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Category: neuroscience – Page 286

Six types of loves differentially recruit reward and social cognition brain areas

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.

New MIT study finds neurons process language at varied timescales

This research uncovers diverse neural roles in processing words and complex sentences.

MIT neuroscientists have identified several brain regions responsible for processing language using functional magnetic resonance imaging (fMRI).

However, discovering the specific functions of neurons in those regions has proven difficult because fMRI, which measures changes in blood flow, doesn’t have a high resolution to reveal what small populations of neurons are doing.

Now, using a more precise technique that involves recording electrical activity directly from the brain, MIT neuroscientists have identified different clusters of neurons that appear to process different amounts of linguistic context.

Thought-to-text chip smaller than Neuralink achieves 91% accuracy

The brain-machine interface race is on. While Elon Musk’s Neuralink has garnered most of the headlines in this field, a new small and thin chip out of Switzerland makes it look downright clunky by comparison. It also works impressively well.

The chip has been developed by researchers at the Ecole Polytechnique Federale de Lausanne (EPFL) and represents a leap forward in the sizzling space of brain-machine-interfaces (BMIs) – devices that are able to read activity in the brain and translate it into real-world output such as text on a screen. That’s because this particular device – known as a miniaturized brain-machine interface (MiBMI) – is extremely small, consisting of two thin chips measuring just 8 mm2 total. By comparison, Elon Musk’s Neuralink device clocks in at comparatively gargantuan size of about 23 × 8 mm (about 0.3 x .9 in).

Additionally, the EPFL chipset uses very little power, is reported to be minimally invasive, and consists of a fully integrated system that processes data in real time. That’s different from Neuralink, which requires the insertion of 64 electrodes into the brain and carries out its processing via an app located on a device outside of the brain.

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

The brain undergoes dynamic functional changes with age1,2,3.

Analyses of neuroimaging datasets from 5,306 participants across 15 countries found generally larger brain-age gaps in Latin American compared with non-Latin American populations, which were influenced by disparities in socioeconomic and health-related factors.

Non-cognitive skills: DNA-based analyses suggest a hidden key to academic success

A new Nature Human Behaviour study, jointly led by Dr. Margherita Malanchini at Queen Mary University of London and Dr. Andrea Allegrini at University College London, has revealed that non-cognitive skills, such as motivation and self-regulation, are as important as intelligence in determining academic success. These skills become increasingly influential throughout a child’s education, with genetic factors playing a significant role.

The research, conducted in collaboration with an international team of experts, suggests that fostering non-cognitive skills alongside could significantly improve educational outcomes.

“Our research challenges the long-held assumption that intelligence is the primary driver of ,” says Dr. Malanchini, Senior Lecturer in Psychology at Queen Mary University of London.

An entire brain-machine interface on a chip

Brain-machine interfaces (BMIs) have emerged as a promising solution for restoring communication and control to individuals with severe motor impairments. Traditionally, these systems have been bulky, power-intensive, and limited in their practical applications. Researchers at EPFL have developed the first high-performance, Miniaturized Brain-Machine Interface (MiBMI), offering an extremely small, low-power, highly accurate, and versatile solution.

Published in the latest issue of the IEEE Journal of Solid-State Circuits (“MiBMI: A 192/512-Channel 2.46mm 2 Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes”) and presented at the International Solid-State Circuits Conference, the MiBMI not only enhances the efficiency and scalability of brain-machine interfaces but also paves the way for practical, fully implantable devices. This technology holds the potential to significantly improve the quality of life for patients with conditions such as amyotrophic lateral sclerosis (ALS) and spinal cord injuries.

An image of the chip. (Image: EPFL)

Self-deployable, biodegradable electrode offers minimally invasive brain signal monitoring

Sensors that can be easily and safely introduced in the brain could have important medical applications and could also contribute to the development of brain-interfacing devices. While significant progress has been made toward the development of these sensors, most existing devices can only be deployed via invasive surgical procedures that can have numerous complications.

Researchers at Seoul National University and other institutes in South Korea recently created a new biodegradable and self-deployable tent that could be far easier to insert onto the surface of the human brain. Their proposed electrode design, outlined in Nature Electronics, could naturally degrade inside the human body without leaving any residues, which means that once it is inserted in the body it does not need to be surgically removed.

“Our recent paper was born out of a growing awareness of the clinical challenges linked to the implantation of electrodes via invasive brain surgery,” Seung-Kyun Kang, corresponding author of the paper, told Medical Xpress.

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