ABSTRACT
Attention filters sensory inputs to enhance task-relevant information. It is guided by an "attentional template" that represents the stimulus features that are currently relevant. To understand how the brain learns and uses templates, we trained monkeys to perform a visual search task that required them to repeatedly learn new attentional templates. Neural recordings found that templates were represented across the prefrontal and parietal cortex in a structured manner, such that perceptually neighboring templates had similar neural representations. When the task changed, a new attentional template was learned by incrementally shifting the template toward rewarded features. Finally, we found that attentional templates transformed stimulus features into a common value representation that allowed the same decision-making mechanisms to deploy attention, regardless of the identity of the template. Altogether, our results provide insight into the neural mechanisms by which the brain learns to control attention and how attention can be flexibly deployed across tasks.
Subject(s)
Attention , Decision Making , Learning , Parietal Lobe , Reward , Animals , HaplorhiniABSTRACT
The glycine transporter 1 (GlyT1) plays a crucial role in the regulation of both inhibitory and excitatory neurotransmission by removing glycine from the synaptic cleft. Given its close association with glutamate/glycine co-activated NMDA receptors (NMDARs), GlyT1 has emerged as a central target for the treatment of schizophrenia, which is often linked to hypofunctional NMDARs. Here, we report the cryo-EM structures of GlyT1 bound with substrate glycine and drugs ALX-5407, SSR504734, and PF-03463275. These structures, captured at three fundamental states of the transport cycle-outward-facing, occluded, and inward-facing-enable us to illustrate a comprehensive blueprint of the conformational change associated with glycine reuptake. Additionally, we identified three specific pockets accommodating drugs, providing clear insights into the structural basis of their inhibitory mechanism and selectivity. Collectively, these structures offer significant insights into the transport mechanism and recognition of substrate and anti-schizophrenia drugs, thus providing a platform to design small molecules to treat schizophrenia.
Subject(s)
Glycine Plasma Membrane Transport Proteins , Humans , Biological Transport , Glycine/metabolism , Glycine Plasma Membrane Transport Proteins/chemistry , Glycine Plasma Membrane Transport Proteins/metabolism , Glycine Plasma Membrane Transport Proteins/ultrastructure , Receptors, N-Methyl-D-Aspartate/metabolism , Schizophrenia/metabolism , Synaptic Transmission , Imidazoles/chemistry , Sarcosine/analogs & derivatives , Piperidines/chemistryABSTRACT
Alzheimer's disease (AD) is the most common cause of dementia worldwide, but the molecular and cellular mechanisms underlying cognitive impairment remain poorly understood. To address this, we generated a single-cell transcriptomic atlas of the aged human prefrontal cortex covering 2.3 million cells from postmortem human brain samples of 427 individuals with varying degrees of AD pathology and cognitive impairment. Our analyses identified AD-pathology-associated alterations shared between excitatory neuron subtypes, revealed a coordinated increase of the cohesin complex and DNA damage response factors in excitatory neurons and in oligodendrocytes, and uncovered genes and pathways associated with high cognitive function, dementia, and resilience to AD pathology. Furthermore, we identified selectively vulnerable somatostatin inhibitory neuron subtypes depleted in AD, discovered two distinct groups of inhibitory neurons that were more abundant in individuals with preserved high cognitive function late in life, and uncovered a link between inhibitory neurons and resilience to AD pathology.
Subject(s)
Alzheimer Disease , Brain , Aged , Humans , Alzheimer Disease/metabolism , Alzheimer Disease/pathology , Brain/metabolism , Brain/pathology , Cognition , Cognitive Dysfunction/metabolism , Neurons/metabolismABSTRACT
Human reasoning depends on reusing pieces of information by putting them together in new ways. However, very little is known about how compositional computation is implemented in the brain. Here, we ask participants to solve a series of problems that each require constructing a whole from a set of elements. With fMRI, we find that representations of novel constructed objects in the frontal cortex and hippocampus are relational and compositional. With MEG, we find that replay assembles elements into compounds, with each replay sequence constituting a hypothesis about a possible configuration of elements. The content of sequences evolves as participants solve each puzzle, progressing from predictable to uncertain elements and gradually converging on the correct configuration. Together, these results suggest a computational bridge between apparently distinct functions of hippocampal-prefrontal circuitry and a role for generative replay in compositional inference and hypothesis testing.
Subject(s)
Hippocampus , Prefrontal Cortex , Humans , Brain , Frontal Lobe , Hippocampus/physiology , Magnetic Resonance Imaging/methods , Neural Pathways , Prefrontal Cortex/physiologyABSTRACT
Cerebrospinal fluid (CSF) contains a tightly regulated immune system. However, knowledge is lacking about how CSF immunity is altered with aging or neurodegenerative disease. Here, we performed single-cell RNA sequencing on CSF from 45 cognitively normal subjects ranging from 54 to 82 years old. We uncovered an upregulation of lipid transport genes in monocytes with age. We then compared this cohort with 14 cognitively impaired subjects. In cognitively impaired subjects, downregulation of lipid transport genes in monocytes occurred concomitantly with altered cytokine signaling to CD8 T cells. Clonal CD8 T effector memory cells upregulated C-X-C motif chemokine receptor 6 (CXCR6) in cognitively impaired subjects. The CXCR6 ligand, C-X-C motif chemokine ligand 16 (CXCL16), was elevated in the CSF of cognitively impaired subjects, suggesting CXCL16-CXCR6 signaling as a mechanism for antigen-specific T cell entry into the brain. Cumulatively, these results reveal cerebrospinal fluid immune dysregulation during healthy brain aging and cognitive impairment.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Neurodegenerative Diseases , Humans , Middle Aged , Aged , Aged, 80 and over , Ligands , Brain , Aging , Lipids , BiomarkersABSTRACT
COVID survivors frequently experience lingering neurological symptoms that resemble cancer-therapy-related cognitive impairment, a syndrome for which white matter microglial reactivity and consequent neural dysregulation is central. Here, we explored the neurobiological effects of respiratory SARS-CoV-2 infection and found white-matter-selective microglial reactivity in mice and humans. Following mild respiratory COVID in mice, persistently impaired hippocampal neurogenesis, decreased oligodendrocytes, and myelin loss were evident together with elevated CSF cytokines/chemokines including CCL11. Systemic CCL11 administration specifically caused hippocampal microglial reactivity and impaired neurogenesis. Concordantly, humans with lasting cognitive symptoms post-COVID exhibit elevated CCL11 levels. Compared with SARS-CoV-2, mild respiratory influenza in mice caused similar patterns of white-matter-selective microglial reactivity, oligodendrocyte loss, impaired neurogenesis, and elevated CCL11 at early time points, but after influenza, only elevated CCL11 and hippocampal pathology persisted. These findings illustrate similar neuropathophysiology after cancer therapy and respiratory SARS-CoV-2 infection which may contribute to cognitive impairment following even mild COVID.
Subject(s)
COVID-19 , Influenza, Human , Neoplasms , Animals , Humans , Influenza, Human/pathology , Mice , Microglia/pathology , Myelin Sheath , Neoplasms/pathology , SARS-CoV-2ABSTRACT
Cognitive flexibility, the ability to alter strategy according to changing stimulus-response-reward relationships, is critical for updating learned behavior. Attentional set-shifting, a test of cognitive flexibility, depends on the activity of prefrontal cortex (PFC). It remains unclear, however, what role PFC neurons play to support set-shifting. Using optogenetics and two-photon calcium imaging, we demonstrate that medial PFC activity does not bias sensorimotor responses during set-shifting, but rather enables set-shifting by encoding trial feedback information, a role it has been known to play in other contexts. Unexpectedly, the functional properties of PFC cells did not vary with their efferent projection targets. Instead, representations of trial feedback formed a topological gradient, with cells more strongly selective for feedback information located further from the pial surface, where afferent input from the anterior cingulate cortex was denser. These findings identify a critical role for deep PFC projection neurons in enabling set-shifting through behavioral feedback monitoring.
Subject(s)
Cognition/physiology , Neurofeedback , Neurons/physiology , Prefrontal Cortex/physiology , Animals , Male , Mice , Mice, Inbred C57BLABSTRACT
An ability to build structured mental maps of the world underpins our capacity to imagine relationships between objects that extend beyond experience. In rodents, such representations are supported by sequential place cell reactivations during rest, known as replay. Schizophrenia is proposed to reflect a compromise in structured mental representations, with animal models reporting abnormalities in hippocampal replay and associated ripple activity during rest. Here, utilizing magnetoencephalography (MEG), we tasked patients with schizophrenia and control participants to infer unobserved relationships between objects by reorganizing visual experiences containing these objects. During a post-task rest session, controls exhibited fast spontaneous neural reactivation of presented objects that replayed inferred relationships. Replay was coincident with increased ripple power in hippocampus. Patients showed both reduced replay and augmented ripple power relative to controls, convergent with findings in animal models. These abnormalities are linked to impairments in behavioral acquisition and subsequent neural representation of task structure.
Subject(s)
Learning , Neurons/pathology , Schizophrenia/pathology , Schizophrenia/physiopathology , Alpha Rhythm/physiology , Behavior , Brain Mapping , Female , Hippocampus/physiopathology , Humans , Magnetoencephalography , Male , Models, Biological , Task Performance and AnalysisABSTRACT
The hippocampus is thought to encode a "cognitive map," a structural organization of knowledge about relationships in the world. Place cells, spatially selective hippocampal neurons that have been extensively studied in rodents, are one component of this map, describing the relative position of environmental features. However, whether this map extends to abstract, cognitive information remains unknown. Using the relative reward value of cues to define continuous "paths" through an abstract value space, we show that single neurons in primate hippocampus encode this space through value place fields, much like a rodent's place neurons encode paths through physical space. Value place fields remapped when cues changed but also became increasingly correlated across contexts, allowing maps to become generalized. Our findings help explain the critical contribution of the hippocampus to value-based decision-making, providing a mechanism by which knowledge of relationships in the world can be incorporated into reward predictions for guiding decisions.
Subject(s)
Hippocampus/physiology , Neurons/physiology , Animals , Macaca mulatta , Male , Models, Neurological , Task Performance and AnalysisABSTRACT
Single-cell transcriptomics has been widely applied to classify neurons in the mammalian brain, while systems neuroscience has historically analyzed the encoding properties of cortical neurons without considering cell types. Here we examine how specific transcriptomic types of mouse prefrontal cortex (PFC) projection neurons relate to axonal projections and encoding properties across multiple cognitive tasks. We found that most types projected to multiple targets, and most targets received projections from multiple types, except PFCâPAG (periaqueductal gray). By comparing Ca2+ activity of the molecularly homogeneous PFCâPAG type against two heterogeneous classes in several two-alternative choice tasks in freely moving mice, we found that all task-related signals assayed were qualitatively present in all examined classes. However, PAG-projecting neurons most potently encoded choice in cued tasks, whereas contralateral PFC-projecting neurons most potently encoded reward context in an uncued task. Thus, task signals are organized redundantly, but with clear quantitative biases across cells of specific molecular-anatomical characteristics.
Subject(s)
Cognition/physiology , Neurons/physiology , Prefrontal Cortex/physiology , Task Performance and Analysis , Animals , Calcium/metabolism , Choice Behavior , Cues , Imaging, Three-Dimensional , Integrases/metabolism , Mice, Inbred C57BL , Odorants , Optogenetics , Periaqueductal Gray/physiology , Reward , Single-Cell Analysis , Transcriptome/geneticsABSTRACT
Every day we make decisions critical for adaptation and survival. We repeat actions with known consequences. But we also draw on loosely related events to infer and imagine the outcome of entirely novel choices. These inferential decisions are thought to engage a number of brain regions; however, the underlying neuronal computation remains unknown. Here, we use a multi-day cross-species approach in humans and mice to report the functional anatomy and neuronal computation underlying inferential decisions. We show that during successful inference, the mammalian brain uses a hippocampal prospective code to forecast temporally structured learned associations. Moreover, during resting behavior, coactivation of hippocampal cells in sharp-wave/ripples represent inferred relationships that include reward, thereby "joining-the-dots" between events that have not been observed together but lead to profitable outcomes. Computing mnemonic links in this manner may provide an important mechanism to build a cognitive map that stretches beyond direct experience, thus supporting flexible behavior.
Subject(s)
Decision Making/physiology , Nerve Net/physiology , Thinking/physiology , Animals , Brain/physiology , Female , Hippocampus/metabolism , Hippocampus/physiology , Humans , Male , Memory/physiology , Mice , Mice, Inbred C57BL , Models, Neurological , Neurons/metabolism , Neurons/physiology , Prospective Studies , Young AdultABSTRACT
Chemotherapy results in a frequent yet poorly understood syndrome of long-term neurological deficits. Neural precursor cell dysfunction and white matter dysfunction are thought to contribute to this debilitating syndrome. Here, we demonstrate persistent depletion of oligodendrocyte lineage cells in humans who received chemotherapy. Developing a mouse model of methotrexate chemotherapy-induced neurological dysfunction, we find a similar depletion of white matter OPCs, increased but incomplete OPC differentiation, and a persistent deficit in myelination. OPCs from chemotherapy-naive mice similarly exhibit increased differentiation when transplanted into the microenvironment of previously methotrexate-exposed brains, indicating an underlying microenvironmental perturbation. Methotrexate results in persistent activation of microglia and subsequent astrocyte activation that is dependent on inflammatory microglia. Microglial depletion normalizes oligodendroglial lineage dynamics, myelin microstructure, and cognitive behavior after methotrexate chemotherapy. These findings indicate that methotrexate chemotherapy exposure is associated with persistent tri-glial dysregulation and identify inflammatory microglia as a therapeutic target to abrogate chemotherapy-related cognitive impairment. VIDEO ABSTRACT.
Subject(s)
Cognitive Dysfunction/chemically induced , Methotrexate/adverse effects , Oligodendroglia/drug effects , Animals , Brain/metabolism , Cell Differentiation , Cell Lineage , Cognitive Dysfunction/metabolism , Disease Models, Animal , Drug Therapy , Drug-Related Side Effects and Adverse Reactions , Humans , Methotrexate/pharmacology , Mice , Microglia/metabolism , Myelin Sheath/metabolism , Nerve Fibers, Myelinated , Neurogenesis/physiology , Neuroglia/metabolism , Neurons/drug effects , Oligodendroglia/metabolism , White Matter/metabolismABSTRACT
The increasing proportion of variance in human complex traits explained by polygenic scores, along with progress in preimplantation genetic diagnosis, suggests the possibility of screening embryos for traits such as height or cognitive ability. However, the expected outcomes of embryo screening are unclear, which undermines discussion of associated ethical concerns. Here, we use theory, simulations, and real data to evaluate the potential gain of embryo screening, defined as the difference in trait value between the top-scoring embryo and the average embryo. The gain increases very slowly with the number of embryos but more rapidly with the variance explained by the score. Given current technology, the average gain due to screening would be ≈2.5 cm for height and ≈2.5 IQ points for cognitive ability. These mean values are accompanied by wide prediction intervals, and indeed, in large nuclear families, the majority of children top-scoring for height are not the tallest.
Subject(s)
Embryo, Mammalian/metabolism , Genetic Testing , Multifactorial Inheritance/genetics , Adult , Family , Genome-Wide Association Study , Humans , PhenotypeABSTRACT
It has long been argued that only humans could produce and understand language. But now, for the first time, artificial language models (LMs) achieve this feat. Here we survey the new purchase LMs are providing on the question of how language is implemented in the brain. We discuss why, a priori, LMs might be expected to share similarities with the human language system. We then summarize evidence that LMs represent linguistic information similarly enough to humans to enable relatively accurate brain encoding and decoding during language processing. Finally, we examine which LM properties-their architecture, task performance, or training-are critical for capturing human neural responses to language and review studies using LMs as in silico model organisms for testing hypotheses about language. These ongoing investigations bring us closer to understanding the representations and processes that underlie our ability to comprehend sentences and express thoughts in language.
Subject(s)
Brain , Language , Humans , Brain/physiology , Animals , Artificial Intelligence , Models, NeurologicalABSTRACT
The activity patterns of grid cells form distinctively regular triangular lattices over the explored spatial environment and are largely invariant to visual stimuli, animal movement, and environment geometry. These neurons present numerous fascinating challenges to the curious (neuro)scientist: What are the circuit mechanisms responsible for creating spatially periodic activity patterns from the monotonic input-output responses of single neurons? How and why does the brain encode a local, nonperiodic variable-the allocentric position of the animal-with a periodic, nonlocal code? And, are grid cells truly specialized for spatial computations? Otherwise, what is their role in general cognition more broadly? We review efforts in uncovering the mechanisms and functional properties of grid cells, highlighting recent progress in the experimental validation of mechanistic grid cell models, and discuss the coding properties and functional advantages of the grid code as suggested by continuous attractor network models of grid cells.
Subject(s)
Cognition , Grid Cells , Models, Neurological , Animals , Cognition/physiology , Grid Cells/physiology , Humans , Space Perception/physiology , Nerve Net/physiology , Brain/physiology , Neurons/physiologyABSTRACT
In mammals, the activity of neurons in the entorhinal-hippocampal network is modulated by the animal's position and its movement through space. At multiple stages of this distributed circuit, distinct populations of neurons can represent a rich repertoire of navigation-related variables like the animal's location, the speed and direction of its movements, or the presence of borders and objects. Working together, spatially tuned neurons give rise to an internal representation of space, a cognitive map that supports an animal's ability to navigate the world and to encode and consolidate memories from experience. The mechanisms by which, during development, the brain acquires the ability to create an internal representation of space are just beginning to be elucidated. In this review, we examine recent work that has begun to investigate the ontogeny of circuitry, firing patterns, and computations underpinning the representation of space in the mammalian brain.
Subject(s)
Hippocampus , Space Perception , Animals , Space Perception/physiology , Hippocampus/physiology , Neurons/physiology , Movement , Cognition , MammalsABSTRACT
The discovery of neural signals that reflect the dynamics of perceptual decision formation has had a considerable impact. Not only do such signals enable detailed investigations of the neural implementation of the decision-making process but they also can expose key elements of the brain's decision algorithms. For a long time, such signals were only accessible through direct animal brain recordings, and progress in human neuroscience was hampered by the limitations of noninvasive recording techniques. However, recent methodological advances are increasingly enabling the study of human brain signals that finely trace the dynamics of the unfolding decision process. In this review, we highlight how human neurophysiological data are now being leveraged to furnish new insights into the multiple processing levels involved in forming decisions, to inform the construction and evaluation of mathematical models that can explain intra- and interindividual differences, and to examine how key ancillary processes interact with core decision circuits.
Subject(s)
Brain , Decision Making , Algorithms , Animals , Brain Mapping , HumansABSTRACT
Improvements in understanding the neurobiological basis of mental illness have unfortunately not translated into major advances in treatment. At this point, it is clear that psychiatric disorders are exceedingly complex and that, in order to account for and leverage this complexity, we need to collect longitudinal data sets from much larger and more diverse samples than is practical using traditional methods. We discuss how smartphone-based research methods have the potential to dramatically advance our understanding of the neuroscience of mental health. This, we expect, will take the form of complementing lab-based hard neuroscience research with dense sampling of cognitive tests, clinical questionnaires, passive data from smartphone sensors, and experience-sampling data as people go about their daily lives. Theory- and data-driven approaches can help make sense of these rich data sets, and the combination of computational tools and the big data that smartphones make possible has great potential value for researchers wishing to understand how aspects of brain function give rise to, or emerge from, states of mental health and illness.
Subject(s)
Mental Disorders , Neurosciences , Humans , Mental Health , SmartphoneABSTRACT
There are currently a number of theories of rodent hippocampal function. They fall into two major groups that differ in the role they impute to space in hippocampal information processing. On one hand, the cognitive map theory sees space as crucial and central, with other types of nonspatial information embedded in a primary spatial framework. On the other hand, most other theories see the function of the hippocampal formation as broader, treating all types of information as equivalent and concentrating on the processes carried out irrespective of the specific material being represented, stored, and manipulated. One crucial difference, therefore, is the extent to which theories see hippocampal pyramidal cells as representing nonspatial information independently of a spatial framework. Studies have reported the existence of single hippocampal unit responses to nonspatial stimuli, both to simple sensory inputs as well as to more complex stimuli such as objects, conspecifics, rewards, and time, and these findings been interpreted as evidence in favor of a broader hippocampal function. Alternatively, these nonspatial responses might actually be feature-in-place signals where the spatial nature of the response has been masked by the fact that the objects or features were only presented in one location or one spatial context. In this article, we argue that when tested in multiple locations, the hippocampal response to nonspatial stimuli is almost invariably dependent on the animal's location. Looked at collectively, the data provide strong support for the cognitive map theory.
Subject(s)
Hippocampus/physiology , Memory/physiology , Place Cells/physiology , Pyramidal Cells/physiology , AnimalsABSTRACT
Aging is associated with a progressive decline of brain function, and the underlying causes and possible interventions to prevent this cognitive decline have been the focus of intense investigation. The maintenance of neuronal function over the lifespan requires proper epigenetic regulation, and accumulating evidence suggests that the deterioration of the neuronal epigenetic landscape contributes to brain dysfunction during aging. Epigenetic aging of neurons may, however, be malleable. Recent reports have shown age-related epigenetic changes in neurons to be reversible and targetable by rejuvenation strategies that can restore brain function during aging. This review discusses the current evidence that identifies neuronal epigenetic aging as a driver of cognitive decline and a promising target of brain rejuvenation strategies, and it highlights potential approaches for the specific manipulation of the aging neuronal epigenome to restore a youthful epigenetic state in the brain.