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As brain recording techniques improve, it may be possible someday to make such recordings without opening the brain, perhaps using sensitive electrodes attached to the scalp. Currently, scalp EEG can measure brain activity to detect an individual letter from a stream of letters, but the approach takes at least 20 seconds to identify a single letter, making communication effortful and difficult, Knight said.

"Noninvasive techniques are just not accurate enough today. Let's hope, for patients, that in the future we could, from just electrodes placed outside on the skull, read activity from deeper regions of the brain with a good signal quality. But we are far from there," Bellier said.

Bellier, Knight and their colleagues reported the results today in the journal PLOS Biology, noting that they have added "another brick in the wall of our understanding of music processing in the human brain."

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The brain machine interfaces used today to help people communicate when they're unable to speak can decode words, but the sentences produced have a robotic quality akin to how the late Stephen Hawking sounded when he used a speech-generating device.

More recently, other researchers have taken Knight's work much further. Eddie Chang, a UC San Francisco neurosurgeon and senior co-author of the 2012 paper, has recorded signals from the motor area of the brain associated with jaw, lip and tongue movements to reconstruct the speech intended by a paralyzed patient, with the words displayed on a computer screen.

That work, reported in 2021, employed artificial intelligence to interpret the brain recordings from a patient trying to vocalize a sentence based on a set of 50 words.

While Chang's technique is proving successful, the new study suggests that recording from the auditory regions of the brain, where all aspects of sound are processed, can capture other aspects of speech that are important in human communication.

For the new study, Bellier reanalyzed brain recordings obtained in 2008 and 2015 as patients were played the approximately 3-minute Pink Floyd song, which is from the 1979 album The Wall. He hoped to go beyond previous studies, which had tested whether decoding models could identify different musical pieces and genres, to actually reconstruct music phrases through regression-based decoding models.

Knight is embarking on new research to understand the brain circuits that allow some people with aphasia due to stroke or brain damage to communicate by singing when they cannot otherwise find the words to express themselves.

Other co-authors of the paper are Helen Wills Neuroscience Institute postdoctoral fellows Anas Llorens and Dborah Marciano, Aysegul Gunduz of the University of Florida and Gerwin Schalk and Peter Brunner of Albany Medical College in New York and Washington University, who captured the brain recordings. The research was funded by the National Institutes of Health and the Brain Initiative, a partnership between federal and private funders with the goal of accelerating the development of innovative neurotechnologies.

Music is a universal human experience. Past research has identified parts of the brain that respond to specific elements of music, such as melody, harmony, and rhythm. Music activates many of the same brain regions that speech does. But how these regions interact to process the complexity of music has been unclear.

An NIH-funded research team, led by Drs. Ludovic Bellier and Robert Knight at the University of California, Berkeley, used computer models to try to reconstruct a piece of music from the brain activity it elicited in listeners. The study appeared in PLoS Biology on August 15, 2023.

Certain patterns of brain activity matched specific musical elements. One pattern consisted of short bursts of activity at a range of frequencies. These corresponded to the onset of lead guitar or synthesizer motifs. Another pattern involved sustained activity at very high frequencies. This occurred when vocals were heard. A third pattern corresponded to the notes of the rhythm guitar. Electrodes detecting each pattern were grouped together within the STG.

To narrow down which brain regions were most important for accurate song reconstruction, the researchers repeated the reconstruction with signals from various electrodes removed. Removing electrodes from the right STG had the greatest impact on reconstruction accuracy. The team also found that music could be accurately reconstructed without the full set of significant electrodes; almost 170 had no effect on accuracy.

These findings could provide the basis for incorporating musical elements into brain-computer interfaces. Such interfaces have been developed to enable people with disabilities that compromise speech to communicate. But the speech generated by these interfaces has an unnatural, robotic quality to it. Incorporating musical elements could lead to more natural-sounding speech synthesis.

Although COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Yet, there is no consensus on the consequences of CNS infections. Here, we used three independent approaches to probe the capacity of SARS-CoV-2 to infect the brain. First, using human brain organoids, we observed clear evidence of infection with accompanying metabolic changes in infected and neighboring neurons. However, no evidence for type I interferon responses was detected. We demonstrate that neuronal infection can be prevented by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Second, using mice overexpressing human ACE2, we demonstrate SARS-CoV-2 neuroinvasion in vivo. Finally, in autopsies from patients who died of COVID-19, we detect SARS-CoV-2 in cortical neurons and note pathological features associated with infection with minimal immune cell infiltrates. These results provide evidence for the neuroinvasive capacity of SARS-CoV-2 and an unexpected consequence of direct infection of neurons by SARS-CoV-2.

If you haven't heard it before, Maggot Brain is a 10 minute song by Funkadelic, which for the most part is just a guitar solo. I fucking love this song and would love some similar recommendations. Guitar>vocals imo

During the COVID-19 pandemic, we have seen that people can adapt quickly to ensure that their social needs are met after being forced to isolate and socially distance. Many individuals turned immediately to music, as evidenced by people singing from balconies, watching live concerts on social media, and group singing online. In this article, we show how these musical adaptations can be understood through the latest advances in the social neuroscience of music-an area that, to date, has been largely overlooked. By streamlining and synthesizing prior theory and research, we introduce a model of the brain that sheds light on the social functions and brain mechanisms that underlie the musical adaptations used for human connection. We highlight the role of oxytocin and the neurocircuitry associated with reward, stress, and the immune system. We show that the social brain networks implicated in music production (in contrast to music listening) overlap with the networks in the brain implicated in the social processes of human cognition-mentalization, empathy, and synchrony-all of which are components of herding; moreover, these components have evolved for social affiliation and connectedness. We conclude that the COVID-19 pandemic could be a starting point for an improved understanding of the relationship between music and the social brain, and we outline goals for future research in the social neuroscience of music. In a time when people across the globe have been unable to meet in person, they have found a way to meet in the music. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Just heard Maggot Brain by Funkadelic for the first time and holy shit, what an amazing song. Any recommendations for similar tracks like this? Doesn't need to be technically complex or even guitar based... just something that I can put on, close my eyes, and dissolve into the universe with!

Although sophisticated insights have been gained into the neurobiology of singing in songbirds, little comparable knowledge exists for humans, the most complex singers in nature. Human song complexity is evidenced by the capacity to generate both richly structured melodies and coordinated multi-part harmonizations. The present study aimed to elucidate this multi-faceted vocal system by using 15O-water positron emission tomography to scan "listen and respond" performances of amateur musicians either singing repetitions of novel melodies, singing harmonizations with novel melodies, or vocalizing monotonically. Overall, major blood flow increases were seen in the primary and secondary auditory cortices, primary motor cortex, frontal operculum, supplementary motor area, insula, posterior cerebellum, and basal ganglia. Melody repetition and harmonization produced highly similar patterns of activation. However, whereas all three tasks activated secondary auditory cortex (posterior Brodmann Area 22), only melody repetition and harmonization activated the planum polare (BA 38). This result implies that BA 38 is responsible for an even higher level of musical processing than BA 22. Finally, all three of these "listen and respond" tasks activated the frontal operculum (Broca's area), a region involved in cognitive/motor sequence production and imitation, thereby implicating it in musical imitation and vocal learning.

Anatomical Abbreviations: A, arcopallium; AAC, central nucleus of the anterior arcopallium; AACd, dorsal part of the central nucleus of the anterior arcopallium; AACv, ventral part of the central nucleus of the anterior arcopallium; ACM, caudal medial arcopallium; AH, anterior hyperpallium; Ai, intermediate arcopallium; AMV, anterior ventral mesopallium; AN, anterior nidopallium; Area X, a vocal nucleus; AR, androgen receptor; Av, nucleus avalanche; B, basorostralis; Cb, cerebellum; CM, caudal mesopallium; CSt, caudal striatum; CMM, caudomedial mesopallium; DLN, dorsal lateral nidopallium; DLM, dorsal lateral nucleus of the thalamus; DM, dorsal medial nucleus of the midbrain; DMm, magnocellular nucleus of the dorsal thalamus; E, entopallium; GP, globus pallidus; H, hyperpallium; Hp, hippocampus; HVC, a vocal nucleus (no abbreviation); HVo, oval nucleus of the ventral hyperstriatum; HVoc, HVo complex; IH, intercalated hyperpallium; IEG, immediate early gene; LAI, lateral intermediate arcopallium; LAN, lateral nucleus of the anterior nidopallium; LAM, lateral nucleus of the anterior mesopallium; LMAN, lateral part of the magnocellular nucleus of the anterior nidopallium; M, mesopallium; MAN, magnocellular nucleus of the anterior nidopallium; MLd, dorsal part of the lateral mesencephalic nucleus; MMSt, magnocellular nucleus of the medial striatum; MO, oval nucleus of the anterior mesopallium; MD, dorsal mesopallium; MV, ventral mesopallium; nXIIts, 12th nucleus, tracheosyringeal part; N, nidopallium; NAo, oval nucleus of the anterior neostriatum; NAO, oval nucleus of the anterior nidopallium; NAoc, NAo complex; NAom, medial division of the oval nucleus of the anterior neostriatum; NAs, supralaminar area of the frontal neostriatum; NCM, caudomedial nidopallium; NDC, caudal dorsal nidopallium; NIDL, dorsal lateral intermediate nidopallium; Nif, interfacial nucleus of the nidopallium; NLc, central nucleus of the anterior neostriatum; NLC, central nucleus of the lateral nidopallium; NLs, supracentral nucleus of the lateral nidopallium; NLv, ventral lateral nidopallium; TeO, optic tectum; Ov, nucleus ovoidalis; PH, posterior hyperpallium; RA, robust nucleus of the arcopallium; Rt, nucleus rotundus; SLN, supra lateral nidopallium; St, striatum; VA, vocal nucleus of the arcopallium; VAM, vocal nucleus of the anterior mesopallium; VAN, vocal nucleus of the anterior nidopallium; VANp, posterior part of the vocal nucleus of the anterior nidopallium; VASt, vocal nucleus of the anterior striatum; VMM, vocal nucleus of the medial mesopallium; VMN, vocal nucleus of the medial nidopallium; VLN, vocal nucleus of the lateral nidopallium 006ab0faaa