Contributions of Basal Ganglia Circuits to Perception, Attention, and Consciousness.

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. Here, we review anatomical, functional, and clinical evidence to demonstrate how the BG can influence perceptual processing and conscious states. This depends on the integrative relationship between cortex, BG, and thalamus, which allows contributions to sensory gating, predictive processing, selective attention, and representation of the temporal structure of events.

Thalamic contributions to the state and contents of consciousness.

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. Through reciprocal interactions with deep-layer cortical neurons, matrix neurons support wakefulness and determine perceptual thresholds, whereas the cortical interactions of core neurons maintain content and enable perceptual constancy. We further propose that conscious integration, segregation, and continuity depend on the convergent nature of corticothalamic projections enabling dimensionality reduction, a thalamic reticular nucleus-mediated divisive normalization-like process, and sustained coherent activity in thalamocortical loops, respectively. Overall, we conclude that the thalamus plays a central topological role in brain structures controlling conscious experience.

Primate thalamic nuclei select abstract rules and shape prefrontal dynamics.

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 primate-specific thalamus to select rules. To test this, we simultaneously measured spiking activity across PFC and two connected thalamic nuclei of monkeys applying rules. Abstract rule information first appeared in the ventroanterior thalamus (VA) - the main thalamic hub between BG and PFC. The mediodorsal thalamus (MD) also represented rule information before PFC, which persisted after rule cues were removed, to help maintain activation of relevant posterior PFC cell ensembles. MD, a major recipient of midbrain dopamine input, was first to represent information about behavioral outcomes. This persisted after the trial (also in PFC). A PFC-BG-thalamus model reproduced key findings, and thalamic-lesion modeling disrupted PFC rule representations. These results suggest a revised view of the neural basis of flexible behavior in primates, featuring a central role for thalamus in selecting high-level cognitive information from PFC and implementing post-error behavioral adjustments, and of the functional organization of PFC along its anterior-posterior dimension.

Evaluation of putative signatures of consciousness using specific definitions of responsiveness, connectedness, and consciousness.

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). METHODS: Using published data generated through the UNderstanding Consciousness Connectedness and Intra-Operative Unresponsiveness Study (NCT03284307), we evaluated 10 previously published resting-state EEG-based measures that were derived using unresponsiveness as a proxy for unconsciousness. Measures were tested across dexmedetomidine and propofol sedation and natural sleep. These markers represent the complexity, connectivity, cross-frequency coupling, graph theory, and power spectrum measures. RESULTS: Although many of the proposed markers were associated with consciousness per se (reported subjective experience), none were specific to consciousness alone; rather, each was also associated with connectedness (i.e. awareness of the environment). In addition, multiple markers showed no association with consciousness and were associated only with connectedness. Of the markers tested, loss of normalised-symbolic transfer entropy (front to back) was associated with connectedness across all three experimental conditions, whereas the transition from disconnected consciousness to unconsciousness was associated with significant decreases in permutation entropy and spectral exponent (P<0.05 for all conditions). CONCLUSIONS: None of the proposed EEG-based neural correlates of unresponsiveness corresponded solely to consciousness, highlighting the need for a more conservative use of the term (un)consciousness when assessing unresponsive participants. CLINICAL TRIAL REGISTRATION: NCT03284307.

The non-specific matrix thalamus facilitates the cortical information processing modes relevant for conscious awareness.

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. This model captures key features seen in propofol anesthesia, including diminished network integration, lowered state diversity, impaired susceptibility to perturbation, and decreased corticocortical coherence. Collectively, these signatures reflect a suppression of information transfer across the cerebral cortex. We recover these signatures of conscious arousal by selectively stimulating the matrix thalamus, recapitulating empirical results in macaque, as well as wake-like information processing states that reflect the thalamic modulation of large-scale cortical attractor dynamics. Our results highlight the role of matrix thalamocortical projections in shaping many features of complex cortical dynamics to facilitate the unique communication states supporting conscious awareness.

Brain Circuitry of Consciousness: A Review of Current Models and a Novel Synergistic Model With Clinical Application.

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. We review recent evidence describing the roles of the thalamocortical system and brainstem arousal nuclei in supporting awareness and arousal and discuss the utility of various neuroimaging studies in evaluating disorders of consciousness. We explore recent theoretical progress in mechanistic models of consciousness, focusing on 2 major models, the global neuronal workspace and integrated information theory, and review areas of controversy. Finally, we consider the potential implications of recent research for the day-to-day decision-making of clinical neurosurgeons and propose a simple "three-strikes" model to infer the integrity of the thalamocortical system, which can guide prognosticating return to consciousness.

Microscale multicircuit brain stimulation: Achieving real-time brain state control for novel applications.

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. Because of the dysfunction in distributed neural circuits - each requiring fine, tailored modulation - that characterizes most neuropsychiatric disorders, this approach holds limited promise. To develop the next generation of neuromodulation therapies, we will have to achieve fine-grained, closed-loop control over multiple neural circuits. Recent work has demonstrated spatial and frequency selectivity using microstimulation with many small, closely-spaced contacts, mimicking endogenous neural dynamics. Using custom electrode design and stimulation parameters, it should be possible to achieve bidirectional control over behavioral outcomes, such as increasing or decreasing arousal during central thalamic stimulation. Here, we discuss one possible approach, which we term microscale multicircuit brain stimulation (MMBS). We discuss how machine learning leverages behavioral and neural data to find optimal stimulation parameters across multiple contacts, to drive the brain towards desired states associated with behavioral goals. We expound a mathematical framework for MMBS, where behavioral and neural responses adjust the model in real-time, allowing us to adjust stimulation in real-time. These technologies will be critical to the development of the next generation of neurostimulation therapies, which will allow us to treat problems like disorders of consciousness and cognition.

Dynamic causal modelling of auditory surprise during disconnected consciousness: The role of feedback connectivity.

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). These states were captured using a serial awakening paradigm with the sedative alpha2 adrenergic agonist dexmedetomidine, chosen based on our published hypothesis that suppression of noradrenaline signaling is key to induce a state of sensory disconnection. High-density electroencephalography was recorded from 18 human subjects before and after administration of dexmedetomidine. By investigating event-related potentials and taking advantage of advances in Dynamic Causal Modeling (DCM), we assessed alterations in effective connectivity between nodes of a previously established auditory processing network. We found that during disconnected consciousness, the scalp-level response to standard tones produced a P3 response that was absent during connected consciousness. This P3 response resembled the response to oddball tones seen in connected consciousness. DCM showed that disconnection produced increases in standard tone feedback signaling throughout the auditory network. Simulation analyses showed that these changes in connectivity, most notably the increase in feedback from right superior temporal gyrus to right A1, can explain the new P3 response. Together these findings show that during disconnected consciousness there is a disruption of normal predictive coding processes, so that all incoming auditory stimuli become similarly surprising.

Thalamic deep brain stimulation paradigm to reduce consciousness: Cortico-striatal dynamics implicated in mechanisms of consciousness.

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. We used multi-microelectrode DBS targeted to CL in macaques while recording from frontal, parietal, and striatal regions. DBS induced episodes of abnormally long, vacant staring with low-frequency oscillations here termed vacant, perturbed consciousness (VPC). DBS modulated VPC likelihood in a frequency-specific manner. VPC events corresponded to decreases in measures of neural complexity (entropy) and integration (Φ*), proposed indices of consciousness, and substantial changes to communication in CST circuits. During VPC, power spectral density and coherence at low frequencies increased across CST circuits, especially in thalamo-parietal and cortico-striatal pathways. Decreased consciousness and neural integration corresponded to shifts in cortico-striatal network configurations that dissociated parietal and subcortical structures. Overall, the features of VPC and implicated networks were similar to those of absence epilepsy. As this same multi-microelectrode DBS method-but at different stimulation frequencies-can also increase consciousness in anesthetized macaques, it can be used to flexibly address questions of consciousness with limited confounds, as well as inform clinical investigations of other consciousness disorders.

Predictive Feedback, Early Sensory Representations, and Fast Responses to Predicted Stimuli Depend on NMDA Receptors.

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). While there are theoretical and computational frameworks for prediction, the circuit and receptor-level mechanisms are unclear. Using high-density EEG, Bayesian modeling, and machine learning, we show that inferred "causal" relationships between stimuli and frontal alpha activity account for reaction times (a proxy for predictions) on a trial-by-trial basis in an audiovisual delayed match-to-sample task which elicited predictions. Predictive ß feedback activated sensory representations in advance of predicted stimuli. Low-dose ketamine, an NMDAR blocker, but not the control drug dexmedetomidine, perturbed behavioral indices of predictions, their representation in higher-order cortex, feedback to posterior cortex, and pre-activation of sensory templates in higher-order sensory cortex. This study suggests that predictions depend on alpha activity in higher-order cortex, ß feedback, and NMDARs, and ketamine blocks access to learned predictive information.SIGNIFICANCE STATEMENT We learn the statistical regularities around us, creating associations between sensory stimuli. These associations can be exploited by generating predictions, which enable fast and efficient behavior. When predictions are perturbed, it can negatively influence perception and even contribute to psychiatric disorders, such as schizophrenia. Here we show that the frontal lobe generates predictions and sends them to posterior brain areas, to activate representations of predicted sensory stimuli before their appearance. Oscillations in neural activity (α and ß waves) are vital for these predictive mechanisms. The drug ketamine blocks predictions and the underlying mechanisms. This suggests that the generation of predictions in the frontal lobe, and the feedback pre-activating sensory representations in advance of stimuli, depend on NMDARs.

Disentangling the influences of multiple thalamic nuclei on prefrontal cortex and cognitive control.

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. This includes contributions to transformations such as rule-to-choice (parvocellular mediodorsal nucleus), value-to-choice (magnocellular mediodorsal nucleus), mnemonic-to-choice (anteromedial nucleus) and sensory-to-choice (medial pulvinar). Common mechanisms appear to be thalamic modulation of cortical gain and cortico-cortical functional connectivity. The anatomy also implies a unique role for medial PFC in modulating processing in thalamocortical circuits involving other orbital and lateral PFC regions. We further discuss how cortico-basal ganglia circuits may provide a mechanism through which PFC controls cortico-cortical functional connectivity.

Consciousness depends on integration between parietal cortex, striatum, and thalamus.

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. To test substrates and measures of consciousness, we recorded simultaneously from frontal cortex, parietal cortex, and subcortical structures, the striatum and thalamus, in awake, sleeping, and anesthetized macaques. We manipulated consciousness on a finer scale using thalamic stimulation, rousing macaques from continuously administered anesthesia. Our results show that, unlike measures targeting complexity, a measure additionally capturing neural integration (Φ∗) robustly correlated with changes in consciousness. Machine learning approaches show parietal cortex, striatum, and thalamus contributed more than frontal cortex to decoding differences in consciousness. These findings highlight the importance of integration between parietal and subcortical structures and challenge a key role for frontal cortex in consciousness.

Thalamus Modulates Consciousness via Layer-Specific Control of Cortex.

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. We found that neurons in thalamus and deep cortical layers are most sensitive to changes in consciousness level, consistent across different anesthetic agents and sleep. Deep-layer activity is sustained by interactions with CL. Consciousness also depends on deep-layer neurons providing feedback to superficial layers (not to deep layers), suggesting that long-range feedback and intracolumnar signaling are important. To show causality, we stimulated CL in anesthetized macaques and effectively restored arousal and wake-like neural processing. This effect was location and frequency specific. Our findings suggest layer-specific thalamocortical correlates of consciousness and inform how targeted deep brain stimulation can alleviate disorders of consciousness.

Topographic organization of connections between prefrontal cortex and mediodorsal thalamus: Evidence for a general principle of indirect thalamic pathways between directly connected cortical areas.

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. Tract tracer studies in macaques, involving subsets of PFC areas, have converged on coarse MD-PFC connectivity principles; but proposed finer-grained topographic schemes, which constrain interactions between MD and PFC, disagree in many respects. To investigate a unifying topographic scheme, we performed probabilistic tractography on diffusion MRI data from eight macaque monkeys, and estimated the probable paths connecting MD with each of all 19 architectonic areas of PFC. We found a connectional topography where the orderly progression from ventromedial to anterior to posterolateral PFC was represented from anteromedial to posterolateral MD. The projection zones of posterolateral PFC areas in MD showed substantial overlap, and those of ventral and anteromedial PFC areas in MD overlapped. The exception was cingulate area 24: its projection zone overlapped with projections zones of all other PFC areas. Overall, our data suggest that nearby, functionally related, directly connected PFC areas have partially overlapping projection zones in MD, consistent with a role for MD in coordinating communication across PFC. Indeed, the organizing principle for PFC projection zones in MD appears to reflect the flow of information across the hierarchical, multi-level PFC architecture. In addition, cingulate area 24 may have privileged access to influence thalamocortical interactions involving all other PFC areas.

Temporal Dynamics and Response Modulation across the Human Visual System in a Spatial Attention Task: An ECoG Study.

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. Electrode locations were reconstructed using a probabilistic atlas of the human visual system. HFB responses showed high spatial selectivity and tuning, constituting ECoG response fields (RFs), within and outside the topographic visual system. In accordance with monkey physiology studies, both RF widths and onset latencies increased systematically across the visual processing hierarchy. We used the spatial specificity of HFB responses to quantitatively study spatial attention effects and their temporal dynamics to probe a hierarchical top-down model suggesting that feedback signals back propagate the visual processing hierarchy. Consistent with such a model, the strengths of attentional modulation were found to be greater and modulation latencies to be shorter in posterior parietal cortex, middle temporal cortex and ventral extrastriate cortex compared with early visual cortex. However, inconsistent with such a model, attention effects were weaker and more delayed in anterior parietal and frontal cortex.SIGNIFICANCE STATEMENT In the human brain, visual attention has been predominantly studied using methods with high spatial, but poor temporal resolution such as fMRI, or high temporal, but poor spatial resolution such as EEG/MEG. Here, we investigate temporal dynamics and attention effects across the human visual system at a mesoscopic level that combines precise spatial and temporal measurements by using electrocorticography in epilepsy patients performing a classical spatial attention task. Electrode locations were reconstructed using a probabilistic atlas of the human visual system, thereby relating them to topography and processing hierarchy. We demonstrate regional differences in temporal dynamics across the attention network. Our findings do not fully support a top-down model that promotes influences on visual cortex by reversing the processing hierarchy.

Feedback from human posterior parietal cortex enables visuospatial category representations as early as primary visual cortex.

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. Methods: In this study, we decoded functional MRI signals and measured causal influences, across visual, parietal, and prefrontal cortex from participants performing categorization based on coarse- or fine-scale spatial information in thirteen healthy adults. Results: We show that category information based on coarse discriminations was represented in the PPC, in the intraparietal sulcus region, IPS1/2, at an early stage of categorization trials, whereas representations of category information based on fine-scale discriminations formed later during interactions between IPS1/2 and primary visual cortex (V1). Specifically, when fine-scale discriminations were necessary, we decoded significant category information from V1 at an intermediate stage of trials and again from IPS1/2 at a late stage. IPS1/2 feedback was critical, because categorization performance improved as causal influence from IPS1/2 to V1 increased. Further, these mechanisms were plastic, as the selectivity of IPS1/2 and V1 responses shifted markedly with retraining to categorize the same stimuli into two new groups. Conclusions: Our findings suggest that reentrant processing between the PPC and visual cortex enables flexible abstraction of category information.

Coding of spatial attention priorities and object features in the macaque lateral intraparietal cortex.

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. We studied the relationship between object feature and spatial attention properties of LIP cells in two macaques by measuring the cells' orientation selectivity and the degree of attentional enhancement while performing a delayed match-to-sample task. Monkeys had to match both the location and orientation of two visual gratings presented separately in time. We found a wide range in orientation selectivity and degree of attentional enhancement among LIP neurons. However, cells with significant attentional enhancement had much less orientation selectivity in their response than cells which showed no significant modulation by attention. Additionally, orientation-selective cells showed working memory activity for their preferred orientation, whereas cells showing attentional enhancement also synchronized with local neuronal activity. These results are consistent with models of selective attention incorporating two stages, where an initial feature-selective process guides a second stage of focal spatial attention. We suggest that LIP contributes to both stages, where the first stage involves orientation-selective LIP cells that support working memory of the relevant feature, and the second stage involves attention-enhanced LIP cells that synchronize to provide feedback on spatial priorities.

Spontaneous Neural Dynamics and Multi-scale Network Organization.

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. Subsequent work has sought to identify the corresponding neural signatures via electrophysiological measurements, as this would elucidate the neural origin of spontaneous hemodynamics and would reveal the temporal dynamics of these processes across slower and faster timescales. Here we survey common approaches to quantifying spontaneous neural activity, reviewing their empirical success, and their correspondence with the findings of neuroimaging. We emphasize invasive electrophysiological measurements, which are amenable to amplitude- and phase-based analyses, and which can report variations in connectivity with high spatiotemporal precision. After summarizing key findings from the human brain, we survey work in animal models that display similar multi-scale properties. We highlight that, across many spatiotemporal scales, the covariance structure of spontaneous neural activity reflects structural properties of neural networks and dynamically tracks their functional repertoire.

A Subcortical Pathway for Rapid, Goal-Driven, Attentional Filtering.

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.