This chapter applies a perspective from biophysically grounded computational modeling to explore how the intrinsic properties of thalamic microcircuits support the computational roles that the thalamus plays in perceptual and cognitive functions. A key focus is on the modeling of neurophysiological activity in the thalamus as nonlinear dynamical systems. Dynamical modeling can give insight into thalamic function across levels of analysis, including cellular channel properties, synaptic plasticity, and anatomical connectivity. This chapter reviews how the interplay between cellular and circuit mechanisms supports thalamic contributions to neural oscillations, regulation of brain state, top-down attentional control of sensory processing, and other cognitive functions. Understanding circuit function through biophysically grounded computational modeling and dynamical systems perspectives can also provide insight into how cellular and synaptic alterations caused by pharmacology or disease can impair thalamic function.

The somatosensory thalamocortical system has proven a tractable model for dissecting how different neuronal populations sculpt bidirectional information exchange between the thalamus and the cortex. This chapter reviews corticothalamic (CT) pathways from layers 5 (L5) and 6 (L6) of the primary somatosensory (S1) cortex to first-order ventroposterior (VP) and higher-order posterior medial (POm) somatosensory thalamic nuclei. With a focus on insights gained from recent cell-type–specific approaches in rodent models, we contrast L5 and L6 CT pathways at the scales of network architecture, anatomical connectivity, and physiological characteristics. We further compare the distinct feedforward inhibitory circuits engaged by L6 and L5 CT pathways, which involve the thalamic reticular nucleus and extrathalamic inhibitory nuclei, respectively. Where data exist, we discuss short- and long-term synaptic dynamics of the specific CT circuits. We close with a discussion of the proposed functions of these distinct pathways in conveying “top-down” cortical signals for both the modulation of thalamic processing of sensory information and the transmission of information between cortical regions.

This chapter traces the scientific and clinical evidence supporting the key role of the central thalamus in forebrain arousal-regulation mechanisms. Beginning from the original studies of Moruzzi and Magoun in the late 1940s, the evolving concepts of defined pathways extending from the central regions of the thalamus that modulate arousal via their projections to cortical and striatal neuronal populations are carefully examined.Anatomical and physiological distinctions between the main subnuclei grouped within the often loosely defined "central thalamus," the more rostral central lateral and paracentral nuclei (CL/Pc), and the more caudal centromedian-parafasicularis complex (Cm-Pf) are reviewed across experimental studies in rodents, cats, and non-human primates. In addition, relevant human neuroimaging, neurophysiological, lesion correlation, and interventional neurosurgical studies are compared and discussed in the context of the reviewed basic neuroscience studies characterizing the central thalamus. Several scientific controversies surrounding the contributions of the central thalamus to forebrain arousal are specifically considered. This synoptic review is further used to unpack the rationale for the use of electrical stimulation centered on the CL/Pc populations to support impaired arousal regulation resulting from relatively deafferented frontal cortical and striatal populations in patients across a wide range of outcomes following coma induced by structural brain injuries.

The cortex and thalamus are richly interconnected by feedforward and feedback pathways. For vision, the lateral geniculate nucleus (LGN) of the dorsal thalamus supplies the primary visual cortex with synaptically strong feedforward input that carries information about the external environment. The cortex, in turn, sends an even greater number of axons back to the LGN; however, these corticogeniculate inputs are relatively weak. Based on this anatomy, the cortex appears to be able to modulate the nature of the signals it receives from the LGN, potentially to meet the ongoing processing needs of the cortex. This chapter examines the relationship between the feedforward and feedback pathways interconnecting the LGN and visual cortex, with an emphasis on their organization with respect to the parallel processing streams originating in the retina. It also explores the influence of corticogeniculate feedback on vision.

Modern views on thalamus structure and function are the outcome of a long process of scientific discovery that started centuries ago and is still ongoing. As for other brain systems, strides along this path followed, to a large extent, from the introduction of new research tools capable of providing increasingly accurate delineations of neuronal connections and functional properties. These discoveries, in turn, expanded or corrected previous theories about thalamus operation and the contributions of the thalamus to behavior. Here, I summarize the key steps of this process, from the early descriptions of macroscopic anatomy and lesion effects through electrophysiological, neurochemical, and pathway-tracing studies to current connectomic, functional, and transcriptome investigations at the single-cell and brain-wide level.

The motor thalamus is a complex system made of several subnuclei that together play a pivotal role in the planning and execution of movement. Some subnuclei were considered to form the “classical motor thalamus” (ventroanterior, ventrolateral, and ventromedial nuclei), and other thalamic subnuclei (centrolateral, parafascicular, and centromedian nuclei) innervate sensorimotor cortical areas. The cerebellum innervates all motor thalamus nuclei, with axons from all four different cerebellar nuclei. Decades of neuroanatomical tracer experiments have revealed that the cerebellar nuclei axons form excitatory synapses in the thalamus, thus creating somototopically organized cerebello-thalamo-cortical networks. Electrophysiological data at the synaptic, cellular, and network levels reveal how the action-potential firing patterns of cerebellar and cerebral cortical inputs are integrated in the motor thalamus to synergistically drive its output. In the current chapter, we provide a review of the anatomical and electrophysiological data and share our opinion on how the cerebellum regulates the precise timing of thalamo-cortical activity. We conclude our chapter with a discussion of the role of the cerebello-thalamo-cortical tract in the pathophysiology and treatment of movement disorders, autism spectrum disorders, and epilepsy.

Once thought to be a simple relay, the thalamus is now seen as a more dynamic player in overall cortical functioning. Several relatively recent observations created led to this new understanding: (1) Glutamatergic inputs can be classified as drivers (e.g., main conveyors of information) or modulators. Most inputs in the thalamus and cortex are modulators, and identifying the driver subset has provided insights into thalamocortical circuit functioning. (2) Much of the modulator input to the thalamus relates to control of the response mode of relay cells–tonic or burst. Which mode operates at any time affects the significance of the message conveyed to the cortex. (3) We now appreciate that most of thalamus, called higher order (e.g., pulvinar and medial dorsal nucleus), serves as a central relay in a transthalamic corticocortical information route organized in parallel with direct connections. First-order nuclei (e.g., lateral geniculate and ventral posterior nuclei) instead relay peripheral information to the cortex. Thus, the thalamus not only provides a behaviorally relevant, dynamic control over the nature of the information relayed, but it also plays a key role in basic corticocortical communication. These findings are reviewed, along with speculations regarding the functional significance of transthalamic pathways.

Projection neurons are both the main target of inputs to the thalamus and the only conduit for thalamic outputs. Projection neurons show similar somatodendritic morphologies, electrotonic properties, and membrane conductances, and they are all glutamatergic. Moreover, their axons never cross the midline and always target both the prethalamic reticular nucleus and one or more forebrain structures, chiefly the cerebral cortex and/or striatum. Despite these similarities, however, new anatomical, electrophysiological, and transcriptomic methods with single-cell resolution have in recent years revealed that thalamic projection neurons are remarkably diverse. Differences prominently involve axon arborization and gene-expression patterns, but significant variations in somatodendritic morphology and membrane conductances are also evident. Here, I first review the structural, functional, and gene-expression single-cell level variation observed among thalamic projection neurons. Then, based on evidence currently available for rodents, I propose a tentative catalog of six high-level cell classes. This catalog provides a consistent and cellularly accurate framework for the analysis of classic, large-scale thalamic output pathways such as the thalamocortical, thalamostriatal, and thalamoamygdaloid, among others. Moreover, developmental studies suggest that the neuron classes identified here may reflect a fundamental level of cell-lineage diversity that precedes nuclei formation or the establishment of thalamus connection systems.

Inputs to the thalamus display perplexing heterogeneity in source, transmitter, and the complexity of axon terminals. Almost the entire neuraxis provides excitatory and/or inhibitory terminals to the thalamus. The structure of both glutamatergic and GABAergic inputs varies from simple unisynaptic to highly complex multisynaptic terminals. Variable bouton structures support neurotransmission with different kinetics. In contrast to earlier accounts that proposed the dominance of a single type of input on thalamocortical activity (“relay cell”), in the majority of the thalamus, integration of inputs with different origins, transmitters, and complexities is the rule. Because most thalamic inputs are confined to only a portion of the structure, the emerging picture is that inputs can be integrated in many distinct ways in different thalamic territories. As a consequence, unlike in modular networks, where, however complex the input space is, it is homogeneous across the structure (e.g., the striatum, cerebellum, or cortex), no canonical thalamic module can be defined. The reason for this unique complexity is presently unclear, but the lack of canonical input organization in the thalamus certainly limits the opportunity of generalizing thalamic transfer function between territories. Deciphering the role of the thalamus requires an understanding of the diversity in thalamic input integration in each region.

The higher-order thalamus (e.g., the pulvinar) is widely thought to play a critical role in its interactions with the neocortex, but identifying precisely what that role is has been somewhat challenging.Here, we describe how a computational approach to understanding the nature of learning and memory in the neocortex suggests three distinct, well-defined contributions of the thalamus: (1) attention, which is perhaps the most widely discussed function of the pulvinar, is supported by a pooled inhibition dynamic involving the thalamic reticular nucleus; (2) predictive learning, where the pulvinar serves as a kind of screen on which predictions are projected, and a temporal difference between predictions and subsequent outcomes can drive error-driven learning throughout the thalamocortical system; and (3) executive function in the circuits involving the frontal cortex, where the mediodorsal (MD) thalamus is largely similar anatomically to the pulvinar and could thus support similar attentional and predictive learning functions, whereas ventral thalamic nuclei receive inhibitory modulation from the basal ganglia, supporting a gating function to regulate action based on a strong competition of Go versus No Go informed by reinforcement learning.Taken together, these important modulatory and learning contributions of the thalamus suggest that a full computational understanding of the neocortex is significantly incomplete without an integration of the thalamic circuitry.