BCI using RNN and ECoG devises to Produce Sounds Related to the Computational Simulation of the Human Auditory Pathway in Understanding Phonetic Acquisition

The auditory system is a complex and fragile network of structures working together to perceive, process, and encode sound. Deciphering different phonetic sounds and classifying those units has been an effort many researchers have worked on. However, Dr. Dematties in the research article “Phonetic acquisition in cortical dynamics, a computational approach” examines how linguistic units like phonemes are encoded and classified to form complex acoustic streams in speech data. Additionally, infants can differentiate sounds of words from a complex audio stream through recognizing patterns in speech. The research is accomplished through creating 500 words with different sounds and lengths, CSTM, which stimulates cortical tissues to mimic the respected sounds. They use multiple processes that stimulate the growth of the distal dendritic branch synapsis, thus, allowing for synapses to only be created on pyramidal cells and biases the process of activation in each respective neuron. This approach allows the researcher to control variations in levels of reverberation, noise, and pitch. Furthermore, multiple algorithms are used to activate auditory neurons in order to create the correct phonemes, words, and sounds that can be encoded. The research concludes that through the use of computational simulation, the neurophysiological and neuroanatomical data of the human auditory pathway is able to mimic incidental phonetic acquisition observed in human infants, which is a key mechanism involved during early language learning. The authors propose that these algorithms can be used in creating more efficient and complex AI speech generators and programs that recognize or translate speech. 

Through the utilization of new technology and AI algorithms such as the ones Dematties produced, Neurologist can create brain-computer interfaces (BCI) for mute people that translate neurological and cortical language signals into electro-stimulation produced synthetic speech. Dematties work could accompany this research to achieve the same results in deaf patients as well. To achieve this, Anumanchipalli et al used an approach that used a two-stage decoding approach. Neural signals are translated into representations of movements of vocal-tract articulators into spoken sentences through the use of recurrent neural networks (RNN) and an electrocorticography (ECoG) device. Using a two-stage approach resulted in less acoustic distortion than using direct decoding of acoustic features. The authors argue that “If massive data sets spanning a wide variety of speech conditions were available, direct synthesis would probably match or outperform a two-stage decoding approach” (Pandarinath et al. 2019). Due to the creation of these algorithms by Dematties, direct synthesis is a greater possibility with the utilization of AI in speech and auditory processing. 

Furthermore, due to the development of BCIs, through the use of AI and computational analytical algorithms, new forms of utilization of this technology have been considered for the control of arm and hand movements and in humans with paralysis. Trials have successfully demonstrated that the rapid communication, control of robotic arms, and restoration of sensation and movement of paralyzed limbs in humans using these BCIs is possible.

References

Dematties D, Rizzi S, Thiruvathukal GK, Wainselboim A, Zanutto BS (2019) Phonetic acquisition in cortical dynamics, a computational approach. PLoS ONE 14(6): e02117966. https://doi.org/10.1371/journal.pone.0217966 

Anumanchipalli, G.K., Chartier, J. & Chang, E.F. “Speech synthesis from neural decoding of spoken sentences”. Nature 568, 493–498 (2019). https://doi.org/10.1038/s41586-019-1119-1 

The Connection Between Dreaming and Wellness

 The Connection Between Dreaming and Wellness

Katie Jabaay

Dreaming is a truly elusive phenomenon. The reason why humans dream, how dreaming occurs, how humans can control dreams, and dreams’ connection to health are all being currently researched because the answers to these questions are unclear. Two articles, “People with migraines get less REM sleep, study finds” and “Antidepressant side effects: can antidepressants cause vivid, unusual dreams?” discuss the connections of REM sleep and the physical and mental sides of one’s wellness. These reviews are comparable to the research done by Kokony et. al, which discusses the beginnings of communication in dreams through the research paper “Real-time dialogue between experimenters and dreamers during REM sleep.”

Rogers’ article, “People with migraines get less REM sleep, study finds,” discusses a metaanalysis by Emily Charlotte Stanyer. The paper, “Subjective Sleep Quality and Sleep Architecture in Patients With Migraine,” studies sleep and migraines, and the article provides insight to the research’s takeaways and meaning for people who suffer from migraines. The study found that migraine sufferers have lower quality of sleep according to the Pittsburgh Sleep Quality Index, and polysomnography found that they had a higher amount of waking time during the night as well as less REM sleep per night. Children who had migraines had the unique trait that they fell asleep faster than average children, however, it is speculated that they are falling asleep faster due to chronic sleep deprivation. The most profound connections of migraines and REM sleep are that less REM sleep predicts a rise in migraines and migraine symptoms the following day. The causal relationship is not known, meaning that research is unclear if the lack of REM contributes to migraines or if the opposite is true, but this is still a meaningful connection for further treatment and exploration. 

The other aspect of wellness, mental health, can also be tied to REM sleep. In Geall’s article, “Antidepressant side effects: can antidepressants cause vivid, unusual dreams?” she discusses a seemingly neglected side effect of antidepressants: vivid dreams. The article focuses mainly on women’s experiences with this side effect and the effect it can have on one’s emotional health. The vivid dreams can range from enjoyable, to confusing, to anxiety-inducing, or to terrifying. A theory for these dreams is the combination of the effects of mental illness combined with the drugs’ effect on the REM cycle. Mental illnesses have symptoms of disrupted sleep and heightened nightmares, while antidepressants decrease the time spent in REM and increase neurotransmitters, potentially creating less dreaming time for a more active brain. Overall, these realistic dreams can confuse individuals, make them feel out of touch with reality, and heighten day-to-day anxiety in the mentally ill patients taking these medications, potentially worsening their mental state. 

Both of these articles lend to the fact that sleep, and dreaming sleep in particular, relate to one’s overall wellness. Lack of REM sleep can contribute to one’s migraines, whereas those on antidepressants have more vivid dreams during a shortened REM period. Both of these illnesses can be tied to REM, being the period that most dreaming happens in, in rather similar ways, as abnormal and shortened REM sleep can worsen the quality of one's life. Perhaps a solution to these illnesses is using a person’s lucid dreams. The article “Real-time dialogue between experimenters and dreamers during REM sleep,” written by Konkoly, Chabani, Dresler, Appel, Oudiette, and Paller, discusses a breakthrough in sleep-research where there was two-way communication between sleeping participants and researchers. The experimenters asked the lucid dreaming participants simple questions by saying them out loud, flashing green lights in morse code, or finger tapping, and tracked the participants via polysomnographic methods. All methods of asking questions produced examples of positive results since the participants were able to answer correctly a high percentage of time through either coordinated eye movements or facial twitching. 

One of the many implications of this research is that communication during dreaming could produce “novel approaches to promote health and well-being could be explored…  perhaps opening up new ways to address fundamental questions about consciousness” (Konkoly). If the practice develops past asking yes or no and numerical questions towards complex conversations, the possibilities for treatments of migraines and depression could expand tenfold. The patients would have to be naturally inclined to lucid dreaming and/or trained to do so, but therapy sessions and interviews on pain level and dream content could provide vital information to both ailments. Therapy sessions during REM sleep could teach patients with mental illnesses coping mechanisms to use during nightmares and confusing dreams rather than after. Interviews can be used for migraine patients in order to assess pain levels during sleep, the content, and perceived duration of dreams. This data is currently difficult or even impossible to access, so the idea of in-dream communication is extremely meaningful.

                                                   Bibliography

Geall, Lauren. “What's with All the Wild Dreams on Antidepressants?” Stylist, The Stylist Group, 3 May 2021, https://www.stylist.co.uk/health/mental-health/antidepressants-side-effects-dreams/514151.

 

Konkoly, Karen R., et al. “Real-Time Dialogue between Experimenters and Dreamers during Rem Sleep.” Current Biology, vol. 31, no. 7, 2021, https://doi.org/10.1016/j.cub.2021.01.026. 

Rogers, Kristen. “People with Migraines Get Less REM Sleep, Study Finds.” CNN, Cable News Network, 23 Sept. 2021, https://www.cnn.com/2021/09/22/health/migraine-headache-effects-sleep-study-wellness/index.html. 

Stanyer, Emily Charlotte, et al. “Subjective Sleep Quality and Sleep Architecture in Patients with Migraine: A Meta-Analysis.” Neurology, 2021, https://doi.org/10.1212/wnl.0000000000012701. 

Decision Making in Learned Associations and in Climate Change

The human brain’s ability to actively make decisions and infer possible outcomes based on prior experience or insight is a highly complex process that is still largely unknown. Additionally, researching how and what neural circuits are flexibly used in learned associations is a complex process. In the article “Neural circuits for inference-based decision-making”, Wang and Kahnt attempt to understand how humans rely on past experiences to predict future outcomes in novel context. Through the use of FMRI and ECG, Wang and Kahnt found that the OFC and HC neurons are largely responsible for the learned associations and inferences such as lab 13 explained, “The ability to flexibly utilize prior knowledge and experiences to mentally simulate probable outcomes is critical for making adaptive decisions” (et al. Wang, 2021). Throughout homosapien evolution decision and inference creation has been paramount in the survival and complex building of civilization. However, many decisions can become swayed or perverted through other neural processes that are more pleasurable or less complex such as positive and negative arousal. 

Climate change has become forefront in the world stage as a continuing and exponentially worsening issue. The decisions of world leaders and mega corporations to fix the man-made issues contributing to climate change have been researched in order to understand the neurological methods behind decision making processes of people. In the paper “Environmental neuroeconomics: how neuroscience can inform our understanding of human responses to climate change”, Sawe and Chawla examine how the study of neuroecconomics examines the factors that lead to environmental based decisions. Similarly to Wang and Kahnt, Sawe and Chawla examined literature that used fMRI and ECG to understand the mechanisms underlying individual and collective decision-making around climate change.

To best examine which brain areas are more active in positive climate change action, brain imagining has shown that positive arousal is correlated with activity in the ventral striatum, the reward pathway, because of the higher level region nucleus accumbens’ primary and secondary responses. However, the anterior insula’s activity correlates with negative arousal, such as loss, risks, physiologically and morally aversive situations. People’s responses, which lead to subjective valuation and assessment of benefit-cost tradeoffs, in the aforementioned areas are integrated in the medial prefrontal cortex. A concrete example shows that the “FMRI study of donations to protect state and national park lands from developmental land use threats shows environmental donation decisions are associated with anterior insula activity, and that this activity is amplified in those with stronger pro-environmental attitudes” (et al. Sawe and Chawla, 2021). There are other factors that contribute to the decision making process of climate change such as uncertainty associated with outcomes and impacts of climate change action. Furthermore, the psychology of what people cannot see directly in front of them does not immediately affect them plays a crucial role in the lack of action. Climate change is still viewed as something in the future which leads to indecision due to a lack of urgency to act on climate change. Future time perception and decisive future impact is subject to priming and is thus, malleable, which proves that advocating and educating populations about ways to fix climate change can work. Finally, social behavior effects the brains ability to make decisions due to wanting to “fit in” with societies norms. This behavior further creates a lack of indecision in communities about climate change.  

The direct observation and testing of brain regions to determine how the brain makes learned associations to predict future outcomes and make decisions, in addition to, observing what brain regions are active during positive and negative decision making allow researchers to understand and predict future human-based decisions and societal outcomes. Using this data, researchers can better inform educators and advocates about what works to change or affect people’s decisions and behaviors about climate change.

References

Wang, Fang, Kahnt, Thorsten. (2021, 02, 004). Neural circuits for inference-based decision-making. Science Direct, Elsevier. https://doi.org/10.1016/j.cobeha.2021.02.004 

Sawe, Niki, Chawla, Kiran. (2021, December). Environmental neuroeconomics: how neuroscience can inform our understanding of human responses to climate change. Science Direct, Elsevier. https://doi.org/10.1016/j.cobeha.2021.08.002 

Orbitofrontal cortex use in inference based decision making and object reversal learning

     The Orbitofrontal Cortex (OFC) has been known to control impulsive behaviors as well as adjusting behaviors to have socially desirable responses. There is rapid study being done on the OFC to this date and many papers have been written to show the impact that it has with the decision making as well as learning. Research has also been showing how these 2 factors are directly impacted when their is damage done to the OFC. Thorsten Kahnt et. al studied how much the OFC, hippocampus (HC), and the Amygdala are being used in inference based decision making as well as association decision making. Rudebeck et. al studied how OFC lesions and Amygdala lesions impact object reversal learning in monkeys. 

    Kahnt et. al focused on association based decision making in humans and rats in this study. First, Kahnt conducted a study on humans and how they learn associations between different visual cues (Cue A -> Cue B, Cue C -> Cue D) then learned that one cue (Cue B) led to a reward and another cue (Cue D) did not lead to reward. After these 2 conditioning phases, they were asked in a probe test whether cue A or cue C would lead to a reward. These tasks where done under an fMRI to find where in the brain the most activity is occurring during these tasks. The data concluded that the OFC and HC were used the most together when both the conditioning tasks were being done and shown that these 2 regions of the brain are important to decision making in a human brain. The study then shifted to non-human primate subjects (rats) where a very similar study was done. These rodents and non-human primate subject learned that 2 objects led to 2 different rewards. The rewards consisted of 2 different foods, peanuts and M&Ms. The study showed that they were more likely to not choose the same object twice due to them learning that both objects led to two different rewards. They also found that OFC and the Amygdala were both used together to help learn what rewards came out of the objects. 

    Rudebeck et. al focused on how OFC lesions and Amygdala lesions effected object reversal learning in monkeys. In each trial, 2 objects where over food wells and the monkeys then had to displace one object and depending on the object that was displaced, a reward would be awarded. The reward object would not be changed in all of the trials and this led on for 30 trials. The study found that the monkeys who had OFC lesions where seen to have worse results than monkeys with Amygdala lesions or no lesions at all. The monkeys with Amygdala lesions were seen to have no impact compared to the no lesions group of monkeys. This shows that the OFC is crucial in learning tasks as well as association learning tasks and damage to the OFC can hinder learning. 

    These two research studies have shown that the Orbitofrontal cortex is important to both learning tasks as well as association tasks which include decision making and object reversal learning. Both of these studies have shown how much more the orbitofrontal cortex can truly do besides just impulsive behaviors and inducing socially desirable behaviors. 

References:

Rudebeck PH, Murray EA. Amygdala and orbitofrontal cortex lesions differentially influence choices during object reversal learning. J Neurosci. 2008;28(33):8338-8343. doi:10.1523/JNEUROSCI.2272-08.2008

Fang Wang, Thorsten Kahnt, Neural circuits for inference-based decision-making, Current Opinion in Behavioral Sciences, Volume 41,2021, Pages 10-14, ISSN 2352-1546, https://doi.org/10.1016/j.cobeha.2021.02.004.

Your Nose May Be the Key to Your Past

The nose is a sensory organ that is necessary for one of the most, if not the most important senses in human beings and other animals. Without the sense of smell, our world and how we perceive it would be a whole lot different. Smell, also known as olfaction, is crucial for determining not only the food that we eat but also detecting if there is danger nearby, such as a fire. Smell is the only sense that is fully developed in a human fetus before birth. After being born, a child mainly detects and retains many smells they are exposed to and when the child grows up and is exposed to a familiar odor, detailed memories connected to that odor come flooding back. This familiar experience, which is no stranger to many people, is called the Proust effect, and has pushed researchers to delve deeper and to better understand the relationship between smell and memory.

Many researchers are trying to better understand the neuroscience behind how smell can impact memory, and one of those researchers is Laura K. Shanahan. In Shanahan’s lab, she and her colleagues focus on the influence of olfaction on memory consolidation in the brain of a sleeping human. As described in Shanahan’s paper, “Scents and Reminiscence: Olfactory influences on Memory Consolidation in the Sleeping Human Brain”, to better understand the relationship between odor and memory, Shanahan’s lab performs an experiment. Initially, participants are presented with an encoding task, such as matching a specific card with an odor to a location. After the completion of the encoding task the participants are told to go to sleep. The sleep is monitored in an MRI machine and when participants are observed to be in slow-wave sleep, the researchers present the participants with the odors that were involved in the encoding task. Upon waking up, participants were asked tested on the task they had done before sleeping which required them to memorize the card and location to the best of their ability. The results from this experiment showed that the subjects performed a lot better in the memory post-test when they were exposed to the odor stimuli during slow-wave sleep when compared to the results of the memory post-test of subjects who were not exposed to the odor stimuli during slow-wave sleep. The researchers also tried introducing the odor stimuli during other stages of sleep to determine if it had the same result, but they concluded that the memory-enhancing effect only occurred when the stimuli was introduced in slow-wave sleep. Shanahan’s findings have suggested that odors can greatly influence memory consolidation and that the results that came from experiment with sleeping human brain show how strong of a relationship olfaction has with the hippocampus.

In an article titled, “Why smells bring back such vivid memories”, Ana Sandoiu writes about the phenomenon that occurs when a familiar odor is detected and how research regarding the relationship between olfaction and memory can help better understand Alzheimer’s disease. In the article, Sandoiu begins by talking about a famous French author by the name of Marcel Proust who wrote pages of memories that was triggered by the smell of Madeleines. The writings of Proust help describe how odors can be connected to very detailed long-term memories. The Proust effect, which is described as the recall of episodic memories after an odor stimuli has been greatly studied and researchers have hypothesized the cause of this phenomenon to be due to the location of the olfactory system being very close the brain. The author highlights new findings that show “spatiotemporal information is integrated in a brain region known as the anterior olfactory nucleus (AON), which is implicated in Alzheimer’s disease” (Sandoiu). A researcher by the name of Afif Aqrabawi conducted a study in which mice were subjected to a range of experiments and tests to examine the role of the anterior olfactory nucleus on memory. In the article it states that Aqrabawi’ s study led to the discovery of neural pathways between the hippocampus and the anterior olfactory nucleus. In the experiments, mice were presented with odors and Aqrabawi says that when the neural connection between the hippocampus and AON is intact, the mice preferred spending time smelling a new odor instead of a familiar one. With the neural pathway disrupted, mice preferred to smell the familiar odor as they thought it was a new odor. Aqrabawi explains how this observation helps to better understand the neural circuits that are responsible for episodic memory triggered by smell. The article also talks about how Alzheimer’s disease has shown early degradation of the anterior olfactory neuron and that the odor deficits that are experienced by people who suffer Alzheimer’s have difficulty remembering details about the odors they encountered. The neural pathway that was discovered in Aqrabawi’ s study may be a clue to better understand what the underlying causes of this are.

The research being done by Shanahan, and the study done by Aqrabawi that was described in Sandoiu’ s article, shows the deep connection of the olfactory system and memory. The experiments done in Shanahan’s lab show how even during sleep olfaction can be used as a tool to shape memory consolidation. The olfactory pathway is connected to the limbic system, which is involved in memory and emotion and during sleep, odorants can be presented to individuals without them being aware and awake. Even without participants being actively awake, it reinforces the encoding of memories. The discovery of new connections in Aqrabawi’ s study greatly helps get closer to explaining why odors are so involved with memory. Further research in the relationship between odor and memory can possibly reveal methods that can be used in learning. This research can possibly be used to answer questions regarding if odor can be used to help better encode information in a shorter span of time. How can olfaction help in neurodegenerative disease and maybe in cases of amnesia? While there are many studies focused on the relationship between smell and memory, there is a lot yet to be uncovered.

__________________________________________________________________

Sandoiu, Ana. “Why Smells Bring Back Such Vivid Memories.” Medical News Today, MediLexicon International, 26 July 2018, www.medicalnewstoday.com/articles/322579.

Shanahan, Laura K., and Jay A. Gottfried. “Scents and Reminiscence: Olfactory Influences on Memory Consolidation in the Sleeping Human Brain.” Cognitive Neuroscience of Memory Consolidation, 2017, pp. 335–346., doi:10.1007/978-3-319-45066-7_20.

How Color Influences Brain Activity

 

What if there was a way to know what we’re thinking just by looking at a person's brain map? A recent study was able to find specific regions in the brain that were active when certain colors were shown to the study groups. The researchers were able to know what colors the participants were shown based on which brain area was more active during the study. This study may be able to show us more about our visual perception on objects and how patterns can also have effects on our different brain regions.  

Using MEG (Magnetoencephalography) researchers found that certain hues of colors activate different regions of the brain in participants. Pink, blue, green and orange were used in the study as well as shades of darker and lighter colors. Each color activated a specific region in the brain that allowed researchers to know which colors were being shown to the participant by looking at the brain maps of participants. The colors were also shown on a spiral shape to make it easier for participants to focus more attention on the colors being shown. This may be the reason behind the colors being shown were easier to be identified in brain maps.  

There were 18 participants in the study and 8 colors were used, pink, blue, and orange, and 2 shades of each color, lighter and darker. Within hues there was not much of a difference between seeing the hues as darker or lighter, the brain region. For example, the brain region still perceived the color as orange and not much difference in darker or lighter hues. There were also similarities in detecting light hues of orange and pink which shows that some colors are perceived to be the same based on the hue. Overall, it was easier for participants to identify the darker hues over the light hues.  

It would be interesting to see what other types of studies can be done with this research using MEG to view brain activity. Would researchers be able to see different brain region activity in object and pattern recognition being? What type of data can be gathered in language and word processing to see if certain words or sentences activate different regions of the brain? The studies can also show us more about our thought processes from thoughts to actions as well. Overall, this study can lead to many other studies such as color depth in objects we see every day, in how we interact with our environment on a day-to-day basis. The study can also show us that it can go beyond color perception research and into pattern recognition, or language and word processing.  

 

 

“Color Space Geometry Uncovered with Magnetoencephalography” by Isabelle A. Rosenthal, Shridhar R. Singh, Katherine L. Hermann, Dimitrios Pantazis, Bevil R. Conway. Current Biology 

Sources:  

NeuroscienceNews.com 

https://www.biorxiv.org/content/10.1101/2020.08.10.245324v1 

https://doi.org/10.1016/j.cub.2020.10.062 

https://doi.org/10.1016/j.cub.2020.10.062