Category Archives: Neuroscience

Neuroscience

Unlocking Flow: The Neuroscience of Creative Bliss – Neuroscience News

Summary: A new study involving Philadelphia-area jazz guitarists, has explored the brain processes that enable creative flow. The research reveals that achieving flow requires a solid foundation of expertise, after which one must learn to relax conscious control to allow creativity to flourish.

By measuring brain activity and performance quality during improvisation, the study shows that experienced musicians entering flow exhibit less frontal lobe activity, which is associated with executive functions, and more in sensory processing areas. These findings suggest that mastering and then mentally releasing ones craft is key to achieving the high creativity and productivity associated with flow states.

Key Facts:

Source: The Conversation

Flow, or being in the zone, is a state of amped-up creativity, enhanced productivity and blissful consciousness that, some psychologists believe, is also thesecret to happiness. Its considered thebrains fast track to successin business, the arts or any other field.

But in order to achieve flow, a person must first develop a strong foundation of expertise in their craft. Thats according to anew neuroimaging studyfrom Drexel Universitys Creativity Research Lab, which recruited Philly-area jazz guitarists to better understand the key brain processes that underlie flow. Once expertise is attained, the study found, this knowledge must be unleashed and not overthought in order for flow to be reached.

As acognitive neuroscientistwho is senior author of this study, and a university writing instructor, we are a husband-and-wife team who collaborated on abook about the science of creative insight. We believe that this new neuroscience research reveals practical strategies for enhancing, as well as elucidating, innovative thinking.

The concept of flow has fascinated creative people ever since pioneeringpsychological scientist Mihly Cskszentmihlyibegan investigating the phenomenon in the 1970s.

Yet, a half-century of behavioral research has not answered many basic questions about the brain mechanisms associated with the feeling of effortless attention that exemplifies flow.

The Drexel experiment pitted two conflicting theories of flow against each other to see which better reflects what happens in peoples brains when they generate ideas. One theory proposes that flow is a state ofintensive hyperfocuson a task. The other theory hypothesizes that flow involvesrelaxing ones focusor conscious control.

The team recruited 32 jazz guitarists from the Philadelphia area. Their level of experience ranged from novice to veteran, as quantified by the number of public performances they had given. The researchers placed electrode caps on their heads to record their EEG brain waves while they improvised to chord sequences and rhythms that were provided to them.

Jazz improvisationis a favorite vehicle for cognitive psychologists and neuroscientists who study creativity because it is a measurable real-world task that allows fordivergent thinking the generation of multiple ideas over time.

The musicians themselves rated the degree of flow that they experienced during each performance, and those recordings were later played for expert judges who rated them for creativity.

As jazz greatCharlie Parker is said to have advised, Youve got to learn your instrument, then, you practice, practice, practice. And then, when you finally get up there on the bandstand, forget all that and just wail.

This sentiment aligns with the Drexel study findings. The performances that the musicians self-rated as high in flow were also judged by the outside experts as more creative. Furthermore, the most experienced musicians rated themselves as being in flow more than the novices, suggesting that experience is a precondition for flow. Their brain activity revealed why.

The musicians who were experiencing flow while performing showed reduced activity in parts of their frontal lobes known to be involved inexecutive functionorcognitive control. In other words, flow was associated with relaxing conscious control or supervision over other parts of the brain.

And when the most experienced musicians performed while in a state of flow, their brains showed greater activity in areas known to be involved in hearing and vision, which makes sense given that they were improvising while reading the chord progressions and listening to rhythms provided to them.

In contrast, the least experienced musicians showed very little flow-related brain activity.

We were surprised to learn that flow-state creativity is very different from nonflow creativity.

Previous neuroimaging studies suggested that ideas are usually produced by thedefault-mode network, a group of brain areas involved in introspection, daydreaming and imagining the future. The default-mode network spews ideas like an unattended garden hose spouts water, without direction.

The aim is provided by the executive-control network, residing primarily in the brains frontal lobe, which acts like a gardener who points the hose to direct the water where it is needed.

Creative flow is different: no hose, no gardener. The default-mode and executive-control networks are tamped down so that they cannot interfere with the separate brain network that highly experienced people have built up for producing ideas in their field of expertise.

For example, knowledgeable but relatively inexperienced computer programmers may have to reason their way through every line of code. Veteran coders, however, tapping their specialized brain network for computer programming, may just start writing code fluently without overthinking it until they complete perhaps in one sitting a first-draft program.

The findings that expertise and the ability to surrender cognitive control are key to reaching flow are supported by a2019 studyfrom the Creativity Research Lab. For that study, jazz musicians were asked to play more creatively. Given that direction, the nonexpert musicians were indeed able to improvise more creatively.

That is apparently because their improvisation was largely under conscious control and could therefore be adjusted to meet the demand. For example, during debriefing, one of the novice performers said, I wouldnt use these techniques instinctively, so I had to actively choose to play more creatively.

On the other hand, the expert musicians, whose creative process was baked in through decades of experience, were not able to perform more creatively after being asked to do so. As one of the experts put it, I felt boxed-in, and trying to think more creatively was a hindrance.

The takeaway for musicians, writers, designers, inventors and other creatives who want to tap into flow is that training should involve intensive practice followed by learning to step back and let ones skill take over. Future research may develop possible methods for releasing control once sufficient expertise has been achieved.

Author: John Kounios and Yvette Kounios Source: The Conversation Contact: John Kounios and Yvette Kounios The Conversation Image: The image is credited to Neuroscience News

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Unlocking Flow: The Neuroscience of Creative Bliss - Neuroscience News

Neuroscience

Revolutionizing Glioblastoma Treatment – Neuroscience News

Summary: Researchers demonstrated significant initial success using CAR-T therapy for glioblastoma, a notoriously deadly brain cancer. They detailed the outcomes of the first three patients in a Phase 1 clinical trial who experienced dramatic tumor reductions shortly after treatment.

This innovative approach combines CAR-T cells with bispecific antibodies to more effectively target the heterogeneous cell populations within solid tumors. While the initial results show promise, the team is exploring ways to enhance the longevity of the therapys effectiveness.

Key Facts:

Source: Harvard

A collaborative project to bring the promise of cell therapy to patients with a deadly form of brain cancer has shown dramatic results among the first patients to receive the novel treatment.

In apaperpublished Wednesday in The New England Journal of Medicine, researchers fromMass General Cancer Centershared the results for the first three patient cases from a Phase 1 clinical trial evaluating a new approach to CAR-T therapy for glioblastoma.

Just days after a single treatment, patients experienced dramatic reductions in their tumors, with one patient achieving near-complete tumor regression. In time, the researchers observed tumor progression in these patients, but given the strategys promising preliminary results, the team will pursue strategies to extend the durability of response.

This is a story of bench-to-bedside therapy, with a novel cell therapy designed in the laboratories of Massachusetts General Hospital and translated for patient use within five years, to meet an urgent need, said co-authorBryan Choi, a neurosurgeon at Harvard-affiliated Mass General and an assistant professor at Harvard Medical School.

The CAR-T platform has revolutionized how we think about treating patients with cancer, but solid tumors like glioblastoma have remained challenging to treat because not all cancer cells are exactly alike and cells within the tumor vary.

Our approach combines two forms of therapy, allowing us to treat glioblastoma in a broader, potentially more effective way.

The new approach is a result of years of collaboration and innovation springing from the lab ofMarcela Maus, director of the Cellular Immunotherapy Program and an associate professor at the Medical School.

Maus lab has set up a team of collaborating scientists and expert personnel to rapidly bring next-generation genetically modified T cells from the bench to clinical trials in patients with cancer.

Weve made an investment in developing the team to enable translation of our innovations in immunotherapy from our lab to the clinic, to transform care for patients with cancer, said Maus.

These results are exciting, but they are also just the beginning they tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease. We havent cured patients yet, but that is our audacious goal.

CAR-T (chimeric antigen receptor T-cell) therapy works by using a patients own cells to fight cancer it is known as the most personalized way to treat the disease. A patients cells are extracted, modified to produce proteins on their surface called chimeric antigen receptors, and then injected back into the body to target the tumor directly.

Cells used in this study were manufactured by the Connell and OReilly Families Cell Manipulation Core Facility of the Dana-Farber/Harvard Cancer Center.

CAR-T therapies have been approved for the treatment of blood cancers, but the therapys use for solid tumors is limited. Solid tumors contain mixed populations of cells, allowing some malignant cells to continue to evade the immune systems detection even after treatment with CAR-T. Maus team is working to overcome this challenge by combining two previously separate strategies: CAR-T and bispecific antibodies, known as T-cell engaging antibody molecules.

The version of CAR-TEAM for glioblastoma is designed to be directly injected into a patients brain.

In the new study, the three patients T cells were collected and transformed into the new version of CAR-TEAM cells, which were then infused back into each patient. Patients were monitored for toxicity throughout the duration of the study. All patients had been treated with standard-of-care radiation and temozolomide chemotherapy and were enrolled in the trial after disease recurrence.

The authors note that despite the remarkable responses among the first three patients, they observed eventual tumor progression in all the cases, though in one case, there was no progression for over six months.

Progression corresponded in part with the limited persistence of the CAR-TEAM cells over the weeks following infusion. As a next step, the team is considering serial infusions or preconditioning with chemotherapy to prolong the response.

We report a dramatic and rapid response in these three patients. Our work to date shows signs that we are making progress, but there is more to do, said co-author Elizabeth Gerstner, a Mass General neuro-oncologist.

In addition to Choi, Maus, and Gerstner, other authors are Matthew J. Frigault, Mark B. Leick. Christopher W. Mount, Leonora Balaj, Sarah Nikiforow, Bob S. Carter, William T. Curry, and Kathleen Gallagher.

Funding: The study was supported in part by the National Gene Vector Biorepository at Indiana University, which is funded under a National Cancer Institute contract.

Author: Haley Bridger Source: Harvard Contact: Haley Bridger Harvard Image: The image is credited to Neuroscience News

Original Research: Closed access. Intraventricular CARv3-TEAM-E T Cells in Recurrent Glioblastoma by Bryan D.Choi et al. NJEM

Abstract

Intraventricular CARv3-TEAM-E T Cells in Recurrent Glioblastoma

In this first-in-human, investigator-initiated, open-label study, three participants with recurrent glioblastoma were treated with CARv3-TEAM-E T cells, which are chimeric antigen receptor (CAR) T cells engineered to target the epidermal growth factor receptor (EGFR) variant III tumor-specific antigen, as well as the wild-type EGFR protein, through secretion of a T-cellengaging antibody molecule (TEAM).

Treatment with CARv3-TEAM-E T cells did not result in adverse events greater than grade 3 or dose-limiting toxic effects.

Radiographic tumor regression was dramatic and rapid, occurring within days after receipt of a single intraventricular infusion, but the responses were transient in two of the three participants.

(Funded by Gateway for Cancer Research and others; INCIPIENT ClinicalTrials.gov number,NCT05660369.)

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Revolutionizing Glioblastoma Treatment - Neuroscience News

Neuroscience

Decoding spontaneous thoughts from the brain via machine learning – EurekAlert

image:

First, the data was independently segmented into quintiles (5 levels) for self-relevance and valence based on participants ratings. Next, time points (TRs) were assigned according to the levels of these two dimensions, resulting in a total of 55 quantized TR indices. Utilizing these indices, exemplified by level 2 for self-relevance and level 5 for valence highlighted as red-shaded TRs in the figure, each index's fMRI and rating data were averaged, thereby generating 25 fMRI images and corresponding rating data for each participant. Subsequently, employing these orthogonalized data, whole-brain pattern-based predictive models were developed using principal component regression (PCR) along with leave-one-subject-out cross-validation (LOSO-CV) and random-split cross-validation (RS-CV).

Credit: Institute for Basic Science

A team of researchers led by KIM Hong Ji and WOO Choong-Wan at the Center for Neuroscience Imaging Research (CNIR) within the Institute for Basic Science (IBS), in collaboration with Emily FINN at Dartmouth College, has unlocked a new realm of understanding within the human brain. The team demonstrated the possibility of using functional Magnetic Resonance Imaging (fMRI) and machine learning algorithms to predict subjective feelings in peoples thoughts while reading stories or in a freely thinking state.

The brain is constantly active, and spontaneous thoughts occur even during rest or sleep. These thoughts can be anything ranging from memories of the past to aspirations for the future, and they are often intertwined with emotions and personal concerns. However, because spontaneous thought typically occurs without any constraint of consciousness, researching them poses challenges - even simply asking individuals what they are currently thinking can change the nature of their thoughts.

New research suggests that it may be possible to develop predictive models of affective contents during spontaneous thought by combining personal narratives with fMRI. Narratives and spontaneous thoughts share similar characteristics, including rich semantic information and temporally unfolding nature. To capture a diverse range of thought patterns, participants engaged in one-on-one interviews to craft personalized narrative stimuli, reflecting their past experiences and emotions. While participants read their stories inside the MRI scanner, their brain activity was recorded.

After the fMRI scan, the participants were asked to read the stories again and report perceived self-relevance (i.e., how much this content is related to themselves) and valence (i.e., how much this content is positive or negative) at each moment. Using a quintile (five levels) from each participant's self-relevance and valence ratings, 25 (5 levels of self-relevance rating 5 levels of valence rating) possible segments of fMRI and rating data were created. The team then harnessed machine learning techniques to train predictive models, combining these data with the fMRI brain scans from 49 individuals to decode the emotional dimensions of thoughts in real time.

To interpret the brain representations of the predictive models, the research team employed multiple approaches, such as virtual lesion and virtual isolation analyses at both region and network levels. Through these analyses, they discovered the significance of the default mode, ventral attention, and frontoparietal networks in both self-relevance and valence predictions. Specifically, they identified the involvement of the anterior insula and midcingulate cortex in self-relevance prediction, while the left temporoparietal junction and dorsomedial prefrontal cortex played important roles in valence prediction.

Moreover, the predictive models showed their capacity to predict both self-relevance and valence not only during story reading but also when applied to data from 199 individuals engaging in spontaneous, task-free thinking or even during resting. These findings show the promise of daydream decoding.

Several tech companies and research teams are currently endeavoring to decode words or images directly from brain activity, but there are limited initiatives aimed at decoding intimate emotions underlying these thoughts, stated Dr. WOO Choong-Wan, associate director of IBS, who led the study. Our research is centered on human emotions, with the aim of decoding emotions within the natural flow of thoughts to obtain information that can benefit peoples mental health.

KIM Hongji, a doctoral candidate and the first author of this study, emphasized, "This study holds significance as we decoded the emotional state associated with general thoughts, rather than targeting emotions limited to specific tasks," adding, "These findings advance our understanding of the internal states and contexts influencing subjective experiences, potentially shedding light on individual differences in thoughts and emotions, and aiding in the evaluation of mental well-being."

Video abstract can be found at: https://youtu.be/wUr6apaRuAE

Proceedings of the National Academy of Sciences

Experimental study

People

Brain decoding of spontaneous thought: predictive modeling of self-relevance and valence using personal narratives

28-Mar-2024

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Decoding spontaneous thoughts from the brain via machine learning - EurekAlert

Neuroscience

Reducing Toxic AI Responses – Neuroscience News

Summary: Researchers developed a new machine learning technique to improve red-teaming, a process used to test AI models for safety by identifying prompts that trigger toxic responses. By employing a curiosity-driven exploration method, their approach encourages a red-team model to generate diverse and novel prompts that reveal potential weaknesses in AI systems.

This method has proven more effective than traditional techniques, producing a broader range of toxic responses and enhancing the robustness of AI safety measures. The research, set to be presented at the International Conference on Learning Representations, marks a significant step toward ensuring that AI behaviors align with desired outcomes in real-world applications.

Key Facts:

Source: MIT

A user could ask ChatGPT to write a computer program or summarize an article, and the AI chatbot would likely be able to generate useful code or write a cogent synopsis. However, someone could also ask for instructions to build a bomb, and the chatbot might be able to provide those, too.

To prevent this and other safety issues, companies that build large language models typically safeguard them using a process called red-teaming. Teams of human testers write prompts aimed at triggering unsafe or toxic text from the model being tested. These prompts are used to teach the chatbot to avoid such responses.

But this only works effectively if engineers know which toxic prompts to use. If human testers miss some prompts, which is likely given the number of possibilities, a chatbot regarded as safe might still be capable of generating unsafe answers.

Researchers from Improbable AI Lab at MIT and the MIT-IBM Watson AI Lab used machine learning to improve red-teaming. They developed a technique to train a red-team large language model to automatically generate diverse prompts that trigger a wider range of undesirable responses from the chatbot being tested.

They do this by teaching the red-team model to be curious when it writes prompts, and to focus on novel prompts that evoke toxic responses from the target model.

The technique outperformed human testers and other machine-learning approaches by generating more distinct prompts that elicited increasingly toxic responses. Not only does their method significantly improve the coverage of inputs being tested compared to other automated methods, but it can also draw out toxic responses from a chatbot that had safeguards built into it by human experts.

Right now, every large language model has to undergo a very lengthy period of red-teaming to ensure its safety. That is not going to be sustainable if we want to update these models in rapidly changing environments.

Our method provides a faster and more effective way to do this quality assurance, says Zhang-Wei Hong, an electrical engineering and computer science (EECS) graduate student in the Improbable AI lab and lead author of apaper on this red-teaming approach.

Hongs co-authors include EECS graduate students Idan Shenfield, Tsun-Hsuan Wang, and Yung-Sung Chuang; Aldo Pareja and Akash Srivastava, research scientists at the MIT-IBM Watson AI Lab; James Glass, senior research scientist and head of the Spoken Language Systems Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL); and senior author Pulkit Agrawal, director of Improbable AI Lab and an assistant professor in CSAIL. The research will be presented at the International Conference on Learning Representations.

Automated red-teaming

Large language models, like those that power AI chatbots, are often trained by showing them enormous amounts of text from billions of public websites. So, not only can they learn to generate toxic words or describe illegal activities, the models could also leak personal information they may have picked up.

The tedious and costly nature of human red-teaming, which is often ineffective at generating a wide enough variety of prompts to fully safeguard a model, has encouraged researchers to automate the process using machine learning.

Such techniques often train a red-team model using reinforcement learning. This trial-and-error process rewards the red-team model for generating prompts that trigger toxic responses from the chatbot being tested.

But due to the way reinforcement learning works, the red-team model will often keep generating a few similar prompts that are highly toxic to maximize its reward.

For their reinforcement learning approach, the MIT researchers utilized a technique called curiosity-driven exploration. The red-team model is incentivized to be curious about the consequences of each prompt it generates, so it will try prompts with different words, sentence patterns, or meanings.

If the red-team model has already seen a specific prompt, then reproducing it will not generate any curiosity in the red-team model, so it will be pushed to create new prompts, Hong says.

During its training process, the red-team model generates a prompt and interacts with the chatbot. The chatbot responds, and a safety classifier rates the toxicity of its response, rewarding the red-team model based on that rating.

Rewarding curiosity

The red-team models objective is to maximize its reward by eliciting an even more toxic response with a novel prompt. The researchers enable curiosity in the red-team model by modifying the reward signal in the reinforcement learning set up.

First, in addition to maximizing toxicity, they include an entropy bonus that encourages the red-team model to be more random as it explores different prompts. Second, to make the agent curious they include two novelty rewards.

One rewards the model based on the similarity of words in its prompts, and the other rewards the model based on semantic similarity. (Less similarity yields a higher reward.)

To prevent the red-team model from generating random, nonsensical text, which can trick the classifier into awarding a high toxicity score, the researchers also added a naturalistic language bonus to the training objective.

With these additions in place, the researchers compared the toxicity and diversity of responses their red-team model generated with other automated techniques. Their model outperformed the baselines on both metrics.

They also used their red-team model to test a chatbot that had been fine-tuned with human feedback so it would not give toxic replies. Their curiosity-driven approach was able to quickly produce 196 prompts that elicited toxic responses from this safe chatbot.

We are seeing a surge of models, which is only expected to rise. Imagine thousands of models or even more and companies/labs pushing model updates frequently. These models are going to be an integral part of our lives and its important that they are verified before released for public consumption.

Manual verification of models is simply not scalable, and our work is an attempt to reduce the human effort to ensure a safer and trustworthy AI future, says Agrawal.

In the future, the researchers want to enable the red-team model to generate prompts about a wider variety of topics. They also want to explore the use of a large language model as the toxicity classifier. In this way, a user could train the toxicity classifier using a company policy document, for instance, so a red-team model could test a chatbot for company policy violations.

If you are releasing a new AI model and are concerned about whether it will behave as expected, consider using curiosity-driven red-teaming, says Agrawal.

Funding: This research is funded, in part, by Hyundai Motor Company, Quanta Computer Inc., the MIT-IBM Watson AI Lab, an Amazon Web Services MLRA research grant, the U.S. Army Research Office, the U.S. Defense Advanced Research Projects Agency Machine Common Sense Program, the U.S. Office of Naval Research, the U.S. Air Force Research Laboratory, and the U.S. Air Force Artificial Intelligence Accelerator.

Author: Adam Zewe Source: MIT Contact: Adam Zewe MIT Image: The image is credited to Neuroscience News

Original Research: The findings will be presented at the International Conference on Learning Representations

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Reducing Toxic AI Responses - Neuroscience News

Neuroscience

Angela Bryan Awarded Hazel Barnes Prize | Psychology and Neuroscience – University of Colorado Boulder

Published: April 10, 2024

CU Psychology and Neuroscience ProfessorAngela Bryan(Social) was awarded the Hazel Barnes Prize for 2024. From the Office the Chancellor's website: This is "the largest and most prestigious single faculy award funded by the University of Colorado Boulder.It was established in 1991 by former Chancellor James Corbridge in honor of Philosophy Professor Emerita Hazel Barnes to recognize 'the enriching interrelationship between teaching and research'.

"Nominees are regionally and nationally recognized, tenured faculty members who are not only outstanding teachers, but who also have distinguished records in research and scholarship. The Hazel Barnes Prize selection committee is comprised of past recipients."

Read more about the prize and check out thelist of past recipients on the chancellor's website.

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Angela Bryan Awarded Hazel Barnes Prize | Psychology and Neuroscience - University of Colorado Boulder

Neuroscience

Biohaven Showcases Innovative Neuroscience Portfolio with 20 Presentations at the 2024 American Academy of … – PR Newswire

DENVER, CO and NEW HAVEN, Conn., April 13, 2024 /PRNewswire/ -- Biohaven Ltd.(NYSE: BHVN) announced today that 20 abstracts, including 8 oral presentations and 12 posters, will be featured this weekend starting April 13th at the 2024 American Academy of Neurology (AAN) Annual Meeting, taking place in Denver, Colorado. The presentations highlight Biohaven's leadership in neuroscience and extensive development programs evaluating novel therapies to treat neurological diseases, with abstracts covering programs that includeKv7 ion channel modulation, molecular degraders of extracellular protein (MoDEs), TRPM3 antagonism, TYK2/JAK1 inhibition, glutamate modulation, and myostatin inhibition.

Irfan Qureshi, M.D., Chief Medical Officer of Biohaven, commented, "The research being presented at the AAN Annual Meeting emphasizes Biohaven's commitment to developing new therapeutic options across a range of neurological diseases. By targeting novel mechanisms of action, differentiated from currently available treatments and other therapies in development, and following innovative science, Biohaven continues to strive for better treatments for people living with neurological disorders. We are particularly honored that the AAN Science Committee selected our BHV-2100 (TRPM3) abstract as an AAN Abstract of Distinction, recognizing it as the top abstract in the pain category. Following the completion of Phase 1 studies in the first half of 2024, we look forward to initiating a Phase 2 study with BHV-2100 in migraine in the second half of the year and are excited by the potential for this novel nonopioid approach to treat pain."

Vlad Coric M.D., Chief Executive Officer and Chairman of Biohaven, added, "Our leadership in neuroscience research is on full display at the AAN Annual Meeting with the breadth and depth of clinical, epidemiological, and preclinical programs highlighted in our scientific presentations. Central nervous system (CNS) disorders continue to represent one of the highest unmet medical needs facing our society and we must act urgently to bring better treatments to patients and improve clinical outcomes. We believe that the next generation of therapies for CNS disorders will include MoDEs for autoimmune disorders, ion channel modulation for epilepsy, migraine and other pain disorders, immune modulation for neurodegenerative disorders including Parkinson's and Alzheimer's diseases, myostatin targeting drugs for neuromuscular disorders and glutamate modulating agents for neuropsychiatric disorders. I am so proud of the team at Biohaven who are working tirelessly to alleviate the burden of these devastating disorders."

The complete list of Biohaven's accepted abstract titles is below. Full abstracts can be viewed online at https://index.mirasmart.com/AAN2024/.

Oral Presentations:

Poster Presentations:

Posters and presentations will be available on thePosters and Presentationspage after the conference atwww.biohaven.com.

About BiohavenBiohavenis a biopharmaceutical company focused on the discovery, development, and commercialization of life-changing treatments in key therapeutic areas, including immunology, neuroscience, and oncology. The company is advancing its innovative portfolio of therapeutics, leveraging its proven drug development experience and multiple proprietary drug development platforms.Biohaven'sextensive clinical and preclinical programs include Kv7 ion channel modulation for epilepsy and mood disorders; extracellular protein degradation for immunological diseases; TRPM3 antagonism for migraine and neuropathic pain; TYK2/JAK1 inhibition for neuroinflammatory disorders; glutamate modulation for OCD and SCA; myostatin inhibition for neuromuscular and metabolic diseases, including SMA and obesity; and antibody recruiting, bispecific molecules and antibody drug conjugates for cancer.

Forward-looking StatementsThis news release includes forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. The use of certain words, including "continue", "plan", "will", "believe", "may", "expect", "anticipate" and similar expressions, is intended to identify forward-looking statements. Investors are cautioned that any forward-looking statements, including statements regarding the future development, timing and potential marketing approval and commercialization of development candidates, are not guarantees of future performance or results and involve substantial risks and uncertainties. Actual results, developments and events may differ materially from those in the forward-looking statements as a result of various factors including: the expected timing, commencement and outcomes ofBiohaven'splanned and ongoing clinical trials; the timing of planned interactions and filings with the FDA; the timing and outcome of expected regulatory filings; complying with applicableU.S.regulatory requirements; the potential commercialization ofBiohaven'sproduct candidates; the potential forBiohaven'sproduct candidates to be first in class therapies; and the effectiveness and safety ofBiohaven'sproduct candidates. Additional important factors to be considered in connection with forward-looking statements are described inBiohaven'sfilings with theSecurities and Exchange Commission, including within the sections titled "Risk Factors" and "Management's Discussion and Analysis of Financial Condition and Results of Operations". The forward-looking statements are made as of the date of this news release, andBiohavendoes not undertake any obligation to update any forward-looking statements, whether as a result of new information, future events or otherwise, except as required by law.

Investor Contact:Jennifer Porcelli Vice President, Investor Relations [emailprotected] 201-248-0741

Media Contact:Mike Beyer Sam Brown Inc. [emailprotected] 312-961-2502

MoDE is a trademark of Biohaven Therapeutics Ltd.

Biohaven AAN 2024 Oral & Poster Presentations:

Functional Impairments in Patients with KCNQ2-DEE: Associations Among Key Clinical Features Sunday 4/14/24: 8:00-9:00 P1- Poster Session 1 Colorado Convention Center Exhibit Hall B-E

The Phase 3 RESILIENT Study: Taldefgrobep Alfa in Spinal Muscular Atrophy Sunday 4/14/24: 11:45 - 12:45 P2 - Poster Session 2 Colorado Convention Center - Exhibit Hall

Association of Anti-inflammatory Therapy Use with the Incidence of Parkinson's Disease: A Person-Time Analysis Among Patients with Autoimmune Diseases Sunday 4/14/24: 1:00-3:00 (1:24-1:36) S2 Movement Disorders: Epidemiology and Clinical Aspects Colorado Convention Center- Mile High 4CD

Re-weighting MDS-UPDRS Motor Items for Optimal Sensitivity to Parkinson's Disease Progression in Untreated Patients Using Parkinson's Progression Markers Initiative Data Sunday 4/14/24: 1:00-3:00 (1:36-1:48) S2 Movement Disorders: Epidemiology and Clinical Aspects Colorado Convention Center- Mile High 4CD

Population Pharmacokinetic Modeling of Riluzole After Administration of a Next Generation Prodrug Troriluzole Sunday 4/14/24: 1:00 - 3:00 (2:12-2:24) S3 - General Neurology 1 Colorado Convention Center - Four Seasons 2/3

Next Generation Prodrug Troriluzole: Increased Bioavailability of Riluzole with No Food Effect in Healthy Subjects Sunday 4/14/24: 3:30 - 5:30 (4:30-4:42) S5 - ALS and CMT: New Therapeutic Approaches Colorado Convention Center - Four Seasons 1

BHV-2100, A First-In-Class TRPM3 Antagonist for the Treatment of Pain Monday 4/15/24: 11:15-12:15 (11:27-11:39) S13 Pain Research Colorado Convention Center 605

Troriluzole Exhibits Favorable Hepatic Safety Profile Across a Diverse Range of Disorders Monday 4/15/24: 11:45 - 12:45 P4 - Poster Session 4 Colorado Convention Center - Exhibit Hall

Safety, Tolerability, and Pharmacokinetics of Single and Multiple Rising Doses of a Next Generation Prodrug Troriluzole in Healthy Subjects Monday 4/15/24: 11:45 - 12:45 P4 - Poster Session 4 Colorado Convention Center - Exhibit Hall

No Clinically Relevant Effects of Hepatic Impairment on the Pharmacokinetics of a Next Generation Prodrug Troriluzole Monday 4/15/24: 11:45 - 12:45 P4 - Poster Session Colorado Convention Center - Exhibit Hall

Automated Video-based Characterization of Movement Quality in a Phase III Clinical Trial of Troriluzole in Subjects with Spinocerebellar Ataxia Tuesday 4/16/24: 8:00-9:00 P6- Poster Session 6 Colorado Convention Center Exhibit Hall

Psychometric Validation of the Modified-functional Scale for the Assessment and Rating of Ataxias Tuesday 4/16/24: 11:45-12:45 P7 Poster Session 7 Colorado Convention Center Exhibit Hall

Development of a Novel Composite Measure (SCACOMS) to Assess Disease Progression in Spinocerebellar Ataxia Tuesday 4/16/24: 11:45-12:45 P7 - Poster Session 7 Colorado Convention Center Exhibit Hall

Phase 1 Study Evaluating the Safety and Tolerability of BHV-7000, a Novel, Selective Kv7.2/7.3 Potassium Channel Activator, in Healthy Adults Tuesday 4/16/24: 5:30 - 6:30 P8 - Poster Session 8 Colorado Convention Center - Exhibit Hall

Novel, Selective Kv7.2/7.3 Potassium Channel Activator, BHV-7000, Demonstrates Dose-dependent Pharmacodynamic Effects on EEG Parameters in Healthy Adults

Tuesday 4/16/24: 5:30 - 6:30 P8 - Poster Session 8 Colorado Convention Center - Exhibit Hall

Determinants of Health-related Quality of Life of Patients with Focal Epilepsy: A Systematic Literature Review Wednesday 4/17/24: 8:00-9:00 P9- Poster Session 9 Colorado Convention Center Exhibit Hall

Characterization of BHV-7000: A Novel Kv7/2/7.3 Activator for the Treatment of Seizures Wednesday 4/17/24: 1:00-3:00 (2:00-2:12) S29- Epilepsy Diagnostics and Therapeutics Colorado Convention Center 605

Matching-adjusted Indirect Comparison of Troriluzole Versus Untreated Natural History Cohort in Spinocerebellar Ataxia Wednesday 4/17/24: 3:30-5:30 (5:06-5:18) S35 Movement Disorders: Hyperkinetic Movement Disorders Colorado Convention Center Four Seasons 4

Re-weighting MDS-UPDRS Part II Items for Optimal Sensitivity to Parkinson's Disease Progression Using Parkinson's Progression Markers Initiative Natural History Data Wednesday 4/17/24: 5:30-6:30 P11 Poster Session 11 Colorado Convention Center Exhibit Hall

Novel Bispecific Degrader BHV-1300 Achieves Rapid, Robust, and Selective IgG Reduction in Preclinical Models Including Nonhuman Primates Thursday 4/18/24: 1:00 - 3:00 (1:36-1:48) S43 - General Neurology 2 Colorado Convention Center - 108/110/112

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Neuroscience

Those Who Use Willpower Deemed More Trustworthy – Neuroscience News

Summary: Individuals who rely on willpower to resist temptations are perceived as more trustworthy than those using external commitment strategies like swear jars or internet-blocking apps. This study involved over 2,800 U.S. participants in online experiments, comparing perceptions of integrity between those using internal versus external methods for achieving goals.

The findings suggest a societal bias favors self-reliance over external aids, impacting the adoption of potentially beneficial commitment strategies. This research highlights how personal choices in goal achievement can influence social trustworthiness perceptions.

Key Facts:

Source: APA

People who use willpower to overcome temptations and achieve their goals are perceived as more trustworthy than those who use strategies that involve external incentives or deterrents such as swear jars or internet-blocking apps according to research published by the American Psychological Association.

The knowledge that people can use external commitment strategies to overcome self-control problems has existed in some form for thousands of years. Since at least the time of Homer and Odysseus, the focus has primarily been on the efficacy of these strategies for the person choosing to engage in them, said lead author Ariella Kristal, PhD, of Columbia University.

This prior work has demonstrated, for example, that Odysseus made the right decision to tie himself to the mast rather than attempting to use willpower to resist the sirens in the moment.

Known as commitment strategies, these approaches have been shown to improve success for a variety of goals, including smoking cessation, weight loss, academic achievement and saving money, according to Kristal. Despite the benefits of commitment strategies, though, little research has been done on how they affect others perceptions of people using them.

To better understand how peoples use of commitment strategies over willpower affects others perceptions of them, Kristal and her co-author, Julian Zlatev, PhD, of Harvard Business School, conducted a series of online experiments involving more than 2,800 participants from the United States.

The research was published in theJournal of Personality and Social Psychology.

In most of the experiments, participants were presented with a hypothetical situation involving individuals who attempted to achieve a goal using willpower or a commitment strategy.

In one experiment, they were asked to rate the integrity of hypothetical individuals who used willpower to avoid an unwanted behavior (e.g., eating junk food or drinking alcohol) versus paying $5 every time they engaged in the unwanted behavior. In another scenario, hypothetical individuals either used willpower or an app to avoid distracting websites like Facebook or Instagram.

Overall, individuals who were described as using commitment strategies to achieve their goals were judged to be less trustworthy than those who used willpower alone.

In two experiments, researchers found that participants were more likely to rate hypothetical users of commitment strategies as less trustworthy, even though the participants recognized the strategies were more effective than willpower alone.

In another, participants were less likely to choose an external commitment strategy if they thought others might find out.

People appear particularly hesitant to adopt commitment strategies when their use will be made public and, while not as high, peoples resistance continues to remain elevated even when the use of strategies will be kept private, said Kristal.

This occurs despite the fact that people do recognize and acknowledge the benefits of these commitment strategies.

The researchers believe that the choice to use a commitment strategy signals to others a deficiency in an individuals character. That is, people believe those who require external aid (as opposed to using just willpower) are more likely to have failed in the past and therefore are less capable of overcoming self-control problems on their own.

Past failures of self-control can be seen by others as moral failures. Because morality is an important component of integrity in particular, and trustworthiness more broadly, people who rely on commitment strategies may be viewed as less trustworthy than those who simply use willpower, said Kristal.

These findings have important implications for developing programs and initiatives that rely on external strategies to help people achieve their goals, according to Kristal.

By examining the role of interpersonal judgments in self-control strategy choice, we can begin to understand why people may fail to adopt these beneficial strategies and how to better promote effective strategy use.

Author: James Sliwa Source: APA Contact: James Sliwa APA Image: The image is credited to Neuroscience News

Original Research: Closed access. Going Beyond the Self in Self-Control: Interpersonal Consequences of Commitment Strategies by Ariella Kristal et al. Journal of Personality and Social Psychology

Abstract

Going Beyond the Self in Self-Control: Interpersonal Consequences of Commitment Strategies

Commitment strategies are effective mechanisms individuals can use to overcome self-control problems. Across seven studies (and two supplemental studies), we explore the negative interpersonal consequences of commitment strategy choice and use.

In Study 1, using an incentivized trust game, we demonstrate that individuals trust people who choose to use a commitment strategy less than those who choose to use willpower to achieve their goals.

Study 2 shows this relationship holds across four domains and for integrity-based trust in particular.

Study 3 provides evidence that it is the choice to use the strategy rather than strategy use itself that incurs this integrity penalty.

In Studies 45b, we demonstrate that this effect is driven, at least in part, by the fact that people infer past performance from strategy choice.

Finally, Study 6 provides evidence that people select commitment strategies more in private than in public, which is consistent with the notion that people anticipate the negative consequences of commitment strategy choice.

Thus, we establish the role of willpower as a positive signal in impression formation as well as the negative interpersonal consequences of choosing to rely on external aides when faced with temptation.

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Those Who Use Willpower Deemed More Trustworthy - Neuroscience News

Neuroscience

How Sex and Gender Shape Our Cognition – Neuroscience News

Summary: Researchers released a new study examining how sex and gender influence cognitive abilities. The study analyzed eight cognitive tasks and found that while spatial cognition correlates more with biological factors such as sex at birth and hormones, verbal cognition is more influenced by sociocultural factors like gender identity.

This research underscores the complexity of cognitive differences and stresses the importance of considering both sex-based and gender-based factors in psychological and neuroscientific research. The teams approach encourages the inclusion of diverse populations to better understand and accurately depict the nuances of cognitive abilities.

Key Facts:

Source: University of Montreal

Many studies have found sex differences in cognitive abilities. In general, women outperform men on verbal and fine motor tasks, while men outperform women on spatial orientation and mental rotation tasks.

However, few studies have considered the influence of sociocultural factors such asgender identity,gender expression(stereotypical male and female behaviors) andsexual orientationin explaining these differences.

Now a new study by scientists at Universit de Montral does just that, by examining performance on eight cognitive tasks in relation to both sex-based and gender-based factors.

The ongoing research is being done by Mina Gurin, a Ph.D. student in neuropsychology, and Fanny Saulnier, an MSc student in psychiatric sciences, under the supervision of psychiatry professor Robert-Paul Juster.

Their results werepublishedin January in the journalBiology of Sex Differences.

The findings confirm thatsex differencesin spatial cognition are indeed better explained by biological factors, i.e., sex assigned at birth and sex hormones. But they also show that sex differences in verbal cognition are better explained by sociocultural factors, i.e., gender identity.

In short, spatial cognition seems more related to sex, while verbal cognition seems more related to gender. Sex assigned at birth is not always the most important variable in explaining sex differences in cognition.

Our findings highlight the importance of considering gender diversity when seeking to understand sex differences and gender diversity in cognition, said Juster.

The research team believes their findings will encourage researchers to use more sophisticated methodologies that use both sex and gender measures.

By including people from diverse backgrounds, we can incorporate more sex- and gender-related variables into the analysis and ultimately get a more accurate picture of cognitive differences, said Gurin.

Author: Batrice St-Cyr-Leroux Source: University of Montreal Contact: Batrice St-Cyr-Leroux University of Montreal Image: The image is credited to Neuroscience News

Original Research: Open access. Sex and gender correlates of sexually polymorphic cognition by Louis Cartier et al. Biology of Sex Differences

Abstract

Sex and gender correlates of sexually polymorphic cognition

Sexually polymorphic cognition (SPC) results from the interaction between biological (birth-assigned sex (BAS), sex hormones) and socio-cultural (gender identity, gender roles, sexual orientation) factors. The literature remains quite mixed regarding the magnitude of the effects of these variables. This project used a battery of classic cognitive tests designed to assess the influence of sex hormones on cognitive performance. At the same time, we aimed to assess the inter-related and respective effects that BAS, sex hormones, and gender-related factors have on SPC.

We recruited 222 adults who completed eight cognitive tasks that assessed a variety of cognitive domains during a 150-min session. Subgroups were separated based on gender identity and sexual orientation and recruited as follows: cisgender heterosexual men (n=46), cisgender non-heterosexual men (n=36), cisgender heterosexual women (n=36), cisgender non-heterosexual women (n=38), gender diverse (n=66). Saliva samples were collected before, during, and after the test to assess testosterone, estradiol, progesterone, cortisol, and dehydroepiandrosterone. Psychosocial variables were derived from self-report questionnaires.

Cognitive performance reflects sex and gender differences that are partially consistent with the literature. Interestingly, biological factors seem to better explain differences in male-typed cognitive tasks (i.e., spatial), while psychosocial factors seem to better explain differences in female-typed cognitive tasks (i.e., verbal).

Our results establish a better comprehension of SPC over and above the effects of BAS as a binary variable. We highlight the importance of treating sex as a biological factor and gender as a socio-cultural factor together since they collectively influence SPC.

Sexually polymorphic cognition (SPC) results from the interaction between biological (birth-assigned sex (BAS), sex hormones) and socio-cultural (gender identity, gender roles, sexual orientation) factors. The literature remains quite mixed regarding the magnitude of the effects of these variables. This project used a battery of classic cognitive tests designed to assess the influence of sex hormones on cognitive performance. At the same time, we aimed to assess the inter-related and respective effects that BAS, sex hormones, and gender-related factors have on SPC.

We recruited 222 adults who completed eight cognitive tasks that assessed a variety of cognitive domains during a 150-min session. Subgroups were separated based on gender identity and sexual orientation and recruited as follows: cisgender heterosexual men (n=46), cisgender non-heterosexual men (n=36), cisgender heterosexual women (n=36), cisgender non-heterosexual women (n=38), gender diverse (n=66). Saliva samples were collected before, during, and after the test to assess testosterone, estradiol, progesterone, cortisol, and dehydroepiandrosterone. Psychosocial variables were derived from self-report questionnaires.

Cognitive performance reflects sex and gender differences that are partially consistent with the literature. Interestingly, biological factors seem to better explain differences in male-typed cognitive tasks (i.e., spatial), while psychosocial factors seem to better explain differences in female-typed cognitive tasks (i.e., verbal).

Our results establish a better comprehension of SPC over and above the effects of BAS as a binary variable. We highlight the importance of treating sex as a biological factor and gender as a socio-cultural factor together since they collectively influence SPC.

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How Sex and Gender Shape Our Cognition - Neuroscience News