Low-cost, portable, easy-to-use kiosks to facilitate home-cage testing of nonhuman primates during vision-based behavioral tasks.

Nonhuman primates (NHPs), especially rhesus macaques, have significantly contributed to our understanding of the neural computations underlying human vision. Besides the established homologies in the visual brain areas between these species and our ability to probe detailed neural mechanisms in monkeys at multiple scales, NHPs' ability to perform human-like visual behavior makes them an extremely appealing animal model of human vision. Traditionally, such behavioral studies have been conducted in controlled laboratory settings, offering experimenters tight control over variables like luminance, eye movements, and auditory interference.

The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates.

Inferences made about objects via vision, such as rapid and accurate categorization, are core to primate cognition despite the algorithmic challenge posed by varying viewpoints and scenes. Until recently, the brain mechanisms that support these capabilities were deeply mysterious. However, over the past decade, this scientific mystery has been illuminated by the discovery and development of brain-inspired, image-computable, artificial neural network (ANN) systems that rival primates in these behavioral feats.

The Impact of Scene Context on Visual Object Recognition: Comparing Humans, Monkeys, and Computational Models.

During natural vision, we rarely see objects in isolation but rather embedded in rich and complex contexts. Understanding how the brain recognizes objects in natural scenes by integrating contextual information remains a key challenge. To elucidate neural mechanisms compatible with human visual processing, we need an animal model that behaves similarly to humans, so that inferred neural mechanisms can provide hypotheses relevant to the human brain.

Multimodal investigations of emotional face processing and social trait judgment of faces.

Faces are among the most important visual stimuli that humans perceive in everyday life. While extensive literature has examined emotional processing and social evaluations of faces, most studies have examined either topic using unimodal approaches. In this review, we promote the use of multimodal cognitive neuroscience approaches to study these processes, using two lines of research as examples: ambiguity in facial expressions of emotion and social trait judgment of faces.

Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition.

The computational role of the abundant feedback connections in the ventral visual stream is unclear, enabling humans and nonhuman primates to effortlessly recognize objects across a multitude of viewing conditions. Prior studies have augmented feedforward convolutional neural networks (CNNs) with recurrent connections to study their role in visual processing; however, often these recurrent networks are optimized directly on neural data or the comparative metrics used are undefined for standard feedforward networks that lack these connections. In this work, we develop task-optimized convolutional recurrent (ConvRNN) network models that more correctly mimic the timing and gross neuroanatomy of the ventral pathway.

A Computational Probe into the Behavioral and Neural Markers of Atypical Facial Emotion Processing in Autism.

Despite ample behavioral evidence of atypical facial emotion processing in individuals with autism spectrum disorder (ASD), the neural underpinnings of such behavioral heterogeneities remain unclear. Here, I have used brain-tissue mapped artificial neural network (ANN) models of primate vision to probe candidate neural and behavior markers of atypical facial emotion recognition in ASD at an image-by-image level. Interestingly, the image-level behavioral patterns of the ANNs better matched the neurotypical subjects 'behavior than those measured in ASD.

Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition.

Distributed neural population spiking patterns in macaque inferior temporal (IT) cortex that support core object recognition require additional time to develop for specific, "late-solved" images. This suggests the necessity of recurrent processing in these computations. Which brain circuits are responsible for computing and transmitting these putative recurrent signals to IT? To test whether the ventrolateral prefrontal cortex (vlPFC) is a critical recurrent node in this system, here, we pharmacologically inactivated parts of vlPFC and simultaneously measured IT activity while monkeys performed object discrimination tasks.

The inferior temporal cortex is a potential cortical precursor of orthographic processing in untrained monkeys.

The ability to recognize written letter strings is foundational to human reading, but the underlying neuronal mechanisms remain largely unknown. Recent behavioral research in baboons suggests that non-human primates may provide an opportunity to investigate this question. We recorded the activity of hundreds of neurons in V4 and the inferior temporal cortex (IT) while naïve macaque monkeys passively viewed images of letters, English words and non-word strings, and tested the capacity of those neuronal representations to support a battery of orthographic processing tasks.

Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity.

Transcranial alternating current stimulation (tACS) is used as a noninvasive tool for cognitive enhancement and clinical applications. The physiological effects of tACS, however, are complex and poorly understood. Most studies of tACS focus on its ability to entrain brain oscillations, but our behavioral results in humans and extracellular recordings in nonhuman primates support the view that tACS at 10 Hz also affects brain function by reducing sensory adaptation.

Neural population control via deep image synthesis.

Particular deep artificial neural networks (ANNs) are today's most accurate models of the primate brain's ventral visual stream. Using an ANN-driven image synthesis method, we found that luminous power patterns (i.e.

Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior.

Non-recurrent deep convolutional neural networks (CNNs) are currently the best at modeling core object recognition, a behavior that is supported by the densely recurrent primate ventral stream, culminating in the inferior temporal (IT) cortex. If recurrence is critical to this behavior, then primates should outperform feedforward-only deep CNNs for images that require additional recurrent processing beyond the feedforward IT response. Here we first used behavioral methods to discover hundreds of these 'challenge' images.

Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks.

Primates, including humans, can typically recognize objects in visual images at a glance despite naturally occurring identity-preserving image transformations (e.g., changes in viewpoint).

Transcranial Alternating Current Stimulation Attenuates Neuronal Adaptation.

We previously showed that brief application of 2 mA (peak-to-peak) transcranial currents alternating at 10 Hz significantly reduces motion adaptation in humans. This is but one of many behavioral studies showing that weak currents applied to the scalp modulate neural processing. Transcranial stimulation has been shown to improve perception, learning, and a range of clinical symptoms.

Testing the assumptions underlying fMRI adaptation using intracortical recordings in area MT.

We investigated how neural activity in the middle temporal area of the macaque monkey changes after 3 sec of exposure to a visual stimulus and used this to gain insight into the assumptions underlying the fMRI adaptation method (fMRIa). We studied both changes in tuning curves following weak and strong motion stimuli (adaptation) and the differences between a first and second exposure to the same stimulus (repetition suppression). Typically, tuning curves had smaller amplitudes and narrower tuning widths after strong adaptation; this was true for single neurons, multi-unit activity (MUA), the evoked local field potential (LFP), as well as gamma band activity.

Social closeness and feedback modulate susceptibility to the framing effect.

Although we often seek social feedback (SFB) from others to help us make decisions, little is known about how SFB affects decisions under risk, particularly from a close peer. We conducted two experiments using an established framing task to probe how decision-making is modulated by SFB valence (positive, negative) and the level of closeness with feedback provider (friend, confederate). Participants faced mathematically equivalent decisions framed as either an opportunity to keep (gain frame) or lose (loss frame) part of an initial endowment.

Transcranial alternating current stimulation attenuates visual motion adaptation.

Transcranial alternating current stimulation (tACS) is used in clinical applications and basic neuroscience research. Although its behavioral effects are evident from prior reports, current understanding of the mechanisms that underlie these effects is limited. We used motion perception, a percept with relatively well known properties and underlying neural mechanisms to investigate tACS mechanisms.

Probing the mechanisms underlying the mitigation of cognitive aging with anodal transcranial direct current stimulation.

Meinzer et al. (J Neurosci 33: 12470-12478, 2013) have recently reported that anodal transcranial direct current stimulation (atDCS) mitigates age-related cognitive changes. Simultaneous measurement of BOLD signal during atDCS also showed "youth-like" processing in an elderly population.

Transcranial electrical stimulation over visual cortex evokes phosphenes with a retinal origin.

Transcranial electrical stimulation (tES) is a promising therapeutic tool for a range of neurological diseases. Understanding how the small currents used in tES spread across the scalp and penetrate the brain will be important for the rational design of tES therapies. Alternating currents applied transcranially above visual cortex induce the perception of flashes of light (phosphenes).