Functional anatomy of non-REM sleep

The state of non-REM sleep (NREM), or slow wave sleep, is associated with a synchronized EEG pattern in which sleep spindles and/or K complexes and high-voltage slow wave activity (SWA) can be recorded over the entire cortical surface. In humans, NREM is subdivided into stages 2 and 3–4 (presently named N3) depending on the proportions of each of these polygraphic events. NREM is necessary for normal physical and intellectual performance and behavior. An overview of the brain structures involved in NREM generation shows that the thalamus and the cerebral cortex are absolutely necessary for the most significant bioelectric and behavioral events of NREM to be expressed; other structures like the basal forebrain, anterior hypothalamus, cerebellum, caudal brain stem, spinal cord and peripheral nerves contribute to NREM regulation and modulation. In NREM stage 2, sustained hyperpolarized membrane potential levels resulting from interaction between thalamic reticular and projection neurons gives rise to spindle oscillations in the membrane potential; the initiation and termination of individual spindle sequences depends on corticothalamic activities. Cortical and thalamic mechanisms are also involved in the generation of EEG delta SWA that appears in deep stage 3–4 (N3) NREM; the cortex has classically been considered to be the structure that generates this activity, but delta oscillations can also be generated in thalamocortical neurons. NREM is probably necessary to normalize synapses to a sustainable basal condition that can ensure cellular homeostasis. Sleep homeostasis depends not only on the duration of prior wakefulness but also on its intensity, and sleep need increases when wakefulness is associated with learning. NREM seems to ensure cell homeostasis by reducing the number of synaptic connections to a basic level; based on simple energy demands, cerebral energy economizing during NREM sleep is one of the prevalent hypotheses to explain NREM homeostasis.Grant BFU2009-06991/BFI from the Spanish Ministry of Science and Innovation supported this wor

Linking Attention to Learning, Expectation, Competition, and Consciousness

The concept of attention has been used in many senses, often without clarifying how or why attention works as it does. Attention, like consciousness, is often described in a disembodied way. The present article summarizes neural models and supportive data and how attention is linked to processes of learning, expectation, competition, and consciousness. A key them is that attention modulates cortical self-organization and stability. Perceptual and cognitive neocortex is organized into six main cell layers, with characteristic sub-lamina. Attention is part of unified design of bottom-up, horizontal, and top-down interactions among indentified cells in laminar cortical circuits. Neural models clarify how attention may be allocated during processes of visual perception, learning and search; auditory streaming and speech perception; movement target selection during sensory-motor control; mental imagery and fantasy; and hallucination during mental disorders, among other processes.Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624

Visual attention deficits in schizophrenia can arise from inhibitory dysfunction in thalamus or cortex

Schizophrenia is associated with diverse cognitive deficits, including disorders of attention-related oculomotor behavior. At the structural level, schizophrenia is associated with abnormal inhibitory control in the circuit linking cortex and thalamus. We developed a spiking neural network model that demonstrates how dysfunctional inhibition can degrade attentive gaze control. Our model revealed that perturbations of two functionally distinct classes of cortical inhibitory neurons, or of the inhibitory thalamic reticular nucleus, disrupted processing vital for sustained attention to a stimulus, leading to distractibility. Because perturbation at each circuit node led to comparable but qualitatively distinct disruptions in attentive tracking or fixation, our findings support the search for new eye movement metrics that may index distinct underlying neural defects. Moreover, because the cortico-thalamic circuit is a common motif across sensory, association, and motor systems, the model and extensions can be broadly applied to study normal function and the neural bases of other cognitive deficits in schizophrenia.R01 MH057414 - NIMH NIH HHS; R01 MH101209 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HHSPublished versio