Neural activity in SII modifies sensory evoked potentials in SI in awake rats

Disconnecting Consciousness: Is There a Common Anesthetic End Point?

A quest for a systems-level neuroscientific basis of anesthetic-induced loss and return of consciousness has been in the forefront of research for the past 2 decades. Recent advances toward the discovery of underlying mechanisms have been achieved using experimental electrophysiology, multichannel electroencephalography, magnetoencephalography, and functional magnetic resonance imaging. By the careful dosing of various volatile and IV anesthetic agents to the level of behavioral unresponsiveness, both specific and common changes in functional and effective connectivity across large-scale brain networks have been discovered and interpreted in the context of how the synthesis of neural information might be affected during anesthesia. The results of most investigations to date converge toward the conclusion that a common neural correlate of anesthetic-induced unresponsiveness is a consistent depression or functional disconnection of lateral frontoparietal networks, which are thought to be critical for consciousness of the environment. A reduction in the repertoire of brain states may contribute to the anesthetic disruption of large-scale information integration leading to unconsciousness. In future investigations, a systematic delineation of connectivity changes with multiple anesthetics using the same experimental design, and the same analytical method will be desirable. The critical neural events that account for the transition between responsive and unresponsive states should be assessed at similar anesthetic doses just below and above the loss or return of responsiveness. There will also be a need to identify a robust, sensitive, and reliable measure of information transfer. Ultimately, finding a behavior-independent measure of subjective experience that can track covert cognition in unresponsive subjects and a delineation of causal factors versus correlated events will be essential to understand the neuronal basis of human consciousness and unconsciousness.

Detection of a Weak Somatosensory Stimulus: Role of the Prestimulus Mu Rhythm and Its Top–Down Modulation

The ongoing neural activity in human primary somatosensory cortex (SI) is characterized by field potential oscillations in the 7–13 Hz range known as the mu rhythm. Recent work has shown that the magnitude of the mu oscillation immediately preceding the onset of a weak stimulus has a significant impact on its detection. The neural mechanisms mediating this impact remain not well understood. In particular, whether and how somatosensory mu rhythm is modulated by executive areas prior to stimulus onset for improved behavioral performance has not been investigated. We addressed these issues by recording 128-channel scalp electroencephalogram from normal volunteers performing a somatosensory perception experiment in which they reported the detection of a near-threshold electrical stimulus (∼50% detection rate) delivered to the right index finger. Three results were found. First, consistent with numerous previous reports, the N1 component (∼140 msec) of the somatosensory-evoked potential was significantly enhanced for perceived stimulus compared to unperceived stimulus. Second, the prestimulus mu power and the evoked N1 amplitude exhibited an inverted-U relationship, suggesting that an intermediate level of prestimulus mu oscillatory activity is conducive to stimulus processing and perception. Third, a Granger causality analysis revealed that the prestimulus causal influence in the mu band from prefrontal cortex to SI was significantly higher for perceived stimulus than for unperceived stimulus, indicating that frontal executive structures, via ongoing mu oscillations, exert cognitive control over posterior sensory cortices to facilitate somatosensory processing.

Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses

Variations in cortical oscillations in the alpha (7-14 Hz) and beta (15-29 Hz) range have been correlated with attention, working memory, and stimulus detection. The mu rhythm recorded with magnetoencephalography (MEG) is a prominent oscillation generated by Rolandic cortex containing alpha and beta bands. Despite its prominence, the neural mechanisms regulating mu are unknown. We characterized the ongoing MEG mu rhythm from a localized source in the finger representation of primary somatosensory (SI) cortex. Subjects showed variation in the relative expression of mu-alpha or mu-beta, which were nonoverlapping for roughly 50% of their respective durations on single trials. To delineate the origins of this rhythm, a biophysically principled computational neural model of SI was developed, with distinct laminae, inhibitory and excitatory neurons, and feedforward (FF, representative of lemniscal thalamic drive) and feedback (FB, representative of higher-order cortical drive or input from nonlemniscal thalamic nuclei) inputs defined by the laminar location of their postsynaptic effects. The mu-alpha component was accurately modeled by rhythmic FF input at approximately 10-Hz. The mu-beta component was accurately modeled by the addition of approximately 10-Hz FB input that was nearly synchronous with the FF input. The relative dominance of these two frequencies depended on the delay between FF and FB drives, their relative input strengths, and stochastic changes in these variables. The model also reproduced key features of the impact of high prestimulus mu power on peaks in SI-evoked activity. For stimuli presented during high mu power, the model predicted enhancement in an initial evoked peak and decreased subsequent deflections. In agreement, the MEG-evoked responses showed an enhanced initial peak and a trend to smaller subsequent peaks. These data provide new information on the dynamics of the mu rhythm in humans and the model provides a novel mechanistic interpretation of this rhythm and its functional significance.

In vivo two-photon voltage-sensitive dye imaging reveals top-down control of cortical layers 1 and 2 during wakefulness

Conventional methods of imaging membrane potential changes have limited spatial resolution, particularly along the axis perpendicular to the cortical surface. The laminar organization of the cortex suggests, however, that the distribution of activity in depth is not uniform. We developed a technique to resolve network activity of different cortical layers in vivo using two-photon microscopy of the voltage-sensitive dye (VSD) ANNINE-6. We imaged spontaneous voltage changes in the barrel field of the somatosensory cortex of head-restrained mice and analyzed their spatiotemporal correlations during anesthesia and wakefulness. EEG recordings always correlated more strongly with VSD signals in layer (L) 2 than in L1. Nearby (<200 mum) cortical areas were correlated with one another during anesthesia. Waking the mouse strongly desynchronized neighboring cortical areas in L1 in the 4- to 10-Hz frequency band. Wakefulness also slightly increased synchrony of neighboring territories in L2 in the 0.5- to 4.0-Hz range. Our observations are consistent with the idea that, in the awake animal, long-range inputs to L1 of the sensory cortex from various cortical and thalamic areas exert top-down control on sensory processing.

Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study

Previous reports conflict as to the role of primary somatosensory neocortex (SI) in tactile detection. We addressed this question in normal human subjects using whole-head magnetoencephalography (MEG) recording. We found that the evoked signal (0-175 ms) showed a prominent equivalent current dipole that localized to the anterior bank of the postcentral gyrus, area 3b of SI. The magnitude and timing of peaks in the SI waveform were stimulus amplitude dependent and predicted perception beginning at approximately 70 ms after stimulus. To make a direct and principled connection between the SI waveform and underlying neural dynamics, we developed a biophysically realistic computational SI model that contained excitatory and inhibitory neurons in supragranular and infragranular layers. The SI evoked response was successfully reproduced from the intracellular currents in pyramidal neurons driven by a sequence of lamina-specific excitatory input, consisting of output from the granular layer (approximately 25 ms), exogenous input to the supragranular layers (approximately 70 ms), and a second wave of granular output (approximately 135 ms). The model also predicted that SI correlates of perception reflect stronger and shorter-latency supragranular and late granular drive during perceived trials. These findings strongly support the view that signatures of tactile detection are present in human SI and are mediated by local neural dynamics induced by lamina-specific synaptic drive. Furthermore, our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception.

Computing with thalamocortical ensembles during different behavioural states

A series of recent studies have indicated that ensembles of neurones, distributed within the neural structures that form the primary thalamocortical loop (TCL) of the trigeminal component of the rat somatosensory system, change the way they respond to similar tactile stimuli, according to both the behavioural strategy employed by animals to gather information and the animal's internal brain states. These findings suggest that top-down influences, which are more likely to play a role during active discrimination than during passive whisker stimulation, may alter the pattern of neuronal firing within both the distinct layers of the primary somatosensory cortex (S1) and the ventral posterior medial nucleus (VPM). We propose that through this physiological process, which involves concurrent dynamic modulations at both cellular and circuit levels in the TCL, rats can either optimize the detection of novel or hard to sense stimuli or they can analyse complex patterns of multi-whisker stimulation, during natural exploration of their surrounding environment.

Differences between primary somatosensory cortex- and vertex-derived somatosensory-evoked potentials in the rat

The somatosensory-evoked potential (SEP) elicited by high-intensity stimulation potentially provides a reliable indicator of analgesic efficacy since it reflects the level of activation of the nociceptive system. In the present study, components in the 10-30-ms latency range of SEPs recorded over the primary somatosensory cortex (SI-SEPs) and vertex (Vx-SEP) in the rat were characterized and compared. SEPs were elicited by electrical tail-base stimulation, and SI-SEPs and Vx-SEPs were recorded simultaneously. Responses to increasing stimulus intensity and stimulus frequency while awake and responses to bolus injection of fentanyl, thiopental, and ketamine were investigated. The SI-SEP positive component (P) occurring at 12 ms after stimulation (P12) showed a significantly lower intensity threshold and was significantly less affected by increasing stimulus frequency and by administration of the different drugs when compared to the Vx-SEP P15. The fact that a single stimulus modality results in different signal characteristics dependent on the recording site supports the view that different neural mechanisms involved in primary processing of somatosensory information are responsible for the generation of the SI-SEP P12 and Vx-SEP P15, respectively. This differentiation between SI-SEPs and Vx-SEPs potentially has distinct consequences using the SEP to evaluate nociception and analgesia in the rat model.

Layer-specific somatosensory cortical activation during active tactile discrimination

Ensemble neuronal activity was recorded in each layer of the whisker area of the primary somatosensory cortex (SI) while rats performed a whisker-dependent tactile discrimination task. Comparison of this activity with SI activity evoked by similar passive whisker stimulation revealed fundamental differences in tactile signal processing during active and passive stimulation. Moreover, significant layer-specific functional differences in SI activity were observed during active discrimination. These differences could not be explained solely by variations in ascending thalamocortical input to SI. Instead, these results suggest that top-down influences during active discrimination may alter the overall functional nature of SI as well as layer-specific mechanisms of tactile processing.

Dynamic changes of gamma activities of somatic cortical evoked potentials during wake-sleep states in rats

Somatic evoked potentials (SEPs) from three brain sites elicited by electrical stimulation in 10 rats were recorded throughout wake-sleep states with intrinsic changes in temporal architectures under different vigilance states. Based on the patterns of spontaneous brain and muscle activities, three characteristic vigilance states could be classified: awake, slow-wave sleep (SWS), and paradoxical sleep (PS). Spontaneous gamma activities prominently appeared under awake and PS states, but less under SWS. SEP was filtered out via a zero-phase highpass filter (20 Hz) to extract the gamma activity of the SEP (gammaSEP). Gamma oscillations of SEPs were clearly observed and were reset by extrinsic electrical stimulation under awake and PS, but not under SWS state. Dynamic changes of gammaSEPs during wake-sleep states were also confirmed by multiple single-trial spectral analyses. Moreover, gamma oscillations were initiated at the parietal site, and the speed of its propagation in both frontal and occipital directions was significantly different. In addition, a clear two-component architecture of SEPs was observed under awake and PS states, and the gamma rhythmic activity was associated with the second component. Because gamma oscillations are related to feature binding in the waking state, evoked gammaSEPs in PS may be related to sensory integration analogous to the awake ones. By contrast, a long-lasting biphasic component of SEPs, which might be associated with augmenting response, was observed during SWS. Based on these results, the sleeping brain continuously monitors and selectively processes incoming flow. Our results also strongly support a two-stage information processing taking place in the cortex during sleep.

Evaluation of methods for eliciting somatosensory-evoked potentials in the awake, freely moving rat

To standardise the method of eliciting somatosensory-evoked potentials (SEPs), SEPs were generated by electrical stimulation of different stimulus sites and recorded bilaterally from the primary somatosensory cortex (S1) and from midline in awake, freely moving rats. Increasing stimulus intensity enhanced amplitudes of all SEPs. At supramaximal stimulation, SEPs following vibrissae and tail stimulation (V-SEP and Ta-SEP, respectively) but not following trunk stimulation (Tr-SEP), fulfilled our criterion of signal-to-noise ratio >or=4. The first V-SEP component coincided with a stimulus artefact, disqualifying these recordings for a standard stimulation protocol. The Ta-SEP generated stable and reproducible recordings and was considered to be the preferred technique. Early components of the contralateral S1 recorded V-SEP and Tr-SEP occurred at latencies different from the other recordings. Increasing stimulus repetition rate (SRR) decreased amplitudes of all SEPs. At the highest obtainable SRR, the amplitude between the V-SEP second positive and second negative components in all recordings was 70-80% of the amplitude at 0.1 Hz, whereas peak amplitudes of subsequent components and those of the Tr-SEP and Ta-SEP were 20-50%. These results indicate that the different SEP components might be generated by different ascending neural pathways.

Timing and connectivity in the human somatosensory cortex from single trial mass electrical activity

Parallel-distributed processing is ubiquitous in the brain but often ignored by experimental designs and methods of analysis, which presuppose sequential and stereotypical brain activations. We introduce here a methodology that can effectively deal with sequential and distributed activity. Regional brain activations elicited by electrical median nerve stimulation are identified in tomographic estimates extracted from single trial magnetoencephalographic signals. Habituation is identified in both primary somatosensory cortex (SI) and secondary somatosensory cortex (SII), often interrupted by resurgence of strong activations. Pattern analysis is used to identify single trials with homogeneous regional brain activations. Common activity patterns with well-defined connectivity are identified within each homogeneous group of single trials across the subjects studied. On the contralateral side one encounters distinct sets of single trials following identical stimuli. We observe in one set of trials sequential activation from SI to SII and insula with onset of SII at 60 msec, whereas in the other set simultaneous early co-activations of the same two areas.