In one of the most comprehensive investigations of its kind, researchers have taken a major step toward untangling the biology underlying suicide risk, moving the field beyond long-standing debates about whether suicidal behavior is simply a consequence of psychiatric illness. By integrating large-scale genetic data with cutting-edge approaches that map how genes act in specific brain cells and circuits, an international team has identified shared genetic liability that cuts across psychiatric diagnoses while also pinpointing druggable biological pathways that could one day inform prevention strategies. The study, published in Translational Psychiatry, offers a sweeping synthesis of how inherited risk factors may translate into molecular vulnerabilities, and it does so with a level of resolution that previous candidate-gene approaches could never achieve.

Suicide remains one of the leading causes of death worldwide, claiming more than 700,000 lives each year according to global health estimates. Despite decades of research, clinical prediction remains stubbornly imprecise, and biological models of suicidal behavior have historically been hampered by small sample sizes, inconsistent findings, and a tendency to conflate suicide risk with the psychiatric disorders with which it so often co-occurs. Major depression, bipolar disorder, schizophrenia, and substance use disorders all carry elevated suicide risk, yet most people with these conditions never attempt suicide, while some individuals who die by suicide have no diagnosed psychiatric illness at all. This paradox has long suggested to researchers that suicidal behavior may possess partially distinct biological underpinnings, and the new study set out to test that hypothesis with unprecedented statistical power.

At the heart of the work lies genome-wide association study methodology, or GWAS, which scans hundreds of thousands to millions of genetic variants spread across the entire genome in very large groups of people, comparing individuals who have experienced suicidal thoughts or behaviors with those who have not. Each variant is tested for statistical association with the outcome, and the results can be combined into polygenic risk scores, numerical summaries of a person’s inherited liability based on the cumulative small effects of thousands of variants. Because no single common variant exerts a large effect, the field depends on aggregating data across massive biobanks and cohorts, a strategy that has only become feasible in the past decade as datasets containing hundreds of thousands of individuals became available.

The research team took particular care to address a central confound: psychiatric disorders themselves are highly heritable, and any genetic signal linked to suicide could simply reflect inherited liability to depression or schizophrenia rather than to suicide specifically. To disentangle this, the investigators applied sophisticated statistical techniques, including genetic correlation analysis and conditional modeling, which allow researchers to ask how much genetic overlap remains between suicidal behavior and psychiatric conditions after accounting for their shared heritability. Their findings revealed a complex architecture. Substantial genetic correlations confirmed that suicide risk shares a meaningful fraction of its inherited basis with major psychiatric disorders, supporting the idea of a common pool of genetic liability. Yet the analyses also uncovered signals that persisted beyond what could be explained by those disorders, pointing to biological mechanisms that may be more specific to the emergence of suicidal thoughts and actions.

A key conceptual innovation of the study is its framing of “shared genetic liability” as a bridge between diagnoses. Rather than treating suicide as an epiphenomenon of any single disorder, the researchers modeled it as a transdiagnostic phenomenon, one whose risk emerges partly from inherited vulnerabilities that cut across diagnostic categories. This perspective aligns with a growing movement in biological psychiatry that emphasizes symptom dimensions and mechanisms over traditional diagnostic boundaries. From this vantage point, the genetic variants that raise risk for depression, PTSD, and schizophrenia may do so partly because they converge on shared molecular pathways, and those same pathways may govern an individual’s threshold for suicidal crises regardless of which diagnosis they carry.

Identifying genetic variants, however, is only the first step. A GWAS signal typically points to a genomic region rather than a specific causal gene or mechanism, since many associated variants fall in non-coding stretches of DNA that regulate gene activity from a distance. To translate statistical associations into biological insight, the team deployed a battery of functional genomics approaches. Transcriptome-wide association studies, known as TWAS, integrate gene expression data to identify genes whose genetically predicted expression levels are linked to suicide risk. Tissue and cell-type enrichment analyses then ask whether the implicated genes are unusually active in particular organs or cell populations. The results converged strikingly on brain tissue, and more specifically on neuronal populations, providing support for the idea that inherited suicide risk is mediated largely through gene regulation within the central nervous system.

The study’s most clinically provocative findings concern druggable biology. Using databases that catalog the protein targets of approved and investigational medications, the researchers examined whether genes implicated in suicide risk were over-represented among known drug targets. The analysis identified several classes of candidate targets, including components of neurotransmitter signaling systems, ion channels, and intracellular signaling cascades that are already the focus of pharmacological development for other conditions. This “druggable genome” approach, which has gained traction in genetics research across many diseases, offers a pragmatic shortcut for translational science: rather than waiting decades for entirely new therapeutic classes to be invented, researchers can prioritize existing or in-development compounds whose molecular targets intersect with genetically implicated pathways.

Among the pathways receiving attention in the analysis were those involving glutamatergic and GABAergic neurotransmission, the primary excitatory and inhibitory systems of the brain, which have repeatedly surfaced in studies of mood disorders and stress response. The endocannabinoid system and inflammatory signaling pathways also appeared in the convergent analyses, consistent with a broader literature linking immune dysregulation and allostatic load to suicidal ideation. Importantly, the authors emphasize that these findings identify hypotheses rather than ready-made treatments. Genetic association with a drug target does not guarantee that modulating that target will reduce suicide risk, and any therapeutic application would require extensive preclinical validation and carefully designed clinical trials. Nevertheless, the work provides a principled, data-driven map for where to look, replacing decades of largely failed candidate-gene speculation with a genome-wide evidence base.

The methodological rigor underpinning the study deserves emphasis, because the genetics of suicidal behavior has a troubled history. Early candidate-gene studies, which typically examined a handful of variants in genes related to serotonin signaling, produced findings that largely failed to replicate and in some cases were later shown to reflect statistical artifacts, small samples, and publication bias. The field has since undergone a reckoning, and modern efforts adhere to far stricter standards: preregistered analyses, very large and ancestrally diverse cohorts, replication in independent samples, and conservative multiple-testing corrections that demand genome-wide significance thresholds on the order of five times ten to the negative eighth power. The new study reflects these lessons, applying sensitivity analyses to guard against confounding from psychiatric comorbidity and examining whether findings generalize across ancestral groups, an issue of considerable importance given that most genetic discovery to date has been conducted in populations of European ancestry.

The implications for clinical practice, while still distant, are worth considering. Polygenic risk scores for suicide-related outcomes currently explain only a small fraction of individual differences in risk, far too little to be used as stand-alone screening tools, and their predictive performance is degraded in populations not represented in the discovery data. Researchers in the field are careful to stress that genetic risk is not destiny: suicidal behavior arises from an intricate interplay of inherited vulnerability, mental illness, trauma, substance use, social isolation, access to lethal means, and the availability of support. What genetics offers is not a crystal ball but a window into mechanism, and mechanistic knowledge is the raw material from which better biomarkers, risk stratification tools, and ultimately targeted interventions are built. In the near term, the druggable pathway findings are most valuable as a guide for laboratory science, directing neurobiologists toward molecular systems whose manipulation might alter suicide-relevant phenotypes in animal models and cellular assays.

Looking forward, the study signals where the field must go next. Sample sizes for suicide-specific genetic analyses remain smaller than those for major psychiatric disorders, and expanding representation across ancestries is essential if the benefits of this research are to be shared equitably. Integrating genetic data with longitudinal measures of life stress, neural imaging, and digital phenotyping may eventually allow researchers to model how inherited liability interacts with environmental triggers across the lifespan. Functional experiments in induced pluripotent stem cell-derived neurons and brain organoids could test whether the implicated genes genuinely alter stress-response circuitry or resilience. And randomized trials in patients carrying high genetic liability, though ethically and logistically complex, represent the logical endpoint of the druggable-target approach.

What the study ultimately delivers is a reframe. Suicide risk, in this analysis, is not an amorphous clinical outcome but a measurable, partly heritable trait whose genetic architecture is now being resolved with the same tools that have transformed our understanding of heart disease, diabetes, and schizophrenia. By demonstrating that shared genetic liability links suicide risk across diagnostic boundaries and by mapping that liability onto specific, pharmacologically tractable biology, the researchers have converted a long-standing clinical puzzle into a concrete research agenda. The path from genetic correlation to effective prevention is long, and no genetic finding will soon replace the human work of crisis intervention, connection, and care. But for a problem that has defied biological explanation for generations, the identification of shared, druggable mechanisms represents a genuine and hard-won advance, one that may shape suicide research for years to come.

From fireflies to mammals, evolution may have tuned communication to the rhythm of neurons.

Eliminative materialism is best seen as a nice try at cementing materialism in a world where it faces mounting serious challenges.

Source

In Boé National Park, researchers have repeatedly encountered a small number of trees marked by gouged bark and piles of stones at their bases. These signs suggest that wild chimpanzees have returned to the same trees for years to throw rocks. According to a recent field account by University of Victoria researchers Robyn Nakano and Ammie Kalan, some of these sites have remained in use for over a decade.

This behavior, called accumulative stone throwing, has been observed in only four chimpanzee populations in West Africa. While rocks and trees are widespread in chimpanzee habitats, piling stones at specific trees is rare. Nakano, Kalan, and other researchers suggest this may be a cultural practice within certain groups rather than arising from environmental factors alone.

What the Behavior Looks Like

Video recordings collected through the Pan African Programme and analyzed in a 2016 Scientific Reports study led by Hjalmar Kühl show that mostly adult male chimpanzees throw rocks at particular trees and repeatedly return to the same trunks. During these events, the chimpanzees pant-hoot, a loud call used for long-distance communication, and sometimes perform buttress drumming by repeatedly striking the tree’s buttressed base with their hands and feet.

Pant-hooting and buttress drumming are typical features of displays put on by male chimpanzees. The fact that these behaviors occur alongside stone throwing suggests that accumulative stone throwing may have developed as a variation of these existing social displays.

A Ritualized Behavior, Not a Coincidence

Researchers suspect this behavior may be cultural rather than simply a response to environmental conditions because it occurs only in certain areas, even though appropriate rocks and trees are common throughout chimpanzees’ habitats. Within one population, only particular trees are used as throwing sites. Earlier studies have suggested that the behavior might function as a form of communication or could indicate places of symbolic significance within a community’s territory.

The behavior could also offer archaeologists a rare example of how repeated stone use and accumulation can create material traces that persist after the animals that made them have moved on.

Some primates use stones as tools, including populations that use rocks to open nuts for food. Accumulative stone throwing differs because the behavior occurs in a social context rather than during extractive foraging. The purpose of this behavior for the chimpanzees remains unclear.

Into the Boé Wilderness

Nakano and Kalan conducted their fieldwork from Béli, a village where the Dutch nonprofit Chimbo operates a solar-powered research compound with local partners. The team traveled 22 kilometers by bicycle and on foot into the savanna-woodland to establish a camp, working with field assistants Djei Baldé, Balu Séra, and master’s student Taylor Tippett from the Great Ape Behaviour Lab.

The Boé chimpanzees are not used to humans and tend to avoid them, making direct observation impossible. The team instead set up two video cameras at each known stone-throwing site and placed audio recorders nearby to monitor the area.

Each day began at 6:30 a.m. with visits to two to five sites to replace SD cards and batteries, check equipment, measure trees, and create 3D scans of rocks thrown at the trees for later analysis. The team also recorded chimpanzee nests, feeding traces, and vocalizations along the trails. Their camp was located beside the Fefine River, which continues flowing through the dry season and provides an important water source for wildlife.

A Decade of Stone Throwing

The team found that most sites first identified by the Pan African Programme and revisited in 2017 remained active when Nakano and Kalan’s team returned in 2026. Chimpanzees have returned to these same trees to throw rocks for more than ten years.

The video and audio collected during this trip will allow the team to identify the age and sex of individual stone-throwers and observe how nearby chimpanzees respond to these events. This data could help the researchers determine the purpose of this behavior.

A Landscape Under Threat

Chimpanzees’ habitat in Guinea-Bissau is becoming increasingly threatened by industrial mining. During fieldwork, the researchers discovered boreholes dug to explore bauxite, the ore used to produce aluminum. Although bauxite mining might help promote economic development, comparable operations in neighboring Guinea have caused habitat loss and pollution, with negative effects on both wildlife and local communities. The country’s political instability also presents challenges for environmental oversight.

Nakano and Kalan emphasize that losing these stone-throwing sites would be both a cultural and ecological loss, erasing a documented example of primate material culture.

What’s Still Unknown

Nakano and Kalan are still analyzing the footage from this field season, but the main question of why chimpanzees throw stones at these specific trees remains unanswered. Still, the evidence collected by the cameras and recorders could help determine whether the behavior functions as territorial signaling, long-distance communication, or something else entirely.

Austin Burgess is a writer and researcher with a background in sales, marketing, and data analytics. He holds an MBA, a Bachelor of Science in Business Administration, and a data analytics certification. His work focuses on breaking scientific developments, with an emphasis on emerging biology, cognitive neuroscience, and archaeological discoveries.

New research from Indiana University suggests that when your brain makes a decision, it may not actually “make” it in the way neuroscientists have traditionally assumed.

Conventionally, decision-making has been described as a sequence: you have options to consider, you choose one, and then you act. However, neuroscientist Tom James argues that this sequence may not accurately reflect what actually happens in the brain.

Traditional models suggest that the brain has centralized processes responsible for making decisions. James argues that what people experience as “decision-making” may instead arise from ongoing interactions among perception, movement, the body, and the environment. If correct, this perspective could significantly change how scientists understand human behavior.

The Sandwich Model Debated 

James describes one traditional approach to cognition as the “sandwich model”: sensory systems take in information, cognitive processes evaluate it and determine what to do, and motor systems then carry out the chosen action.

The problem, James argues, is that while scientists can identify many of the physical mechanisms involved in sensation and movement, it is much harder to locate a central point in the brain where a “decision” actually occurs.

Instead, James proposes thinking in terms of “action selection,” in which sensory, sensorimotor, and motor processes continually interact to produce behavior. But does that mean humans don’t actually make decisions?

“Of course they do. We use this language all the time, and it’s very helpful in terms of describing behavior,” James said in a statement. “The leap, I think, is to say that the brain works by having decision-making or control processes. It produces behavior that is well described in that way. But it doesn’t need a process that does that to make it look that way.”

In his view, “decision-making” may therefore be a useful way of describing human behavior rather than something the brain accomplishes through a specific, centralized process or system.

“As mental phenomena, they are defined on too abstract a level for the goals of cognitive neuroscience,” adds James.

Decisions are not “things”

Bridging neuroscience and philosophy, James draws on a physicalist framework associated with philosopher Daniel Dennett. Consider an object’s center of mass: it helps us describe and predict how the object behaves, but it isn’t a separate physical component causing the object to move.

James suggests decisions may work similarly. We can say someone “decided” to pick up a glass, but that does not necessarily mean there is a central location in the brain where that decision was made. Instead, the action could emerge from multiple brain and bodily processes working together.

As an analogy, James describes a robot programmed to follow a wall. Someone watching it might interpret its movements as a series of decisions, yet the robot does not require a centralized decision-making system. Instead, its sensors continually interact with its surroundings to guide its behavior.

James suggests that aspects of human behavior could be understood in much the same way.

A philosophical challenge 

James’s argument also addresses a longstanding philosophical problem. If the brain contains a central system that observes information and decides how we should act, what controls that controller?

This resembles what Dennett famously called the “Cartesian Theater”: the idea of an internal observer somehow watching and interpreting what happens inside the brain. But proposing such an observer only pushes the problem back another step—who, then, observes the observer?

Rather than placing a hypothetical decision-maker somewhere inside the brain, James argues that researchers should focus on the interacting physical systems that produce behavior.

That could mean studying cognition as something that emerges through the ongoing relationship between the brain, body, and environment, rather than as a sequence of isolated stages.

The feeling that “I made a decision” may remain perfectly real and useful as a description of human experience, even if there is no single place or process in the brain where that decision occurs. From James’s perspective, what we call a decision may instead be the outcome of interactions among the brain, body, and surrounding world.

This study can be found in the Journal of Cognitive Neuroscience.

Chrissy Newton is a PR professional and the founder of VOCAB Communications. She currently appears on The Discovery Channel and Max and hosts the Rebelliously Curious podcast, which can be found on YouTube and on all audio podcast streaming platforms. Follow her on X: @ChrissyNewton, Instagram: @BeingChrissyNewton, and chrissynewton.com. To contact Chrissy with a story, please email chrissy @ thedebrief.org.