Autogenous cerebral processes: an invitation to look at the brain from inside out.

While external stimulation can reliably trigger neuronal activity, cerebral processes can operate independently from the environment. In this study, we conceptualize autogenous cerebral processes (ACPs) as intrinsic operations of the brain that exist on multiple scales and can influence or shape stimulus responses, behavior, homeostasis, and the physiological state of an organism. We further propose that the field should consider exploring to what extent perception, arousal, behavior, or movement, as well as other cognitive functions previously investigated mainly regarding their stimulus-response dynamics, are ACP-driven.

Neuronal Population Activity in Macaque Visual Cortices Dynamically Changes through Repeated Fixations in Active Free Viewing.

During free viewing, we move our eyes and fixate on objects to recognize the visual scene of our surroundings. To investigate the neural representation of objects in this process, we studied individual and population neuronal activity in three different visual regions of the brains of macaque monkeys (Macaca fuscata): the primary and secondary visual cortices (V1, V2) and the inferotemporal cortex (IT). We designed a task where the animal freely selected objects in a stimulus image to fixate on while we examined the relationship between spiking activity, the order of fixations, and the fixated objects. We found that activity changed across repeated fixations on the same object in all three recorded areas, with observed reductions in firing rates. Furthermore, the responses of individual neurons became sparser and more selective with individual objects. The population activity for individual objects also became distinct. These results suggest that visual neurons respond dynamically to repeated input stimuli through a smaller number of spikes, thereby allowing for discrimination between individual objects with smaller energy.

Event-related (de)synchronization and potential in whole vs. part sensorimotor learning.

Background: There are different ways to learn a sensorimotor task. This research focuses on whole versus part learning in a complex video game that involves sensorimotor adaptations and skill learning. The primary aim of this research is to compare the changes in (1) event-related potentials (ERP) and (2) Alpha and Beta event-related desynchronization/synchronization [ERD(S)] of EEG between whole and part practice protocols. Materials and methods: 18 Healthy young participants practiced for 5 days a video game with distorted kinematic (advancing skill) and dynamic features (shooting skill) to test the ability to combine sensorimotor skill components learned modularly (part learning, 9 participants) or combined (whole practice, 9 participants). We examined ERP and ERD(S) in EEG channels in the baseline test (day 1) and the retention test (day 5), dissociating epochs with advancing or shooting. We focus the analysis on the main activity of ERP or ERD(S) in different time windows. Results: In the advancing epochs (distorted kinematic), both groups showed a decrease in time for ERP and an increase in Beta ERD activity in central and posterior channels. In the shooting epochs (distorted dynamic), the Whole group showed a decrease in time for ERPs in anterior and central-posterior channels. Additionally, the shooting ERS in the Beta band decreases within sessions in central channels, particularly for the Part group. Conclusion: Neural correlates of kinematic and dynamic control [ERP and ERD(S)] were modulated by sensorimotor learning, which reflects the effect of the type of practice on the execution and the evaluation of the action. These results can be linked with our previous report, where the simultaneous practice of kinematic and dynamic distortions takes advantage of the motor performance on retention tests, indicating a more automatic control for the whole practice group.

Visual-spatial processing impairment in the occipital-frontal connectivity network at early stages of Alzheimer's disease.

Introduction: Alzheimer's disease (AD) is the leading cause of dementia worldwide, but its pathophysiological phenomena are not fully elucidated. Many neurophysiological markers have been suggested to identify early cognitive impairments of AD. However, the diagnosis of this disease remains a challenge for specialists. In the present cross-sectional study, our objective was to evaluate the manifestations and mechanisms underlying visual-spatial deficits at the early stages of AD. Methods: We combined behavioral, electroencephalography (EEG), and eye movement recordings during the performance of a spatial navigation task (a virtual version of the Morris Water Maze adapted to humans). Participants (69-88 years old) with amnesic mild cognitive impairment-Clinical Dementia Rating scale (aMCI-CDR 0.5) were selected as probable early AD (eAD) by a neurologist specialized in dementia. All patients included in this study were evaluated at the CDR 0.5 stage but progressed to probable AD during clinical follow-up. An equal number of matching healthy controls (HCs) were evaluated while performing the navigation task. Data were collected at the Department of Neurology of the Clinical Hospital of the Universidad de Chile and the Department of Neuroscience of the Faculty of Universidad de Chile. Results: Participants with aMCI preceding AD (eAD) showed impaired spatial learning and their visual exploration differed from the control group. eAD group did not clearly prefer regions of interest that could guide solving the task, while controls did. The eAD group showed decreased visual occipital evoked potentials associated with eye fixations, recorded at occipital electrodes. They also showed an alteration of the spatial spread of activity to parietal and frontal regions at the end of the task. The control group presented marked occipital activity in the beta band (15-20 Hz) at early visual processing time. The eAD group showed a reduction in beta band functional connectivity in the prefrontal cortices reflecting poor planning of navigation strategies. Discussion: We found that EEG signals combined with visual-spatial navigation analysis, yielded early and specific features that may underlie the basis for understanding the loss of functional connectivity in AD. Still, our results are clinically promising for early diagnosis required to improve quality of life and decrease healthcare costs.

SaFiDe: Detection of saccade and fixation periods based on eye-movement attributes from video-oculography, scleral coil or electrooculography data.

In this work we present SaFiDe, a deterministic method to detect eye movements (saccades and fixations) from eye-trace data. We developed this method for human and nonhuman primate data from video- and coil-recorded eye traces and further applied the algorithm to eye traces computed from electrooculograms. All the data analyzed were from free-exploration paradigms, where the main challenge was to detect periods of saccades and fixations that were uncued by the task. The method uses velocity and acceleration thresholds, calculated from the eye trace, to detect saccade and fixation periods. We show that our fully deterministic method detects saccades and fixations from eye traces during free visual exploration. The algorithm was implemented in MATLAB, and the code is publicly available on a GitHub repository.•The algorithm presented is entirely deterministic, simplifying the comparison between subjects and tasks.•Thus far, the algorithm presented can operate over video-based eye tracker data, human electrooculogram records, or monkey scleral eye coil data.

Voluntary self-initiation of the stimuli onset improves working memory and accelerates visual and attentional processing.

The ability of an organism to voluntarily control the stimuli onset modulates perceptual and attentional functions. Since stimulus encoding is an essential component of working memory (WM), we conjectured that controlling the initiation of the perceptual process would positively modulate WM. To corroborate this proposition, we tested twenty-five healthy subjects in a modified-Sternberg WM task under three stimuli presentation conditions: an automatic presentation of the stimuli, a self-initiated presentation of the stimuli (through a button press), and a self-initiated presentation with random-delay stimuli onset. Concurrently, we recorded the subjects' electroencephalographic signals during WM encoding. We found that the self-initiated condition was associated with better WM accuracy, and earlier latencies of N1, P2 and P3 evoked potential components representing visual, attentional and mental review of the stimuli processes, respectively. Our work demonstrates that self-initiated stimuli enhance WM performance and accelerate early visual and attentional processes deployed during WM encoding. We also found that self-initiated stimuli correlate with an increased attentional state compared to the other two conditions, suggesting a role for temporal stimuli predictability. Our study remarks on the relevance of self-control of the stimuli onset in sensory, attentional and memory updating processing for WM.

Cortico-Hippocampal Oscillations Are Associated With the Developmental Onset of Hippocampal-Dependent Memory.

Hippocampal-dependent memories emerge late during postnatal development, aligning with hippocampal maturation. During sleep, the two-stage memory formation model states that through hippocampal-neocortical interactions, cortical slow-oscillations (SO), thalamocortical Spindles, and hippocampal sharp-wave ripples (SWR) are synchronized, allowing for the consolidation of hippocampal-dependent memories. However, evidence supporting this hypothesis during development is still lacking. Therefore, we performed successive object-in-place tests during a window of memory emergence and recorded in vivo the occurrence of SO, Spindles, and SWR during sleep, immediately after the memory encoding stage of the task. We found that hippocampal-dependent memory emerges at the end of the 4th postnatal week independently of task overtraining. Furthermore, we observed that those animals with better performance in the memory task had increased Spindle density and duration and lower density of SWR. Moreover, we observed changes in the SO-Spindle and Spindle-SWR temporal-coupling during this developmental period. Our results provide new evidence for the onset of hippocampal-dependent memory and its relationship to the oscillatory phenomenon occurring during sleep that helps us understand how memory consolidation models fit into the early stages of postnatal development.

Alpha EEG Activity and Pupil Diameter Coupling during Inactive Wakefulness in Humans.

Variations in human behavior correspond to the adaptation of the nervous system to different internal and environmental demands. Attention, a cognitive process for weighing environmental demands, changes over time. Pupillary activity, which is affected by fluctuating levels of cognitive processing, appears to identify neural dynamics that relate to different states of attention. In mice, for example, pupil dynamics directly correlate with brain state fluctuations. Although, in humans, alpha-band activity is associated with inhibitory processes in cortical networks during visual processing, and its amplitude is modulated by attention, conclusive evidence linking this narrowband activity to pupil changes in time remains sparse. We hypothesize that, as alpha activity and pupil diameter indicate attentional variations over time, these two measures should be comodulated. In this work, we recorded the electroencephalographic (EEG) and pupillary activity of 16 human subjects who had their eyes fixed on a gray screen for 1 min. Our study revealed that the alpha-band amplitude and the high-frequency component of the pupil diameter covariate spontaneously. Specifically, the maximum alpha-band amplitude was observed to occur ∼300 ms before the peak of the pupil diameter. In contrast, the minimum alpha-band amplitude was noted to occur ∼350 ms before the trough of the pupil diameter. The consistent temporal coincidence of these two measurements strongly suggests that the subject's state of attention, as indicated by the EEG alpha amplitude, is changing moment to moment and can be monitored by measuring EEG together with the diameter pupil.

Latency shortening with enhanced sparseness and responsiveness in V1 during active visual sensing.

In natural vision, neuronal responses to visual stimuli occur due to self-initiated eye movements. Here, we compare single-unit activity in the primary visual cortex (V1) of non-human primates to flashed natural scenes (passive vision condition) to when they freely explore the images by self-initiated eye movements (active vision condition). Active vision enhances the number of neurons responding, and the response latencies become shorter and less variable across neurons. The increased responsiveness and shortened latency during active vision were not explained by increased visual contrast. While the neuronal activities in all layers of V1 show enhanced responsiveness and shortened latency, a significant increase in lifetime sparseness during active vision is observed only in the supragranular layer. These findings demonstrate that the neuronal responses become more distinct in active vision than passive vision, interpreted as consequences of top-down predictive mechanisms.

Extending the integrate-and-fire model to account for metabolic dependencies.

It is widely accepted that the brain, like any other physical system, is subjected to physical constraints that restrict its operation. The brain's metabolic demands are particularly critical for proper neuronal function, but the impact of these constraints continues to remain poorly understood. Detailed single-neuron models are recently integrating metabolic constraints, but these models' computational resources make it challenging to explore the dynamics of extended neural networks, which are governed by such constraints. Thus, there is a need for a simplified neuron model that incorporates metabolic activity and allows us to explore the dynamics of neural networks. This work introduces an energy-dependent leaky integrate-and-fire (EDLIF) neuronal model extension to account for the effects of metabolic constraints on the single-neuron behavior. This simple, energy-dependent model could describe the relationship between the average firing rate and the Adenosine triphosphate (ATP) cost as well as replicate a neuron's behavior under a clinical setting such as amyotrophic lateral sclerosis (ALS). Additionally, EDLIF model showed better performance in predicting real spike trains - in the sense of spike coincidence measure - than the classical leaky integrate-and-fire (LIF) model. The simplicity of the energy-dependent model presented here makes it computationally efficient and, thus, suitable for studying the dynamics of large neural networks.

The Energy Homeostasis Principle: A Naturalistic Approach to Explain the Emergence of Behavior.

It is still elusive to explain the emergence of behavior and understanding based on its neural mechanisms. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding emerge. FEP starts from a whole-organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort but starts from single-neuron phenomena and builds up to whole-organism behavior and understanding. In this work, we further develop the EHP as a distinct but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of the function, purpose, and conception of goal-oriented behavior. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing by explaining basic learning scenarios up to simple anticipatory behavior. Finally, we end the article with an evolutionary perspective of how this non-goal-oriented behavior appeared. We acknowledge that our proposal, in its current form, is still far from explaining the emergence of understanding. Nonetheless, we set the ground for an alternative neuron-based framework to ultimately explain understanding.

Interoceptive insular cortex participates in sensory processing of gastrointestinal malaise and associated behaviors.

The insular cortex plays a central role in the perception and regulation of bodily needs and emotions. Its modular arrangement, corresponding with different sensory modalities, denotes a complex organization, and reveals it to be a hub that is able to coordinate autonomic and behavioral responses to many types of stimuli. Yet, little is known about the dynamics of its electrical activity at the neuronal level. We recorded single neurons in behaving rats from the posterior insula cortex (pIC), a subdivision considered as a primary interoceptive cortex, during gastrointestinal (GI) malaise, a state akin to the emotion of disgust in humans. We found that a large proportion of pIC neurons were modulated during the rodent compensatory behaviors of lying on belly (LOB) and Pica. Furthermore, we demonstrated that LOB was correlated with low-frequency oscillations in the field potentials and spikes at the theta (8 Hz) band, and that low-frequency electrical microstimulation of pIC elicited LOB and Pica. These findings demonstrate that pIC neurons play a critical role in GI malaise perception, and that the pIC influences the expression of behaviors that alleviate GI malaise. Our model provides an accessible approach at the single cell level to study innate emotional behaviors, currently elusive in humans.

Corrigendum: The Energy Homeostasis Principle: Neuronal Energy Regulation Drives Local Network Dynamics Generating Behavior.

[This corrects the article DOI: 10.3389/fncom.2019.00049.].

The Energy Homeostasis Principle: Neuronal Energy Regulation Drives Local Network Dynamics Generating Behavior.

A major goal of neuroscience is understanding how neurons arrange themselves into neural networks that result in behavior. Most theoretical and experimental efforts have focused on a top-down approach which seeks to identify neuronal correlates of behaviors. This has been accomplished by effectively mapping specific behaviors to distinct neural patterns, or by creating computational models that produce a desired behavioral outcome. Nonetheless, these approaches have only implicitly considered the fact that neural tissue, like any other physical system, is subjected to several restrictions and boundaries of operations. Here, we proposed a new, bottom-up conceptual paradigm: The Energy Homeostasis Principle, where the balance between energy income, expenditure, and availability are the key parameters in determining the dynamics of neuronal phenomena found from molecular to behavioral levels. Neurons display high energy consumption relative to other cells, with metabolic consumption of the brain representing 20% of the whole-body oxygen uptake, contrasting with this organ representing only 2% of the body weight. Also, neurons have specialized surrounding tissue providing the necessary energy which, in the case of the brain, is provided by astrocytes. Moreover, and unlike other cell types with high energy demands such as muscle cells, neurons have strict aerobic metabolism. These facts indicate that neurons are highly sensitive to energy limitations, with Gibb's free energy dictating the direction of all cellular metabolic processes. From this activity, the largest energy, by far, is expended by action potentials and post-synaptic potentials; therefore, plasticity can be reinterpreted in terms of their energy context. Consequently, neurons, through their synapses, impose energy demands over post-synaptic neurons in a close loop-manner, modulating the dynamics of local circuits. Subsequently, the energy dynamics end up impacting the homeostatic mechanisms of neuronal networks. Furthermore, local energy management also emerges as a neural population property, where most of the energy expenses are triggered by sensory or other modulatory inputs. Local energy management in neurons may be sufficient to explain the emergence of behavior, enabling the assessment of which properties arise in neural circuits and how. Essentially, the proposal of the Energy Homeostasis Principle is also readily testable for simple neuronal networks.

Timing Is of the Essence: Improvement in Perception During Active Sensing.

Active sensing refers to the concept of animals perceiving their environment while involving self-initiated motor acts. As a consequence of these motor acts, this activity produces direct and timely changes in the sensory surface. Is the brain able to take advantage of the precise time-locking that occurs during active sensing? Is the intrinsic predictability present during active sensing, impacting the sensory processes? We conjecture that if stimuli presentation is evoked by a self-initiated motor act, sensory discrimination and timing accuracy would improve. We studied this phenomenon when rats had to locate the position of a brief light stimulus, either when it was elicited by a warning light [passive condition (PC)] or when it was generated by a lever press [active condition (AC)]. We found that during the PC, rats had 66% of correct responses, vs. a significantly higher 77% of correct responses in AC. Furthermore, reaction times reduced from 1,181 ms during AC to 816 ms during PC For the latter condition, the probability of detecting the side of the light stimulus was negatively correlated with the time lag between the motor act and the evoked light and with a 38% reduction on performance per second of delay. These experiment shows that the mechanism that underlies sensory improvement during active behaviors have a constrained time dynamic, where the peak performances occur during the motor act, decreasing proportionally to the lag between the motor act and the stimulus presentation. This result is consistent with the evidence already found in humans, of a precise time dynamic of the improvement of sensory acuity after a motor act and reveals an equivalent process in rodents. Our results support the idea that perception and action are precisely coordinated in the brain.

Finger Temperature: A Psychophysiological Assessment of the Attentional State.

Attention is a key cognitive phenomenon that is studied to understand cognitive disorders or even to estimate workloads to prevent accidents. Usually, it is studied using brain activity, even though it has many psychophysiological correlates. In the present study, we aim to evaluate if finger temperature, as a surrogate of peripheral vasoconstriction, can be used to obtain similar and complementary information to electroencephalography (EEG) brain activity measurements. To conduct this, 34 participants were recruited and submitted to performing four tasks-one as a baseline, and three attentional tasks. These three attentional tasks measured sustained attention, resilience to distractors, and attentional resources. During the tasks, the room, forehead, tympanic, and finger temperatures were measured. Furthermore, we included a 32-channel EEG recording. Our results showed a strong monotonic association between the finger temperature and the Alpha and Beta EEG spectral bands. When predicting attentional performance, the finger temperature was complementary to the EEG spectral measurements, through the prediction of aspects of attentional performance that had not been assessed by spectral EEG activity, or through the improvement of the model's fit. We also found that during the baseline task (non-goal-oriented task), the spectral EEG activity has an inverted correlation, as compared to a goal-oriented task. Our current results suggest that the psychophysiological assessment of attention is complementary to classic EEG approach, while also having the advantage of easy implementation of analysis tools in environments of reducing control (workplaces, student classrooms).

EEG Classification During Scene Free-Viewing for Schizophrenia Detection.

Currently, the diagnosis of schizophrenia is made solely based on interviews and behavioral observations by a trained psychiatrist. Technologies such as electroencephalography (EEG) are used for differential diagnosis and not to support the psychiatrist's positive diagnosis. Here, we show the potential of EEG recordings as biomarkers of the schizophrenia syndrome. We recorded EEG while schizophrenia patients freely viewed natural scenes, and we analyzed the average EEG activity locked to the image onset. We found significant differences between patients and healthy controls in occipital areas approximately 500 ms after image onset. These differences were used to train a classifier to discriminate the schizophrenia patients from the controls. The best classifier had 81% sensitivity for the detection of patients and specificity of 59% for the detection of controls, with an overall accuracy of 71%. These results indicate that EEG signals from a free-viewing paradigm discriminate patients from healthy controls and have the potential to become a tool for the psychiatrist to support the positive diagnosis of schizophrenia.

Autonomic nervous system assessment by pupillary response as a potential biomarker for cardiovascular risk: A pilot study.

BACKGROUND: Cardiovascular risk (CVR) biomarkers are of increasing interest because of their potential utility in management of cardiovascular diseases. The activity of the autonomic nervous system (ANS) is known to be highly correlated with CVR and therefore, is a putative biomarker. Common ANS measurement tools have several technological limitations and high-variance signals. The pupillary responses (PR) is controlled by both components of the ANS, and recent advances in pupillometry are making this measurement, easy and reliable. Thus, PR assessment could become a useful clinical tool to measure the ANS modulation and its relation to CVR. Here, we aimed to evaluate differences in PR between low CVR and moderate/high CVR individuals. METHODS: We performed a cross-sectional study. We recruited voluntaries with low CVR (group 1, n = 12) and patients with moderate/high CVR (group 2, n = 7). An eye tracker was used to measure PR to different visual stimulus that included colors (white, black, gray) and images with known emotional valence (pleasant, unpleasant and neutrals), which were intercalated by pink "noise" images. Differences in PR between both CVR groups were assessed by Mann Whitney U test of different epochs of the PR. RESULTS: PR was significantly different between both CVR groups (p-value < 0,05) when the observed images were unpleasant, neutral, and pink noise, for different epochs of the PR. CONCLUSIONS: This is the first study that demonstrates that PR is different according to CVR. Thus, PR could be considered as a novel biomarker of CVR to be tested in prospective studies.

Parallel learning processes of a visuomotor adaptation task in a changing environment.

During the control of reaching movements, a key contribution of the visual system is the localization of relevant environmental targets. In motor adaptation processes, the visual evaluation of effector motor behavior enables learning from errors, which demands continuous visual attentional focus. However, most current adaptation paradigms include static targets; therefore, when a learning situation develops in a highly variable environment and there is a double demand for visual resources (environment and motor performance), the evolution of learning processes is unknown. In order to understand how learning processes evolve in a variable environment, a video game task was designed in which subjects were asked to manage a 60° counterclockwise-rotated cursor to capture descending targets with initially unpredictable trajectories. During the task, the cursor and eye movements were recorded to dissect visuomotor coordination. We observed that the pursuit of the targets conditioned a predominant and continuous visual inspection of the environment instead of the rotated cursor. As learning progressed, subjects exhibited a linear reduction in directional error and selected a motor strategy based on the degree of reward, which improved the performance. These results suggest that when the environment demands high visual attention, error-based and reinforced motor learning processes are implemented simultaneously, thus enabling efficient predictive behavior.

Emotional Content Modulates Attentional Visual Orientation During Free Viewing of Natural Images.

Visual attention is the process that enables us to select relevant visual stimuli in our environment to achieve a goal or perform adaptive behaviors. In this process, bottom-up mechanisms interact with top-down mechanisms underlying the automatic and voluntary orienting of attention. Cognitive functions, such as emotional processing, can influence visual attention by increasing or decreasing the resources destined for processing stimuli. The relationship between attention and emotion has been explored mainly in the field of automatic attentional capturing; especially, emotional stimuli are suddenly presented and detection rates or reaction times are recorded. Unlike these paradigms, natural visual scenes may be comprised in multiple stimuli with different emotional valences. In this setting, the mechanisms supporting voluntary visual orientation, under the influence of the emotional components of stimuli, are unknown. We employed a mosaic of pictures with different emotional valences (positive, negative, and neutral) and explored the dynamics of attentional visual orientation, assessed by eye tracking and measurements of pupil diameter. We found that pictures with affective content display increased dwelling times when compared to neutral pictures with a larger effect for negative pictures. The valence, regardless of the arousal levels, was the main factor driving the behavioral modulation of visual orientation. On the other hand, the visual exploration was accompanied by a systematic pupillary response, with the pupil contraction and dilation influenced by the arousal levels, with minor effects driven by the valence. Our results emphasize that arousal and valence should be considered different dimensions of emotional processing both interacting with cognitive processes such as visual attention.