In his new book, to be published in September, neuroscientist Francisco Aboitiz links consciousness back to the earliest days of biological life.

Abstract. Feelings of love are among the most significant human phenomena. Love informs the formation and maintenance of pair bonds, parent-offspring attachments, and influences relationships with others and even nature. However, little is known about the neural mechanisms of love beyond romantic and maternal types. Here, we characterize the brain areas involved in love for six different objects: romantic partner, one’s children, friends, strangers, pets, and nature. We used functional magnetic resonance imaging (fMRI) to measure brain activity, while we induced feelings of love using short stories. Our results show that neural activity during a feeling of love depends on its object. Interpersonal love recruited social cognition brain areas in the temporoparietal junction and midline structures significantly more than love for pets or nature. In pet owners, love for pets activated these same regions significantly more than in participants without pets. Love in closer affiliative bonds was associated with significantly stronger and more widespread activation in the brain’s reward system than love for strangers, pets, or nature. We suggest that the experience of love is shaped by both biological and cultural factors, originating from fundamental neurobiological mechanisms of attachment.
Organoid intelligence (OI) is an emerging scientific field aiming to create biocomputers where lab-grown brain organoids serve as ‘biological hardware’
In their article, published in Frontiers in Science, Smirnova et al., outline the multidisciplinary strategy needed to pursue this vision: from next-generation organoid and brain-computer interface technologies, to new machine-learning algorithms and big data infrastructures.
https://www.frontiersin.org/journals/.…
Citation:
Smirnova L, Caffo BS, Gracias DH, Huang Q, Morales Pantoja IE, Tang B, et al. (2023) Organoid intelligence(OI): the new frontier in biocomputing and intelligence-in-a-dish. Front. Sci. 1:1017235. doi: 10.3389/fsci.2023.
Have you ever wonder how SNNs work and their difference from traditional neural networks? Or how SNNs play an important role in computing beyond the Moore’s Law?
What is SNN?
Spiking neural network (SNN) is a new form of neural networks with biologically realistic mechanisms designed to emulate the efficiency and effectiveness of the biological brain.
Note: This post is co-authored with Stacy Li, a PhD student at Berkeley studying aging biology! Highly appreciate all her help in writing, editing, and fact-checking my understanding!
Have you ever wondered what it would be like to upload your mind to a computer? To have a digital copy of your personality, memories, and skills that could live on after your biological death? This is the idea behind whole brain emulation, a hypothetical process of scanning a brain and creating a software version of it that can run on any compatible hardware. In this video, we will explore the science and challenges of whole brain emulation, the ethical and social implications of creating digital minds, and the potential benefits and risks of this technology for humanity. Join us as we dive into the fascinating world of whole-brain emulation!
#wholebrainemulation.
#minduploading.
#digitalimmortality.
#artificialintelligence.
#neuroscience.
#braincomputerinterface.
#substrateindependentminds.
#transhumanism.
#futurism.
#mindcloning
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Can biology be explained entirely in terms of chemistry and then physics? If so, that’s “reductionism.” Or are there “emergent” properties at higher levels of the hierarchy of life that cannot be explained by properties at lower or more basic levels?
Watch more videos on the philosophy of biology: https://shorturl.at/0D92A
Michael Ruse is the Lucyle T. Wekmeister Professor and Director of the History and Philosophy of Science Program at Florida State University.
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