Biology subjects

Torterolo, P. D.

Publications and source records attributed to Torterolo, P. D..

4 recordsLinked to original sources

bioRxiv2026

State-dependent top-down and bottom-up processes in gamma-band (~40 Hz) oscillations of the cat EEG

Cognitive processes rely on extensive thalamocortical and corticocortical recurrent interactions. The gamma frequency band ([~]40 Hz) of the electroencephalogram (EEG) emerges from these interactions. Importantly, cognitive processing depends on the interplay between bottom-up sensory inputs and top-down influences from higher-order cortical areas. However, the extent to which gamma-band oscillations are associated with directional patterns of functional interactions remains unclear. Therefore, the aim of this study was to investigate the directionality of gamma-band information flow during wakefulness (W) and sleep, under spontaneous conditions and in response to auditory stimulation. Cats were chronically implanted for polysomnographic recordings, with electrodes placed in multiple cortical and thalamic regions. Information-flow directionality was assessed using two complementary methods: (i) time-lag analysis of gamma-band amplitude envelopes between pairs of channels, and (ii) Granger Causality analysis of the same channel pairs. During quiet W gamma-band oscillations exhibited a predominantly top-down directional organization, from higher- to lower-order cortical areas, as well as from cortical regions to thalamic nuclei. Following auditory stimulation, a prominent gamma response emerged between 0.5 and 1.5 s after stimulus onset. Within this time window, distinct patterns of gamma-band information flow were observed depending on the nature of the stimulus. Specifically, a bottom-up directional predominance was observed for simple auditory stimuli (clicks), whereas top-down processing prevailed for complex variable stimuli. In contrast, no consistent directionality of information flow was observed during either NREM or REM sleep, regardless of whether auditory stimulation was present. These findings extend our understanding of gamma-band information-flow dynamics during wakefulness and sleep.

neuroscience↗

bioRxiv2023

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

neuroscience↗

bioRxiv2021

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

neuroscience↗

bioRxiv2019

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↗