Medication Treatment for Tics and Tourette’s

There are several kinds of medication than can help kids with Tourette’s or another tic disorder. But it’s important to note that not all kids who develop tics need treatment. Tics are very common. They often go away on their own, and they tend to bother parents more than they do the children experiencing them. Drawing attention to them can make them worse. So doing nothing can be the best strategy — at least initially.

Treatment comes into play if tics are upsetting your child, giving them pain, or making it hard for them to function in everyday life — say they’re disrupting class or getting bullied because of their tics.

The first recommended step in treatment is a specialized form of therapy called comprehensive behavioral intervention for tics (CBIT). CBIT is centered on habit reversal training, in which the child learns to recognize when they have an urge to tic and substitute a competing response — an easier, more comfortable, or less noticeable action or behavior that makes the tic impossible. For instance, if a child’s tic is jerking their head to the side, the strategy might be to put their chin down instead.

But if therapy isn’t effective in reducing a child’s tics, medication can help.

Guanfacine and clonidine for tics

First-line medications for Tourette’s and other tic disorders are a class of drugs called alpha-2 agonists, explains Paul Mitrani, MD, PhD, a child and adolescent psychiatrist at the Child Mind Institute. Alpha agonists decrease the release of a neurotransmitter called norepinephrine, which stimulates the nervous system. Alpha agonists serve as a kind of dimmer switch — by calming down the system, they make the urge to tic less frequent, less intense, and by extension, easier to control.

The two alpha-2 agonists usually prescribed for tics are guanfacine and clonidine. Dr. Mitrani reports that he usually starts by prescribing guanfacine because it comes in a longer-acting form (Intuniv), which reduces symptoms for a full 24 hours. Clonidine’s long-acting form (Kapvay) is effective for 12 hours.

Dr. Mitrani adds that there is a new liquid form of clonidine called Onyda XR that lasts 24 hours, but there isn’t yet a strong body of evidence regarding its effectiveness for tics. Onyda XR is FDA-approved for ADHD, as are Kapvay and Intuniv.

While no alpha agonist medications are FDA-approved specifically for tics, Kapvay and Intuniv are frequently used off-label for them. There is ample research on their effectiveness for tics, and they are recommended by clinical practice guidelines.

Some children respond better to several doses of short-acting guanfacine or clonidine, Dr. Mitrani notes, rather than a smoother dose of a long-acting medication. This may be because medication can be timed to peak at times when kids need tic suppression most, such as at school.

Alpha agonists are the preferred first line medications for tic disorders because their side-effects, including drowsiness and low blood pressure, are relatively mild.

Antipsychotics for tics

If alpha agonists aren’t helping, the next step would be to try an antipsychotic medication, which can be more effective for treating tics, Dr. Mitrani notes, but their side effects are potentially more difficult to tolerate.

Aripiprazole (Abilify), which is FDA-approved for tics, is often Dr. Mitrani’s first choice among the antipsychotic medications. Abilify is a second-generation, or atypical, antipsychotic, a group of medications that have fewer side effects than older antipsychotics. Side effects of Abilify can include restlessness, agitation and weight gain.

Haloperidol (Haldol) is also effective for tics, but it’s an older antipsychotic with more side effect concerns, Dr. Mitrani notes. “I’ve only had one patient ever on Haldol, and he tolerated it well and it really helped with his tics when other things did not.”

Risperidone (Risperdal) is another atypical antipsychotic that can help, but its side effects tend to be worse than Abilify. Risperidone can cause more concerning weight gain and metabolic, neurological, and hormonal changes that can be harmful. Sometimes other medications are used to manage the weight gain from antipsychotics.

When kids with tics also have ADHD

More than three-quarters of kids diagnosed with a tic disorder also have another disorder. When a child has multiple disorders, a clinician will want to evaluate which is causing the child the most difficulty and prioritize treating that.

The most common co-occurring disorder with tics is ADHD. “If tics are the bigger problem, we would start with treating them,” says Dr. Mitrani. “If the ADHD is the bigger problem, which it typically is, we usually treat that first.”

In the past, it was recommended that children with tics and ADHD avoid stimulant medication, based on research that showed it made tics worse. But newer studies counter that finding, Dr. Mitrani notes, concluding that the old research was based on very high doses of amphetamine-based medications. To lower the risk of exacerbating tics, he recommends starting kids with ADHD and tics on methylphenidate-based medication.

“If your child is starting a stimulant,” he adds, “and you see worsening of tics — and it’s clearly related to when the stimulant is in their system — the best approach might be a lower dose of stimulant combined with guanfacine or clonidine.”

One advantage to that combination, he notes, is that kids with ADHD who have behavior problems can benefit from the guanfacine or clonidine being active in the mornings before the stimulant starts working and in the evenings when it’s out of their system.

Kids with other co-occurring disorders

When children with tics have other co-occurring disorders, such as anxiety, OCD, or depression, treating them with medication needs to be done very carefully, Dr. Mitrani says. Since children are typically not bothered by the tics themselves, it’s almost always the other disorder that is more problematic for them.  And, he adds, when the other problems cause distress, it can make the tics worse.

For anxiety, OCD, and depression, the first-line medication treatment is an antidepressant. Antidepressants can actually help alleviate tics indirectly, since they reduce anxiety. “Stress increases tics, so if there is significant anxiety and you treat the anxiety, the tics may get better,” Dr. Mitrani says. “And then maybe you don’t need the guanfacine or clonidine. But again, it depends on what the co-occurring disorders are and what’s the bigger problem for the child.”

Monitoring medication for tics

Due to the waxing and waning nature of tics, it can be challenging to see the full effect of medication and other interventions. It is important to give medication enough time to work, Dr. Mitrani notes, typically a few weeks, to see if the overall pattern, frequency, and severity of tics has improved. And children who are being treated should continue to be monitored regularly for any changes, as tics can recur or worsen, especially when a child is excited, tired, or experiencing more stress.

Most children with tics see a natural improvement or even resolution of tics as they progress through adolescence. If there seems to be a long-standing improvement, it is appropriate to consider reducing or stopping medication, especially if the child is experiencing side effects, Dr. Mitrani notes. If tics continue and are causing distress, it is important to keep treating them.

A child going off any of these medications — alpha agonists or antipsychotics — should do so gradually, by having their dose reduced over weeks or even longer, to avoid unpleasant or dangerous side effects of sudden withdrawal.

The post Medication Treatment for Tics and Tourette’s appeared first on Child Mind Institute.

Nancy Cox, a CDC veteran and a stalwart in global flu research, dies at 77

Nancy Cox, who for decades was a global leader in influenza research, has died. Cox headed the influenza team at the Centers for Disease Control and Prevention for 22 years, shepherding it from a branch of 14 people to a division of over 100. She was also director of the World Health Organization’s Collaborating Center for the Surveillance, Epidemiology, and Control of Influenza at the CDC.

Cox died Thursday from glioblastoma, a cancer of the brain. She was 77.

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Opinion: The podcast telling the stories behind Ambien, Ozempic, EpiPens, and other game-changing drugs

Below is a lightly edited, AI-generated transcript of the “First Opinion Podcast” interview with Thomas Goetz. Be sure to sign up for the weekly “First Opinion Podcast” on Apple PodcastsSpotify, or wherever you get your podcasts. Get alerts about each new episode by signing up for the “First Opinion Podcast” newsletter. And don’t forget to sign up for the First Opinion newsletter, delivered every Sunday.

Torie Bosch: Whether it’s Ambien or Wegovy, ivermectin or fluoride, every drug in your medicine cabinet or advertised on TV has a story behind it. Not just how it came to be, but how it ends up affecting society in unexpected ways, big or small.

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Associations of psychological distress, gaming motives and internet gaming disorder in adolescents: a network analysis

Background and objectiveThe rapid popularization of the Internet among Chinese adolescents has resulted in the emergence of a public major concern known as Internet Gaming Disorder (IGD). As demonstrated by previous studies, an association has been demonstrated among emotional distress, gaming motives and IGD. Nevertheless, the specific pathways connecting these constructs remain to be elucidated. The present study aims to explore the network structure characterizing the interactions among these three constructs and to identify potential targets for psychological interventions.MethodsThis was a cross-sectional survey conducted in city of Hangzhou. A total of 3,795 middle school students were included in the analysis. The 21-item Depression Anxiety Stress Scale (DASS-21), the Motives for Online Gaming Questionnaire (MOGQ), and the Chinese version of the Ten-Item Internet Gaming Disorder Test (IGDT-10) were used to assess emotional distress, gaming motives and IGD symptoms, respectively. Network analyses were performed using R4.5.1 software to explore the interrelationships among emotional distress, gaming motives and IGD symptoms, and identify the core symptoms and bridge symptoms.ResultsIn the depression combined network model, the presence of bridge symptoms was indicated by no initiative (D2), gaming for escape or mood relief (IGD8) and fantasy motive (fan). In anxiety combined network model, the bridge symptoms included coping motive(cop), gaming for escape or mood relief (IGD8), withdrawal (IGD2), mouth dryness (A1), and fear of embarrassment (A4). The bridge symptoms in the stress combined network model were gaming for escape or mood relief (IGD8), difficulty winding down (S1), withdrawal (IGD2), nervous energy expenditure (S3), and coping motive (cop).ConclusionThe present study explored complex network structure among psychological distress, gaming motivation, and IGD. and suggested fantasy and coping motive as bridges connecting psychological distress and IGD. Besides, our research identified no initiative, mouth dryness, difficulty winding down, fear of embarrassment, and nervous energy expenditure as the best targets for intervention to reduce IGD.
<![CDATA[FDA accelerates psychedelic drug development to advance agents for TRD, PTSD, and AUD. ]]>

Three reasons why DeepSeek’s new model matters

On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model. Notably, the model can process much longer prompts than its last generation, thanks to a new design that helps it handle large amounts of text more efficiently. Like DeepSeek’s previous models, V4 is open source, meaning it is available for anyone to download, use, and modify.

V4 marks DeepSeek’s most significant release since R1, the reasoning model it launched in January 2025. R1, which was trained on limited computing resources, stunned the global AI industry with its strong performance and efficiency, turning DeepSeek from a little-known research team into China’s best-known AI company almost overnight. It also helped set off a wave of open-weight model releases from other Chinese AI firms. 

DeepSeek has kept a relatively low profile since then—but earlier this month, it effectively teased V4’s release when it added “expert” and “flash” modes to the online version of its model, prompting speculation that the updates were tied to a bigger upcoming release.

While the company has become a powerful symbol of China’s AI ambitions, its big return to cutting-edge frontier models comes after months of scrutiny—including major personnel departures, delays to previous model launches, and growing scrutiny from both the US and Chinese governments. 

So, will V4 shake the AI field the way R1 did? Almost certainly not, but here are three big reasons why this release matters.

1. It breaks new ground for an open-source model.

As with R1 before it, DeepSeek claims that V4’s performance rivals the best models available at a fraction of the price. This is great news for developers and for companies using the tech, because it means they can access frontier AI capabilities on their own terms, and without worrying about skyrocketing costs.

The new model comes in two versions, both of which are available on DeepSeek’s website and in its app, with API access also open to developers. V4-Pro is a larger model built for coding and complex agent tasks, and V4-Flash is a smaller version designed to be faster and cheaper to run. Both versions offer reasoning modes, in which the model can carefully parse a user’s prompt and show each step as it works through the problem.

For V4-Pro, DeepSeek charges $1.74 per million input tokens and $3.48 per million output tokens, a fraction of the cost of comparable models from OpenAI and Anthropic. V4-Flash is even cheaper, at about $0.14 per million input tokens and about $0.28 per million output tokens, making it one of the cheapest top-tier models available. This would make it a very appealing model to build applications on.

In terms of performance, V4 is, perhaps unsurprisingly, a huge jump from R1—and it seems to be a strong alternative to just about all the latest big AI models. On the major benchmarks, according to results shared by the company, DeepSeek V4-Pro competes with leading closed-source models, matching the performance of Anthropic’s Claude-Opus-4.6, OpenAI’s GPT-5.4, and Google’s Gemini-3.1. And compared to other open-source models, such as Alibaba’s Qwen-3.5 or Z.ai’s GLM-5.1, DeepSeek V4 exceeds them all on coding, math, and STEM problems, making it one of the strongest open-source models ever released. 

DeepSeek also says that V4-Pro now ranks among the strongest open-source models on benchmarks for agentic coding tasks and performs well on other tests that measure ability to carry out multistep problems. Its writing ability and world knowledge also leads the field, according to benchmarking results shared by the company. 

In a technical report released alongside the model, DeepSeek shared results from an internal survey of 85 experienced developers: More than 90% included V4-Pro among their top model choices for coding tasks.

DeepSeek says it has specifically optimized V4 for popular agent frameworks such as Claude Code, OpenClaw, and CodeBuddy.

2. It delivers on a new approach to memory efficiency.

One of the key innovations of V4 is its long context window—the amount of text the model can process at once. Both versions can handle 1 million tokens, which is large enough to fit all three volumes of The Lord of the Rings and The Hobbit combined. The company says this context window size is now the default across all DeepSeek services and it matches what is offered by cutting-edge versions of models like Gemini and Claude. 

But it’s important to know not just that DeepSeek has made this leap, but how it did so. V4 makes significant architectural changes to the company’s former models—especially in the attention mechanism, which is the feature of AI models that helps them understand each part of a prompt in relation to the rest. As the prompt text gets longer, these comparisons become much more costly, making attention one of the main bottlenecks for long-context models.

DeepSeek’s innovation was to make the model more selective about what it pays attention to. Instead of treating all earlier text as equally important, V4 compresses older information and focuses on the parts most likely to matter in the present moment, while still keeping nearby text in full so it does not miss important details. 

DeepSeek says this sharply reduces the cost of using long context. In a 1-million-token context, V4-Pro uses only 27% of the computing power required by its previous model, V3.2, while cutting memory use to 10%. The reduction in V4-Flash is even larger, using just 10% of the computing power and 7% of the memory. In practice, this could make it cheaper to build tools that need to work across huge amounts of material, such as an AI coding assistant that can read an entire codebase or a research agent that can analyze a long archive of documents without constantly forgetting what came before.

DeepSeek’s interest in long context windows didn’t start with V4. Over the past year and a half, the company has quietly published a series of papers on how AI models “remember” information, experimenting with compression and mathematical techniques to extend what AI models could realistically handle.

3. It marks the first steps on the hard road away from Nvidia.

V4 is DeepSeek’s first model optimized for domestic Chinese chips, such as Huawei’s Ascend—a move that has turned the launch into something of a test of whether China’s homegrown AI industry can begin to loosen its dependence on US chip giant Nvidia. 

This was largely expected, since The Information reported earlier this month that DeepSeek did not give American chipmakers like Nvidia and AMD early access to V4, though prerelease access is common to allow chipmakers to optimize support of the new model ahead of a launch. Instead, the company reportedly gave early access only to Chinese chipmakers. 

On Friday, Huawei said its Ascend supernode products, based on the Ascend 950 series, would support DeepSeek V4. This means that companies and individuals who want to run their own modified version of Deepseek V4 will be able to use Huawei chips easily.

Reuters previously reported that Chinese government officials recommended that DeepSeek integrate Huawei chips in its training process. And this pressure fits a broader pattern in China’s industrial policy: Strategic sectors are often pushed, and sometimes effectively required, to align with national self-reliance goals. But there’s a particular urgency when it comes to AI. Since 2022, US export controls have cut Chinese firms off from Nvidia’s most powerful chips, and they later also restricted access to downgraded China-market versions. Beijing’s response has been to accelerate the push for a domestic AI stack, from chips to software frameworks to data centers.

Chinese authorities have reportedly been pushing data centers and public computing projects to use more domestic chips, including through reported bans on foreign-made chips, sourcing quotas, and requirements to pair Nvidia chips with Chinese alternatives from companies such as Huawei and Cambricon. 

Still, replacing Nvidia is not as simple as swapping one chip for another. Nvidia’s advantage lies not only in its chips, but in the software ecosystem developers have spent years building around them. Moving to Huawei’s Ascend chips means adapting model code, rebuilding tools, and proving that systems built around those chips are stable enough for serious use.

To be clear, DeepSeek does not appear to have fully moved beyond Nvidia. The company’s technical report reveals that it is using Chinese chips to run the model for inference, or when someone asks the model to complete a task. But Liu Zhiyuan, a computer science professor at Tsinghua University, told MIT Technology Review that DeepSeek appears to have adapted only part of V4’s training process for Chinese chips. The report does not say whether some key long-context features were adapted to domestic chips, so Liu says V4 may still have been trained mainly on Nvidia chips. Multiple sources who spoke on the condition of anonymity, due to political sensitivity around these issues, told MIT Technology Review that Chinese chips still don’t perform as well as Nvidia chips but are better suited for inference than training.

DeepSeek is also tying the future costs of V4 to this hardware shift. The company says V4-Pro prices could fall significantly after Huawei’s Ascend 950 supernodes begin shipping at scale in the second half of this year. 

If that works, V4 could be an early sign that China is successfully building a parallel AI infrastructure.