Parallel patterns of cognitive aging in marmosets and macaques.

As humans age, some experience cognitive impairment while others do not. When impairment does occur, it is not expressed uniformly across cognitive domains and varies in severity across individuals. Translationally relevant model systems are critical for understanding the neurobiological drivers of this variability, which is essential to uncovering the mechanisms underlying the brain's susceptibility to the effects of aging. As such, non-human primates are particularly important due to shared behavioral, neuroanatomical, and age-related neuropathological features with humans. For many decades, macaque monkeys have served as the primary non-human primate model for studying the neurobiology of cognitive aging. More recently, the common marmoset has emerged as an advantageous model for this work due to its short lifespan that facilitates longitudinal studies. Despite their growing popularity as a model, whether marmosets exhibit patterns of age-related cognitive impairment comparable to those observed in macaques and humans remains unexplored. To address this major limitation for the development and evaluation of the marmoset as a model of cognitive aging, we directly compared working memory ability as a function of age in macaques and marmosets on the identical working memory task. Our results demonstrate that marmosets and macaques exhibit remarkably similar age-related working memory deficits, highlighting the value of the marmoset as a model for cognitive aging research within the neuroscience community.

A Comparison of Rapid Rule-Learning Strategies in Humans and Monkeys.

Interspecies comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of the strategies of female macaque monkeys to male and female humans on a variant of the Wisconsin Card Sorting Test (WCST), a widely studied and applied task that provides a multiattribute measure of cognitive function and depends on the frontal lobe. WCST performance requires the inference of a rule change given ambiguous feedback. We found that well-trained monkeys infer new rules three times more slowly than minimally instructed humans. Input-dependent hidden Markov model-generalized linear models were fit to their choices, revealing hidden states akin to feature-based attention in both species. Decision processes resembled a win-stay, lose-shift strategy with interspecies similarities as well as key differences. Monkeys and humans both test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidate choice options. We quantitatively show that perseveration, random exploration, and poor sensitivity to negative feedback account for the slower task-switching performance in monkeys.

Non-Stationary Dynamic Mode Decomposition.

Many physical processes display complex high-dimensional time-varying behavior, from global weather patterns to brain activity. An outstanding challenge is to express high dimensional data in terms of a dynamical model that reveals their spatiotemporal structure. Dynamic Mode Decomposition is a means to achieve this goal, allowing the identification of key spatiotemporal modes through the diagonalization of a finite dimensional approximation of the Koopman operator. However, these methods apply best to time-translationally invariant or stationary data, while in many typical cases, dynamics vary across time and conditions. To capture this temporal evolution, we developed a method, Non-Stationary Dynamic Mode Decomposition, that generalizes Dynamic Mode Decomposition by fitting global modulations of drifting spatiotemporal modes. This method accurately predicts the temporal evolution of modes in simulations and recovers previously known results from simpler methods. To demonstrate its properties, the method is applied to multi-channel recordings from an awake behaving non-human primate performing a cognitive task.

Non-Stationary Dynamic Mode Decomposition.

Many physical processes display complex high-dimensional time-varying behavior, from global weather patterns to brain activity. An outstanding challenge is to express high dimensional data in terms of a dynamical model that reveals their spatiotemporal structure. Dynamic Mode Decomposition is a means to achieve this goal, allowing the identification of key spatiotemporal modes through the diagonalization of a finite dimensional approximation of the Koopman operator. However, DMD methods apply best to time-translationally invariant or stationary data, while in many typical cases, dynamics vary across time and conditions. To capture this temporal evolution, we developed a method, Non-Stationary Dynamic Mode Decomposition (NS-DMD), that generalizes DMD by fitting global modulations of drifting spatiotemporal modes. This method accurately predicts the temporal evolution of modes in simulations and recovers previously known results from simpler methods. To demonstrate its properties, the method is applied to multi-channel recordings from an awake behaving non-human primate performing a cognitive task.

Multiple memory systems for efficient temporal order memory.

We report distinct contributions of multiple memory systems to the retrieval of the temporal order of events. The neural dynamics related to the retrieval of movie scenes revealed that recalling the temporal order of close events elevates hippocampal theta power, like that observed for recalling close spatial relationships. In contrast, recalling far events increases beta power in the orbitofrontal cortex, reflecting recall based on the overall movie structure.

Schema formation in a neural population subspace underlies learning-to-learn in flexible sensorimotor problem-solving.

Learning-to-learn, a progressive speedup of learning while solving a series of similar problems, represents a core process of knowledge acquisition that draws attention in both neuroscience and artificial intelligence. To investigate its underlying brain mechanism, we trained a recurrent neural network model on arbitrary sensorimotor mappings known to depend on the prefrontal cortex. The network displayed an exponential time course of accelerated learning. The neural substrate of a schema emerges within a low-dimensional subspace of population activity; its reuse in new problems facilitates learning by limiting connection weight changes. Our work highlights the weight-driven modifications of the vector field, which determines the population trajectory of a recurrent network and behavior. Such plasticity is especially important for preserving and reusing the learned schema in spite of undesirable changes of the vector field due to the transition to learning a new problem; the accumulated changes across problems account for the learning-to-learn dynamics.

Comparing rapid rule-learning strategies in humans and monkeys.

Inter-species comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of macaque monkey and human strategies on an analogue of the Wisconsin Card Sort Test, a widely studied and applied multi-attribute measure of cognitive function, wherein performance requires the inference of a changing rule given ambiguous feedback. We found that well-trained monkeys rapidly infer rules but are three times slower than humans. Model fits to their choices revealed hidden states akin to feature-based attention in both species, and decision processes that resembled a Win-stay lose-shift strategy with key differences. Monkeys and humans test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidates. An attention-set based learning stage categorization revealed that perseveration, random exploration and poor sensitivity to negative feedback explain the under-performance in monkeys.

A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations.

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery.

Improving the Efficacy and Accessibility of Intracranial Viral Vector Delivery in Non-Human Primates.

Non-human primates (NHPs) are precious resources for cutting-edge neuroscientific research, including large-scale viral vector-based experimentation such as optogenetics. We propose to improve surgical outcomes by enhancing the surgical preparation practices of convection-enhanced delivery (CED), which is an efficient viral vector infusion technique for large brains such as NHPs'. Here, we present both real-time and next-day MRI data of CED in the brains of ten NHPs, and we present a quantitative, inexpensive, and practical bench-side model of the in vivo CED data. Our bench-side model is composed of food coloring infused into a transparent agar phantom, and the spread of infusion is optically monitored over time. Our proposed method approximates CED infusions into the cortex, thalamus, medial temporal lobe, and caudate nucleus of NHPs, confirmed by MRI data acquired with either gadolinium-based or manganese-based contrast agents co-infused with optogenetic viral vectors. These methods and data serve to guide researchers and surgical team members in key surgical preparations for intracranial viral delivery using CED in NHPs, and thus improve expression targeting and efficacy and, as a result, reduce surgical risks.

Event segmentation reveals working memory forgetting rate.

We encounter the world as a continuous flow and effortlessly segment sequences of events into episodes. This process of event segmentation engages working memory (WM) for tracking the flow of events and impacts subsequent memory accuracy. WM is limited in how much information (i.e., WM capacity) and for how long the information is retained (i.e., forgetting rate). In this study, across multiple tasks, we estimated participants' WM capacity and forgetting rate in a dynamic context and evaluated their relationship to event segmentation. A U-shaped relationship across tasks shows that individuals who segmented the movie more finely or coarsely than the average have a faster WM forgetting rate. A separate task assessing long-term memory retrieval revealed that the coarse-segmenters have better recognition of temporal order of events compared to the fine-segmenters. These findings show that event segmentation employs dissociable memory strategies and correlates with how long information is retained in WM.

Value representation in the monkey hippocampus.

The hippocampus is thought to form cognitive maps across different domains of experience, including space and time. Recent work by Knudsen and Wallis identifies a map of abstract value space in the monkey hippocampus. We consider how these abstract variables might contribute to a comprehensive hippocampal representation of ongoing experience.

Improving rigor and reproducibility in nonhuman primate research.

Nonhuman primates (NHPs) are a critical component of translational/preclinical biomedical research due to the strong similarities between NHP and human physiology and disease pathology. In some cases, NHPs represent the most appropriate, or even the only, animal model for complex metabolic, neurological, and infectious diseases. The increased demand for and limited availability of these valuable research subjects requires that rigor and reproducibility be a prime consideration to ensure the maximal utility of this scarce resource. Here, we discuss a number of approaches that collectively can contribute to enhanced rigor and reproducibility in NHP research.

The grid code for ordered experience.

Entorhinal cortical grid cells fire in a periodic pattern that tiles space, which is suggestive of a spatial coordinate system. However, irregularities in the grid pattern as well as responses of grid cells in contexts other than spatial navigation have presented a challenge to existing models of entorhinal function. In this Perspective, we propose that hippocampal input provides a key informative drive to the grid network in both spatial and non-spatial circumstances, particularly around salient events. We build on previous models in which neural activity propagates through the entorhinal-hippocampal network in time. This temporal contiguity in network activity points to temporal order as a necessary characteristic of representations generated by the hippocampal formation. We advocate that interactions in the entorhinal-hippocampal loop build a topological representation that is rooted in the temporal order of experience. In this way, the structure of grid cell firing supports a learned topology rather than a rigid coordinate frame that is bound to measurements of the physical world.

Gender bias in academia: A lifetime problem that needs solutions.

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow, and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in science. Here, we argue that gender bias is not a single problem but manifests as a collection of distinct issues that impact researchers' lives. We disentangle these facets and propose concrete solutions that can be adopted by individuals, academic institutions, and society.

A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex.

Episodic memory is believed to be intimately related to our experience of the passage of time. Indeed, neurons in the hippocampus and other brain regions critical to episodic memory code for the passage of time at a range of timescales. The origin of this temporal signal, however, remains unclear. Here, we examined temporal responses in the entorhinal cortex of macaque monkeys as they viewed complex images. Many neurons in the entorhinal cortex were responsive to image onset, showing large deviations from baseline firing shortly after image onset but relaxing back to baseline at different rates. This range of relaxation rates allowed for the time since image onset to be decoded on the scale of seconds. Further, these neurons carried information about image content, suggesting that neurons in the entorhinal cortex carry information about not only when an event took place but also, the identity of that event. Taken together, these findings suggest that the primate entorhinal cortex uses a spectrum of time constants to construct a temporal record of the past in support of episodic memory.

Anatomy and Function of the Primate Entorhinal Cortex.

The entorhinal cortex (EC) is a critical element of the hippocampal formation located within the medial temporal lobe (MTL) in primates. The EC has historically received attention for being the primary mediator of cortical information going into and coming from the hippocampus proper. In this review, we highlight the significance of the EC as a major player in memory processing, along with other associated structures in the primate MTL. The complex, convergent topographies of cortical and subcortical input to the EC, combined with short-range intrinsic connectivity and the selective targeting of EC efferents to the hippocampus, provide evidence for subregional specialization and integration of information beyond what would be expected if this structure were a simple conduit of information for the hippocampus. Lesion studies of the EC provide evidence implicating this region as critical for memory and the flexible use of complex relational associations between experienced events. The physiology of this structure's constituent principal cells mirrors the complexity of its anatomy. EC neurons respond preferentially to aspects of memory-dependent paradigms including object, place, and time. EC neurons also show striking spatial representations as primates explore visual space, similar to those identified in rodents navigating physical space. In this review, we highlight the great strides that have been made toward furthering our understanding of the primate EC, and we identify paths forward for future experiments to provide additional insight into the role of this structure in learning and memory.

Device-Embedded Cameras for Eye Tracking-Based Cognitive Assessment: Implications for Teleneuropsychology.

Introduction:Widespread screening for cognitive decline is an important challenge to address as the aging population grows, but there is currently a shortage of clinical infrastructure to meet the demand for in-person evaluation. Remotely delivered assessments that utilize eye-tracking data from webcams, such as visual paired comparison (VPC) tasks, could increase access to remote, asynchronous neuropsychological screening for cognitive decline but further validation against clinical-grade eye trackers is required.Methods:To demonstrate equivalence between a novel automated scoring system for eye-tracking metrics acquired through a laptop-embedded camera and a gold-standard eye tracker, we analyzed VPC data from 18 subjects aged 50+ with normal cognitive function across three visits. The eye tracker data were scored by the manufacturer's software, and the webcam data were scored by a novel algorithm.Results:Automated scoring of webcam-based VPC data revealed strong correlations with the clinical-grade eye-tracking camera. Correlation of mean VPC performance across all time points was robust: r = 0.95 (T1 r = 0.97; T2 r = 0.88; T3 r = 0.97; p's < 0.001). Correlation of per-trial performance across time points was also robust: r = 0.88 (T1 r = 0.85; T2 r = 0.89; T3 r = 0.92; p's < 0.001). Mean differences between performance data acquired by each device were 0.00.Conclusion:These results suggest that device-embedded cameras are a valid and scalable alternative to traditional laboratory-based equipment for gaze-based tasks measuring cognitive function. The validation of this technique represents an important technical advance for the field of teleneuropsychology.

Recognition Memory in Marmoset and Macaque Monkeys: A Comparison of Active Vision.

The core functional organization of the primate brain is remarkably conserved across the order, but behavioral differences evident between species likely reflect derived modifications in the underlying neural processes. Here, we performed the first study to directly compare visual recognition memory in two primate species-rhesus macaques and marmoset monkeys-on the same visual preferential looking task as a first step toward identifying similarities and differences in this cognitive process across the primate phylogeny. Preferences in looking behavior on the task were broadly similar between the species, with greater looking times for novel images compared with repeated images as well as a similarly strong preference for faces compared with other categories. Unexpectedly, we found large behavioral differences among the two species in looking behavior independent of image familiarity. Marmosets exhibited longer looking times, with greater variability compared with macaques, regardless of image content or familiarity. Perhaps most strikingly, marmosets shifted their gaze across the images more quickly, suggesting a different behavioral strategy when viewing images. Although such differences limit the comparison of recognition memory across these closely related species, they point to interesting differences in the mechanisms underlying active vision that have significant implications for future neurobiological investigations with these two nonhuman primate species. Elucidating whether these patterns are reflective of species or broader phylogenetic differences (e.g., between New World and Old World monkeys) necessitates a broader sample of primate taxa from across the Order.