Publications by authors named "Yuri B Saalmann"

In this video article, accompanying the paper "An approach to learning the hierarchical organization of the frontal lobe", we discuss a data driven approach to learning brain connectivity. Hierarchical models of brain connectivity are useful to understand how the brain can process sensory information, make decisions, and perform other high-level tasks. Despite extensive research, understanding the structure of the prefrontal cortex (PFC) remains a crucial challenge.

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Consciousness can be conceptualized as varying along at least two dimensions: the global state of consciousness and the content of conscious experience. Here, we highlight the cellular and systems-level contributions of the thalamus to conscious state and then argue for thalamic contributions to conscious content, including the integrated, segregated, and continuous nature of our experience. We underscore vital, yet distinct roles for core- and matrix-type thalamic neurons.

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Research into ascending sensory pathways and cortical networks has generated detailed models of perception. These same cortical regions are strongly connected to subcortical structures, such as the basal ganglia (BG), which have been conceptualized as playing key roles in reinforcement learning and action selection. However, because the BG amasses experiential evidence from higher and lower levels of cortical hierarchies, as well as higher-order thalamus, it is well positioned to dynamically influence perception.

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Flexible behavior depends on abstract rules to generalize beyond specific instances, and outcome monitoring to adjust actions. Cortical circuits are posited to read out rules from high-dimensional representations of task-relevant variables in prefrontal cortex (PFC). We instead hypothesized that converging inputs from PFC, directly or via basal ganglia (BG), enable thalamus to select rules.

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Background: Understanding the neural correlates of consciousness has important ramifications for the theoretical understanding of consciousness and for clinical anaesthesia. A major limitation of prior studies is the use of responsiveness as an index of consciousness. We identified a collection of measures derived from unresponsive subjects and more specifically their association with consciousness (any subjective experience) or connectedness (specific experience of environmental stimuli).

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The neurobiological mechanisms of arousal and anesthesia remain poorly understood. Recent evidence highlights the key role of interactions between the cerebral cortex and the diffusely projecting matrix thalamic nuclei. Here, we interrogate these processes in a whole-brain corticothalamic neural mass model endowed with targeted and diffusely projecting thalamocortical nuclei inferred from empirical data.

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How consciousness arises in the brain has important implications for clinical decision-making. We summarize recent findings in consciousness studies to provide a toolkit for clinicians to assess deficits in consciousness and predict outcomes after brain injury. Commonly encountered disorders of consciousness are highlighted, followed by the clinical scales currently used to diagnose them.

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Neurological and psychiatric disorders typically result from dysfunction across multiple neural circuits. Most of these disorders lack a satisfactory neuromodulation treatment. However, deep brain stimulation (DBS) has been successful in a limited number of disorders; DBS typically targets one or two brain areas with single contacts on relatively large electrodes, allowing for only coarse modulation of circuit function.

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The neural mechanisms through which individuals lose sensory awareness of their environment during anesthesia remains poorly understood despite being of vital importance to the field. Prior research has not distinguished between sensory awareness of the environment (connectedness) and consciousness itself. In the current study, we investigated the neural correlates of sensory awareness by contrasting neural responses to an auditory roving oddball paradigm during consciousness with sensory awareness (connected consciousness) and consciousness without sensory awareness (disconnected consciousness).

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Anesthetic manipulations provide much-needed causal evidence for neural correlates of consciousness, but non-specific drug effects complicate their interpretation. Evidence suggests that thalamic deep brain stimulation (DBS) can either increase or decrease consciousness, depending on the stimulation target and parameters. The putative role of the central lateral thalamus (CL) in consciousness makes it an ideal DBS target to manipulate circuit-level mechanisms in cortico-striato-thalamic (CST) systems, thereby influencing consciousness and related processes.

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Learned associations between stimuli allow us to model the world and make predictions, crucial for efficient behavior (e.g., hearing a siren, we expect to see an ambulance and quickly make way).

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The prefrontal cortex (PFC) has a complex relationship with the thalamus, involving many nuclei which occupy predominantly medial zones along its anterior-to-posterior extent. Thalamocortical neurons in most of these nuclei are modulated by the affective and cognitive signals which funnel through the basal ganglia. We review how PFC-connected thalamic nuclei likely contribute to all aspects of cognitive control: from the processing of information on internal states and goals, facilitating its interactions with mnemonic information and learned values of stimuli and actions, to their influence on high-level cognitive processes, attentional allocation and goal-directed behavior.

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The neural substrates of consciousness remain elusive. Competing theories that attempt to explain consciousness disagree on the contribution of frontal versus posterior cortex and omit subcortical influences. This lack of understanding impedes the ability to monitor consciousness, which can lead to adverse clinical consequences.

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Functional MRI and electrophysiology studies suggest that consciousness depends on large-scale thalamocortical and corticocortical interactions. However, it is unclear how neurons in different cortical layers and circuits contribute. We simultaneously recorded from central lateral thalamus (CL) and across layers of the frontoparietal cortex in awake, sleeping, and anesthetized macaques.

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Our ability to act flexibly, according to goals and context, is known as cognitive control. Hierarchical levels of control, reflecting different levels of abstraction, are represented across prefrontal cortex (PFC). Although the mediodorsal thalamic nucleus (MD) is extensively interconnected with PFC, the role of MD in cognitive control is unclear.

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The selection of behaviorally relevant information from cluttered visual scenes (often referred to as "attention") is mediated by a cortical large-scale network consisting of areas in occipital, temporal, parietal, and frontal cortex that is organized into a functional hierarchy of feedforward and feedback pathways. In the human brain, little is known about the temporal dynamics of attentional processing from studies at the mesoscopic level of electrocorticography (ECoG), that combines millisecond temporal resolution with precise anatomical localization of recording sites. We analyzed high-frequency broadband responses (HFB) responses from 626 electrodes implanted in 8 epilepsy patients who performed a spatial attention task.

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Introduction: Categorization is a fundamental cognitive process, whereby the brain assigns meaning to sensory stimuli. Previous studies have found category representations in prefrontal cortex and posterior parietal cortex (PPC). However, these higher-order areas lack the fine-scale spatial representations of early sensory areas, and it remains unclear what mechanisms enable flexible categorization based on fine-scale features.

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Primate posterior parietal cortex (PPC) is known to be involved in controlling spatial attention. Neurons in one part of the PPC, the lateral intraparietal area (LIP), show enhanced responses to objects at attended locations. Although many are selective for object features, such as the orientation of a visual stimulus, it is not clear how LIP circuits integrate feature-selective information when providing attentional feedback about behaviorally relevant locations to the visual cortex.

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Spontaneous neural activity has historically been viewed as task-irrelevant noise that should be controlled for via experimental design, and removed through data analysis. However, electrophysiology and functional MRI studies of spontaneous activity patterns, which have greatly increased in number over the past decade, have revealed a close correspondence between these intrinsic patterns and the structural network architecture of functional brain circuits. In particular, by analyzing the large-scale covariation of spontaneous hemodynamics, researchers are able to reliably identify functional networks in the human brain.

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Prefrontal cortex can exercise goal-driven attentional control over sensory information via cortical pathways. However, recent work demonstrates that prefrontal cortex can also influence thalamic relay nuclei via the thalamic reticular nucleus. This suggests the prefrontal-thalamic pathway mediates rapid and goal-driven attentional filtering at the earliest stages of sensory processing.

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The intralaminar and medial thalamic nuclei are part of the higher-order thalamus, which receives little sensory input, and instead forms extensive cortico-thalamo-cortical pathways. The large mediodorsal thalamic nucleus predominantly connects with the prefrontal cortex, the adjacent intralaminar nuclei connect with fronto-parietal cortex, and the midline thalamic nuclei connect with medial prefrontal cortex and medial temporal lobe. Taking into account this connectivity pattern, it is not surprising that the intralaminar and medial thalamus has been implicated in a variety of cognitive functions, including memory processing, attention and orienting, as well as reward-based behavior.

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We represent behaviorally relevant information in different spatial reference frames in order to interact effectively with our environment. For example, we need an egocentric (e.g.

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The brain directs its limited processing resources through various selection mechanisms, broadly referred to as attention. The present study investigated the temporal dynamics of two such selection mechanisms: space- and object-based selection. Previous evidence has demonstrated that preferential processing resulting from a spatial cue (i.

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