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Pascovich, C.

Publications and source records attributed to Pascovich, C..

9 recordsLinked to original sources

Thalamic and cortical signals synergistically represent auditory prediction errors

Prediction errors (PEs) are commonly described as cortical signals generated within sensory hierarchies, but whether the thalamus participates in their encoding and transmission remains unclear. We recorded Local Field Potentials (LFP) from the medial and lateral geniculate nuclei and electrocorticography (ECoG) from multiple cortical regions in three awake cats during two auditory prediction tasks. Mutual information (MI) analyses revealed PE encoding in both thalamic and cortical signals. Co-information (co-I) analyses showed off-diagonal temporal synergy between early and later thalamic response components, consistent with an early response inducing a neural state change that shaped the informational content of subsequent activity. Multivariate co-information (MVCo-I) further revealed that thalamic and cortical population activity carried complementary PE information unavailable from either thalamic or cortical areas alone. These synergistic interactions were reliable across animals for violations of structured auditory sequences and weaker for repetition-based deviants. These findings show that auditory PEs are not simply relayed or duplicated across the thalamocortical hierarchy. Instead, they emerge through state-dependent transformations within the thalamus and complementary interactions between thalamic and cortical populations, identifying the thalamus as an active node of context-dependent PE processing.

neuroscience↗

Distilling the neurophenomenological signatures of pure awareness during Transcendental Meditation

Pure awareness (PA) has been proposed as a form of minimal phenomenal experience, but its neurophenomenological signatures remain poorly characterized. Transcendental Meditation (TM) offers a particularly tractable empirical model of PA because its procedure is standardized, its induction is effortless, and it reliably elicits reports of awareness with minimal content. We combined electroencephalography (EEG) with Temporal Experience Tracing in 33 experienced TM practitioners and their matched controls (performing mental counting). TM practitioners reported significantly greater intensity and temporal variability of PA, independent of years of meditation practice. We then used multivariate classification of theoretically motivated EEG markers spanning temporal entropy, aperiodic activity, complexity, and linear and nonlinear functional connectivity. We observed a double dissociation. When TM was contrasted with counting, temporal entropy and aperiodic dynamics were the strongest discriminators, whereas phase-coherence functional connectivity contributed least. Conversely, when TM was contrasted with its own baseline, low-frequency functional connectivity dominated, whereas temporal entropy contributed minimally. Complementary topographical analyses indicated that these differences were not reducible to a few localized univariate effects, but were better understood as distributed multivariate neural patterns. Finally, TM showed little evidence of carryover into subsequent rest, whereas counting induced more residual change. Together, these findings provide a systematic electrophysiological characterization of PA and support neurophenomenology as a tractable framework for studying minimal phenomenal experience.

neuroscience↗

Differential Effects of Haloperidol on Neural Oscillations During Wakefulness and Sleep

The electrical activity of the brain, characterized by its frequency components, reflects a complex interplay between periodic (oscillatory) and aperiodic components. These components are associated with various neurophysiological processes, such as the excitation-inhibition balance (aperiodic activity) or interregional communication (oscillatory activity). However, we do not fully understand whether these components are truly independent or if different neuromodulators modulate them in different ways. The dopaminergic system has a critical role for cognition and motivation, being a potential modulator of these power spectrum components. To improve our understanding of these questions, we investigated the differential effects of this system on these components using electrocorticogram recordings in cats, which show clear oscillations and aperiodic 1/f activity. Specifically, we focused on the effects of haloperidol (a D2 receptor antagonist) on oscillatory and aperiodic dynamics during wakefulness and sleep. By parameterizing the power spectrum into these two components, our findings reveal a state-dependent modulation of oscillatory activity by the D2 receptor across the brain. Surprisingly, aperiodic activity was not significantly affected and exhibited inconsistent changes across the brain. This suggests a nuanced interplay between neuromodulation and the distinct components of brain oscillations, providing insights into the selective regulation of oscillatory dynamics in awake states.

neuroscience↗

Cortical high-frequency oscillations ({approx} 110 Hz) in cats are state-dependent and enhanced by a subanesthetic dose of ketamine

Ketamine is an NMDA receptor antagonist that has both antidepressant and anesthetic properties. At subanesthetic doses, ketamine can cause transient psychosis in humans, and is used to model psychosis in experimental animals. In rodents, subanesthetic doses of ketamine increase the power of high-frequency oscillations (HFO, 100-180 Hz) in the electroencephalogram and field potentials, a frequency band linked to cognitive functions. However, the effects of ketamine in higher mammals, with more translatable relevance, are poorly investigated. Here, we have examined cortical HFO during wakefulness, sleep, and after administering a sub-anesthetic dose of ketamine (15 mg/kg), utilizing the cat as an animal model. Four cats were implanted with cortical electrodes for chronic polysomnographic recordings. HFO power, connectivity, information flow directionality, and their relationships with respiratory activity were analyzed. During wakefulness, but not during sleep, we found that HFO were coupled with the inspiratory phase of the respiration. After ketamine administration, HFO were enhanced significantly and remained associated with the inspiratory phase. The analysis of the information flow after ketamine suggest that HFO originate from the olfactory bulb and stream towards the prefrontal cortex. Accordingly, occluding the nostrils significantly reduced HFO power in both the olfactory bulb and prefrontal cortex. In contrast, auditory stimulation did not affect HFO. In conclusion, spontaneous cortical HFO show certain state-dependent features in cats, and enhancement of this rhythm by ketamine may disrupt cortical information processing, which could contribute to some of the neuropsychiatric manifestations associated with ketamine. HighlightsO_LIKetamine is used to model psychosis in humans and experimental animals C_LIO_LISubanesthetic doses of ketamine increase the power of high-frequency oscillations C_LIO_LIHigh-frequency oscillations are coupled with the inspiratory phase of respiration C_LIO_LIThese oscillations originate in the olfactory bulb and stream to the neocortex C_LIO_LINostril occlusion lowers high-frequency activity in the olfactory bulb and neocortex C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/543142v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@e386feorg.highwire.dtl.DTLVardef@1b3c06aorg.highwire.dtl.DTLVardef@1d93ecorg.highwire.dtl.DTLVardef@1daa161_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Electrophysiological characterization of medial preoptic neurons in lactating rats and its modulation by hypocretin-1

The medial preoptic area (mPOA) undergoes through neuroanatomical changes across the postpartum period, during which its neurons play a critical role in the regulation of maternal behavior. In addition, this area is also crucial for sleep-wake regulation. We have previously shown that hypocretins (HCRT) within the mPOA facilitate active maternal behaviors in postpartum rats, while the blockade of endogenous HCRT in this area promotes nursing and sleep. To explore the mechanisms behind these HCRT actions, we aimed to evaluate the effects of juxta-cellular HCRT-1 administration on mPOA neurons in urethane-anesthetized postpartum and virgin female rats. We recorded mPOA single units and the electroencephalogram (EEG) and applied HCRT-1 juxta-cellular by pressure pulses. Our main results show that the electrophysiological characteristics of the mPOA neurons and their relationship with the EEG of postpartum rats did not differ from virgin rats. Additionally, neurons that respond to HCRT-1 had a slower firing rate than those that did not. In addition, administration of HCRT increased the activity in one group of neurons while decreasing it in another, both in postpartum and virgin rats. The mechanisms by which HCRT modulate functions controlled by the mPOA involve different cell populations.

neuroscience↗

Low Frequency Oscillations drive EEG's complexity changes during wakefulness and sleep

Recently, the sleep-wake states have been analysed using novel complexity measures, complementing the classical analysis of EEGs by frequency bands. This new approach consistently shows a decrease in EEGs complexity during slow-wave sleep, yet it is unclear how cortical oscillations shape these complexity variations. In this work, we analyse how the frequency content of brain signals affects the complexity estimates in freely moving rats. We find that the low-frequency spectrum - including the Delta, Theta, and Sigma frequency bands - drives the complexity changes during the sleep-wake states. This happens because low-frequency oscillations emerge from neuronal population patterns, as we show by recovering the complexity variations during the sleep-wake cycle from micro, meso, and macroscopic recordings. Moreover, we find that the lower frequencies reveal synchronisation patterns across the neocortex, such as a sensory-motor decoupling that happens during REM sleep. Overall, our works shows that EEGs low frequencies are critical in shaping the sleep-wake states complexity across cortical scales.

neuroscience↗

Ketamine and sleep modulate neural complexity dynamics in cats

There is increasing evidence that level of consciousness can be captured by neural informational complexity: for instance, complexity, as measured by the Lempel Ziv (LZ) compression algorithm, decreases during anesthesia and non-rapid eye movement (NREM) sleep in humans and rats, when compared to LZ in awake and REM sleep. In contrast, LZ is higher in humans under the effect of psychedelics, including subanesthetic doses of ketamine. However, it is both unclear how this result would be modulated by varying ketamine doses, and whether it would extend to other species. Here we studied LZ with and without auditory stimulation during wakefulness and different sleep stages in 5 cats implanted with intracranial electrodes, as well as under subanesthetic doses of ketamine (5, 10, and 15 mg/kg i.m.). In line with previous results, LZ was lowest in NREM sleep, but similar in REM and wakefulness. Furthermore, we found an inverted U-shaped curve following different levels of ketamine doses in a subset of electrodes, primarily in prefrontal cortex. However, it is worth noting that the variability in the ketamine dose-response curve across cats and cortices was larger than that in the sleep-stage data, highlighting the differential local dynamics created by two different ways of modulating conscious state. These results replicate previous findings, both in humans and other species, demonstrating that neural complexity is highly sensitive to capture state changes between wake and sleep stages while adding a local cortical description. Finally, this study describes the differential effects of ketamine doses, replicating a rise in complexity for low doses, and further fall as doses approach anesthetic levels in a differential manner depending on the cortex. In briefPrevious studies have shown that Lempel Ziv complexity (LZ) decreases during anesthesia and non-rapid eyes movement (NREM) sleep in humans and rats whereas it increases in REM sleep and under the effect of psychedelics. In this work we show that in the cat, LZ is lowest in NREM sleep, but similar in REM and wakefulness. We also found a ketamine inverted U-shape dose-response curve only in the auditory and prefrontal cortex, with a much larger variability in the ketamine across cats and cortices when compared to the sleep cycle. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/449513v2_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1bab0d0org.highwire.dtl.DTLVardef@1ae33dborg.highwire.dtl.DTLVardef@1cea0f6org.highwire.dtl.DTLVardef@a9b1e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Electrocortical temporal complexity during wakefulness and sleep: an updated account

The states of sleep and wakefulness are critical physiological processes associated with different brain patterns of activity. The intracranial electroencephalogram allows us to measure these changes, thus, it is a critical tool for its study. Recently, we showed that the electrocortical temporal complexity decreased from wakefulness to sleep. Nevertheless, the origin of this complex activity remains a controversial topic due to the existence of possible artifacts contaminating the brain signals. In this work, we showed that complexity decreases during sleep, independently of the electrode configuration employed. This fact strongly suggests that the basis for the behavioral-state differences in complexity does not have an extracranial origin; i.e., generated from the brain.

neuroscience↗

Decreased electrocortical temporal complexity distinguishes sleep from wakefulness

In most mammals, the sleep-wake cycle is constituted by three behavioral states: wakefulness (W), non-NREM (NREM) sleep, and REM sleep. These states are associated with drastic changes in cognitive capacities, mostly determined by the function of the thalamo-cortical system. The intra-cranial electroencephalogram or electocorticogram (ECoG), is an important tool for measuring the changes in the thalamo-cortical activity during W and sleep. In the present study we analyzed broad-band ECoG recordings of the rat by means of a time-series complexity measure that is easy to implement and robust to noise: the Permutation Entropy (PeEn). We found that PeEn is maximal during W and decreases during sleep. These results bring to light the different thalamo-cortical dynamics emerging during sleep-wake states, which are associated with the well-known spectral changes that occur when passing from W to sleep. Moreover, the PeEn analysis allows to determine behavioral states independently of the electrodes cortical location, which points to an underlying global pattern in the signal that differs among the cycle states that is missed by classical methods. Consequently, our data suggest that PeEn analysis of a single EEG channel could allow for cheap, easy, and efficient sleep monitoring.

neuroscience↗