Biology subjects

Chialvo, D. R.

Publications and source records attributed to Chialvo, D. R..

3 recordsLinked to original sources

bioRxiv2021

Non-linear functional brain co-activations in short-term memory distortion tasks

Recent works shed light on the neural correlates of true and false recognition and the influence of time of day on cognitive performance. The current study aimed to investigate the modulation of the false memory formation by the time of day using a non-linear correlation analysis originally designed for fMRI resting-state data. Fifty-four young and healthy participants (32 females, mean age: 24.17 y.o., SD: 3.56 y.o.) performed in MR scanner the modified Deese-Roediger-McDermott paradigm in short-term memory during one session in the morning and another in the evening. Subjects responses were modeled with a general linear model, which includes as a predictor the non-linear correlations of regional BOLD activity with the stimuli, separately for encoding and retrieval phases. The results show the dependence of the non-linear correlations measures with the time of day and the type of the probe. In addition, the results indicate differences in the correlations measures with hippocampal regions between positive and lure probes. Besides confirming previous results on the influence of time-of-day on cognitive performance, the study demonstrates the effectiveness of the non-linear correlation analysis method for the characterization of fMRI task paradigms.

neuroscience↗

bioRxiv2020

Scale-free dynamics in animal groups and brain networks

Collective phenomena fascinate by the emergence of order in systems composed of a myriad of small entities. They are ubiquitous in nature and can be found over a vast range of scales in physical and biological systems. Their key feature is the seemingly effortless emergence of adaptive collective behavior that cannot be trivially explained by the properties of the systems individual components. This perspective focuses on recent insights into the similarities of correlations for two apparently disparate phenomena: flocking in animal groups and neuronal ensemble activity in the brain. We first will summarize findings on the spontaneous organization in bird flocks and macro-scale human brain activity utilizing correlation functions and insights from critical dynamics. We then will discuss recent experimental findings that apply these approaches to the collective response of neurons to visual and motor processing, i.e. to local perturbations of neuronal networks at the meso- and microscale. We show how scale-free correlation functions capture the collective organization of neuronal avalanches in evoked neuronal populations in nonhuman primates and between neurons during visual processing in rodents. These experimental findings suggest that the coherent collective neural activity observed at scales much larger than the length of the direct neuronal interactions is demonstrative of a phase transition. We discuss the experimental support for either discontinuous or continuous phase transitions. We conclude that at or near a phase-transition neuronal information can propagate in the brain with the same efficiency as proposed to occur in the collective adaptive response observed in some animal groups.

neuroscience↗

bioRxiv2020

Trial-by-trial variability in cortical responses exhibits scaling in spatial correlations predicted from critical dynamics

Simple sensory stimuli or motor outputs engage large populations of neurons in the mammalian cortex. When stimuli or outputs repeat, the robust population response contrasts with fluctuating responses of individual neurons, known as trial-by-trial variability. To understand this apparent discrepancy, a detailed identification of the underlying spatiotemporal correlations is required. Here, we analyze spatial correlations in the instantaneous fluctuations between neurons relative to the neuronal population. Using 2-photon imaging of visual and auditory responses in primary cortices of awake mice, we show that these correlations grow linearly with the size of the observed cortical area. We extend these observations to the cortical mesoscale by analyzing local field potentials in behaving nonhuman primates. In network simulations, we demonstrate this linear growth in spatial correlation to emerge at criticality. Our findings suggest that trial-by-trial variability is a signature of critical dynamics in cortex maintaining robust, long-range spatial correlations among neurons.

neuroscience↗