Independent response modulation of visual cortical neurons by attentional and behavioral states

Physically activated modes of attentional control

As we navigate through the day, our attentional control processes are constantly challenged by changing sensory information, goals, expectations, and motivations. At the same time, our bodies and brains are impacted by changes in global physiological state that can influence attentional processes. Based on converging lines of evidence from brain recordings in physically active humans and nonhumans, we propose a new framework incorporating at least two physically activated modes of attentional control in humans: altered gain control and differential neuromodulation of control networks. We discuss the implications of this framework for understanding a broader range of states and cognitive functions studied both in the laboratory and in the wild.

Reward history guides focal attention in whisker somatosensory cortex

Prior reward is a potent cue for attentional capture, but the underlying neurobiology is largely unknown. In a novel whisker touch detection task, we show that mice flexibly shift attention between specific whiskers on a trial-by-trial timescale, guided by the recent history of stimulus-reward association. Two-photon calcium imaging and spike recordings revealed a robust neurobiological correlate of attention in the somatosensory cortex (S1), boosting sensory responses to the attended whisker in L2/3 and L5, but not L4. Attentional boosting in L2/3 pyramidal cells was topographically precise and whisker-specific, and shifted receptive fields toward the attended whisker. L2/3 VIP interneurons were broadly activated by whisker stimuli, motion, and arousal but did not carry a whisker-specific attentional signal, and thus did not mediate spatially focused tactile attention. Together, these findings establish a new model of focal attention in the mouse whisker tactile system, showing that the history of stimuli and rewards in the recent past can dynamically engage local modulation in cortical sensory maps to guide flexible shifts in ongoing behavior.

Cooperative thalamocortical circuit mechanism for sensory prediction errors

The brain functions as a prediction machine, utilizing an internal model of the world to anticipate sensations and the outcomes of our actions. Discrepancies between expected and actual events, referred to as prediction errors, are leveraged to update the internal model and guide our attention towards unexpected events1-10. Despite the importance of prediction-error signals for various neural computations across the brain, surprisingly little is known about the neural circuit mechanisms responsible for their implementation. Here we describe a thalamocortical disinhibitory circuit that is required for generating sensory prediction-error signals in mouse primary visual cortex (V1). We show that violating animals' predictions by an unexpected visual stimulus preferentially boosts responses of the layer 2/3 V1 neurons that are most selective for that stimulus. Prediction errors specifically amplify the unexpected visual input, rather than representing non-specific surprise or difference signals about how the visual input deviates from the animal's predictions. This selective amplification is implemented by a cooperative mechanism requiring thalamic input from the pulvinar and cortical vasoactive-intestinal-peptide-expressing (VIP) inhibitory interneurons. In response to prediction errors, VIP neurons inhibit a specific subpopulation of somatostatin-expressing inhibitory interneurons that gate excitatory pulvinar input to V1, resulting in specific pulvinar-driven response amplification of the most stimulus-selective neurons in V1. Therefore, the brain prioritizes unpredicted sensory information by selectively increasing the salience of unpredicted sensory features through the synergistic interaction of thalamic input and neocortical disinhibitory circuits.

Modeling circuit mechanisms of opposing cortical responses to visual flow perturbations

In an ever-changing visual world, animals' survival depends on their ability to perceive and respond to rapidly changing motion cues. The primary visual cortex (V1) is at the forefront of this sensory processing, orchestrating neural responses to perturbations in visual flow. However, the underlying neural mechanisms that lead to distinct cortical responses to such perturbations remain enigmatic. In this study, our objective was to uncover the neural dynamics that govern V1 neurons' responses to visual flow perturbations using a biologically realistic computational model. By subjecting the model to sudden changes in visual input, we observed opposing cortical responses in excitatory layer 2/3 (L2/3) neurons, namely, depolarizing and hyperpolarizing responses. We found that this segregation was primarily driven by the competition between external visual input and recurrent inhibition, particularly within L2/3 and L4. This division was not observed in excitatory L5/6 neurons, suggesting a more prominent role for inhibitory mechanisms in the visual processing of the upper cortical layers. Our findings share similarities with recent experimental studies focusing on the opposing influence of top-down and bottom-up inputs in the mouse primary visual cortex during visual flow perturbations.

Disinhibition by VIP interneurons is orthogonal to cross-modal attentional modulation in primary visual cortex

Attentional modulation of sensory processing is a key feature of cognition; however, its neural circuit basis is poorly understood. A candidate mechanism is the disinhibition of pyramidal cells through vasoactive intestinal peptide (VIP) and somatostatin (SOM)-positive interneurons. However, the interaction of attentional modulation and VIP-SOM disinhibition has never been directly tested. We used all-optical methods to bi-directionally manipulate VIP interneuron activity as mice performed a cross-modal attention-switching task. We measured the activities of VIP, SOM, and parvalbumin (PV)-positive interneurons and pyramidal neurons identified in the same tissue and found that although activity in all cell classes was modulated by both attention and VIP manipulation, their effects were orthogonal. Attention and VIP-SOM disinhibition relied on distinct patterns of changes in activity and reorganization of interactions between inhibitory and excitatory cells. Circuit modeling revealed a precise network architecture consistent with multiplexing strong yet non-interacting modulations in the same neural population.

Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making

Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.

Visual attention to features and space in mice using reverse correlation

Visual attention allows the brain to evoke behaviors based on the most important visual features. Mouse models offer immense potential to gain a circuit-level understanding of this phenomenon, yet how mice distribute attention across features and locations is not well understood. Here, we describe a new approach to address this limitation by training mice to detect weak vertical bars in a background of dynamic noise while spatial cues manipulate their attention. By adapting a reverse-correlation method from human studies, we linked behavioral decisions to stimulus features and locations. We show that mice deployed attention to a small rostral region of the visual field. Within this region, mice attended to multiple features (orientation, spatial frequency, contrast) that indicated the presence of weak vertical bars. This attentional tuning grew with training, multiplicatively scaled behavioral sensitivity, approached that of an ideal observer, and resembled the effects of attention in humans. Taken together, we demonstrate that mice can simultaneously attend to multiple features and locations of a visual stimulus.

Probing inter-areal computations with a cellular resolution two-photon holographic mesoscope

Brain computation depends on intricately connected yet highly distributed neural networks. Due to the absence of the requisite technologies, causally testing fundamental hypotheses on the nature of inter-areal processing have remained largely out-of-each. Here we developed the first two photon holographic mesoscope, a system capable of simultaneously reading and writing neural activity patterns with single cell resolution across large regions of the brain. We demonstrate the precise photo-activation of spatial and temporal sequences of neurons in one brain area while reading out the downstream effect in several other regions. Investigators can use this new platform to understand feed-forward and feed-back processing in distributed neural circuits with single cell precision for the first time.

Probing top-down information in neocortical layer 1

Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally generated top-down information. Decades of work have elucidated how sensory neocortex processes physical stimulus features. By contrast, examining how top-down information is encoded and integrated with bottom-up signals has been challenging using traditional neuroscience methods. Recent technological advances in functional imaging of brain-wide afferents in behaving mice have enabled the direct measurement of top-down information. Here, we review the emerging literature on encoding of these internally generated signals by different projection systems enriched in neocortical layer 1 during defined brain functions, including memory, attention, and predictive coding. Moreover, we identify gaps in current knowledge and highlight future directions for this rapidly advancing field.