Cortical sensory processing across motivational states during goal-directed behavior

Effects of Different Individuals and Verbal Tones on Neural Networks in the Brain of Children with Cerebral Palsy

Background/Objectives: Motivation is a key factor for improving motor function and cognitive control in patients. Motivation for rehabilitation is influenced by the relationship between the therapist and patient, wherein appropriate voice encouragement is necessary to increase motivation. Therefore, we examined the differences between mothers and other individuals, such as physical therapists (PTs), in their verbal interactions with children with cerebral palsy who have poor communication abilities, as well as the neurological and physiological effects of variations in the tone of their speech. Methods: The three participants were children with cerebral palsy (Participant A: boy, 3 years; Participant B: girl, 7 years; Participant C: girl, 9 years). Participants' mothers and the assigned PTs were asked to speak under three conditions. During this, the brain activity of the participants was measured using a 19-channel electroencephalogram. The results were further analyzed using Independent Component Analysis frequency analysis with exact Low-Resolution Brain Electromagnetic Tomography, allowing for the identification and visualization of neural activity in three-dimensional brain functional networks. Results: The results of the ICA frequency analysis for each participant revealed distinct patterns of brain activity in response to verbal encouragement from the mother and PT, with differences observed across the theta, alpha, and beta frequency bands. Conclusions: Our study suggests that the children were attentive to their mothers' inquiries and focused on their internal experiences. Furthermore, it was indicated that when addressed by the PT, the participants found it easier to grasp the meanings and intentions of the words.

The DMC-Behavior Platform: An Open-Source Framework for Auditory-Guided Perceptual Decision-Making in Head-Fixed Mice

Perceptual decision-making describes the process of selecting an appropriate action based on the sensory information present in the immediate environment and is hence an omnipresent factor in the life of animals. In preclinical research, a widespread approach to study the neuronal correlates of perceptual decision-making is to record (and manipulate) neuronal activity in head-fixed mice performing behavioral tasks. In contrast to the technologies used to record/manipulate neuronal activity, standardization of the behavioral training of mice is generally neglected, a circumstance that is particularly true for behavioral tasks involving auditory stimuli. Here, we present the DMC-Behavior Platform, an open-source, cost-efficient framework for training head-fixed mice in perceptual decision-making tasks involving auditory stimuli. Combining the DMC-Behavior Platform with strategies to record and manipulate neuronal activity offers many opportunities to test hypotheses on the neuronal underpinnings of cognitive processes. We demonstrate the utility of the platform by training mice on auditory variants of three behavioral tasks commonly used to study perceptual decision-making: a detection, a Go/NoGo, and a two-alternative forced choice task. The presented work establishes the seamless integration and synchronization of external devices to record neuronal activity, task-related, and nontask-related behavioral variables. Our platform provides a valuable tool for more standardized and reproducible investigations into the neuronal circuits underlying auditory-guided decision-making.

Stimulus selection enhances value-modulated somatosensory processing in the superior colliculus

A fundamental trait of intelligent behavior is the ability to respond selectively to stimuli with higher value. Where along the neural hierarchy does somatosensory processing transition from a map of stimulus location to a map of stimulus value? To address this question, we recorded single-unit activity from populations of neurons in somatosensory cortex (S1) and midbrain superior colliculus (SC) in mice conditioned to respond to a positive-valued stimulus and withhold responses to an adjacent, negative-valued stimulus. The stimulus preference of the S1 population was equally weighted towards either stimulus, in line with a somatotopic map. Surprisingly, we discovered a large population of SC neurons that were disproportionately biased towards the positive stimulus. This disproportionate bias was largely driven by enhanced spike suppression for the negative stimulus. Removing the opportunity for mice to behaviorally select the positive stimulus reduced positive stimulus bias and spontaneous firing rates in SC but not S1, suggesting that neural selectivity was augmented by task readiness. Similarly, the spontaneous firing rates of SC but not S1 neurons predicted reaction times, suggesting that SC neurons played a persistent role in perceptual decision-making. Taken together, these data indicate that the somatotopic map in S1 is transformed into a value-based map in SC that encodes stimulus priority.

Interconnected neural circuits mediating social reward

Across species, social behaviors are shaped and maintained through positive reinforcement of affiliative social interactions. As with nonsocial rewards, the reinforcing properties of social interactions have been shown to involve interplay between various brain regions and the mesolimbic reward system. In this review, we summarize findings from rodent research on the neural circuits that encode and mediate different components of social reward-seeking behavior. We explore methods to parse and study social reward-related behaviors using available behavioral paradigms. We also compare the neural mechanisms that support social versus nonsocial reward-seeking. Finally, we discuss how internal state and neuromodulatory systems affect reward-seeking behavior and the neural circuits that underlie social reward.

Analysis methods for large-scale neuronal recordings

Simultaneous recordings from hundreds or thousands of neurons are becoming routine because of innovations in instrumentation, molecular tools, and data processing software. Such recordings can be analyzed with data science methods, but it is not immediately clear what methods to use or how to adapt them for neuroscience applications. We review, categorize, and illustrate diverse analysis methods for neural population recordings and describe how these methods have been used to make progress on longstanding questions in neuroscience. We review a variety of approaches, ranging from the mathematically simple to the complex, from exploratory to hypothesis-driven, and from recently developed to more established methods. We also illustrate some of the common statistical pitfalls in analyzing large-scale neural data.

Sex differences in neural representations of social and nonsocial reward in the medial prefrontal cortex

The reinforcing nature of social interactions is necessary for the maintenance of appropriate social behavior. However, the neural substrates underlying social reward processing and how they might differ based on the sex and internal state of the animal remains unknown. It is also unclear whether these neural substrates are shared with those involved in nonsocial rewarding processing. We developed a fully automated, two choice (social-sucrose) operant assay in which mice choose between social and nonsocial rewards to directly compare the reward-related behaviors associated with two competing stimuli. We performed cellular resolution calcium imaging of medial prefrontal cortex (mPFC) neurons in male and female mice across varying states of water restriction and social isolation. We found that mPFC neurons maintain largely non-overlapping, flexible representations of social and nonsocial reward that vary with internal state in a sex-dependent manner. Additionally, optogenetic manipulation of mPFC activity during the reward period of the assay disrupted reward-seeking behavior across male and female mice. Thus, using a two choice operant assay, we have identified sex-dependent, non-overlapping neural representations of social and nonsocial reward in the mPFC that vary with internal state and that are essential for appropriate reward-seeking behavior.

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.

High-dimensional cortical signals reveal rich bimodal and working memory-like representations among S1 neuron populations

Complexity is important for flexibility of natural behavior and for the remarkably efficient learning of the brain. Here we assessed the signal complexity among neuron populations in somatosensory cortex (S1). To maximize our chances of capturing population-level signal complexity, we used highly repeatable resolvable visual, tactile, and visuo-tactile inputs and neuronal unit activity recorded at high temporal resolution. We found the state space of the spontaneous activity to be extremely high-dimensional in S1 populations. Their processing of tactile inputs was profoundly modulated by visual inputs and even fine nuances of visual input patterns were separated. Moreover, the dynamic activity states of the S1 neuron population signaled the preceding specific input long after the stimulation had terminated, i.e., resident information that could be a substrate for a working memory. Hence, the recorded high-dimensional representations carried rich multimodal and internal working memory-like signals supporting high complexity in cortical circuitry operation.

Vagus nerve stimulation during training fails to improve learning in healthy rats

Learning new skills requires neuroplasticity. Vagus nerve stimulation (VNS) during sensory and motor events can increase neuroplasticity in networks related to these events and might therefore serve to facilitate learning on sensory and motor tasks. We tested if VNS could broadly improve learning on a wide variety of tasks across different skill domains in healthy, female adult rats. VNS was paired with presentation of stimuli or on successful trials during training, strategies known to facilitate plasticity and improve recovery in models of neurological disorders. VNS failed to improve either rate of learning or performance for any of the tested tasks, which included skilled forelimb motor control, speech sound discrimination, and paired-associates learning. These results contrast recent findings from multiple labs which found VNS pairing during training produced learning enhancements across motor, auditory, and cognitive domains. We speculate that these contrasting results may be explained by key differences in task designs, training timelines and animal handling approaches, and that while VNS may be able to facilitate rapid and early learning processes in healthy subjects, it does not broadly enhance learning for difficult tasks.

Differential representation of sensory information and behavioral choice across layers of the mouse auditory cortex

The activity of neurons in sensory areas sometimes covaries with upcoming choices in decision-making tasks. However, the prevalence, causal origin, and functional role of choice-related activity remain controversial. Understanding the circuit-logic of decision signals in sensory areas will require understanding their laminar specificity, but simultaneous recordings of neural activity across the cortical layers in forced-choice discrimination tasks have not yet been performed. Here, we describe neural activity from such recordings in the auditory cortex of mice during a frequency discrimination task with delayed report, which, as we show, requires the auditory cortex. Stimulus-related information was widely distributed across layers but disappeared very quickly after stimulus offset. Choice selectivity emerged toward the end of the delay period-suggesting a top-down origin-but only in the deep layers. Early stimulus-selective and late choice-selective deep neural ensembles were correlated, suggesting that the choice-selective signal fed back to the auditory cortex is not just action specific but develops as a consequence of the sensory-motor contingency imposed by the task.

Involvement of primary somatosensory cortex in motor learning and task execution

The primary somatosensory cortex (S1) is responsible for processing information related to tactile stimulation, motor learning and control. Despite its significance, the connection between S1 and the primary motor cortex (M1), as well as its role in motor learning, remains a topic of ongoing exploration. In the present study, we silenced S1 by the GABA receptor agonist muscimol to study the potential roles of S1 in motor learning and task execution. Our results show that the inhibition of S1 leads to an immediate impairment in performance during the training session and also a substantial reduction in performance improvement during post-test session on the subsequent day. To understand the underlying mechanism, we used intravital two-photon imaging to investigate the dynamics of dendritic spines of layer V pyramidal neurons and the calcium activities of pyramidal neurons in M1 after inhibition of S1. Notably, S1 inhibition reduces motor training-induced spine formation and facilitates the elimination of existing spines of layer V pyramidal neurons in M1. The calcium activities in M1 exhibit a significant decrease during both resting and running periods following S1 inhibition. Furthermore, inhibition of S1, but not M1, significantly impairs the execution of the acquired motor task in the well-trained animals. Together, these findings reveal that S1 plays important roles in motor learning and task execution.

Separation of bimodal fMRI responses in mouse somatosensory areas into V1 and non-V1 contributions

Multisensory integration is necessary for the animal to survive in the real world. While conventional methods have been extensively used to investigate the multisensory integration process in various brain areas, its long-range interactions remain less explored. In this study, our goal was to investigate interactions between visual and somatosensory networks on a whole-brain scale using 15.2-T BOLD fMRI. We compared unimodal to bimodal BOLD fMRI responses and dissected potential cross-modal pathways with silencing of primary visual cortex (V1) by optogenetic stimulation of local GABAergic neurons. Our data showed that the influence of visual stimulus on whisker activity is higher than the influence of whisker stimulus on visual activity. Optogenetic silencing of V1 revealed that visual information is conveyed to whisker processing via both V1 and non-V1 pathways. The first-order ventral posteromedial thalamic nucleus (VPM) was functionally affected by non-V1 sources, while the higher-order posterior medial thalamic nucleus (POm) was predominantly modulated by V1 but not non-V1 inputs. The primary somatosensory barrel field (S1BF) was influenced by both V1 and non-V1 inputs. These observations provide valuable insights for into the integration of whisker and visual sensory information.

Interareal Synaptic Inputs Underlying Whisking-Related Activity in the Primary Somatosensory Barrel Cortex

Body movements influence brain-wide neuronal activities. In the sensory cortex, thalamocortical bottom-up inputs and motor-sensory top-down inputs are thought to affect the dynamics of membrane potentials (Vm ) of neurons and change their processing of sensory information during movements. However, direct perturbation of the axons projecting to the sensory cortex from other remote areas during movements has remained unassessed, and therefore the interareal circuits generating motor-related signals in sensory cortices remain unclear. Using a Gi/o -coupled opsin, eOPN3, we here inhibited interareal signals incoming to the whisker primary somatosensory barrel cortex (wS1) of awake male mice and tested their effects on whisking-related changes in neuronal activities in wS1. Spontaneous whisking in air induced the changes in spike rates of a subset of wS1 neurons, which were accompanied by depolarization and substantial reduction of slow-wave oscillatory fluctuations of Vm Despite an extensive innervation, inhibition of inputs from the whisker primary motor cortex (wM1) to wS1 did not alter the spike rates and Vm dynamics of wS1 neurons during whisking. In contrast, inhibition of axons from the whisker-related thalamus (wTLM) and the whisker secondary somatosensory cortex (wS2) to wS1 largely attenuated the whisking-related supra- and sub-threshold Vm dynamics of wS1 neurons. Notably, silencing inputs from wTLM markedly decreased the modulation depth of whisking phase-tuned neurons in wS1, while inhibiting wS2 inputs did not impact the whisking variable tuning of wS1 neurons. Thus, sensorimotor integration in wS1 during spontaneous whisking is predominantly facilitated by direct synaptic inputs from wTLM and wS2 rather than from wM1.

Distributed and specific encoding of sensory, motor, and decision information in the mouse neocortex during goal-directed behavior

Goal-directed behaviors involve coordinated activity in many cortical areas, but whether the encoding of task variables is distributed across areas or is more specifically represented in distinct areas remains unclear. Here, we compared representations of sensory, motor, and decision information in the whisker primary somatosensory cortex, medial prefrontal cortex, and tongue-jaw primary motor cortex in mice trained to lick in response to a whisker stimulus with mice that were not taught this association. Irrespective of learning, properties of the sensory stimulus were best encoded in the sensory cortex, whereas fine movement kinematics were best represented in the motor cortex. However, movement initiation and the decision to lick in response to the whisker stimulus were represented in all three areas, with decision neurons in the medial prefrontal cortex being more selective, showing minimal sensory responses in miss trials and motor responses during spontaneous licks. Our results reconcile previous studies indicating highly specific vs. highly distributed sensorimotor processing.

Activation of M1 cholinergic receptors in mouse somatosensory cortex enhances information processing and detection behaviour

To optimise sensory representations based on environmental demands, the activity of cortical neurons is regulated by neuromodulators such as Acetylcholine (ACh). ACh is implicated in cognitive functions including attention, arousal and sleep cycles. However, it is not clear how specific ACh receptors shape the activity of cortical neurons in response to sensory stimuli. Here, we investigate the role of a densely expressed muscarinic ACh receptor M1 in information processing in the mouse primary somatosensory cortex and its influence on the animal's sensitivity to detect vibrotactile stimuli. We show that M1 activation results in faster and more reliable neuronal responses, manifested by a significant reduction in response latencies and the trial-to-trial variability. At the population level, M1 activation reduces the network synchrony, and thus enhances the capacity of cortical neurons in conveying sensory information. Consistent with the neuronal findings, we show that M1 activation significantly improves performances in a vibriotactile detection task.

Reward Modulates Visual Responses in the Superficial Superior Colliculus of Mice

The processing of sensory input is constantly adapting to behavioral demands and internal states. The drive to obtain reward, e.g., searching for water when thirsty, is a strong behavioral demand and associating the reward with its source, a certain environment or action, is paramount for survival. Here, we show that water reward increases subsequent visual activity in the superficial layers of the superior colliculus (SC), which receive direct input from the retina and belong to the earliest stages of visual processing. We trained mice of either sex to perform a visual decision task and recorded the activity of neurons in the SC using two-photon calcium imaging and high-density electrophysiological recordings. Responses to visual stimuli in around 20% of visually responsive neurons in the superficial SC were affected by reward delivered in the previous trial. Reward mostly increased visual responses independent from modulations due to pupil size changes. The modulation of visual responses by reward could not be explained by movements like licking. It was specific to responses to the following visual stimulus, independent of slow fluctuations in neural activity and independent of how often the stimulus was previously rewarded. Electrophysiological recordings confirmed these results and revealed that reward affected the early phase of the visual response around 80 ms after stimulus onset. Modulation of visual responses by reward, but not pupil size, significantly improved the performance of a population decoder to detect visual stimuli, indicating the relevance of reward modulation for the visual performance of the animal.SIGNIFICANCE STATEMENT To learn which actions lead to food, water, or safety, it is necessary to integrate the receiving of reward with sensory stimuli related to the reward. Cortical stages of sensory processing have been shown to represent stimulus-reward associations. Here, we show, however, that reward influences neurons at a much earlier stage of sensory processing, the superior colliculus (SC), receiving direct input from the retina. Visual responses were increased shortly after the animal received the water reward, which led to an improved stimulus signal in the population of these visual neurons. Reward modulation of early visual responses may thus improve perception of visual environments predictive of reward.

Meso-Py: Dual Brain Cortical Calcium Imaging in Mice during Head-Fixed Social Stimulus Presentation

We present a cost-effective, compact foot-print, and open-source Raspberry Pi-based widefield imaging system. The compact nature allows the system to be used for close-proximity dual-brain cortical mesoscale functional-imaging to simultaneously observe activity in two head-fixed animals in a staged social touch-like interaction. We provide all schematics, code, and protocols for a rail system where head-fixed mice are brought together to a distance where the macrovibrissae of each mouse make contact. Cortical neuronal functional signals (GCaMP6s; genetically encoded Ca2+ sensor) were recorded from both mice simultaneously before, during, and after the social contact period. When the mice were together, we observed bouts of mutual whisking and cross-mouse correlated cortical activity across the cortex. Correlations were not observed in trial-shuffled mouse pairs, suggesting that correlated activity was specific to individual interactions. Whisking-related cortical signals were observed during the period where mice were together (closest contact). The effects of social stimulus presentation extend outside of regions associated with mutual touch and have global synchronizing effects on cortical activity.

Striatal Dopamine Signals and Reward Learning

We are constantly bombarded by sensory information and constantly making decisions on how to act. In order to optimally adapt behavior, we must judge which sequences of sensory inputs and actions lead to successful outcomes in specific circumstances. Neuronal circuits of the basal ganglia have been strongly implicated in action selection, as well as the learning and execution of goal-directed behaviors, with accumulating evidence supporting the hypothesis that midbrain dopamine neurons might encode a reward signal useful for learning. Here, we review evidence suggesting that midbrain dopaminergic neurons signal reward prediction error, driving synaptic plasticity in the striatum underlying learning. We focus on phasic increases in action potential firing of midbrain dopamine neurons in response to unexpected rewards. These dopamine neurons prominently innervate the dorsal and ventral striatum. In the striatum, the released dopamine binds to dopamine receptors, where it regulates the plasticity of glutamatergic synapses. The increase of striatal dopamine accompanying an unexpected reward activates dopamine type 1 receptors (D1Rs) initiating a signaling cascade that promotes long-term potentiation of recently active glutamatergic input onto striatonigral neurons. Sensorimotor-evoked glutamatergic input, which is active immediately before reward delivery will thus be strengthened onto neurons in the striatum expressing D1Rs. In turn, these neurons cause disinhibition of brainstem motor centers and disinhibition of the motor thalamus, thus promoting motor output to reinforce rewarded stimulus-action outcomes. Although many details of the hypothesis need further investigation, altogether, it seems likely that dopamine signals in the striatum might underlie important aspects of goal-directed reward-based learning.

Physiological state gates sensorimotor cortical processing and goal-directed behavior

Goal-directed behavior is often studied under food- and water-restricted states. A study by Matteucci et al.¹ in this issue of Neuron reveals that task performance and sensorimotor cortical encoding are impaired under both low and high motivational states but improve with physiological adaption.