Biology subjects

Hudetz, A. G.

Publications and source records attributed to Hudetz, A. G..

23 records · Page 2Linked to original sources

bioRxiv2020

Higher-order sensorimotor circuit of the brain' global network supports human consciousness

The neural correlates of consciousness, defined as the minimum neuronal mechanisms sufficient for any conscious percept, are usually subject to different interpretations depending on whether one uses measures of local or global brain activities. We argue that the local regions may support consciousness by serving as hubs within the brains global network. We adopt a unique functional magnetic resonance imaging resting state dataset that encompasses various conscious states, including non-rapid eye movement (NREM)-sleep, rapid eye movement (REM)-sleep, anesthesia, and brain injury patients. Using a graph-theoretical measure for detecting local hubs within the brains global network, we identify various higher-order sensory and motor regions as hubs with significantly reduced degree centrality during unconsciousness. Additionally, these regions form a sensorimotor circuit which correlates with levels of consciousness. Our findings suggest that integration of higher-order sensorimotor function may be a key mechanism of consciousness. This opens novel perspectives for therapeutic modulation of unconsciousness.

neuroscience↗

bioRxiv2020

Model of intracellular ATP production reproduces common electrophysiological signatures of anesthesia

Accumulating evidence suggest that general anesthetics with diverse chemical structure reduce cerebral metabolism with consequent reduction of intracellular adenosine triphosphate (ATP) levels. How cerebral hypometabolism is associated with the typical electroencephalographic (EEG) changes under general anesthesia remains largely unknown.. We hypothesized that the deficit in ATP production would reduce high-frequency activity, increase low-frequency activity, and cause burst suppression, which are common dose-dependent anesthetic effects on the EEG. To test the hypothesis, we developed a novel neural network model consisting of leaky integrate-and-fire neurons with additional dependency on ATP dynamics. The effect of varying rate of ATP production on neuronal and population activity patterns was simulated under various excitatory/inhibitory balance conditions. A decrease of ATP production suppressed neuronal spiking and enhanced synchronization of neurons over a range of excitatory/inhibitory synaptic strength ratios. As anticipated, the initially asynchronous fast activity was replaced by globally desynchronized slow oscillation and, on further decrease of ATP production, changed into burst suppression with enhanced global synchronization. This study substantiates a novel biophysical mechanism for anesthetic-induced EEG changes through a relationship between energy production and synchronization of neural network.

neuroscience↗

bioRxiv2020

State-dependent cortical unit activity reflects dynamic brain state transitions in anesthesia

How anesthesia affects cortical neuronal spiking and information transfer could help understand the neuronal basis of conscious state. Recent investigations suggest that global state of the anesthetized brain is not stationary but changes spontaneously at a fixed level of anesthetic concentration. How cortical unit activity changes with dynamically transitioning brain states under anesthesia is unclear. We hypothesized that distinct cortical states are characterized by distinct neuronal spike patterns. Extracellular unit activity was measured with sixty-four-channel silicon microelectrode arrays in cortical layers 5/6 of primary visual cortex of chronically instrumented, freely moving male rats (N = 7) during stepwise reduction of the anesthetic desflurane (6, 4, 2, and 0%). Unsupervised machine learning applied to multi-unit spike patterns revealed five distinct brain states of which four occurred at various anesthetic concentrations and shifted spontaneously. In deeper anesthesia states, the number of active units and overall spike rate decreased while the remaining active units showed increased bursting (excitatory neurons), spike timing variability, unit-to-population correlation and unit-to-unit transfer entropy, especially among putative excitatory units, despite the overall decrease in transfer entropy. A novel desynchronized brain state with increased spike timing variability, entropy and electromyographic activity that occurred mostly in deep anesthesia was discovered. These results provide evidence for distinct unit activity patterns associated with spontaneous changes in local cortical brain states at stationary anesthetic conditions. The appearance of a paradoxical, desynchronized brain state in deep anesthesia contends the prevailing view of monotonic dose-dependent anesthetic effects on the brain. SIGNIFICANCE STATEMENTRecent studies suggest that spontaneous changes in brain state occur under anesthesia. However, the spiking behavior of cortical neurons associated with such state changes has not been investigated. We found that local brain states defined by multi-unit activity had non-unitary relationship with the current anesthetic level. A paradoxical brain state displaying asynchronous firing pattern and high electromyographic activity was found unexpectedly at high-dose anesthesia. In contrast, the synchronous fragmentation of neuronal spiking appeared to be a robust signature of the state of anesthesia. The findings challenge the assumption of monotonic, anesthetic dose-dependent behavior of cortical neuron populations. They enhance the interpretation of neuroscientific data obtained under anesthesia and understanding of the neuronal basis of anesthetic-induced state of unconsciousness.

neuroscience↗

bioRxiv2020

Differential effect of anesthesia on visual cortex neurons with diverse population coupling

IntroductionFiring rate (FR) and population coupling (PC) are intrinsic properties of cortical neurons. Neurons with different FR and PC have diverse excitability to stimulation, tuning curve, and synaptic plasticity. Therefore, investigation of the effect of anesthesia on neurons with different FR and PC would be important to understand state-dependent information processing in neuronal circuits. MethodsTo test how anesthesia affects neurons with diverse PC and FR, we measured single-unit activities in deep layers of primary visual cortex at three levels of anesthesia with desflurane and in wakefulness. Based on PC and FR in wakefulness, neurons were classified into three distinct groups: high PC-high FR (HPHF), low PC-high FR (LPHF), and low PC-low FR (LPLF) neurons. ResultsApplying repeated light flashes as visual stimuli, HPHF neurons showed the strongest early response (FR at 20-150ms post-stimulus) among the three groups, whereas the response of LPHF neurons persisted longest (up to 440ms). Anesthesia profoundly altered PC and FR, and differently affected the three neuron groups: (i) PC and FR became strongly correlated suppressing population-independent spike activity; (ii) Pairwise correlation of spikes between neurons could be predicted by a PC-based raster model suggesting uniform neuron-to-neuron coupling; (iii) Contrary to evoked-potential studies under anesthesia, the flash-induced early response of HPHF neurons was attenuated, and their spike timing was split and delayed; (iv) Late response (FR at 200-400ms post-stimulus) was suppressed both in HPHF and LPHF neurons. ConclusionsAnesthetic-induced association between PC and FR suggests reduced information content in the neural circuit. Altered response of HPHF neurons to visual stimuli suggests that anesthesia interferes with conscious sensory processing in primary sensory cortex.

neuroscience↗

bioRxiv2019

Criticality as a determinant of integrated information {Phi} in human brain networks

Integrated information theory (IIT) postulates that consciousness arises from the cause-effect structure of a system but the optimal network conditions for this structure have not been elucidated. In the study, we test the hypothesis that network criticality, a dynamically balanced state between a large variation of functional network configurations and a large constraint of structural network configurations, is a necessary condition for the emergence of a cause-effect structure that results in a large {Phi}, a surrogate of integrated information. We also hypothesized that if the brain deviates from criticality, the cause-effect structure is obscured and {Phi} diminishes. We tested these hypotheses with a large-scale brain network model and high-density electroencephalography (EEG) acquired during various levels of human consciousness during general anesthesia. In the modeling study, maximal criticality coincided with maximal {Phi}. The constraint of the structural network on the functional network is maximized in the maximal criticality. The EEG study demonstrated an explicit relationship between {Phi}, criticality, and level of consciousness. Functional brain network significantly correlated with structural brain network only in conscious states. The results support the hypothesis that network criticality maximizes {Phi}.

neuroscience↗