Predictive Neuronal Adaptation as a Basis for Consciousness

Being able to correctly predict the future and to adjust own actions accordingly can offer a great survival advantage. In fact, this could be the main reason why brains evolved. Consciousness, the most mysterious feature of brain activity, also seems to be related to predicting the future and detecting surprise: a mismatch between actual and predicted situation. Similarly at a single neuron level, predicting future activity and adapting synaptic inputs accordingly was shown to be the best strategy to maximize the metabolic energy for a neuron. Following on these ideas, here we examined if surprise minimization by single neurons could be a basis for consciousness. First, we showed in simulations that as a neural network learns a new task, then the surprise within neurons (defined as the difference between actual and expected activity) changes similarly to the consciousness of skills in humans. Moreover, implementing adaptation of neuronal activity to minimize surprise at fast time scales (tens of milliseconds) resulted in improved network performance. This improvement is likely because adapting activity based on the internal predictive model allows each neuron to make a more “educated” response to stimuli. Based on those results, we propose that the neuronal predictive adaptation to minimize surprise could be a basic building block of conscious processing. Such adaptation allows neurons to exchange information about own predictions and thus to build more complex predictive models. To be precise, we provide an equation to quantify consciousness as the amount of surprise minus the size of the adaptation error. Since neuronal adaptation can be studied experimentally, this can allow testing directly our hypothesis. Specifically, we postulate that any substance affecting neuronal adaptation will also affect consciousness. Interestingly, our predictive adaptation hypothesis is consistent with multiple ideas presented previously in diverse theories of consciousness, such as global workspace theory, integrated information, attention schema theory, and predictive processing framework. In summary, we present a theoretical, computational, and experimental support for the hypothesis that neuronal adaptation is a possible biological mechanism of conscious processing, and we discuss how this could provide a step toward a unified theory of consciousness.

Sensory Adaptation in the Whisker-Mediated Tactile System: Physiology, Theory, and Function

In the natural environment, organisms are constantly exposed to a continuous stream of sensory input. The dynamics of sensory input changes with organism's behaviour and environmental context. The contextual variations may induce >100-fold change in the parameters of the stimulation that an animal experiences. Thus, it is vital for the organism to adapt to the new diet of stimulation. The response properties of neurons, in turn, dynamically adjust to the prevailing properties of sensory stimulation, a process known as “neuronal adaptation.” Neuronal adaptation is a ubiquitous phenomenon across all sensory modalities and occurs at different stages of processing from periphery to cortex. In spite of the wealth of research on contextual modulation and neuronal adaptation in visual and auditory systems, the neuronal and computational basis of sensory adaptation in somatosensory system is less understood. Here, we summarise the recent finding and views about the neuronal adaptation in the rodent whisker-mediated tactile system and further summarise the functional effect of neuronal adaptation on the response dynamics and encoding efficiency of neurons at single cell and population levels along the whisker-mediated touch system in rodents. Based on direct and indirect pieces of evidence presented here, we suggest sensory adaptation provides context-dependent functional mechanisms for noise reduction in sensory processing, salience processing and deviant stimulus detection, shift between integration and coincidence detection, band-pass frequency filtering, adjusting neuronal receptive fields, enhancing neural coding and improving discriminability around adapting stimuli, energy conservation, and disambiguating encoding of principal features of tactile stimuli.

Predictive neuronal adaptation as a basis for consciousness.

Being able to correctly predict the future and to adjust own actions accordingly, offers great survival advantage. In fact, this could be the main reason for organisms to evolve their brains. The most mysterious feature of brain activity: consciousness, also seems to be related to predicting the future and detecting surprise: a mismatch between actual and predicted situation. Even at the single neuron level, predicting future activity and adapting synaptic inputs accordingly, is the best strategy to maximize metabolic energy for a neuron. Following on those ideas, here we examine if surprise minimization by single neurons could be a basis for consciousness. First, we show in simulations that as a neural network learns a task, then the surprise within neurons, defined as: difference between actual and expected activity, changes similarly as consciousness of a learned skill in humans. Moreover, implementing adaptation of neuronal activity to minimize surprise at fast time scales (tens of ms), resulted in improved network performance. This improvement is likely due to the fact that adapting activity based on the internal predictive model, allows each neuron for a more “educated” response to stimuli. Based on those results, we propose that: neuronal predictive adaptation to minimize surprise could be a basic building block of conscious processing. This is because, adapting activity toward a predicted level, allows neurons to exchange not only information about stimulus but also about its internal model predictions and thus, to build more complex predictive models. To be precise, we provide an equation to quantify consciousness as the amount of surprise minus the size of the adaptation error. Since neuronal adaptation can be studied experimentally, this allows for directly testing our hypothesis. Specifically, we postulate that any substance affecting neuronal adaptation will also affect consciousness. Interestingly, our predictive adaptation hypothesis is consistent with multiple ideas presented previously in diverse theories of consciousness, such as global workspace theory, integrated information, attention schema theory, and predictive processing framework. In summary, we present a theoretical, computational and experimental support for the hypothesis that neuronal adaptation is a possible biological mechanism of conscious processing, and we discuss how this could provide a step toward a unified theory of consciousness.

Foreground stimuli and task engagement enhance neuronal adaptation to background noise in the inferior colliculus of macaques

Auditory neuronal responses are influenced by maskers and distractors. However, it is still unclear whether the neuronal sensitivity to the masker stimulus is influenced by task-dependent factors. Our study represents one of the first attempts to investigate how task involvement influences the neural representation of background sounds in the subcortical, midbrain auditory neurons of behaving animals.

Neuronal adaptation in the course of the prolonged task improves visual stimuli processing

Brain optimally utilizes resources to resist mental fatigue during the prolonged period of cognitive activity. Neural mechanisms underlying long-term cognitive performance remain unknown. We show that during the 40-minutes visual stimuli classification task, subjects improve behavioral performance in terms of response time and correctness. We observe that the prestimulus θ and α power grows during the experiment manifesting the mental fatigue. The prestimulus β power, in its turn, increases locally in the region, engaged in the ongoing stimulus processing, that may reflect the neuronal adaptation. Our results evidence that the neuronal adaptation is enhanced in the course of the experiment reducing the cognitive demands required to activate the stimulus-related brain regions.

A Preliminary Review of Neurolinguistics Research in Simultaneous Interpreting (SI)

The present review article, with no pretense of being exhaustive, aims at shedding light on some of the major empirical studies conducted in recent years in Simultaneous Interpreting (SI) from a neurolinguistics point of view.Some of the issues that will be covered include the definition and development of expertise in SI, neuronal adaptation and the cognitive complexity of SI. The present preliminary review will end with some questions that future research could focus on and, hopefully, provide some answers to.