Plasticity of the primary visual cortex and mechanisms of perceptual learning

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The review explores current insights into the cellular and molecular mechanisms of visual perceptual learning. It provides evidences that perceptual learning is underlaid by long-term synaptic plasticity occurring within the neural networks of the primary visual cortex. Key models of perceptual learning in animals, including stimulus-dependent plasticity and reinforcement learning, are analyzed. Furthermore, the review provides a rationale for the use of the visual cortex, particularly in rodents, as a convenient model for investigating general mechanisms of learning and memory in vivo. Using this approach, the role of homo- and heterosynaptic plasticity in long-term modifications of sensory responses in the visual cortex was convincingly demonstrated. The data obtained on the model of plasticity of visual responses can be extrapolated to general mechanisms of learning and memory, including those beyond perceptual learning.

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I. Smirnov

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

编辑信件的主要联系方式.
Email: malyshev@ihna.ru
俄罗斯联邦, Moscow

A. Malyshev

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Email: malyshev@ihna.ru
俄罗斯联邦, Moscow

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2. Fig. 1. Stimulus-dependent learning. (a) – experimental setup. A mouse is presented with a visual stimulus – a grid moving across a monitor screen. Stimulus-induced evoked potential (EP) is recorded in the primary visual cortex, and a piezoelectric sensor connected to the animal’s paw records involuntary movements that occur in response to the visual stimulus, the so-called vidgeting. (б) – when the same visual stimulus is shown every day, the amplitude of vidgeting in response to this stimulus gradually decreases, while the amplitude of the evoked potential recorded from the 4th layer of the visual cortex, on the contrary, increases (в) – which is called stimulus-selective response plasticity (SRP) in the English-language literature. From (Montgomery et al., 2022), with modifications.

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3. Fig. 2. Experiment on changing the receptive properties of a single neuron in the visual cortex. (a) – in the middle – the scheme of the experiment: vertical and horizontal moving bars were shown to the animal on the screen, while the response in the form of action potentials was recorded in the pyramidal neurons of the primary visual cortex using the juxtacellular recording method. Juxtacellular recording is a type of extracellular recording performed using a glass pipette (top left). The pipette is positioned so close to the body of the neuron being recorded that it becomes possible to iontophoretically fill the neuron with a vital dye (most often neurobiotin) with subsequent morphological identification of the cell (see the example in Fig. 3). In addition, a thin optical fiber is inserted into the glass pipette (electrode), which allows optogenetic stimulation of the cell expressing channelrhodopsin. In this experiment, optogenetic stimulation of the neuron (pairing) was performed during the demonstration of a stimulus of non-optimal orientation. After 200 such pairings, the amplitude of the response to the stimulus of this orientation increased and became greater than the response to the stimulus of the perpendicular orientation. (б) – poststimulus histograms of neuron responses to a stimulus of non-optimal (left) and optimal (right) orientations before combinations, (в) – after combinations. Based on (Smirnov, Malyshev, 2023).

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4. Fig. 3. Plasticity of receptive properties of neurons in the visual cortex of mice induced by optogenetic tetanization in vivo. In this series of experiments, mice were presented with a visual stimulus in the form of gratings moving across the screen in 12 different directions, and the resulting action potentials were recorded juxtacellularly. A typical response of a simple cell is shown in the form of regular bursts of action potentials with a burst frequency corresponding to the frequency of the grating. It was found that optogenetically induced high-frequency action potential bursts in neurons (optogenetic tetanization) lead to a change in the tuning curve (graph in polar coordinates on the bottom right). After tetanization (blue curve), neurons become less tuned – the response to the optimal orientation decreases, while to some non-optimal ones it increases. On the bottom left is an example of morphological identification of a neuron after an electrophysiological experiment in the visual cortex of a mouse, whose neurons express the fast channelrhodopsin oChief with the fluorescent protein Venus. According to (Smirnov et al., 2024).

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