Contrast dependence and differential contributions from somatostatin- and parvalbumin-expressing neurons to spatial integration in mouse V1

Experience-dependent specialization of receptive field surround for selective coding of natural scenes

At eye opening, neurons in primary visual cortex (V1) are selective for stimulus features, but circuits continue to refine in an experience-dependent manner for some weeks thereafter. How these changes contribute to the coding of visual features embedded in complex natural scenes remains unknown. Here we show that normal visual experience after eye opening is required for V1 neurons to develop a sensitivity for the statistical structure of natural stimuli extending beyond the boundaries of their receptive fields (RFs), which leads to improvements in coding efficiency for full-field natural scenes (increased selectivity and information rate). These improvements are mediated by an experience-dependent increase in the effectiveness of natural surround stimuli to hyperpolarize the membrane potential specifically during RF-stimulus epochs triggering action potentials. We suggest that neural circuits underlying surround modulation are shaped by the statistical structure of visual input, which leads to more selective coding of features in natural scenes.

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V1 firing is more selective to natural than phase-scrambled surround stimuli

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Improved selectivity is caused by Vm hyperpolarisation prior to RF-spiking events

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Natural surround sensitivity is experience dependent, absent in immature/deprived V1

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Vision shapes circuits to improve V1 coding of natural scenes across RF and surround

Tasks for inhibitory interneurons in intact brain circuits

Synaptic inhibition, brought about by a rich variety of interneuron types, counters excitation, modulates the gain, timing, tuning, bursting properties of principal cell firing, and exerts selective filtering of synaptic excitation. At the network level, it allows for coordinating transient interactions among the principal cells to form cooperative assemblies for efficient transmission of information and routing of excitatory activity across networks, typically in the form of brain oscillations. Recent techniques based on targeted expression of neuronal activity modulators, such as optogenetics, allow physiological identification and perturbation of specific interneuron subtypes in the intact brain. Combined with large-scale recordings or imaging techniques, these approaches facilitate our understanding of the multiple roles of inhibitory interneurons in shaping circuit functions.

Visual cortex modulates the magnitude but not the selectivity of looming-evoked responses in the superior colliculus of awake mice

Neural circuits in the brain often receive inputs from multiple sources, such as the bottom-up input from early processing stages and the top-down input from higher-order areas. Here we study the function of top-down input in the mouse superior colliculus (SC), which receives convergent inputs from the retina and visual cortex. Neurons in the superficial SC display robust responses and speed tuning to looming stimuli that mimic approaching objects. The looming-evoked responses are reduced by almost half when the visual cortex is optogenetically silenced in awake, but not in anesthetized, mice. Silencing the cortex does not change the looming speed tuning of SC neurons, or the response time course, except at the lowest tested speed. Furthermore, the regulation of SC responses by the corticotectal input is organized retinotopically. This effect we revealed may thus provide a potential substrate for the cortex, an evolutionarily new structure, to modulate SC-mediated visual behaviors.

Orientation-tuned surround suppression in mouse visual cortex

The firing rates of neurons in primary visual cortex (V1) are suppressed by large stimuli, an effect known as surround suppression. In cats and monkeys, the strength of suppression is sensitive to orientation; responses to regions containing uniform orientations are more suppressed than those containing orientation contrast. This effect is thought to be important for scene segmentation, but the underlying neural mechanisms are poorly understood. We asked whether it is possible to study these mechanisms in the visual cortex of mice, because of recent advances in technology for studying the cortical circuitry in mice. It is unknown whether neurons in mouse V1 are sensitive to orientation contrast. We measured the orientation selectivity of surround suppression in the different layers of mouse V1. We found strong surround suppression in layer 4 and the superficial layers, part of which was orientation tuned: iso-oriented surrounds caused more suppression than cross-oriented surrounds. Surround suppression was delayed relative to the visual response and orientation-tuned suppression was delayed further, suggesting two separate suppressive mechanisms. Previous studies proposed that surround suppression depends on the activity of inhibitory somatostatin-positive interneurons in the superficial layers. To test the involvement of the superficial layers we topically applied lidocaine. Silencing of the superficial layers did not prevent orientation-tuned suppression in layer 4. These results show that neurons in mouse V1, which lacks orientation columns, show orientation-dependent surround suppression in layer 4 and the superficial layers and that surround suppression in layer 4 does not require contributions from neurons in the superficial layers.

Efficient training protocol for rapid learning of the two-alternative forced-choice visual stimulus detection task

The potential of genetically engineered rodent models has accelerated demand for training procedures of behavioral tasks. Such training is generally time consuming and often shows large variability in learning speed between animals. To overcome these problems, we developed an efficient and stable training system for the two-alternative forced-choice (2AFC) visual stimulus detection task for freely behaving rodents. To facilitate the task learning, we introduced a spout-lever as the operandum and a three-step training program with four ingenuities: (1) a salient stimulus to draw passive attention, (2) a reward-guaranteed trial to keep motivation, (3) a behavior-corrective trial, and (4) switching from a reward-guaranteed trial to a nonguaranteed one to correct behavioral patterns. Our new training system realizes 1-week completion of the whole learning process, during which all rats were able to learn effortlessly the association between (1) lever-manipulation and reward and (2) visual stimulus and reward in a step-by-step manner. Thus, our new system provides an effective and stable training method for the 2AFC visual stimulus detection task. This method should help accelerate the move toward research bridging the visual functions measured in behavioral tasks and the contributing specific neurons/networks that are genetically manipulated or optically controlled.

Corticocortical feedback increases the spatial extent of normalization

Normalization has been proposed as a canonical computation operating across different brain regions, sensory modalities, and species. It provides a good phenomenological description of non-linear response properties in primary visual cortex (V1), including the contrast response function and surround suppression. Despite its widespread application throughout the visual system, the underlying neural mechanisms remain largely unknown. We recently observed that corticocortical feedback contributes to surround suppression in V1, raising the possibility that feedback acts through normalization. To test this idea, we characterized area summation and contrast response properties in V1 with and without feedback from V2 and V3 in alert macaques and applied a standard normalization model to the data. Area summation properties were well explained by a form of divisive normalization, which computes the ratio between a neuron's driving input and the spatially integrated activity of a "normalization pool." Feedback inactivation reduced surround suppression by shrinking the spatial extent of the normalization pool. This effect was independent of the gain modulation thought to mediate the influence of contrast on area summation, which remained intact during feedback inactivation. Contrast sensitivity within the receptive field center was also unaffected by feedback inactivation, providing further evidence that feedback participates in normalization independent of the circuit mechanisms involved in modulating contrast gain and saturation. These results suggest that corticocortical feedback contributes to surround suppression by increasing the visuotopic extent of normalization and, via this mechanism, feedback can play a critical role in contextual information processing.

Mouse primary visual cortex is used to detect both orientation and contrast changes

In mammals, the lateral geniculate nucleus (LGN) and the superior colliculus (SC) are the major targets of visual inputs from the retina. The LGN projects mainly to primary visual cortex (V1) while the SC targets the thalamus and brainstem, providing two potential pathways for processing visual inputs. Indeed, cortical lesion experiments in rodents have yielded mixed results, leading to the hypothesis that performance of simple visual behaviors may involve computations performed entirely by this subcortical pathway through the SC. However, these previous experiments have been limited by both their assays of behavioral performance and their use of lesions to change cortical activity. To determine the contribution of V1 to these tasks, we trained mice to perform threshold detection tasks in which they reported changes in either the contrast or orientation of visual stimuli. We then reversibly inhibited V1 by optogenetically activating parvalbumin-expressing inhibitory neurons with channelrhodopsin-2. We found that suppressing activity in V1 substantially impaired performance in visual detection tasks. The behavioral deficit depended on the retinotopic position of the visual stimulus, confirming that the effect was due to the specific suppression of the visually driven V1 neurons. Behavioral effects were seen with only moderate changes in neuronal activity, as inactivation that raised neuronal contrast thresholds by a median of only 14% was associated with a doubling of behavioral contrast detection threshold. Thus, detection of changes in either orientation or contrast is dependent on, and highly sensitive to, the activity of neurons in V1.

From circuit motifs to computations: mapping the behavioral repertoire of cortical interneurons

The exquisite architecture of cortex incorporates a myriad of inhibitory interneuron types. Until recently, the dearth of techniques for cell type identification in awake animals has made it difficult to link interneuron activity with circuit function, computation and behavior. This situation has changed dramatically in recent years with the advent of novel tools for targeting genetically distinct interneuron types so their activity can be observed and manipulated. The association of different interneuron subtypes with specific circuit functions, such as gain modulation or disinhibition, is starting to reveal canonical circuit motifs conserved across neocortical regions. Moreover, it appears that some interneuron types are recruited at specific behavioral events and likely control the flow of information among and within brain areas at behavioral time scales. Based on these results we propose that interneuron function goes beyond network coordination and interneurons should be viewed as integral elements of cortical computations serving behavior.

Interneuron cell types are fit to function

Understanding brain circuits begins with an appreciation of their component parts - the cells. Although GABAergic interneurons are a minority population within the brain, they are crucial for the control of inhibition. Determining the diversity of these interneurons has been a central goal of neurobiologists, but this amazing cell type has so far defied a generalized classification system. Interneuron complexity within the telencephalon could be simplified by viewing them as elaborations of a much more finite group of developmentally specified cardinal classes that become further specialized as they mature. Our perspective emphasizes that the ultimate goal is to dispense with classification criteria and directly define interneuron types by function.

Spatial integration in mouse primary visual cortex

Responses of many neurons in primary visual cortex (V1) are suppressed by stimuli exceeding the classical receptive field (RF), an important property that might underlie the computation of visual saliency. Traditionally, it has proven difficult to disentangle the underlying neural circuits, including feedforward, horizontal intracortical, and feedback connectivity. Since circuit-level analysis is particularly feasible in the mouse, we asked whether neural signatures of spatial integration in mouse V1 are similar to those of higher-order mammals and investigated the role of parvalbumin-expressing (PV+) inhibitory interneurons. Analogous to what is known from primates and carnivores, we demonstrate that, in awake mice, surround suppression is present in the majority of V1 neurons and is strongest in superficial cortical layers. Anesthesia with isoflurane-urethane, however, profoundly affects spatial integration: it reduces the laminar dependency, decreases overall suppression strength, and alters the temporal dynamics of responses. We show that these effects of brain state can be parsimoniously explained by assuming that anesthesia affects contrast normalization. Hence, the full impact of suppressive influences in mouse V1 cannot be studied under anesthesia with isoflurane-urethane. To assess the neural circuits of spatial integration, we targeted PV+ interneurons using optogenetics. Optogenetic depolarization of PV+ interneurons was associated with increased RF size and decreased suppression in the recorded population, similar to effects of lowering stimulus contrast, suggesting that PV+ interneurons contribute to spatial integration by affecting overall stimulus drive. We conclude that the mouse is a promising model for circuit-level mechanisms of spatial integration, which relies on the combined activity of different types of inhibitory interneurons.