State Dependence of Stimulus-Induced Variability Tuning in Macaque MT

Behavioral states marked by varying levels of arousal and attention modulate some properties of cortical responses (e.g. average firing rates or pairwise correlations), yet it is not fully understood what drives these response changes and how they might affect downstream stimulus decoding. Here we show that changes in state modulate the tuning of response variance-to-mean ratios (Fano factors) in a fashion that is neither predicted by a Poisson spiking model nor changes in the mean firing rate, with a substantial effect on stimulus discriminability. We recorded motion-sensitive neurons in middle temporal cortex (MT) in two states: alert fixation and light, opioid anesthesia. Anesthesia tended to lower average spike counts, without decreasing trial-to-trial variability compared to the alert state. Under anesthesia, within-trial fluctuations in excitability were correlated over longer time scales compared to the alert state, creating supra-Poisson Fano factors. In contrast, alert-state MT neurons have higher mean firing rates and largely sub-Poisson variability that is stimulus-dependent and cannot be explained by firing rate differences alone. The absence of such stimulus-induced variability tuning in the anesthetized state suggests different sources of variability between states. A simple model explains state-dependent shifts in the distribution of observed Fano factors via a suppression in the variance of gain fluctuations in the alert state. A population model with stimulus-induced variability tuning and behaviorally constrained information-limiting correlations explores the potential enhancement in stimulus discriminability by the cortical population in the alert state.Comment: 36 pages, 18 figure

Phase transitions in single neurons and neural populations: Critical slowing, anesthesia, and sleep cycles

The firing of an action potential by a biological neuron represents a dramatic transition from small-scale linear stochastics (subthreshold voltage fluctuations) to gross-scale nonlinear dynamics (birth of a 1-ms voltage spike). In populations of neurons we see similar, but slower, switch-like there-and-back transitions between low-firing background states and high-firing activated states. These state transitions are controlled by varying levels of input current (single neuron), varying amounts of GABAergic drug (anesthesia), or varying concentrations of neuromodulators and neurotransmitters (natural sleep), and all occur within a milieu of unrelenting biological noise. By tracking the altering responsiveness of the excitable membrane to noisy stimulus, we can infer how close the neuronal system (single unit or entire population) is to switching threshold. We can quantify this “nearness to switching” in terms of the altering eigenvalue structure: the dominant eigenvalue approaches zero, leading to a growth in correlated, low-frequency power, with exaggerated responsiveness to small perturbations, the responses becoming larger and slower as the neural population approaches its critical point–-this is critical slowing. In this chapter we discuss phase-transition predictions for both single-neuron and neural-population models, comparing theory with laboratory and clinical measurement

Response Dynamics of Entorhinal Cortex in Awake, Anesthetized, and Bulbotomized Rats. <i>Brain Research</i> <b>911</b>(2)

The generation of oscillatory activity may be crucial to brain function. The coordination of individual neurons into rhythmic and coherently active populations is thought to result from interactions between excitatory and inhibitory cells mediated by local feedback connections. By using extracellular recording wires and silicon microprobes to measure electrically evoked damped oscillatory responses at the level of neural populations in the entorhinal cortex, and by using current-source density analysis to determine the spatial pattern of evoked responses, we show that the propagation of activity through the cortical circuit and consequent oscillations in the local field potential are dependent upon background neural activity. Pharmacological manipulations as well as surgical disconnection of the olfactory bulb serve to quell the background excitatory input incident to entorhinal cortex, resulting in evoked responses without characteristic oscillations and showing no signs of polysynaptic feedback. Electrical stimulation at 200 Hz applied to the lateral olfactory tract provides a substitute for the normal background activity emanating from the bulb and enables the generation of oscillatory responses once again. We conclude that a nonzero background level of activity is necessary and sufficient to sustain normal oscillatory responses and polysynaptic transmission through the entorhinal cortex

Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke.

Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; &lt;4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation

SENSORY REGRESSION TIME FROM SUBARACHNOID BLOCK WITH HYPERBARIC 0.75% BUPIVACAINE IN THE OBESE PATIENT

The purpose of this study was to determine if obese patients have a different sensory regression time from subarachnoid block than non-obese patients using hyperbaric 0.75% bupivacaine. A quasi-experimental design was used. Twenty patients were separated into two groups; one group was classified as obese, and the other group was classified as non-obese. The data consisting of age, height, weight, sex, and surgical procedure were recorded preoperatively. All the patients received hyperbaric 0.75% bupivacaine via subarachnoid puncture. The levels of spinal anesthesia were recorded at the highest level achieved. The injection time was also recorded. When the surgery was completed, the patient was transferred to the recovery room and levels of sensory blockade were checked by pin-prick with an 18-gauge needle every 10 minutes until complete recovery from the spinal anesthesia had been achieved. The hypothesis, there will be no difference in sensory regression time from SAB with hyperbaric 0.75% bupivacaine between obese and non-obese patients, failed to be rejected. No statistically significant difference, using linear regression analysis, was found in mean regression time between groups (obese versus non-obese)

Large-scale changes in cortical dynamics triggered by repetitive somatosensory electrical stimulation.

BackgroundRepetitive somatosensory electrical stimulation (SES) of forelimb peripheral nerves is a promising therapy; studies have shown that SES can improve motor function in stroke subjects with chronic deficits. However, little is known about how SES can directly modulate neural dynamics. Past studies using SES have primarily used noninvasive methods in human subjects. Here we used electrophysiological recordings from the rodent primary motor cortex (M1) to assess how SES affects neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics.MethodsWe performed acute extracellular recordings in 7 intact adult Long Evans rats under ketamine-xylazine anesthesia while they received transcutaneous SES. We recorded single unit spiking and local field potentials (LFP) in the M1 contralateral to the stimulated arm. We then compared neural firing rate, spike-field coherence (SFC), and power spectral density (PSD) before and after stimulation.ResultsFollowing SES, the firing rate of a majority of neurons changed significantly from their respective baseline values. There was, however, a diversity of responses; some neurons increased while others decreased their firing rates. Interestingly, SFC, a measure of how a neuron's firing is coupled to mesoscale oscillatory dynamics, increased specifically in the δ-band, also known as the low frequency band (0.3- 4 Hz). This increase appeared to be driven by a change in the phase-locking of broad-spiking, putative pyramidal neurons. These changes in the low frequency range occurred without a significant change in the overall PSD.ConclusionsRepetitive SES significantly and persistently altered the local cortical dynamics of M1 neurons, changing both firing rates as well as the SFC magnitude in the δ-band. Thus, SES altered the neural firing and coupling to ongoing mesoscale dynamics. Our study provides evidence that SES can directly modulate cortical dynamics

Neural Substrates of Chronic Pain in the Thalamocortical Circuit

Chronic pain (CP), a pathological condition with a large repertory of signs and symptoms, has no recognizable neural functional common hallmark shared by its diverse expressions. The aim of the present research was to identify potential dynamic markers shared in CP models, by using simultaneous electrophysiological extracellular recordings from the rat ventrobasal thalamus and the primary somatosensory cortex. We have been able to extract a neural signature attributable solely to CP, independent from of the originating conditions. This study showed disrupted functional connectivity and increased redundancy in firing patterns in CP models versus controls, and interpreted these signs as a neural signature of CP. In a clinical perspective, we envisage CP as disconnection syndrome and hypothesize potential novel therapeutic appraisal

Interacting Turing-Hopf Instabilities Drive Symmetry-Breaking Transitions in a Mean-Field Model of the Cortex: A Mechanism for the Slow Oscillation

Electrical recordings of brain activity during the transition from wake to anesthetic coma show temporal and spectral alterations that are correlated with gross changes in the underlying brain state. Entry into anesthetic unconsciousness is signposted by the emergence of large, slow oscillations of electrical activity (≲1  Hz) similar to the slow waves observed in natural sleep. Here we present a two-dimensional mean-field model of the cortex in which slow spatiotemporal oscillations arise spontaneously through a Turing (spatial) symmetry-breaking bifurcation that is modulated by a Hopf (temporal) instability. In our model, populations of neurons are densely interlinked by chemical synapses, and by interneuronal gap junctions represented as an inhibitory diffusive coupling. To demonstrate cortical behavior over a wide range of distinct brain states, we explore model dynamics in the vicinity of a general-anesthetic-induced transition from “wake” to “coma.” In this region, the system is poised at a codimension-2 point where competing Turing and Hopf instabilities coexist. We model anesthesia as a moderate reduction in inhibitory diffusion, paired with an increase in inhibitory postsynaptic response, producing a coma state that is characterized by emergent low-frequency oscillations whose dynamics is chaotic in time and space. The effect of long-range axonal white-matter connectivity is probed with the inclusion of a single idealized point-to-point connection. We find that the additional excitation from the long-range connection can provoke seizurelike bursts of cortical activity when inhibitory diffusion is weak, but has little impact on an active cortex. Our proposed dynamic mechanism for the origin of anesthetic slow waves complements—and contrasts with—conventional explanations that require cyclic modulation of ion-channel conductances. We postulate that a similar bifurcation mechanism might underpin the slow waves of natural sleep and comment on the possible consequences of chaotic dynamics for memory processing and learning

Critical Changes in Cortical Neuronal Interactions in Anesthetized and Awake Rats

Background: Neuronal interactions are fundamental for information processing, cognition and consciousness. Anesthetics reduce spontaneous cortical activity; however, neuronal reactivity to sensory stimuli is often preserved or augmented. How sensory stimulus-related neuronal interactions change under anesthesia has not been elucidated. Here we investigated visual stimulus-related cortical neuronal interactions during stepwise emergence from desflurane anesthesia. Methods: Parallel spike trains were recorded with 64-contact extracellular microelectrode arrays from the primary visual cortex of chronically instrumented, unrestrained rats (N=6) at 8%, 6%, 4%, 2% desflurane anesthesia and wakefulness. Light flashes were delivered to the retina by transcranial illumination at 5-15s randomized intervals. Information theoretical indices, integration and interaction complexity, were calculated from the probability distribution of coincident spike patterns and used to quantify neuronal interactions before and after flash stimulation. Results: Integration and complexity showed significant negative associations with desflurane concentration (N=60). Flash stimulation increased integration and complexity at all anesthetic levels (N=60); the effect on complexity was reduced in wakefulness. During stepwise withdrawal of desflurane, the largest increase in integration (74%) and post-stimulus complexity (35%) occurred prior to reaching 4% desflurane concentration – a level associated with the recovery of consciousness according to the rats\u27 righting reflex. Conclusions: Neuronal interactions in the cerebral cortex are augmented during emergence from anesthesia. Visual flash stimuli enhance neuronal interactions in both wakefulness and anesthesia; the increase in interaction complexity is attenuated as post-stimulus complexity reaches plateau. The critical changes in cortical neuronal interactions occur during transition to consciousness