Top-Down Control of Sweet and Bitter Taste in the Mammalian Brain.

Hardwired circuits encoding innate responses have emerged as an essential feature of the mammalian brain. Sweet and bitter evoke opposing predetermined behaviors. Sweet drives appetitive responses and consumption of energy-rich food sources, whereas bitter prevents ingestion of toxic chemicals. Here we identified and characterized the neurons in the brainstem that transmit sweet and bitter signals from the tongue to the cortex. Next we examined how the brain modulates this hardwired circuit to control taste behaviors. We dissect the basis for bitter-evoked suppression of sweet taste and show that the taste cortex and amygdala exert strong positive and negative feedback onto incoming bitter and sweet signals in the brainstem. Finally we demonstrate that blocking the feedback markedly alters responses to ethologically relevant taste stimuli. These results illustrate how hardwired circuits can be finely regulated by top-down control and reveal the neural basis of an indispensable behavioral response for all animals.

Generation of Functional Human 3D Cortico-Motor Assembloids.

Neurons in the cerebral cortex connect through descending pathways to hindbrain and spinal cord to activate muscle and generate movement. Although components of this pathway have been previously generated and studied in vitro, the assembly of this multi-synaptic circuit has not yet been achieved with human cells. Here, we derive organoids resembling the cerebral cortex or the hindbrain/spinal cord and assemble them with human skeletal muscle spheroids to generate 3D cortico-motor assembloids. Using rabies tracing, calcium imaging, and patch-clamp recordings, we show that corticofugal neurons project and connect with spinal spheroids, while spinal-derived motor neurons connect with muscle. Glutamate uncaging or optogenetic stimulation of cortical spheroids triggers robust contraction of 3D muscle, and assembloids are morphologically and functionally intact for up to 10 weeks post-fusion. Together, this system highlights the remarkable self-assembly capacity of 3D cultures to form functional circuits that could be used to understand development and disease.

General Anesthesia Decouples Cortical Pyramidal Neurons.

The mystery of general anesthesia is that it specifically suppresses consciousness by disrupting feedback signaling in the brain, even when feedforward signaling and basic neuronal function are left relatively unchanged. The mechanism for such selectiveness is unknown. Here we show that three different anesthetics have the same disruptive influence on signaling along apical dendrites in cortical layer 5 pyramidal neurons in mice. We found that optogenetic depolarization of the distal apical dendrites caused robust spiking at the cell body under awake conditions that was blocked by anesthesia. Moreover, we found that blocking metabotropic glutamate and cholinergic receptors had the same effect on apical dendrite decoupling as anesthesia or inactivation of the higher-order thalamus. If feedback signaling occurs predominantly through apical dendrites, the cellular mechanism we found would explain not only how anesthesia selectively blocks this signaling but also why conscious perception depends on both cortico-cortical and thalamo-cortical connectivity.

Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences.

What specific features should visual neurons encode, given the infinity of real-world images and the limited number of neurons available to represent them? We investigated neuronal selectivity in monkey inferotemporal cortex via the vast hypothesis space of a generative deep neural network, avoiding assumptions about features or semantic categories. A genetic algorithm searched this space for stimuli that maximized neuronal firing. This led to the evolution of rich synthetic images of objects with complex combinations of shapes, colors, and textures, sometimes resembling animals or familiar people, other times revealing novel patterns that did not map to any clear semantic category. These results expand our conception of the dictionary of features encoded in the cortex, and the approach can potentially reveal the internal representations of any system whose input can be captured by a generative model.

Corticoamygdala Transfer of Socially Derived Information Gates Observational Learning.

Observational learning is a powerful survival tool allowing individuals to learn about threat-predictive stimuli without directly experiencing the pairing of the predictive cue and punishment. This ability has been linked to the anterior cingulate cortex (ACC) and the basolateral amygdala (BLA). To investigate how information is encoded and transmitted through this circuit, we performed electrophysiological recordings in mice observing a demonstrator mouse undergo associative fear conditioning and found that BLA-projecting ACC (ACC→BLA) neurons preferentially encode socially derived aversive cue information. Inhibition of ACC→BLA alters real-time amygdala representation of the aversive cue during observational conditioning. Selective inhibition of the ACC→BLA projection impaired acquisition, but not expression, of observational fear conditioning. We show that information derived from observation about the aversive value of the cue is transmitted from the ACC to the BLA and that this routing of information is critically instructive for observational fear conditioning. VIDEO ABSTRACT.

Human-Specific NOTCH2NL Genes Affect Notch Signaling and Cortical Neurogenesis.

Genetic changes causing brain size expansion in human evolution have remained elusive. Notch signaling is essential for radial glia stem cell proliferation and is a determinant of neuronal number in the mammalian cortex. We find that three paralogs of human-specific NOTCH2NL are highly expressed in radial glia. Functional analysis reveals that different alleles of NOTCH2NL have varying potencies to enhance Notch signaling by interacting directly with NOTCH receptors. Consistent with a role in Notch signaling, NOTCH2NL ectopic expression delays differentiation of neuronal progenitors, while deletion accelerates differentiation into cortical neurons. Furthermore, NOTCH2NL genes provide the breakpoints in 1q21.1 distal deletion/duplication syndrome, where duplications are associated with macrocephaly and autism and deletions with microcephaly and schizophrenia. Thus, the emergence of human-specific NOTCH2NL genes may have contributed to the rapid evolution of the larger human neocortex, accompanied by loss of genomic stability at the 1q21.1 locus and resulting recurrent neurodevelopmental disorders.

Cortical Layer-Dependent Signaling in Cognition: Three Computational Modes of the Canonical Circuit.

The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded neurons in behaving monkeys. This review examines recent advances in laminar signaling in these two computations, using predictive coding computation as a common reference, and shows that each of these computations recruits distinct laminar circuits, particularly in layer 5, depending on the cognitive demands. These findings highlight many open questions, including how different interareal feedback pathways, originating from and terminating at different layers, convey distinct functional signals.

Deconstruction of Corticospinal Circuits for Goal-Directed Motor Skills.

Corticospinal neurons (CSNs) represent the direct cortical outputs to the spinal cord and play important roles in motor control across different species. However, their organizational principle remains unclear. By using a retrograde labeling system, we defined the requirement of CSNs in the execution of a skilled forelimb food-pellet retrieval task in mice. In vivo imaging of CSN activity during performance revealed the sequential activation of topographically ordered functional ensembles with moderate local mixing. Region-specific manipulations indicate that CSNs from caudal or rostral forelimb area control reaching or grasping, respectively, and both are required in the transitional pronation step. These region-specific CSNs terminate in different spinal levels and locations, therefore preferentially connecting with the premotor neurons of muscles engaged in different steps of the task. Together, our findings suggest that spatially defined groups of CSNs encode different movement modules, providing a logic for parallel-ordered corticospinal circuits to orchestrate multistep motor skills.

Regulation of Cerebral Cortex Folding by Controlling Neuronal Migration via FLRT Adhesion Molecules.

The folding of the mammalian cerebral cortex into sulci and gyri is thought to be favored by the amplification of basal progenitor cells and their tangential migration. Here, we provide a molecular mechanism for the role of migration in this process by showing that changes in intercellular adhesion of migrating cortical neurons result in cortical folding. Mice with deletions of FLRT1 and FLRT3 adhesion molecules develop macroscopic sulci with preserved layered organization and radial glial morphology. Cortex folding in these mutants does not require progenitor cell amplification but is dependent on changes in neuron migration. Analyses and simulations suggest that sulcus formation in the absence of FLRT1/3 results from reduced intercellular adhesion, increased neuron migration, and clustering in the cortical plate. Notably, FLRT1/3 expression is low in the human cortex and in future sulcus areas of ferrets, suggesting that intercellular adhesion is a key regulator of cortical folding across species.

Cortical Integration of Vestibular and Visual Cues for Navigation, Visual Processing, and Perception.

Despite increasing evidence of its involvement in several key functions of the cerebral cortex, the vestibular sense rarely enters our consciousness. Indeed, the extent to which these internal signals are incorporated within cortical sensory representation and how they might be relied upon for sensory-driven decision-making, during, for example, spatial navigation, is yet to be understood. Recent novel experimental approaches in rodents have probed both the physiological and behavioral significance of vestibular signals and indicate that their widespread integration with vision improves both the cortical representation and perceptual accuracy of self-motion and orientation. Here, we summarize these recent findings with a focus on cortical circuits involved in visual perception and spatial navigation and highlight the major remaining knowledge gaps. We suggest that vestibulo-visual integration reflects a process of constant updating regarding the status of self-motion, and access to such information by the cortex is used for sensory perception and predictions that may be implemented for rapid, navigation-related decision-making.

Folding brains: from development to disease modeling.

The human brain is characterized by the large size and intricate folding of its cerebral cortex, which are fundamental for our higher cognitive function and frequently altered in pathological dysfunction. Cortex folding is not unique to humans, nor even to primates, but is common across mammals. Cortical growth and folding are the result of complex developmental processes that involve neural stem and progenitor cells and their cellular lineages, the migration and differentiation of neurons, and the genetic programs that regulate and fine-tune these processes. All these factors combined generate mechanical stress and strain on the developing neural tissue, which ultimately drives orderly cortical deformation and folding. In this review we examine and summarize the current knowledge on the molecular, cellular, histogenic, and mechanical mechanisms that are involved in and influence folding of the cerebral cortex, and how they emerged and changed during mammalian evolution. We discuss the main types of pathological malformations of human cortex folding, their specific developmental origin, and how investigating their genetic causes has illuminated our understanding of key events involved. We close our review by presenting the animal and in vitro models of cortex folding that are currently used to study these devastating developmental brain disorders in children, and what are the main challenges that remain ahead of us to fully understand brain folding.

Cellular and Molecular Mechanisms Linking Human Cortical Development and Evolution.

The cerebral cortex is at the core of brain functions that are thought to be particularly developed in the human species. Human cortex specificities stem from divergent features of corticogenesis, leading to increased cortical size and complexity. Underlying cellular mechanisms include prolonged patterns of neuronal generation and maturation, as well as the amplification of specific types of stem/progenitor cells. While the gene regulatory networks of corticogenesis appear to be largely conserved among all mammals including humans, they have evolved in primates, particularly in the human species, through the emergence of rapidly divergent transcriptional regulatory elements, as well as recently duplicated novel genes. These human-specific molecular features together control key cellular milestones of human corticogenesis and are often affected in neurodevelopmental disorders, thus linking human neural development, evolution, and diseases.

Network state transitions during cortical development.

Mammalian cortical networks are active before synaptogenesis begins in earnest, before neuronal migration is complete, and well before an animal opens its eyes and begins to actively explore its surroundings. This early activity undergoes several transformations during development. The most important of these is a transition from episodic synchronous network events, which are necessary for patterning the neocortex into functionally related modules, to desynchronized activity that is computationally more powerful and efficient. Network desynchronization is perhaps the most dramatic and abrupt developmental event in an otherwise slow and gradual process of brain maturation. In this Review, we summarize what is known about the phenomenology of developmental synchronous activity in the rodent neocortex and speculate on the mechanisms that drive its eventual desynchronization. We argue that desynchronization of network activity is a fundamental step through which the cortex transitions from passive, bottom-up detection of sensory stimuli to active sensory processing with top-down modulation.

Neural networks of the mouse neocortex.

Numerous studies have examined the neuronal inputs and outputs of many areas within the mammalian cerebral cortex, but how these areas are organized into neural networks that communicate across the entire cortex is unclear. Over 600 labeled neuronal pathways acquired from tracer injections placed across the entire mouse neocortex enabled us to generate a cortical connectivity atlas. A total of 240 intracortical connections were manually reconstructed within a common neuroanatomic framework, forming a cortico-cortical connectivity map that facilitates comparison of connections from different cortical targets. Connectivity matrices were generated to provide an overview of all intracortical connections and subnetwork clusterings. The connectivity matrices and cortical map revealed that the entire cortex is organized into four somatic sensorimotor, two medial, and two lateral subnetworks that display unique topologies and can interact through select cortical areas. Together, these data provide a resource that can be used to further investigate cortical networks and their corresponding functions.

A high-performance speech neuroprosthesis.

Speech brain-computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speech into text1,2 or sound3,4. Early demonstrations, although promising, have not yet achieved accuracies sufficiently high for communication of unconstrained sentences from a large vocabulary1-7. Here we demonstrate a speech-to-text BCI that records spiking activity from intracortical microelectrode arrays. Enabled by these high-resolution recordings, our study participant-who can no longer speak intelligibly owing to amyotrophic lateral sclerosis-achieved a 9.1% word error rate on a 50-word vocabulary (2.7 times fewer errors than the previous state-of-the-art speech BCI2) and a 23.8% word error rate on a 125,000-word vocabulary (the first successful demonstration, to our knowledge, of large-vocabulary decoding). Our participant's attempted speech was decoded  at 62 words per minute, which is 3.4 times as fast as the previous record8 and begins to approach the speed of natural conversation (160 words per minute9). Finally, we highlight two aspects of the neural code for speech that are encouraging for speech BCIs: spatially intermixed tuning to speech articulators that makes accurate decoding possible from only a small region of cortex, and a detailed articulatory representation of phonemes that persists years after paralysis. These results show a feasible path forward for restoring rapid communication to people with paralysis who can no longer speak.

A high-performance neuroprosthesis for speech decoding and avatar control.

Speech neuroprostheses have the potential to restore communication to people living with paralysis, but naturalistic speed and expressivity are elusive1. Here we use high-density surface recordings of the speech cortex in a clinical-trial participant with severe limb and vocal paralysis to achieve high-performance real-time decoding across three complementary speech-related output modalities: text, speech audio and facial-avatar animation. We trained and evaluated deep-learning models using neural data collected as the participant attempted to silently speak sentences. For text, we demonstrate accurate and rapid large-vocabulary decoding with a median rate of 78 words per minute and median word error rate of 25%. For speech audio, we demonstrate intelligible and rapid speech synthesis and personalization to the participant's pre-injury voice. For facial-avatar animation, we demonstrate the control of virtual orofacial movements for speech and non-speech communicative gestures. The decoders reached high performance with less than two weeks of training. Our findings introduce a multimodal speech-neuroprosthetic approach that has substantial promise to restore full, embodied communication to people living with severe paralysis.

Neuromodulation of Brain State and Behavior.

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.

Interneuron Types as Attractors and Controllers.

Cortical interneurons display striking differences in shape, physiology, and other attributes, challenging us to appropriately classify them. We previously suggested that interneuron types should be defined by their role in cortical processing. Here, we revisit the question of how to codify their diversity based upon their division of labor and function as controllers of cortical information flow. We suggest that developmental trajectories provide a guide for appreciating interneuron diversity and argue that subtype identity is generated using a configurational (rather than combinatorial) code of transcription factors that produce attractor states in the underlying gene regulatory network. We present our updated three-stage model for interneuron specification: an initial cardinal step, allocating interneurons into a few major classes, followed by definitive refinement, creating subclasses upon settling within the cortex, and lastly, state determination, reflecting the incorporation of interneurons into functional circuit ensembles. We close by discussing findings indicating that major interneuron classes are both evolutionarily ancient and conserved. We propose that the complexity of cortical circuits is generated by phylogenetically old interneuron types, complemented by an evolutionary increase in principal neuron diversity. This suggests that a natural neurobiological definition of interneuron types might be derived from a match between their developmental origin and computational function.

The Anatomy and Physiology of Claustrum-Cortex Interactions.

The claustrum is one of the most widely connected regions of the forebrain, yet its function has remained obscure, largely due to the experimentally challenging nature of targeting this small, thin, and elongated brain area. However, recent advances in molecular techniques have enabled the anatomy and physiology of the claustrum to be studied with the spatiotemporal and cell type-specific precision required to eventually converge on what this area does. Here we review early anatomical and electrophysiological results from cats and primates, as well as recent work in the rodent, identifying the connectivity, cell types, and physiological circuit mechanisms underlying the communication between the claustrum and the cortex. The emerging picture is one in which the rodent claustrum is closely tied to frontal/limbic regions and plays a role in processes, such as attention, that are associated with these areas.

Developmental mechanisms underlying the evolution of human cortical circuits.

The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.