Effects of Daytime Electric Light Exposure on Human Alertness and Higher Cognitive Functions: A Systematic Review

This paper reports the results of a systematic review conducted on articles examining the effects of daytime electric light exposure on alertness and higher cognitive functions. For this, we selected 59 quantitative research articles from 11 online databases. The review protocol was registered with PROSPERO (CRD42020157603). The results showed that both short-wavelength dominant light exposure and higher intensity white light exposure induced alertness. However, those influences depended on factors like the participants’ homeostatic sleep drive and the time of day the participants received the light exposure. The relationship between light exposure and higher cognitive functions was not as straightforward as the alerting effect. The optimal light property for higher cognitive functions was reported dependent on other factors, such as task complexity and properties of control light. Among the studies with short-wavelength dominant light exposure, ten studies (morning: 3; afternoon: 7) reported beneficial effects on simple task performances (reaction time), and four studies (morning: 3; afternoon: 1) on complex task performances. Four studies with higher intensity white light exposure (morning: 3; afternoon: 1) reported beneficial effects on simple task performance and nine studies (morning: 5; afternoon: 4) on complex task performance. Short-wavelength dominant light exposure with higher light intensity induced a beneficial effect on alertness and simple task performances. However, those effects did not hold for complex task performances. The results indicate the need for further studies to understand the influence of short-wavelength dominant light exposure with higher illuminance on alertness and higher cognitive functions.

Transcutaneous Auricular Vagus Nerve Stimulation Improves Spatial Working Memory in Healthy Young Adults

Working memory (WM) is one of the core components of higher cognitive functions. There exists debate regarding the extent to which current techniques can enhance human WM capacity. Here, we examined the WM modulation effects of a previously less studied technique, transcutaneous auricular vagus nerve stimulation (taVNS). In experiment 1, a within-subject study, we aimed to investigate whether and which stimulation protocols of taVNS can modulate spatial WM performance in healthy adults. Forty-eight participants performed baseline spatial n-back tasks (1, 3-back) and then received online taVNS, offline taVNS, or sham stimulation before or during (online group) the posttest of spatial n-back tasks in random order. Results showed that offline taVNS could significantly increase hits in spatial 3-back task, whereas no effect was found in online taVNS or sham group. No significant taVNS effects were found on correct rejections or reaction time of accurate trials (aRT) in both online and offline protocols. To replicate the results found in experiment 1 and further investigate the generalization effect of offline taVNS, we carried out experiment 2. Sixty participants were recruited and received offline taVNS or offline earlobe stimulation in random order between baseline and posttests of behavioral tests (spatial/digit 3-back tasks). Results replicated the findings; offline taVNS could improve hits but not correct rejections or aRT in spatial WM performance, which were found in experiment 1. However, there were no significant stimulation effects on digit 3-back task. Overall, the findings suggest that offline taVNS has potential on modulating WM performance.

Chapter 9. Spike-Based Symbolic Computations on Bit Strings and Numbers

The brain uses recurrent spiking neural networks for higher cognitive functions such as symbolic computations, in particular, mathematical computations. We review the current state of research on spike-based symbolic computations of this type. In addition, we present new results which show that surprisingly small spiking neural networks can perform symbolic computations on bit sequences and numbers and even learn such computations using a biologically plausible learning rule. The resulting networks operate in a rather low firing rate regime, where they could not simply emulate artificial neural networks by encoding continuous values through firing rates. Thus, we propose here a new paradigm for symbolic computation in neural networks that provides concrete hypotheses about the organization of symbolic computations in the brain. The employed spike-based network models are the basis for drastically more energy-efficient computer hardware – neuromorphic hardware. Hence, our results can be seen as creating a bridge from symbolic artificial intelligence to energy-efficient implementation in spike-based neuromorphic hardware.

Cholinesterase Inhibitors Used for the Management of Alzheimer’s Disease: A Review

Alzheimer’s disease (AD) is defined as a progressive neurodegenerative disorder that has lately become the top reason for dementia in the elderly population (usually above 60-65 years). As mentioned before, most AD cases are sporadic and have a late onset. This disease is characterized by impairment of higher cognitive functions like deficits in memory, language comprehension, coordination, etc. The primary pathophysiology behind Alzheimer’s disease is loss of cholinergic innervation due to the formation of neuritic (senile) amyloid-beta plaques and tau protein-containing neurofibrillary tangles (NFTs) in parts of the brain associated with memory functions. These neurofibrillary tangles (NFTs) and amyloid β plaques can cause the induction of other aetiologies of Alzhedisease-likes like neuroinflammation and central hyperexcitability. The brain's main regions affected by Alzheimer’s disease are the neocortex, the basal nucleus of Meynert, and the hippocampus. These areas are associated with higher cognitive functions like memory, arousal, attention, sensory processing, etc. Thus, cholinesterase inhibitors have been widely used as first-line drug therapy for symptomatic relief in Alzheimer’s disease. They function by inhibiting acetylcholinesterase or catabolizing it and henceforth enhancing synaptic availability of Acetylcholine. The commonly prescribed drugs of this class include donepezil, galantamine, physostigmine, metrifonate, and rivastigmine. This article will discuss the widely used cholinesterase inhibitors (old & new) for managing AD symptoms in detail.

From Action to Cognition: Neural Reuse, Network Theory and the Emergence of Higher Cognitive Functions

The aim of this article is to discuss the logic and assumptions behind the concept of neural reuse, to explore its biological advantages and to discuss the implications for the cognition of a brain that reuses existing circuits and resources. We first address the requirements that must be fulfilled for neural reuse to be a biologically plausible mechanism. Neural reuse theories generally take a developmental approach and model the brain as a dynamic system composed of highly flexible neural networks. They often argue against domain-specificity and for a distributed, embodied representation of knowledge, which sets them apart from modular theories of mental processes. We provide an example of reuse by proposing how a phylogenetically more modern mental capacity (mental rotation) may appear through the reuse and recombination of existing resources from an older capacity (motor planning). We conclude by putting arguments into context regarding functional modularity, embodied representation, and the current ontology of mental processes.

Education shapes the structure of semantic memory and impacts creative thinking

Education is central to the acquisition of knowledge, such as when children learn new concepts. It is unknown, however, whether educational differences impact not only what concepts children learn, but how those concepts come to be represented in semantic memory—a system that supports higher cognitive functions, such as creative thinking. Here we leverage computational network science tools to study hidden knowledge structures of 67 Swiss schoolchildren from two distinct educational backgrounds—Montessori and traditional, matched on socioeconomic factors and nonverbal intelligence—to examine how educational experience shape semantic memory and creative thinking. We find that children experiencing Montessori education show a more flexible semantic network structure (high connectivity/short paths between concepts, less modularity) alongside higher scores on creative thinking tests. The findings indicate that education impacts how children represent concepts in semantic memory and suggest that different educational experiences can affect higher cognitive functions, including creative thinking.

Bridging the Gap Between Neurons and Cognition Through Assemblies of Neurons

During recent decades, our understanding of the brain has advanced dramatically at both the cellular and molecular levels and at the cognitive neurofunctional level; however, a huge gap remains between the microlevel of physiology and the macrolevel of cognition. We propose that computational models based on assemblies of neurons can serve as a blueprint for bridging these two scales. We discuss recently developed computational models of assemblies that have been demonstrated to mediate higher cognitive functions such as the processing of simple sentences, to be realistically realizable by neural activity, and to possess general computational power.

Non‐invasive real‐time access to spatial attention information from 3T fMRI BOLD signals

Access to higher cognitive functions in real-time remains very challenging, because these functions are internally driven and their assessment is based onto indirect measures. In addition, recent finding show that these functions are highly dynamic. Previous studies using intra-cortical recordings in monkeys, succeed to access the (x,y) position of covert spatial attention, in real-time, using classification methods applied to monkey prefrontal multi-unit activity and local field potentials. In contrast, the direct access to attention with non-invasive methods is limited to predicting the attention localisation based on a quadrant classification. Here, we demonstrate the feasibility to track covert spatial attention localization using non-invasive fMRI BOLD signals, with an unprecedented spatial resolution. We further show that the errors produced by the decoder are not randomly distributed but concentrate on the locations neighbouring the cued location and that behavioral errors correlate with weaker decoding performance. Last, we also show that the voxels contributing to the decoder precisely match the visual retinotopic organization of the occipital cortex and that single trial access to attention is limited by the intrinsic dynamics of spatial attention. Taken together, these results open the way to the development of remediation and enhancement neurofeedback protocols targeting the attentional function.

Intrinsic bursts facilitate learning of Lévy flight movements in recurrent neural network models

Isolated spikes and bursts of spikes are thought to provide the two major modes of information coding by neurons. Bursts are known to be crucial for fundamental processes between neuron pairs, such as neuronal communications and synaptic plasticity. Deficits in neuronal bursting can also impair higher cognitive functions and cause mental disorders. Despite these findings on the roles of bursts, whether and how bursts have an advantage over isolated spikes in the network-level computation remains elusive. Here, we demonstrate in a computational model that not isolated spikes but intrinsic bursts can greatly facilitate learning of Lévy flight random walk trajectories by synchronizing burst onsets across neural population. Lévy flight is a hallmark of optimal search strategies and appears in cognitive behaviors such as saccadic eye movements and memory retrieval. Our results suggest that bursting is a crucial component of sequence learning by recurrent neural networks in the brain.

The Epigenome in Neurodevelopmental Disorders

Neurodevelopmental diseases (NDDs), such as autism spectrum disorders, epilepsy, and schizophrenia, are characterized by diverse facets of neurological and psychiatric symptoms, differing in etiology, onset and severity. Such symptoms include mental delay, cognitive and language impairments, or restrictions to adaptive and social behavior. Nevertheless, all have in common that critical milestones of brain development are disrupted, leading to functional deficits of the central nervous system and clinical manifestation in child- or adulthood. To approach how the different development-associated neuropathologies can occur and which risk factors or critical processes are involved in provoking higher susceptibility for such diseases, a detailed understanding of the mechanisms underlying proper brain formation is required. NDDs rely on deficits in neuronal identity, proportion or function, whereby a defective development of the cerebral cortex, the seat of higher cognitive functions, is implicated in numerous disorders. Such deficits can be provoked by genetic and environmental factors during corticogenesis. Thereby, epigenetic mechanisms can act as an interface between external stimuli and the genome, since they are known to be responsive to external stimuli also in cortical neurons. In line with that, DNA methylation, histone modifications/variants, ATP-dependent chromatin remodeling, as well as regulatory non-coding RNAs regulate diverse aspects of neuronal development, and alterations in epigenomic marks have been associated with NDDs of varying phenotypes. Here, we provide an overview of essential steps of mammalian corticogenesis, and discuss the role of epigenetic mechanisms assumed to contribute to pathophysiological aspects of NDDs, when being disrupted.