly large fluctuations in the perception of time. To investigate the neuronal correlates of time perception, we recorded from neurons in the prefrontal cortex and midbrain of monkeys performing a temporal-discrimination task. Visual time intervals were presented at a timescale relevant to natural behavior (

Saccadic eye movements rapidly displace the image of the world that is projected onto the retinas. In anticipation of each saccade, many neurons in the visual system shift their receptive fields. This presaccadic change in visual sensitivity, known as remapping, was first documented in the parietal cortex and has been studied in many other brain regions. Remapping requires information about upcoming saccades via corollary discharge. Analyses of neurons in a corollary discharge pathway that targets the frontal eye field (FEF) suggest that remapping may be assembled in the FEF's local microcircuitry. Complementary data from reversible inactivation, neural recording, and modeling studies provide evidence that remapping contributes to transsaccadic continuity of action and perception. Multiple forms of remapping have been reported in the FEF and other brain areas, however, and questions remain about the reasons for these differences. In this review of recent progress, we identify three hypotheses that may help to guide further investigations into the structure and function of circuits for remapping.

Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through satisficing, fast but "good-enough" heuristic decision making that prioritizes some sources of information (cues) while ignoring others. However, the decision-making strategies we adopt under uncertainty and time pressure, for example during emergencies that demand split-second choices, are presently unknown. To characterize these decision strategies quantitatively, the present study examined how people solve a novel multicue probabilistic classification task under varying time pressure, by tracking shifts in decision strategies using variational Bayesian inference. We found that under low time pressure, participants correctly weighted and integrated all available cues to arrive at near-optimal decisions. With increasingly demanding, subsecond time pressures, however, participants systematically discounted a subset of the cue information by dropping the least informative cue(s) from their decision making process. Thus, the human cognitive apparatus copes with uncertainty and severe time pressure by adopting a "drop-the-worst" cue decision making strategy that minimizes cognitive time and effort investment while preserving the consideration of the most diagnostic cue information, thus maintaining "good-enough" accuracy. This advance in our understanding of satisficing strategies could form the basis of predicting human choices in high time pressure scenarios. (PsycINFO Database Record