Bidirectional Interaction of Hippocampal Ripples and Cortical Slow Waves Leads to Coordinated Spiking Activity During NREM Sleep.

The dialogue between cortex and hippocampus is known to be crucial for sleep-dependent memory consolidation. During slow wave sleep, memory replay depends on slow oscillation (SO) and spindles in the (neo)cortex and sharp wave-ripples (SWRs) in the hippocampus. The mechanisms underlying interaction of these rhythms are poorly understood. We examined the interaction between cortical SO and hippocampal SWRs in a model of the hippocampo-cortico-thalamic network and compared the results with human intracranial recordings during sleep. We observed that ripple occurrence peaked following the onset of an Up-state of SO and that cortical input to hippocampus was crucial to maintain this relationship. A small fraction of ripples occurred during the Down-state and controlled initiation of the next Up-state. We observed that the effect of ripple depends on its precise timing, which supports the idea that ripples occurring at different phases of SO might serve different functions, particularly in the context of encoding the new and reactivation of the old memories during memory consolidation. The study revealed complex bidirectional interaction of SWRs and SO in which early hippocampal ripples influence transitions to Up-state, while cortical Up-states control occurrence of the later ripples, which in turn influence transition to Down-state.

The generation and propagation of the human alpha rhythm.

The alpha rhythm is the longest-studied brain oscillation and has been theorized to play a key role in cognition. Still, its physiology is poorly understood. In this study, we used microelectrodes and macroelectrodes in surgical epilepsy patients to measure the intracortical and thalamic generators of the alpha rhythm during quiet wakefulness. We first found that alpha in both visual and somatosensory cortex propagates from higher-order to lower-order areas. In posterior cortex, alpha propagates from higher-order anterosuperior areas toward the occipital pole, whereas alpha in somatosensory cortex propagates from associative regions toward primary cortex. Several analyses suggest that this cortical alpha leads pulvinar alpha, complicating prevailing theories of a thalamic pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortical layers. Together, these results suggest that the alpha rhythm likely reflects short-range supragranular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus. These physiological insights suggest how alpha could mediate feedback throughout the thalamocortical system.

Theta Bursts Precede, and Spindles Follow, Cortical and Thalamic Downstates in Human NREM Sleep.

Since their discovery, slow oscillations have been observed to group spindles during non-REM sleep. Previous studies assert that the slow-oscillation downstate (DS) is preceded by slow spindles (10-12 Hz) and followed by fast spindles (12-16 Hz). Here, using both direct transcortical recordings in patients with intractable epilepsy (n = 10, 8 female), as well as scalp EEG recordings from a healthy cohort (n = 3, 1 female), we find in multiple cortical areas that both slow and fast spindles follow the DS. Although discrete oscillations do precede DSs, they are theta bursts (TBs) centered at 5-8 Hz. TBs were more pronounced for DSs in NREM stage 2 (N2) sleep compared with N3. TB with similar properties occur in the thalamus, but unlike spindles they have no clear temporal relationship with cortical TB. These differences in corticothalamic dynamics, as well as differences between spindles and theta in coupling high-frequency content, are consistent with NREM theta having separate generative mechanisms from spindles. The final inhibitory cycle of the TB coincides with the DS peak, suggesting that in N2, TB may help trigger the DS. Since the transition to N1 is marked by the appearance of theta, and the transition to N2 by the appearance of DS and thus spindles, a role of TB in triggering DS could help explain the sequence of electrophysiological events characterizing sleep. Finally, the coordinated appearance of spindles and DSs are implicated in memory consolidation processes, and the current findings redefine their temporal coupling with theta during NREM sleep.SIGNIFICANCE STATEMENT Sleep is characterized by large slow waves which modulate brain activity. Prominent among these are downstates (DSs), periods of a few tenths of a second when most cells stop firing, and spindles, oscillations at ∼12 times a second lasting for ∼a second. In this study, we provide the first detailed description of another kind of sleep wave: theta bursts (TBs), a brief oscillation at ∼six cycles per second. We show, recording during natural sleep directly from the human cortex and thalamus, as well as on the scalp, that TBs precede, and spindles follow DSs. TBs may help trigger DSs in some circumstances, and could organize cortical and thalamic activity so that memories can be consolidated during sleep.

Thalamocortical and intracortical laminar connectivity determines sleep spindle properties.

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.

Neuroanatomical correlates of emotion-processing in children with unilateral brain lesion: A preliminary study of limbic system organization.

In this study, MRI and DTI were employed to examine subcortical volume and microstructural properties (FA, MD) of the limbic network, and their relationships with affect discrimination in 13 FL (6 right FL, M = 10.17 years; 7 left FL; M = 10.09) and 13 typically-developing children (TD; M = 10.16). Subcortical volume of the amygdala, hippocampus and thalamus and FA and MD of the fornix and anterior thalamic radiation (ATR) were examined. Results revealed no group differences across emotion-perception tasks or amygdalar volume. However, contrasting neuroanatomical patterns were observed in right versus left FL youth. Right FL participants showed increased left hippocampal and thalamic volume relative to left FL participants; whereas, the latter group showed increased right thalamic volume. DTI findings also indicated right FL children show greater MD of right fornix than other groups, whereas, left FL youth showed greater MD of left fornix. Right FL youth also showed lower FA of right fornix than left FL children, whereby the latter showed greater FA of left fornix and ATR. Differential associations between DTI indices and auditory/visual emotion-perception were observed across FL groups. Findings indicate diverging brain-behavioral relationships for emotion-perception among right and left FL children.

Coordination of cortical and thalamic activity during non-REM sleep in humans.

Every night, the human brain produces thousands of downstates and spindles during non-REM sleep. Previous studies indicate that spindles originate thalamically and downstates cortically, loosely grouping spindle occurrence. However, the mechanisms whereby the thalamus and cortex interact in generating these sleep phenomena remain poorly understood. Using bipolar depth recordings, we report here a sequence wherein: (1) convergent cortical downstates lead thalamic downstates; (2) thalamic downstates hyperpolarize thalamic cells, thus triggering spindles; and (3) thalamic spindles are focally projected back to cortex, arriving during the down-to-upstate transition when the cortex replays memories. Thalamic intrinsic currents, therefore, may not be continuously available during non-REM sleep, permitting the cortex to control thalamic spindling by inducing downstates. This archetypical cortico-thalamo-cortical sequence could provide the global physiological context for memory consolidation during non-REM sleep.

Cellular and neurochemical basis of sleep stages in the thalamocortical network.

The link between the combined action of neuromodulators in the brain and global brain states remains a mystery. In this study, using biophysically realistic models of the thalamocortical network, we identified the critical intrinsic and synaptic mechanisms, associated with the putative action of acetylcholine (ACh), GABA and monoamines, which lead to transitions between primary brain vigilance states (waking, non-rapid eye movement sleep [NREM] and REM sleep) within an ultradian cycle. Using ECoG recordings from humans and LFP recordings from cats and mice, we found that during NREM sleep the power of spindle and delta oscillations is negatively correlated in humans and positively correlated in animal recordings. We explained this discrepancy by the differences in the relative level of ACh. Overall, our study revealed the critical intrinsic and synaptic mechanisms through which different neuromodulators acting in combination result in characteristic brain EEG rhythms and transitions between sleep stages.

Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night.

During sleep, the thalamus generates a characteristic pattern of transient, 11-15 Hz sleep spindle oscillations, which synchronize the cortex through large-scale thalamocortical loops. Spindles have been increasingly demonstrated to be critical for sleep-dependent consolidation of memory, but the specific neural mechanism for this process remains unclear. We show here that cortical spindles are spatiotemporally organized into circular wave-like patterns, organizing neuronal activity over tens of milliseconds, within the timescale for storing memories in large-scale networks across the cortex via spike-time dependent plasticity. These circular patterns repeat over hours of sleep with millisecond temporal precision, allowing reinforcement of the activity patterns through hundreds of reverberations. These results provide a novel mechanistic account for how global sleep oscillations and synaptic plasticity could strengthen networks distributed across the cortex to store coherent and integrated memories.

The Contribution of Thalamocortical Core and Matrix Pathways to Sleep Spindles.

Sleep spindles arise from the interaction of thalamic and cortical neurons. Neurons in the thalamic reticular nucleus (TRN) inhibit thalamocortical neurons, which in turn excite the TRN and cortical neurons. A fundamental principle of anatomical organization of the thalamocortical projections is the presence of two pathways: the diffuse matrix pathway and the spatially selective core pathway. Cortical layers are differentially targeted by these two pathways with matrix projections synapsing in superficial layers and core projections impinging on middle layers. Based on this anatomical observation, we propose that spindles can be classified into two classes, those arising from the core pathway and those arising from the matrix pathway, although this does not exclude the fact that some spindles might combine both pathways at the same time. We find evidence for this hypothesis in EEG/MEG studies, intracranial recordings, and computational models that incorporate this difference. This distinction will prove useful in accounting for the multiple functions attributed to spindles, in that spindles of different types might act on local and widespread spatial scales. Because spindle mechanisms are often hijacked in epilepsy and schizophrenia, the classification proposed in this review might provide valuable information in defining which pathways have gone awry in these neurological disorders.

Synchronization of isolated downstates (K-complexes) may be caused by cortically-induced disruption of thalamic spindling.

Sleep spindles and K-complexes (KCs) define stage 2 NREM sleep (N2) in humans. We recently showed that KCs are isolated downstates characterized by widespread cortical silence. We demonstrate here that KCs can be quasi-synchronous across scalp EEG and across much of the cortex using electrocorticography (ECOG) and localized transcortical recordings (bipolar SEEG). We examine the mechanism of synchronous KC production by creating the first conductance based thalamocortical network model of N2 sleep to generate both spontaneous spindles and KCs. Spontaneous KCs are only observed when the model includes diffuse projections from restricted prefrontal areas to the thalamic reticular nucleus (RE), consistent with recent anatomical findings in rhesus monkeys. Modeled KCs begin with a spontaneous focal depolarization of the prefrontal neurons, followed by depolarization of the RE. Surprisingly, the RE depolarization leads to decreased firing due to disrupted spindling, which in turn is due to depolarization-induced inactivation of the low-threshold Ca2+ current (IT). Further, although the RE inhibits thalamocortical (TC) neurons, decreased RE firing causes decreased TC cell firing, again because of disrupted spindling. The resulting abrupt removal of excitatory input to cortical pyramidal neurons then leads to the downstate. Empirically, KCs may also be evoked by sensory stimuli while maintaining sleep. We reproduce this phenomenon in the model by depolarization of either the RE or the widely-projecting prefrontal neurons. Again, disruption of thalamic spindling plays a key role. Higher levels of RE stimulation also cause downstates, but by directly inhibiting the TC neurons. SEEG recordings from the thalamus and cortex in a single patient demonstrated the model prediction that thalamic spindling significantly decreases before KC onset. In conclusion, we show empirically that KCs can be widespread quasi-synchronous cortical downstates, and demonstrate with the first model of stage 2 NREM sleep a possible mechanism whereby this widespread synchrony may arise.

Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization.

Sleep spindles are bursts of 11-15 Hz that occur during non-rapid eye movement sleep. Spindles are highly synchronous across the scalp in the electroencephalogram (EEG) but have low spatial coherence and exhibit low correlation with the EEG when simultaneously measured in the magnetoencephalogram (MEG). We developed a computational model to explore the hypothesis that the spatial coherence spindles in the EEG is a consequence of diffuse matrix projections of the thalamus to layer 1 compared with the focal projections of the core pathway to layer 4 recorded in the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas.

Sequential temporo-fronto-temporal activation during monitoring of the auditory environment for temporal patterns.

Subjects detected rarely occurring shifts between two simple tone-patterns, in a paradigm that dissociated the effects of rarity from those of pitch, habituation, and attention. Whole-head magnetoencephalography suggested that rare attended pattern-shifts evoked activity first in the superior temporal plane (sTp, peak ~100 ms), then superior temporal sulcus (sTs, peak ~130 ms), then posteroventral prefrontal (pvpF, peak ~230 ms), and anterior temporal cortices (aT, peak ~370 ms). Activity was more prominent in the right hemisphere. After subtracting the effects of nonshift tones (balanced for pitch and habituation status), weak but consistent differential effects of pattern-shifts began in aT at 90-130 ms, spread to sTs and sTp at ∼130 ms, then pvpF, and finally returned to aT. Cingulate activity resembled prefrontal. Responses to pattern shifts were greatly attenuated when the same stimuli were ignored, suggesting that the initial superior temporal activity reflected an attention-related mismatch negativity. The prefrontal activity at ~230 ms corresponded in latency and task correlates with simultaneously recorded event-related potential components N2b and P3a; the subsequent temporal activity corresponded to the P3b. These results were confirmed in sensors specific for frontal or temporal cortex, and thus are independent of the inverse method used. Overall, these results suggest that auditory working memory for temporal patterns begins with detection of the pattern change by an interaction of anterior and superior temporal structures, followed by identification of the event and its consequences led by posteroventral prefrontal and cingulate cortices, and finally, definitive encoding of the event in anterior temporal areas.

Objective phonological and subjective perceptual characteristics of syllables modulate spatiotemporal patterns of superior temporal gyrus activity.

Natural consonant-vowel syllables are reliably classified by most listeners as voiced or voiceless. However, our previous research [Liederman, J., Frye, R., Fisher, J.M., Greenwood, K., Alexander, R., 2005. A temporally dynamic context effect that disrupts voice onset time discrimination of rapidly successive stimuli. Psychon Bull Rev. 12, 380-386] suggests that among synthetic stimuli varying systematically in voice onset time (VOT), syllables that are classified reliably as voiceless are nonetheless perceived differently within and between listeners. This perceptual ambiguity was measured by variation in the accuracy of matching two identical stimuli presented in rapid succession. In the current experiment, we used magnetoencephalography (MEG) to examine the differential contribution of objective (i.e., VOT) and subjective (i.e., perceptual ambiguity) acoustic features on speech processing. Distributed source models estimated cortical activation within two regions of interest in the superior temporal gyrus (STG) and one in the inferior frontal gyrus. These regions were differentially modulated by VOT and perceptual ambiguity. Ambiguity strongly influenced lateralization of activation; however, the influence on lateralization was different in the anterior and middle/posterior portions of the STG. The influence of ambiguity on the relative amplitude of activity in the right and left anterior STG activity depended on VOT, whereas that of middle/posterior portions of the STG did not. These data support the idea that early cortical responses are bilaterally distributed whereas late processes are lateralized to the dominant hemisphere and support a "how/what" dual-stream auditory model. This study helps to clarify the role of the anterior STG, especially in the right hemisphere, in syllable perception. Moreover, our results demonstrate that both objective phonological and subjective perceptual characteristics of syllables independently modulate spatiotemporal patterns of cortical activation.

Subcortical and cerebellar atrophy in mesial temporal lobe epilepsy revealed by automatic segmentation.

PURPOSE: To determine the validity and utility of using automated subcortical segmentation to identify atrophy of the hippocampus and other subcortical and cerebellar structures in patients with mesial temporal lobe epilepsy (MTLE). METHODS: Volumetric MRIs were obtained on 21 patients with MTLE (11 right, 10 left) and 21 age- and gender-matched healthy controls. Labeling of subcortical and cerebellar structures was accomplished using automated reconstruction software (FreeSurfer). Multivariate analysis of covariance (MANCOVA) was used to explore group differences in intracranial-normalized, age-adjusted volumes and structural asymmetries. Step-wise discriminant function analysis was used to identify the linear combination of volumes that optimized classification of individual subjects. RESULTS: Results revealed the expected reduction in hippocampal volume on the side ipsilateral to the seizure focus, as well as bilateral reductions in thalamic and cerebellar gray matter volume. Analysis of structural asymmetries revealed significant asymmetry in the hippocampus and putamen in patients compared to controls. The discriminant function analysis revealed that patients with right and left MTLE were best distinguished from one another using a combination of subcortical volumes that included the right and left hippocampus and left thalamus (91-100% correct classification using cross-validation). DISCUSSION: Volumetric data obtained with automated segmentation of subcortical and cerebellar structures approximate data from previous studies based on manual tracings. Our data suggest that automated segmentation can provide a clinically useful means of evaluating the nature and extent of structural damage in patients with MTLE and may increase diagnostic classification of patients, especially when hippocampal atrophy is mild.

Linear coding of voice onset time.

Voice onset time (VOT) provides an important auditory cue for recognizing spoken consonant-vowel syllables. Although changes in the neuromagnetic response to consonant-vowel syllables with different VOT have been examined, such experiments have only manipulated VOT with respect to voicing. We utilized the characteristics of a previously developed asymmetric VOT continuum [Liederman, J., Frye, R. E., McGraw Fisher, J., Greenwood, K., & Alexander, R. A temporally dynamic contextual effect that disrupts voice onset time discrimination of rapidly successive stimuli. Psychonomic Bulletin and Review, 12, 380-386, 2005] to determine if changes in the prominent M100 neuromagnetic response were linearly modulated by VOT. Eight right-handed, English-speaking, normally developing participants performed a VOT discrimination task during a whole-head neuromagnetic recording. The M100 was identified in the gradiometers overlying the right and left temporal cortices and single dipoles were fit to each M100 waveform. A repeated measures analysis of variance with post hoc contrast test for linear trend was used to determine whether characteristics of the M100 were linearly modulated by VOT. The morphology of the M100 gradiometer waveform and the peak latency of the dipole waveform were linearly modulated by VOT. This modulation was much greater in the left, as compared to the right, hemisphere. The M100 dipole moved in a linear fashion as VOT increased in both hemispheres, but along different axes in each hemisphere. This study suggests that VOT may linearly modulate characteristics of the M100, predominately in the left hemisphere, and suggests that the VOT of consonant-vowel syllables, instead of, or in addition to, voicing, should be examined in future experiments.

Vector-based spatial-temporal minimum L1-norm solution for MEG.

Minimum L1-norm solutions have been used by many investigators to analyze MEG responses because they provide high spatial resolution images. However, conventional minimum L1-norm approaches suffer from instability in spatial construction, and poor smoothness of the reconstructed source time-courses. Activity commonly "jumps" from one grid point to (usually) the neighboring grid points. Equivalently, the time-course of one specific grid point can show substantial "spiky-looking" discontinuity. In the present study, we present a new vector-based spatial-temporal analysis using a L1-minimum-norm (VESTAL). This approach is based on a principle of MEG physics: the magnetic waveforms in sensor-space are linear functions of the source time-courses in the imaging-space. Our computer simulations showed that VESTAL provides good reconstruction of the source amplitude and orientation, with high stability and resolution in both the spatial and temporal domains. "Spiky-looking" discontinuity was not observed in the source time-courses. Importantly, the simulations also showed that VESTAL can resolve sources that are 100% correlated. We then examined the performance of VESTAL in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguishes sources very spatially close to each other, including individual primary somatosensory areas (BA 1, 2, 3b), primary motor area (BA 4), and other regions in the somatosensory system (e.g., BA 5, 7, SII, SMA, and temporal-parietal junction) with high temporal stability and resolution. VESTAL's potential for obtaining information on source extent was also examined.

Responses of human anterior cingulate cortex microdomains to error detection, conflict monitoring, stimulus-response mapping, familiarity, and orienting.

Human anterior cingulate cortex (ACC) activity modulation has been observed in numerous tasks, consistent with a wide variety of functions. However, previous recordings have not had sufficient spatial resolution to determine whether microdomains (approximately one to two columns) are involved in multiple tasks, how activity is distributed across cortical layers, or indeed whether modulation reflected neuronal excitation, inhibition, or both. In this study, linear arrays of 24 microelectrodes were used to estimate population synaptic currents and neuronal firing in different layers of ACC during simple/choice reaction time, delayed word recognition, rhyming, auditory oddball, and cued conditional letter-discrimination tasks. Responses to all tasks, with differential responses to errors, familiarity, difficulty, and orienting, were recorded in single microdomains. The strongest responses occurred approximately 300-800 ms after stimulus onset and were usually a current source with inhibited firing, strongly suggesting active inhibition in superficial layers during the behavioral response period. This was usually followed by a sink from approximately 800 to 1400 ms, consistent with postresponse rebound activation. Transient phase locking of task-related theta activity in superficial cingulate layers suggested extended interactions with medial and lateral frontal and temporal sites. These data suggest that each anterior cingulate microdomain participates in a multilobar cortical network after behavioral responses in a variety of tasks.