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Choice information appears in multi-area brain networks mixed with sensory, motor, and cognitive variables. In the posterior cortex-traditionally implicated in decision computations-the presence, strength, and area specificity of choice signals are highly variable, limiting a cohesive understanding of their computational significance. Examining the mesoscale activity in the mouse posterior cortex during a visual task, we found that choice signals defined a decision variable in a low-dimensional embedding space with a prominent contribution along the ventral visual stream. Their subspace was near-orthogonal to concurrently represented sensory and motor-related activations, with modulations by task difficulty and by the animals' attention state. A recurrent neural network trained with animals' choices revealed an equivalent decision variable whose context-dependent dynamics agreed with that of the neural data. Our results demonstrated an independent, multi-area decision variable in the posterior cortex, controlled by task features and cognitive demands, possibly linked to contextual inference computations in dynamic animal-environment interactions.

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During perceptual decision-making, the brain encodes the upcoming decision and the stimulus information in a mixed representation. Paradigms suitable for studying decision computations in isolation rely on stimulus comparisons, with choices depending on relative rather than absolute properties of the stimuli. The adoption of tasks requiring relative perceptual judgments in mice would be advantageous in view of the powerful tools available for the dissection of brain circuits. However, whether and how mice can perform a relative visual discrimination task has not yet been fully established. Here, we show that mice can solve a complex orientation discrimination task in which the choices are decoupled from the orientation of individual stimuli. Moreover, we demonstrate a typical discrimination acuity of 9°, challenging the common belief that mice are poor visual discriminators. We reached these conclusions by introducing a probabilistic choice model that explained behavioral strategies in 40 mice and demonstrated that the circularity of the stimulus space is an additional source of choice variability for trials with fixed difficulty. Furthermore, history biases in the model changed with task engagement, demonstrating behavioral sensitivity to the availability of cognitive resources. In conclusion, our results reveal that mice adopt a diverse set of strategies in a task that decouples decision-relevant information from stimulus-specific information, thus demonstrating their usefulness as an animal model for studying neural representations of relative categories in perceptual decision-making research.

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Visually guided behaviors depend on the activity of cortical networks receiving visual inputs and transforming these signals to guide appropriate actions. However, non-retinal inputs, carrying motor signals as well as cognitive and attentional modulatory signals, also activate these cortical regions. How these networks integrate coincident signals ensuring reliable visual behaviors is poorly understood. In this study, we observe neural responses in the dorsal-parietal cortex of mice during a visual discrimination task driven by visual stimuli and movements. We find that visual and motor signals interact according to two mechanisms: divisive normalization and separation of responses. Interactions are contextually modulated by the animal's state of sustained attention, which amplifies visual and motor signals and increases their discriminability in a low-dimensional space of neural activations. These findings reveal computational principles operating in dorsal-parietal networks that enable separation of incoming signals for reliable visually guided behaviors during interactions with the environment.

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The division of labor between the dorsal and ventral visual pathways has been well studied, but not often with direct comparison at the single-neuron resolution with matched stimuli. Here we directly compared how single neurons in MT and V4, mid-tier areas of the two pathways, process binocular disparity, a powerful cue for 3D perception and actions. We found that MT neurons transmitted disparity signals more quickly and robustly, whereas V4 or its upstream neurons transformed the signals into sophisticated representations more prominently. Therefore, signaling speed and robustness were traded for transformation between the dorsal and ventral pathways. The key factor in this tradeoff was disparity-tuning shape: V4 neurons had more even-symmetric tuning than MT neurons. Moreover, the tuning symmetry predicted the degree of signal transformation across neurons similarly within each area, implying a general role of tuning symmetry in the stereoscopic processing by the two pathways.

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OBJECTIVES: This study examines the effects of total light deprivation on the developing lateral geniculate nucleus, the primary integration centre for visual information METHODS: Sprague-Dawley rats were reared for one month in a dark room from 7th postnatal day before eye opening. A group of rats was taken back into normal condition for 15 days, and then perfused. Coronal sections of LGN were prepared and stained with Cresyl Violet and Cytochrome Oxidase to investigate the number of neurons, volume and length, as well as neuronal activity level. RESULTS: The results showed that LD for one month causes progressive loss of neurons and decreases neuronal activity level in the LGN. CONCLUSION: It can be concluded that during early postnatal development of the rats' visual system, light deprivation causes structural and functional changes in LGN.

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OBJECTIVE: To clarify the organization of the rat lateral geniculate nucleus (LGN). METHODS: A total of 50 male Sprague-Dawley albino rats of 2 months of age were used in this study carried out in the Iran University of Medical Sciences, Tehran, Iran in Spring-Fall 2007. The rats were cardially perfused under deep ether anesthesia, first with a small amount of saline then with a fixative solution containing 4% paraformaldehyde and 0.2% glutaraldehyde in 0.1M phosphate buffer pH 7.2. The brains were removed, processed, and then 50 um coronal sections of the LGN were cut and divided into 3 groups: anterior, middle, and posterior third. Cresyl violet stained sections were studied by light microscopy and counts of neurons were carried out with Olysiabio report software of Olympus Microscope in every other section. RESULTS: We observed that the neuronal density in the anterior, middle, and posterior thirds were statistically different. CONCLUSION: The concentration of neuronal terminals and neuronal connections causes changes in neuronal density.