Image-dependence of the detectability of optogenetic stimulation in macaque inferotemporal cortex

Single-cell optogenetics reveals attenuation-by-suppression in visual cortical neurons

The relationship between neurons' input and spiking output is central to brain computation. Studies in vitro and in anesthetized animals suggest nonlinearities emerge in cells' input-output (activation) functions as network activity increases, yet how neurons transform inputs in vivo has been unclear. Here, we characterize cortical principal neurons' activation functions in awake mice using two-photon optogenetics. We deliver fixed inputs at the soma while neurons' activity varies with sensory stimuli. We find responses to fixed optogenetic input are nearly unchanged as neurons are excited, reflecting a linear response regime above neurons' resting point. In contrast, responses are dramatically attenuated by suppression. This attenuation is a powerful means to filter inputs arriving to suppressed cells, privileging other inputs arriving to excited neurons. These results have two major implications. First, somatic neural activation functions in vivo accord with the activation functions used in recent machine learning systems. Second, neurons' IO functions can filter sensory inputs - not only do sensory stimuli change neurons' spiking outputs, but these changes also affect responses to input, attenuating responses to some inputs while leaving others unchanged.

Revealing the mechanisms of semantic satiation with deep learning models

The phenomenon of semantic satiation, which refers to the loss of meaning of a word or phrase after being repeated many times, is a well-known psychological phenomenon. However, the microscopic neural computational principles responsible for these mechanisms remain unknown. In this study, we use a deep learning model of continuous coupled neural networks to investigate the mechanism underlying semantic satiation and precisely describe this process with neuronal components. Our results suggest that, from a mesoscopic perspective, semantic satiation may be a bottom-up process. Unlike existing macroscopic psychological studies that suggest that semantic satiation is a top-down process, our simulations use a similar experimental paradigm as classical psychology experiments and observe similar results. Satiation of semantic objectives, similar to the learning process of our network model used for object recognition, relies on continuous learning and switching between objects. The underlying neural coupling strengthens or weakens satiation. Taken together, both neural and network mechanisms play a role in controlling semantic satiation.

Perceptography unveils the causal contribution of inferior temporal cortex to visual perception

Neurons in the inferotemporal (IT) cortex respond selectively to complex visual features, implying their role in object perception. However, perception is subjective and cannot be read out from neural responses; thus, bridging the causal gap between neural activity and perception demands independent characterization of perception. Historically, though, the complexity of the perceptual alterations induced by artificial stimulation of IT cortex has rendered them impossible to quantify. To address this old problem, we tasked male macaque monkeys to detect and report optical impulses delivered to their IT cortex. Combining machine learning with high-throughput behavioral optogenetics, we generated complex and highly specific images that were hard for the animal to distinguish from the state of being cortically stimulated. These images, named "perceptograms" for the first time, reveal and depict the contents of the complex hallucinatory percepts induced by local neural perturbation in IT cortex. Furthermore, we found that the nature and magnitude of these hallucinations highly depend on concurrent visual input, stimulation location, and intensity. Objective characterization of stimulation-induced perceptual events opens the door to developing a mechanistic theory of visual perception. Further, it enables us to make better visual prosthetic devices and gain a greater understanding of visual hallucinations in mental disorders.

The neural code for "face cells" is not face-specific

Face cells are neurons that respond more to faces than to non-face objects. They are found in clusters in the inferotemporal cortex, thought to process faces specifically, and, hence, studied using faces almost exclusively. Analyzing neural responses in and around macaque face patches to hundreds of objects, we found graded response profiles for non-face objects that predicted the degree of face selectivity and provided information on face-cell tuning beyond that from actual faces. This relationship between non-face and face responses was not predicted by color and simple shape properties but by information encoded in deep neural networks trained on general objects rather than face classification. These findings contradict the long-standing assumption that face versus non-face selectivity emerges from face-specific features and challenge the practice of focusing on only the most effective stimulus. They provide evidence instead that category-selective neurons are best understood by their tuning directions in a domain-general object space.

Behavioral optogenetics in nonhuman primates; a psychological perspective

Optogenetics has been a promising and developing technology in systems neuroscience throughout the past decade. It has been difficult though to reliably establish the potential behavioral effects of optogenetic perturbation of the neural activity in nonhuman primates. This poses a challenge on the future of optogenetics in humans as the concepts and technology need to be developed in nonhuman primates first. Here, I briefly summarize the viable approaches taken to improve nonhuman primate behavioral optogenetics, then focus on one approach: improvements in the measurement of behavior. I bring examples from visual behavior and show how the choice of method of measurement might conceal large behavioral effects. I will then discuss the "cortical perturbation detection" task in detail as an example of a sensitive task that can record the behavioral effects of optogenetic cortical stimulation with high fidelity. Finally, encouraged by the rich scientific landscape ahead of behavioral optogenetics, I invite technology developers to improve the chronically implantable devices designed for simultaneous neural recording and optogenetic intervention in nonhuman primates.

Surgical Procedure for Implantation of Opto-Array in Nonhuman Primates

Optogenetics allows precise temporal control of neuronal activity in the brain. Engineered viral vectors are routinely used to transduce neurons with light-sensitive opsins. However, reliable virus injection and light delivery in animals with large brains, such as nonhuman primates, has proven challenging. The Opto-Array is a novel yet simple device that is used to deliver light to extended regions of the cortex surface for high-throughput behavioral optogenetics in large brains. Here we present protocols for surgical delivery of virus (Basic Protocol 1) and implantation of the Opto-Array (Basic Protocol 2) in two separate surgeries in a rhesus monkey's inferior temporal cortex. As a proof of concept, we measured the behavioral performance of an animal detecting cortical optogenetic stimulations (Basic Protocol 3) with different illumination power and duration using the Opto-Array. The animal was able to detect the optogenetic stimulation for all tested illumination powers and durations. Regression analysis also showed both power and duration of illumination significantly modulate the detectability of the optogenetic stimulation. The outcome of this approach is superior to the standard practice of injecting and recording through a chamber for large areas of the cortex surface. Moreover, the chronic nature of the Opto-Array allows perturbation of neuronal activity of the same site across multiple sessions because it is highly stable; thus, data can be pooled over months. The detailed surgical method presented here makes it possible to use optogenetics to modulate neuronal activity across large regions of the cortex surface in the nonhuman primate brain. This method also lays the groundwork for future attempts to use optogenetics to restore vision in humans. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Virus injection surgery Basic Protocol 2: Opto-Array implantation surgery Basic Protocol 3: Cortical Perturbation Detection (CPD) task behavioral training.

Neural coding: Stimulating cortex to alter visual perception

A new study has shown that monkeys detect transient external pulses delivered to the highest echelons of visual cortex in a way that depends on concomitant visual inputs. This new work, a technical tour de force, has implications for the development of future visual prosthetic devices.

Separating weak integrated information theory into inspired and aspirational approaches

Mediano et al. (The strength of weak integrated information theory. Trends Cogn Sci 2022;26: 646-55.) separate out strong and weak flavours of the integrated information theory (IIT) of consciousness. They describe 'strong IIT' as attempting to derive a universal formula for consciousness and 'weak IIT' as searching for empirically measurable correlates of aspects of consciousness. We put forward that their overall notion of 'weak IIT' may be too weak. Rather, it should be separated out to distinguish 'aspirational-IIT', which aims to empirically test IIT by making trade-offs to its proposed measures, and 'IIT-inspired' approaches, which adopt high-level ideas of IIT while dropping the mathematical framework it reaches through its introspective, first-principles approach to consciousness.