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.

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.

Local cortical activity of distant brain areas can phase-lock to the olfactory bulb's respiratory rhythm in the freely behaving rat.

An important unresolved question about neural processing is the mechanism by which distant brain areas coordinate their activities and relate their local processing to global neural events. A potential candidate for the local-global integration are slow rhythms such as respiration. In this study, we asked if there are modulations of local cortical processing that are phase-locked to (peripheral) sensory-motor exploratory rhythms. We studied rats on an elevated platform where they would spontaneously display exploratory and rest behaviors. Concurrent with behavior, we monitored whisking through electromyography and the respiratory rhythm from the olfactory bulb (OB) local field potential (LFP). We also recorded LFPs from dorsal hippocampus, primary motor cortex, primary somatosensory cortex, and primary visual cortex. We defined exploration as simultaneous whisking and sniffing above 5 Hz and found that this activity peaked at ~8 Hz. We considered rest as the absence of whisking and sniffing, and in this case, respiration occurred at ~3 Hz. We found a consistent shift across all areas toward these rhythm peaks accompanying behavioral changes. We also found, across areas, that LFP gamma (70-100 Hz) amplitude could phase-lock to the animal's OB respiratory rhythm, a finding indicative of respiration-locked changes in local processing. In a subset of animals, we also recorded the hippocampal theta activity and found that occurred at frequencies overlapped with respiration but was not spectrally coherent with it, suggesting a different oscillator. Our results are consistent with the notion of respiration as a binder or integrator of activity between brain regions.

Visuomotor coordination and cortical connectivity of modular motor learning.

The ability to transfer sensorimotor skill components to new actions and the capacity to use skill components from whole actions are characteristic of the adaptability of the human sensorimotor system. However, behavioral evidence suggests complex limitations for transfer after combined or modular learning of motor adaptations. Also, to date, only behavioral analysis of the consequences of the modular learning has been reported, with little understanding of the sensorimotor mechanisms of control and the interaction between cortical areas. We programmed a video game with distorted kinematic and dynamic features to test the ability to combine sensorimotor skill components learned modularly (composition) and the capacity to use separate sensorimotor skill components learned in combination (decomposition). We examined motor performance, eye-hand coordination, and EEG connectivity. When tested for integrated learning, we found that combined practice initially performed better than separated practice, but differences disappeared after integrated practice. Separate learning promotes fewer anticipatory control mechanisms (depending more on feedback control), evidenced in a lower gaze leading behavior and in higher connectivity between visual and premotor domains, in comparison with the combined practice. The sensorimotor system can acquire motor modules in a separated or integrated manner. However, the system appears to require integrated practice to coordinate the adaptations with the skill learning and the networks involved in the integrated behavior. This integration seems to be related to the acquisition of anticipatory mechanism of control and with the decrement of feedback control.

Similarity in Neuronal Firing Regimes across Mammalian Species.

UNLABELLED: The architectonic subdivisions of the brain are believed to be functional modules, each processing parts of global functions. Previously, we showed that neurons in different regions operate in different firing regimes in monkeys. It is possible that firing regimes reflect differences in underlying information processing, and consequently the firing regimes in homologous regions across animal species might be similar. We analyzed neuronal spike trains recorded from behaving mice, rats, cats, and monkeys. The firing regularity differed systematically, with differences across regions in one species being greater than the differences in similar areas across species. Neuronal firing was consistently most regular in motor areas, nearly random in visual and prefrontal/medial prefrontal cortical areas, and bursting in the hippocampus in all animals examined. This suggests that firing regularity (or irregularity) plays a key role in neural computation in each functional subdivision, depending on the types of information being carried. SIGNIFICANCE STATEMENT: By analyzing neuronal spike trains recorded from mice, rats, cats, and monkeys, we found that different brain regions have intrinsically different firing regimes that are more similar in homologous areas across species than across areas in one species. Because different regions in the brain are specialized for different functions, the present finding suggests that the different activity regimes of neurons are important for supporting different functions, so that appropriate neuronal codes can be used for different modalities.

Synchronization across sensory cortical areas by electrical microstimulation is sufficient for behavioral discrimination.

The temporal correlation hypothesis proposes that cortical neurons engage in synchronized activity, thus configuring a general mechanism to account for a range of cognitive processes from perceptual binding to consciousness. However, most studies supporting this hypothesis have only provided correlational, but not causal evidence. Here, we used electrical microstimulation of the visual and somatosensory cortices of the rat in both hemispheres, to test whether rats could discriminate synchronous versus asynchronous patterns of stimulation applied to the same cortical sites. To disambiguate synchrony from other related parameters, our experiments independently manipulated the rate and intensity of stimulation, the spatial locations of stimulation, the exact temporal sequence of stimulation patterns, and the degree of synchrony across stimulation sites. We found that rats reliably distinguished between 2 microstimulation patterns, differing in the spatial arrangement of cortical sites stimulated synchronously. Also, their performance was proportional to the level of synchrony in the microstimulation patterns. We demonstrated that rats can recognize artificial current patterns containing precise synchronization features, thus providing the first direct evidence that artificial synchronous activity can guide behavior. Such precise temporal information can be used as feedback signals in machine interface arrangements.

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.

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.

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.

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.

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.

Superposition model predicts EEG occipital activity during free viewing of natural scenes.

Visual event-related potentials (ERPs) produced by a stimulus are thought to reflect either an increase of synchronized activity or a phase realignment of ongoing oscillatory activity, with both mechanisms sharing the assumption that ERPs are independent of the current state of the brain at the time of stimulation. In natural viewing, however, visual inputs occur one after another at specific subject-paced intervals through unconstrained eye movements. We conjecture that during natural viewing, ERPs generated after each fixation are better explained by a superposition of ongoing oscillatory activity related to the processing of previous fixations, with new activity elicited by the visual input at the current fixation. We examined the electroencephalography (EEG) signals that occur in humans at the onset of each visual fixation, both while subjects freely viewed natural scenes and while they viewed a black or gray background. We found that the fixation ERPs show visual components that are absent when subjects move their eyes on a homogeneous gray or black screen. Single-trial EEG signals that comprise the ERP are predicted more accurately by a model of superposition than by either phase resetting or the addition of evoked responses and stimulus-independent noise. The superposition of ongoing oscillatory activity and the visually evoked response results in a modification of the ongoing oscillation phase. The results presented suggest that the observed EEG signals reflect changes occurring in a common neuronal substrate rather than a simple summation at the scalp of signals from independent sources.

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.

Dynamics of stimulus-evoked spike timing correlations in the cat lateral geniculate nucleus.

Precisely synchronized neuronal activity has been commonly observed in the mammalian visual pathway. Spike timing correlations in the lateral geniculate nucleus (LGN) often take the form of phase synchronized oscillations in the high gamma frequency range. To study the relations between oscillatory activity, synchrony, and their time-dependent properties, we recorded activity from multiple single units in the cat LGN under stimulation by stationary spots of light. Autocorrelation analysis showed that approximately one third of the cells exhibited oscillatory firing with a mean frequency ∼80 Hz. Cross-correlation analysis showed that 30% of unit pairs showed significant synchronization, and 61% of these pairs consisted of synchronous oscillations. Cross-correlation analysis assumes that synchronous firing is stationary and maintained throughout the period of stimulation. We tested this assumption by applying unitary events analysis (UEA). We found that UEA was more sensitive to weak and transient synchrony than cross-correlation analysis and detected a higher incidence (49% of cell pairs) of significant synchrony (unitary events). In many unit pairs, the unitary events were optimally characterized at a bin width of 1 ms, indicating that neural synchrony has a high degree of temporal precision. We also found that approximately one half of the unit pairs showed nonstationary changes in synchrony that could not be predicted by the modulation of firing rates. Population statistics showed that the onset of synchrony between LGN cells occurred significantly later than that observed between retinal afferents and LGN cells. The synchrony detected among unit pairs recorded on separate tetrodes tended to be more transient and have a later onset than that observed between adjacent units. These findings show that stimulus-evoked synchronous activity within the LGN is often rhythmic, highly nonstationary, and modulated by endogenous processes that are not tightly correlated with firing rate.

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.].