Biology subjects

Tzovara, A.

Publications and source records attributed to Tzovara, A..

5 recordsLinked to original sources

bioRxiv2025

Directed cortico-limbic dialogue in the human brain

How can one trace the brains orderly directed signals amid a tangle of nerve fibers? Because direct access to actual brain signaling is rare in humans, the precise wiring diagrams for cortico-limbic communication during sleep and wake remain essentially unmapped, hampering progress in neuroscience. Now, a unique neurosurgical window on the human brain allows for electrically mapping cortical connections at the hospital, but studies so far have relied on average signals, masking the dynamic nature of signal flow across brain regions. To causally estimate signaling dynamics, we repeatedly probed cortico-limbic networks with short-lived electrical pulses over days and assessed the variable fate of each transmitted signal on a single-trial basis. In the resulting openly available dataset, we characterized signaling probabilities and directionality across thousands local and long-range cortico-limbic connections over days. Challenging established views, we found that limbic structures send twice as many signals as they receive, in both wakefulness and sleep. Our findings provide a fundamental framework for causally interpreting signal flow in the brain and formulating therapeutic strategies for brain networks disorders.

neuroscience↗

bioRxiv2024

Sleep modulates neural timescales and spatiotemporal integration in the human cortex

Spontaneous neural dynamics manifest across multiple timescales, which are intrinsic to brain areas and exhibit hierarchical organization across the cortex. In wake, a hierarchy of timescales is thought to naturally emerge from microstructural properties, gene expression, and recurrent connections. A fundamental question is timescales organization and changes in sleep, where physiological needs are different. Here, we describe two coexisting but distinct measures of neural timescales, obtained from broadband activity and gamma power, which display complementary properties. We leveraged intracranial electroencephalography (iEEG) data to characterize timescale changes from wake to sleep across the cortical hierarchy. We show that both broadband and gamma timescales are globally longer in sleep than in wake. While broadband timescales increase along the sensorimotor-association axis, gamma ones decrease. During sleep, slow waves can explain the increase of broadband and gamma timescales, but only broadband ones show a positive association with slow-wave density across the cortex. Finally, we characterize spatial correlations and their relationship with timescales as a proxy for spatiotemporal integration, finding high integration at long distances in wake for broadband and at short distances in sleep for gamma timescales. Our results suggest that mesoscopic neural populations possess different timescales that are shaped by anatomy and are modulated by the sleep/wake cycle. Significance statementUnderstanding the organization of intrinsic neural dynamics is crucial for investigating brain functions in health and disease. A key question is: how do neural dynamics change in the sleeping brain? Here we focus on neural timescales, which measure temporal autocorrelation and are organized hierarchically across the cortex, and spatial correlations. We show that two types of timescales exist in neural populations recorded with intracranial electroencephalography in humans, corresponding to broadband (0.5-80 Hz) and gamma (40-80 Hz) frequency ranges. Both timescales increase in sleep, where slow waves have an important role, but follow opposite hierarchies: broadband timescales increase from sensory to associative areas, while gamma timescales show the reverse pattern. Finally, timescales covary with spatial correlations, suggesting higher spatiotemporal integration over long distances in wake compared to sleep.

neuroscience↗

bioRxiv2023

Decoding reveals the neural representation of held and manipulate musical thoughts

Vividly imagining a song or a melody is a skill that many people accomplish with relatively little effort. However, we are only beginning to understand how the brain represents, holds, and manipulates these musical "thoughts". Here, we decoded perceived and imagined melodies from magnetoencephalography (MEG) brain data (N = 71) to characterize their neural representation. We found that, during perception, auditory regions represent the sensory properties of individual sounds. In contrast, a widespread network including fronto-parietal cortex, hippocampus, basal nuclei, and sensorimotor regions hold the melody as an abstract unit during both perception and imagination. Furthermore, the mental manipulation of a melody systematically changes its neural representation, reflecting volitional control of auditory images. Our work sheds light on the nature and dynamics of auditory representations, informing future research on neural decoding of auditory imagination.

neuroscience↗

bioRxiv2022

Auditory prediction hierarchy in the human hippocampus and amygdala

Our brains can extract structure from the environment and form predictions given past sensory experience. Predictive circuits have been identified in wide-spread cortical regions. However, the contribution of subcortical areas, such as the hippocampus and amygdala in the formation of predictions remains under-explored. Here, we hypothesized that the hippocampus would be sensitive to predictability in sound sequences, while the amygdala would be sensitive to unexpected violations of auditory rules. We presented epileptic patients undergoing presurgical monitoring with standard and deviant sounds, in a predictable or unpredictable context. Onsets of auditory responses and unpredictable deviance effects were detected at earlier latencies in the temporal cortex compared to the amygdala and hippocampus. Deviance effects in 1-20 Hz local field potentials were detected in the lateral temporal cortex, irrespective of predictability. The amygdala showed stronger deviance responses in the unpredictable context. Additionally, low frequency deviance responses in the hippocampus (1-8 Hz) were observed in the predictable but not in the unpredictable context. Our results reveal a distributed cortical-subcortical network underlying the generation of auditory predictions, comprising temporal cortex and the hippocampus and amygdala, and suggest that the neural basis of sensory predictions and prediction error signals needs to be extended to subcortical regions.

neuroscience↗

bioRxiv2022

Intrinsic neural timescales in the temporal lobe support an auditory processing hierarchy

During rest, intrinsic neural dynamics manifest at multiple timescales, which progressively increase along visual and somatosensory hierarchies. Theoretically, intrinsic timescales are thought to facilitate processing of external stimuli at multiple stages. However, direct links between timescales at rest and sensory processing, as well as translation to the auditory system are lacking. Here, we used intracranial electroencephalography in humans to show that in the auditory network, intrinsic neural timescales progressively increase, while the spectral slope flattens, from temporal to entorhinal cortex, hippocampus, and amygdala. Within the neocortex, intrinsic timescales exhibit spatial gradients that follow the temporal lobe anatomy. Crucially, intrinsic timescales at rest can explain the latency of auditory responses: as intrinsic timescales increase, so do the single-electrode response onset and peak latencies. Our results suggest that the human auditory network exhibits a repertoire of intrinsic neural dynamics, which manifest in cortical gradients with millimeter resolution and may provide a variety of temporal windows to support auditory processing.

neuroscience↗