Quasicriticality explains variability of human neural dynamics across life span.

Aging impacts the brain's structural and functional organization and over time leads to various disorders, such as Alzheimer's disease and cognitive impairment. The process also impacts sensory function, bringing about a general slowing in various perceptual and cognitive functions. Here, we analyze the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) resting-state magnetoencephalography (MEG) dataset-the largest aging cohort available-in light of the quasicriticality framework, a novel organizing principle for brain functionality which relates information processing and scaling properties of brain activity to brain connectivity and stimulus. Examination of the data using this framework reveals interesting correlations with age and gender of test subjects. Using simulated data as verification, our results suggest a link between changes to brain connectivity due to aging and increased dynamical fluctuations of neuronal firing rates. Our findings suggest a platform to develop biomarkers of neurological health.

A computational examination of the two-streams hypothesis: which pathway needs a longer memory?

The two visual streams hypothesis is a robust example of neural functional specialization that has inspired countless studies over the past four decades. According to one prominent version of the theory, the fundamental goal of the dorsal visual pathway is the transformation of retinal information for visually-guided motor behavior. To that end, the dorsal stream processes input using absolute (or veridical) metrics only when the movement is initiated, necessitating very little, or no, memory. Conversely, because the ventral visual pathway does not involve motor behavior (its output does not influence the real world), the ventral stream processes input using relative (or illusory) metrics and can accumulate or integrate sensory evidence over long time constants, which provides a substantial capacity for memory. In this study, we tested these relations between functional specialization, processing metrics, and memory by training identical recurrent neural networks to perform either a viewpoint-invariant object classification task or an orientation/size determination task. The former task relies on relative metrics, benefits from accumulating sensory evidence, and is usually attributed to the ventral stream. The latter task relies on absolute metrics, can be computed accurately in the moment, and is usually attributed to the dorsal stream. To quantify the amount of memory required for each task, we chose two types of neural network models. Using a long-short-term memory (LSTM) recurrent network, we found that viewpoint-invariant object categorization (object task) required a longer memory than orientation/size determination (orientation task). Additionally, to dissect this memory effect, we considered factors that contributed to longer memory in object tasks. First, we used two different sets of objects, one with self-occlusion of features and one without. Second, we defined object classes either strictly by visual feature similarity or (more liberally) by semantic label. The models required greater memory when features were self-occluded and when object classes were defined by visual feature similarity, showing that self-occlusion and visual similarity among object task samples are contributing to having a long memory. The same set of tasks modeled using modified leaky-integrator echo state recurrent networks (LiESN), however, did not replicate the results, except under some conditions. This may be because LiESNs cannot perform fine-grained memory adjustments due to their network-wide memory coefficient and fixed recurrent weights. In sum, the LSTM simulations suggest that longer memory is advantageous for performing viewpoint-invariant object classification (a putative ventral stream function) because it allows for interpolation of features across viewpoints. The results further suggest that orientation/size determination (a putative dorsal stream function) does not benefit from longer memory. These findings are consistent with the two visual streams theory of functional specialization. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11571-021-09703-z.

Microtubule Disruption Without Learning Impairment in the Unicellular Organism, Paramecium: Implications for Information Processing in Microtubules.

Introduction: Information processing in microtubules is an open question that has not been adequately addressed. It was suggested that microtubules could store and process information in the nervous system or even support consciousness. The unicellular organism, Paramecium caudatum, has a microtubular structure but lacks a neuron or neural network. However, it shows intelligent behaviors such as associative learning. This property may suggest that the microtubules are involved in intelligent behavior, information storage, or information processing in this organism. Methods: To test this hypothesis and study the role of microtubules in P. caudatum learning, we utilized a learning task in which the organism associates brightness in its swimming medium with attractive cathodal shocks. To see if microtubules are an integral part of information storage and processing in P. caudatum, we disrupted the microtubular dynamics in the organism using an antimicrotubular agent (parbendazole). Results: We observed that while a partial allosteric modulator of GABA (midazolam) could disrupt the learning process in P. caudatum, the antimicrotubular agent could not interfere with the learning. Conclusion: Microtubules are probably not vital for the learning behavior in P. caudatum. Consequently, our results call for further investigation of the microtubular information processing hypothesis. Highlights: Importance of Information processing in microtubules;Microtubules could store and process information in the nervous system;Unicellular organism, Paramecium caudatum, has a microtubular structure but lacks a neuron or neural network. Plain Language Summary: Information processing in microtubules is an open question that has not been adequately addressed. It was suggested that microtubules could store and process information in the nervous system or even support consciousness. The unicellular organism, Paramecium caudatum, has a microtubular structure but lacks a neuron or neural network. However, it shows intelligent behaviors such as associative learning. This property may suggest that the microtubules are involved in intelligent behavior, information storage, or information processing in this organism. To test this hypothesis and study the role of microtubules in P. caudatum learning, we utilized a learning task in which the organism associates brightness in its swimming medium with attractive cathodal shocks. To see if microtubules are an integral part of information storage and processing in P. caudatum, we disrupted the microtubular dynamics in the organism using an antimicrotubular agent (parbendazole). We observed that while a partial allosteric modulator of GABA (midazolam) could disrupt the learning process in P. caudatum, the antimicrotubular agent could not interfere with the learning. Microtubules are probably not vital for the learning behavior in P. caudatum. Consequently, our results call for further investigation of the microtubular information processing hypothesis.

Studies on the Bottom-Up and Top-Down Neural Information Flow Alterations in Neurodegeneration.

BACKGROUND: A proper explanation for perceptual symptoms in neurodegenerative disorders including Alzheimer's disease and Parkinson's disease (PD) is still lacking. OBJECTIVE: This study aimed at investigating the imbalance between 'bottom-up' and 'top-down' information flow (IF) and processing in PD in relation with visual hallucination symptoms. METHODS: Here, we looked at bottom-up and top-down IF markers using resting state electroencephalographic (EEG) data from PD patients analyzed through three different IF measures (direct Directed Transfer Function (dDTF), full frequency Directed Transfer Function (ff-DTF), and renormalized Partial Directed Coherence (rPDC). RESULTS: We observed an increased gamma band IF and a reduced beta band IF in PD patients compared to healthy controls. Additionally, we noticed a reduced theta band IF in PD patients using dDTF as a measure of IF. By source localizing the EEG activity of the PD patients and healthy controls, we looked at the alterations of IF in the prefrontal cortex of PD patients as well. CONCLUSION: In line with previous studies, our results suggest that the delicate balance between bottom-up and top-down IF is disrupted in Parkinson's disease potentially contributing to the cognitive symptoms of PD patients.

QEEG-based neural correlates of decision making in a well-trained eight year-old chess player.

The neurocognitive substrates of decision making (DM) in the context of chess has appealed to researchers' interest for decades. Expert and beginner chess players are hypothesized to employ different brain functional networks when involved in episodes of critical DM upon chess. Cognitive capacities including, but not restricted to pattern recognition, visuospatial search, reasoning, planning and DM are perhaps the key determinants of rewarding and judgmental decisions in chess. Meanwhile, the precise neural correlates of DM in this context has largely remained elusive. The quantitative electroencephalography (QEEG) is an investigation tool possessing a proper temporal resolution in the study of neural correlates of cognitive tasks at cortical level. Here, we used a 22-channel EEG setup and digital polygraphy in a well-trained 8 year-old boy while engaged in playing chess against the computer. Quantitative analyses were done to map and source-localize the EEG signals. Our analyses indicated a lower power spectral density (PSD) for higher frequency bands in the right hemisphere upon DM-related epochs. Moreover, the information flow upon DM blocks in this particular case was more of posterior towards anterior brain regions.

Neural communication through theta-gamma cross-frequency coupling in a bistable motion perception task.

Functional significance of the neural oscillations has been debated since long. In particular, oscillations have been suggested to play a major role in formation of communication channels between brain regions. It has been previously suggested that gamma coherence increases during communication between hemispheres when subjects perceive a horizontal motion in Stroboscopic Alternative Motion (SAM) stimulus. In addition, disruption of this coherence may change the horizontal perception of SAM. In this study, we investigated the changes of Cross-Frequency Coupling (CFC) in EEG signals from parietal and occipital cortices during horizontal and vertical perception of SAM. Our results suggested that while the strength of CFC in parietal electrodes showed no significant change, CFC in P3-P4 electrode-pair demonstrated a significant correlation during horizontal perception of SAM. Therefore, the CFC between theta- and gamma-band oscillations seems to be correlated with changes in functional interactions between brain regions. Accordingly, we propose that in addition to gamma coherence, CFC is perhaps another neurophysiological mechanism involved in neural communication.

Development of a Brain Computer Interface (BCI) Speller System Based on SSVEP Signals.

BCI is one of the most intriguing technologies among other HCI systems, mostly because of its capability of recording brain activities. Spelling BCIs, which help paralyzed people to maintain communication, are one of the striking topics in the field of BCI. In this scientific a spelling BCI system with high transfer rate and accuracy that uses SSVEP signals is proposed. In addition, we suggested that LED light sources can provide proper signals for speller BCIs and they can be used in future.