Comparison Between Human and Rodent Neurons for Persistent Activity Performance: A Biologically Plausible Computational Investigation

Zhang, Qian; Zeng, Yi; Zhang, Tielin; Yang, Taoyi

doi:10.3389/fnsys.2021.628839

Cited by 10 publications

(10 citation statements)

References 39 publications

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“…To demonstrate the capability of BrainCog for cognitive function simulation, we provide Drosophila decision-making and prefrontal cortex working memory function simulation [36], [37]. For Drosophila nonlinear and linear decision-making simulation, BrainCog verifies the winner-takes-all behaviors of the nonlinear dopaminergic neuron-GABAergic neuron-mushroom body (DA-GABA-MB) circuit under a dilemma and obtains consistent conclusions with Drosophila biological experiments [36].…”

Section: B Brain Simulation 1) Brain Cognitive Function Simulationmentioning

confidence: 82%

“…For the working memory performance of the prefrontal cortex network implemented by BrainCog, we discover that using human neurons to replace rodent neurons without changing network structure can significantly improve the accuracy and completeness of an image memory task [37], and this implies the evolution of the brains are not only on their structures, but also applies to single computational units such as neurons.…”

Section: B Brain Simulation 1) Brain Cognitive Function Simulationmentioning

confidence: 99%

“…Understanding the detailed differences between the brains of humans and other species on multiple scales will help illuminate what makes us unique as a species [150]. The neocortex is associated with many cognitive functions such as working memory, attention and decision making [151], [152], [153], [154], [65].…”

Section: Pfc Working Memorymentioning

confidence: 99%

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BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation

Zeng¹,

Zhao²,

Fang³

et al. 2022

Preprint

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Spiking neural networks (SNNs) have attracted extensive attentions in Brain-inspired Artificial Intelligence and computational neuroscience. They can be used to simulate biological information processing in the brain from multiple scales, including membrane potential, neuronal firing, synaptic transmission, synaptic plasticity, and multiple brain areas coordination. More importantly, SNNs serve as an appropriate level of abstraction to bring inspirations from brain and cognition to Artificial Intelligence. Existing software frameworks support SNNs in machine learning, brain simulations, and specific hardware devices from certain perspectives respectively. However, the community requires an open-source platform that can support building and integrating computational models for brain-inspired AI and brain simulation at multiple scales. In this paper, we present the Brain-inspired Cognitive Intelligence Engine (BrainCog) for creating brain-inspired AI and brain simulation models. BrainCog incorporates different types of spiking neuron models, learning rules, brain areas, etc., as essential modules provided by the platform. Based on these easy-to-use modules, BrainCog supports various brain-inspired cognitive functions, including Perception and Learning, Decision Making, Knowledge Representation and Reasoning, Motor Control, and Social Cognition. These brain-inspired AI models have been effectively validated on various supervised, unsupervised, and reinforcement learning tasks, and they can be used to enable AI models to be with multiple brain-inspired cognitive functions. For brain simulation, BrainCog realizes the function simulation of Drosophila decision-making and prefrontal cortex working memory, the structure simulation of the Neural Circuit

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Section: B Brain Simulation 1) Brain Cognitive Function Simulationmentioning

confidence: 82%

Section: B Brain Simulation 1) Brain Cognitive Function Simulationmentioning

confidence: 99%

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BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation

Zeng¹,

Zhao²,

Fang³

et al. 2022

Preprint

Self Cite

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“…Another potential hurdle in translating in vitro screening data to the development of therapeutics for human patients is the species of the cellular model used. Human neurons do differ significantly from that of rodents 45 . Therefore, it would be ideal to conduct drug screenings in human neural cells.…”

Section: Introductionmentioning

confidence: 80%

Novel adult cortical neuron processing and screening method illustrates sex- and age-dependent effects of pharmaceutical compounds

Sefiani

Rusyn

Geoffroy

2022

Sci Rep

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Neurodegenerative diseases and neurotraumatic injuries are typically age-associated disorders that can reduce neuron survival, neurite outgrowth, and synaptic plasticity leading to loss of cognitive capacity, executive function, and motor control. In pursuit of reducing the loss of said neurological functions, novel compounds are sought that promote neuron viability, neuritogenesis, and/or synaptic plasticity. Current high content in vitro screenings typically use cells that are iPSC-derived, embryonic, or originate from post-natal tissues; however, most patients suffering from neurodegenerative diseases and neurotrauma are of middle-age and older. The chasm in maturity between the neurons used in drug screens and those in a target population is a barrier for translational success of in vitro results. It has been historically challenging to culture adult neurons let alone conduct screenings; therefore, age-appropriate drug screenings have previously not been plausible. We have modified Miltenyi’s protocol to increase neuronal yield, neuron purity, and neural viability at a reduced cost to expand our capacity to screen compounds directly in primary adult neurons. To our knowledge, we developed the first morphology-based screening system using adult cortical neurons and the first to incorporate age and sex as biological variables in a screen using adult cortical neurons. By using primary adult cortical neurons from mice that were 4 to 48 weeks old for screening pharmaceutical agents, we have demonstrated age- and sex-dependent effects on neuritogenesis and neuron survival in vitro. Utilizing age- and sex-appropriate in vitro models to find novel compounds increasing neuron survival and neurite outgrowth, made possible by our modified adult neuron processing method, will greatly increase the relevance of in vitro screening for finding neuroprotective compounds.

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“…However, threaded throughout these projects there remains a reliance on in vivo models employing rodents, and thus a failure to fully embrace human-centric methodologies. This despite mounting scientific evidence that rodent brains fail to fully recapitulate the complexity or functionality of the human organ [ 28 , 29 ], and even declarations that “… species-specific features emphasize the importance of directly studying the human brain.” [ 30 ].…”

Section: Transitioning Biomedical Research Towards Human-based Non-an...mentioning

confidence: 99%

Phase-In to Phase-Out—Targeted, Inclusive Strategies Are Needed to Enable Full Replacement of Animal Use in the European Union

Marshall

Constantino

Seidle

2022

Animals

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In September 2021, the European Parliament voted overwhelmingly in favour of a resolution to phase out animal use for research, testing, and education, through the adoption of an action plan. Here we explore the opportunity that the action plan could offer in developing a more holistic outlook for fundamental and biomedical research, which accounts for around 70% of all animal use for scientific purposes in the EU. We specifically focus on biomedical research to consider how mapping scientific advances to patient needs, taking into account the ambitious health policies of the EU, would facilitate the development of non-animal strategies to deliver safe and effective medicines, for example. We consider what is needed to help accelerate the move away from animal use, taking account of all stakeholders and setting ambitious but realistic targets for the total replacement of animals. Importantly, we envisage this as a ‘phase-in’ approach, encouraging the use of human-relevant NAMs, enabling their development and application across research (with applications for toxicology testing). We make recommendations for three pillars of activity, inspired by similar efforts for making the shift to renewable energy and reducing carbon emissions, and point out where investment—both financial and personnel—may be needed.

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Comparison Between Human and Rodent Neurons for Persistent Activity Performance: A Biologically Plausible Computational Investigation

Cited by 10 publications

References 39 publications

BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation

BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation

Novel adult cortical neuron processing and screening method illustrates sex- and age-dependent effects of pharmaceutical compounds

Phase-In to Phase-Out—Targeted, Inclusive Strategies Are Needed to Enable Full Replacement of Animal Use in the European Union

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