The availability of effective vaccines and a high vaccination rate allowed the recent mitigation, or even withdrawal, of many protective measures for containing the SARS CoV-2 pandemic. At the same time, new and highly mutated variants of the virus are found to have significantly higher transmissibility and reduced vaccine efficacy, thus causing high infection rates during the third year of the pandemic. The combination of reduced measures and increased infectivity poses a particular risk for unvaccinated individuals, including animals susceptible to the virus. Among the latter, non-human primates (NHPs) are particularly vulnerable. They serve as important models in various fields of biomedical research and because of their cognitive capabilities, they receive particular attention in animal welfare regulations around the world. Yet, although they played an extraordinarily important role for developing and testing vaccines against SARS-CoV-2, the protection of captive rhesus monkeys against Covid-19 has rarely been discussed. We here report upon twofold mRNA vaccination of a cohort of 19 elderly rhesus monkeys ( Macaca mulatta ) against infection by SARS-CoV-2. All animals were closely monitored on possible side effects of vaccination, and were tested for neutralising antibodies against the virus. The data show that vaccination of rhesus monkeys is a safe and reliable measure to protect these animals against SARS-CoV-2.

The 5-choice serial reaction time task (5-CSRTT) is a behavioral test often used to study visuospatial attention and impulsiveness in rodents. The task requires animals to allocate attention to a horizontal array of five small apertures equipped with light sources and, within a limited time window, nose-poke one illuminated target aperture to get a food reward at the food magazine located in the opposite wall of the chamber. The task considers behavioral control measures such as response accuracy and reaction times and allows to infer selective attention and impulsivity. Task difficulty can be controlled by modifying the stimulus duration and task design in general. Commercially available apparatus usually consists of an experimental chamber and particular software to specify task parameters, but due to fixed hard- and software, they pose many limitations on changes in the general experimental design and specific task requirements and the related data output. This article explains a fully customizable alternative based on an easy-to-use single-board microcontroller and standard electrotechnical components, an open-access Arduino script, and a Matlab-toolbox for hardware control and behavioral task specifications, respectively. The toolbox includes an optional staircase procedure, enabling automated behavioral training. The complete hardware setup, which can be installed in customized chambers, and the freely adaptable software encourage non-standardized task and chamber design. The design of the system and the open-source code for hardware control and experimental setup are described.

Reaction times (RTs) are an essential metric used for understanding the link between brain and behaviour. As research is reaffirming the tight coupling between neuronal and behavioural RTs, thorough statistical modelling of RT data is thus essential to enrich current theories and motivate novel findings. A statistical distribution is proposed herein that is able to model the complete RT's distribution, including location, scale and shape: the generalised-exponential-Gaussian (GEG) distribution. The GEG distribution enables shifting the attention from traditional means and standard deviations to the entire RT distribution. The mathematical properties of the GEG distribution are presented and investigated via simulations. Additionally, the GEG distribution is featured via four real-life data sets. Finally, we discuss how the proposed distribution can be used for regression analyses via generalised additive models for location, scale and shape (GAMLSS).

Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed changes with pronounced transients, often far exceeding the expected response as derived from their speed tuning profile. We here show that this complex, non-linear behavior emerges from the combined temporal dynamics of excitation and divisive inhibition, and provide a comprehensive mathematical analysis. A central prediction derived from this investigation is that attention increases the steepness of the transient response irrespective of the activation state prior to a stimulus change, and irrespective of the sign of the change (i.e. irrespective of whether the stimulus is accelerating or decelerating). Extracellular recordings of attention-dependent representation of both speed increments and decrements confirmed this prediction and suggest that improved change detection derives from basic computations in a canonical cortical circuitry.

The nonhuman primate (NHP) constitutes an extraordinarily important model in neuroscience research for understanding the neuronal underpinnings of perceptual, motor, cognitive, and executive functions of the primate brain, and to study the physiological causes, effects, and potential treatments of brain disorders. Because of their cognitive capabilities, NHPs receive special attention in animal welfare regulations around the world, and their well-being is a benchmark for the evaluation, monitoring, and refinement of experimental procedures. As a consequence, many typical neuroscientific procedures are considered only mildly severe by animal welfare boards. There is, however, an ongoing debate about possible long-term and cumulative effects. Because of a lack of longitudinal data, it is unclear whether mildly severe procedures may cause more significant harm on the long-term, and to what extent they may impact animal well-being and healthiness over time. We here make use of a database of blood samples drawn over a period of 15 years from 39 rhesus monkeys (Macaca mulatta) to address the issue of long-term, cumulative effects of neuroscientific procedures. A careful analysis of indicative primate blood markers for chronic inflammation, hydration status, and stress levels, their comparison to baseline values from both the same animals and the literature, and evaluation of additional hematologic, physiological, and behavioral parameters did not provide support for the notion of long-term, cumulative effects on the monkeys' healthiness and well-being. The results may serve the community as a reference for the severity assessment of neuroscientific experiments involving NHPs.

Brain signal recordings with epidural microarrays constitute a low-invasive approach for recording distributed neuronal signals. Epidural field potentials (EFPs) may serve as a safe and highly beneficial signal source for a variety of research questions arising from both basic and applied neuroscience. A wider use of these signals, however, is constrained by a lack of data on their specific information content. Here, we make use of the high spatial resolution and the columnar organization of macaque primary visual cortex (V1) to investigate whether and to what extent EFP signals preserve information about various visual stimulus features. Two monkeys were presented with different feature combinations of location, size, shape, and color, yielding a total of 375 stimulus conditions. Visual features were chosen to access different spatial levels of functional organization. We found that, besides being highly specific for locational information, EFPs were significantly modulated by small differences in size, shape, and color, allowing for high stimulus classification rates even at the single-trial level. The results support the notion that EFPs constitute a low-invasive, highly beneficial signal source for longer-term recordings for medical and basic research by showing that they convey detailed and reliable information about constituent features of activating stimuli.

Brain signal recordings with epidural microarrays constitute a low-invasive approach for recording distributed neuronal signals. Epidural field potentials (EFPs) may serve as a safe and highly beneficial signal source for a variety of research questions arising from both basic and applied neuroscience. A wider use of these signals, however, is constrained by a lack of data on their specific information content. Here, we make use of the high spatial resolution and the columnar organization of macaque primary visual cortex (V1) to investigate whether and to what extent EFP signals preserve information about various visual stimulus features. Two monkeys were presented with different feature combinations of location, size, shape, and color, yielding a total of 375 stimulus conditions. Visual features were chosen to access different spatial levels of functional organization. We found that, besides being highly specific for locational information, EFPs were significantly modulated by small differences in size, shape, and color, allowing for high stimulus classification rates even at the single-trial level. The results support the notion that EFPs constitute a low-invasive, highly beneficial signal source for longer-term recordings for medical and basic research by showing that they convey significant and reliable information about constituent features of activating stimuli. ### Competing Interest Statement The authors have declared no competing interest.

Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independent as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed changes with pronounced transients, often far exceeding the expected response as derived from their speed tuning profile. We here show that this complex, non-linear behavior emerges from the combined temporal dynamics of excitation and divisive inhibition, and provide a comprehensive formal analysis. A central prediction derived from this investigation is that attention increases the steepness of the transient response irrespective of the activation state prior to a stimulus change, and irrespective of the sign of the change. Extracellular recordings of attention-dependent representation of both speed increments and decrements confirmed this prediction and suggest that improved change detection derives from basic computations in a canonical cortical circuitry.

Neurophysiological data acquisition using multi-electrode arrays and/or (semi-) chronic recordings frequently has to deal with low signal-to-noise ratio (SNR) of neuronal responses and potential failure of detecting evoked responses within random background fluctuations. Conventional methods to extract action potentials (spikes) from background noise often apply thresholds to the recorded signal, usually allowing reliable detection of spikes when data exhibit a good SNR, but often failing when SNR is poor. We here investigate a threshold-independent, fast, and automated procedure for analysis of low SNR data, based on fullwave-rectification and low-pass filtering the signal as a measure of the entire spiking activity (ESA). We investigate the sensitivity and reliability of the ESA-signal for detecting evoked responses by applying an automated receptive field (RF) mapping procedure to semi-chronically recorded data from primary visual cortex (V1) of five macaque monkeys. For recording sites with low SNR, the usage of ESA improved the detection rate of RFs by a factor of 2.5 in comparison to MUA-based detection. For recording sites with medium and high SNR, ESA delivered 30% more RFs than MUA. This significantly higher yield of ESA-based RF-detection still hold true when using an iterative procedure for determining the optimal spike threshold for each MUA individually. Moreover, selectivity measures for ESA-based RFs were quite compatible with MUA-based RFs. Regarding RF size, ESA delivered larger RFs than thresholded MUA, but size difference was consistent over all SNR fractions. Regarding orientation selectivity, ESA delivered more sites with significant orientation-dependent responses but with somewhat lower orientation indexes than MUA. However, preferred orientations were similar for both signal types. The results suggest that ESA is a powerful signal for applications requiring automated, fast, and reliable response detection, as e.g., brain-computer interfaces and neuroprosthetics, due to its high sensitivity and its independence from user-dependent intervention. Because the full information of the spiking activity is preserved, ESA also constitutes a valuable alternative for offline analysis of data with limited SNR.

Recordings of epidural field potentials (EFPs) allow neuronal activity to be acquired over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations and possess a higher trial-by-trial variability and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short timescales relevant for many clinical and basic neuroscience purposes. We used the high spatial resolution of primary visual cortex to address these issues and investigated the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one of nine closely adjacent locations and recorded neuronal activity with a high-density epidural multielectrode array in three macaque monkeys. With the use of receiver operating characteristics (ROC) to identify the most informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.NEW & NOTEWORTHY Epidural field potential (EFP) recordings provide a minimally invasive approach to investigate large-scale neural networks, but little is known about whether they possess the required specificity for basic and clinical neuroscience. By making use of the spatial selectivity of primary visual cortex, we show that single-trial information can be decoded with close-to-perfect performance, even without using advanced classifiers and based on very few data. This labels EFPs as a highly attractive and widely usable signal.

Nonhuman primates constitute an indispensable model system for studying higher brain functions at the neurophysiological level. Studies involving these animals elucidated the neuronal mechanisms of various cognitive and executive functions, such as visual attention, working memory, and decision-making. Positive reinforcement training (PRT) constitutes the gold standard for training animals on the cognitive tasks employed in these studies. In the laboratory, PRT is usually based on application of a liquid reward as the reinforcer to strengthen the desired behavior and absence of the reward if the animal's response is wrong. By trial and error, the monkey may adapt its behavior and successfully reduce the number of error trials, and eventually learn even very sophisticated tasks. However, progress and success of the training strongly depend on reasonable error rates. If errors get too frequent, they may cause a drop in the animal's motivation to cooperate or its adaptation to high error rates and poor overall performance. We introduce in this report an alternative training regime to minimize errors and base the critical information for learning on graded rewarding. For every new task rule, the feedback to the animal is provided by different amounts of reward to distinguish the desired, optimal behavior from less optimal behavior. We applied this regime in different situations during training of visual attention tasks and analyzed behavioral performance and reaction times to evaluate its effectiveness. For both simple and complex behaviors, graded rewarding was found to constitute a powerful technique allowing for effective training without trade-off in accessible task difficulty or task performance. NEW & NOTEWORTHY Laboratory training of monkeys usually builds on providing a fixed amount of reward for the desired behavior, and no reward otherwise. We present a nonbinary, graded reward schedule to emphasize the positive, desired behavior and to keep errors on a moderate level. Using data from typical training situations, we demonstrate that graded rewards help to effectively guide the animal by success rather than errors and provide a powerful new tool for positive reinforcement training.

Nonspatially selective attention is based on the notion that specific features or objects in the visual environment are effectively prioritized in cortical visual processing. Feature-based attention (FBA), in particular, is a well-studied process that dynamically and selectively addresses neurons preferentially processing the attended feature attribute (e.g., leftward motion). In everyday life, however, behavior may require high sensitivity for an entire feature dimension (e.g., motion), but experimental evidence for a feature dimension-specific attentional modulation on a cellular level is lacking. Therefore, we investigated neuronal activity in macaque motion-selective mediotemporal area (MT) in an experimental setting requiring the monkeys to detect either a motion change or a color change. We hypothesized that neural activity in MT is enhanced when the task requires perceptual sensitivity to motion. In line with this, we found that mean firing rates were higher in the motion task and that response variability and latency were lower compared with values in the color task, despite identical visual stimulation. This task-specific, dimension-based modulation of motion processing emerged already in the absence of visual input, was independent of the relation between the attended and stimulating motion direction, and was accompanied by a spatially global reduction of neuronal variability. The results provide single-cell support for the hypothesis of a feature dimension-specific top-down signal emphasizing the processing of an entire feature class.NEW & NOTEWORTHY Cortical processing serving visual perception prioritizes information according to current task requirements. We provide evidence in favor of a dimension-based attentional mechanism addressing all neurons that process visual information in the task-relevant feature domain. Behavioral tasks required monkeys to attend either color or motion, causing modulations of response strength, variability, latency, and baseline activity of motion-selective monkey area MT neurons irrespective of the attended motion direction but specific to the attended feature dimension.

A1 Functional advantages of cell-type heterogeneity in neural circuits

In human and nonhuman primates, goal-directed behavior requires the selection of relevant pieces of information from the multitude of simultaneous sensory inputs. Feature-based attention (FBA) plays a crucial role in this selection by improving the neuronal representation of an attended stimulus feature. Of particular interest for understanding the neuronal mechanisms behind FBA is the processing fate of spatially unattended stimuli, either sharing the attended feature attribute or belonging to the attended or to a nonattended feature dimension. Using a wide range of cue/stimulus combinations, we investigated event-related potentials from the human brain, recorded under conditions of different feature attention but constant visual stimulation. We found that neural processing of visual stimuli sharing the dimension or the attribute of the attended target is associated with two distinct spatiotemporal processes, particularly prominent during the selection negativity period. Dimension-based modulation of neural signals first emerged over frontal electrode sites, and temporally preceded and accompanied attribute-specific FBA effects at occipital, parieto-occipital, and parietal electrodes. The findings suggest a process of FBA that not only increases responses of those neurons particularly tuned to the attended attribute but also modulates activity in the cortical module that is selective for the feature dimension to which the attended attribute belongs.

Attention is an important prerequisite for visual information processing. It allows the brain to focus on particular aspects of a visual scene, and enables or enhances perception of complex shapes and objects. However, attentional selection is an intricate computational problem, since the target of attentional deployment is often given by an arbitrary combination of features such as the location of an object having a conjunction of particular properties (features), and it is subjected to various neural constraints such as a given anatomical connectivity and broad tuning of neurons. How the brain solves this problem to boost the processing of combinations of different features that are represented across multiple neural areas is largely unknown. Recently, progress in understanding the properties of joint attentional selection was made in a psychophysical study investigating attentional spreading within and across objects [1]: Subjects were asked to report color and speed changes on one of two overlapping random dot patterns. Only one of the features was unique for each object, while the other was shared by both. Reaction times (RTs) recorded under different cueing conditions demonstrated the co-selection of unattended features, with attention spreading from the attended feature attribute in a particular feature dimension to other feature attributes and other feature dimensions. Importantly, this processing benefit was not restricted to the task-relevant object but extended to the unattended object. It is an open question how these observations can be modeled and understood in a coherent framework. In our contribution, we propose two structurally simple models, implementing two complementary neural mechanisms: The first model assumes that the specificity of anatomical connections providing attentional feedback from higher cortical areas is constrained. Consequently, top-down modulation of neural activity in lower visual areas is broadly tuned, targeting all cells representing the cued feature dimension(s) with only a weak preference for the cued feature attribute(s). As a result, attention spreads to uncued feature attributes and to jointly cued feature dimensions. In the second model we assume joint coding of stimulus features such that neurons having a preference for a particular motion direction also have a preference for a specific color. We also assume that neurons are not always perfectly tuned to their preferred feature(s), thus providing a (small) response to non-preferred feature values as well. Attentional feedback in this model precisely targets cells tuned for the cued feature attribute, or the combination of attributes. In this approach, attentional spreading to uncued feature dimensions is mediated by joint tuning, whereas spreading to uncued feature attributes in the same feature dimension is mediated by imperfect tuning. It turns out that both approaches, with appropriately chosen parameters, can qualitatively explain the differences in RTs between the stimulation conditions (Fig. 1). The next step is to develop a neurophysiologically plausible model that allows for explicit predictions for electrophysiological experiments to critically test the proposed mechanisms.

Neurons in the middle temporal area (MT) respond to motion onsets and speed changes with a transient-sustained firing pattern. The latency of the transient response has recently been shown to correlate with reaction time in a speed change detection task, but it is not known how the sign, the amplitude, and the latency of this response depend on the sign and the magnitude of a speed change, and whether these transients can be decoded to explain speed change detection behavior. To investigate this issue, we measured the neuronal representation of a wide range of positive and negative speed changes in area MT of fixating macaques and obtained three major findings. First, speed change transients not only reflect a neuron's absolute speed tuning but are shaped by an additional gain that scales the tuned response according to the magnitude of a relative speed change. Second, by means of a threshold model positive and negative population transients of a moderate number of MT neurons explain detection of both positive and negative speed changes, respectively, at a level comparable to human detection rates under identical visual stimulation. Third, like reaction times in a psychophysical model of velocity detection, speed change response latencies follow a power-law function of the absolute difference of a speed change. Both this neuronal representation and its close correlation with behavioral measures of speed change detection suggest that neuronal transients in area MT facilitate the detection of rapid changes in visual input.