The study, published in Nature Neuroscience, took advantage of a rare scientific opportunity. Six patients at the University of California, San Francisco and Washington University in St. Louis had already been implanted with stereotactic electroencephalography depth electrodes for clinical reasons, either drug-resistant epilepsy or treatment-resistant psychiatric conditions. Because standard clinical practice routes these electrodes through the orbitofrontal cortex from lateral to medial, the researchers could simultaneously record neural activity across the entire medial-lateral span of the region in awake, behaving humans, something functional MRI has never been able to do reliably. The orbitofrontal cortex sits directly above bone and air-filled sinuses, which distorts fMRI signals, and the slow blood-oxygen response it measures cannot resolve the millisecond-scale computations that precede a decision.

While the electrodes recorded, the patients played a video-game-style task built in the Unity game engine. Each trial placed the player at the entrance of a corridor containing lit bombs and lit treasure chests. The number of lit bombs indicated how many rubies could be lost if the bombs exploded, which happened on 40 percent of approached trials; the number of lit chests indicated how many rubies could be gained, with chests opening on 70 percent of trials that reached them. Players had six seconds to decide whether to advance down the corridor or skip to the next one. Avoiding carried no gain and no loss. The probabilities were fixed and fully explained beforehand, so every trial posed a clean, known trade-off between potential reward and potential punishment.

The behavioral data were textbook. Players decided quickly, averaging about 1.3 seconds, and their choices were best captured by a prospect theory model, the framework Kahneman and Tversky developed to describe how humans weigh gains and losses. Five of the six participants showed loss aversion, weighting potential losses more heavily than equivalent gains, and utility functions were nonlinear for both outcomes. Reaction times and a Shannon-entropy measure of decision conflict both scaled inversely with the magnitude of subjective value: offers near indifference, such as seven treasure chests against four bombs, produced the slowest, most conflicted decisions, while lopsided offers were dispatched almost instantly.

The neural recordings revealed something no one had directly observed before in humans. The researchers focused on high-frequency activity, oscillations between 70 and 150 hertz that track the collective firing of local neural ensembles. In the 300 milliseconds before a choice, electrodes near the medial orbital sulcus, a fold of tissue in the medial orbitofrontal cortex, showed a burst of increased activity that was stronger on approach trials than on avoidance trials. Electrodes in the lateralmost centimeter and a half of recorded tissue showed the exact opposite: a suppression of activity that was deeper before approach decisions. Electrode position along the medial-lateral axis inversely correlated with pre-decision activity, and the decision-encoding sign flipped systematically from positive near the sulcus to negative roughly 24 millimeters away.

Critically, this gradient was not just a disguised reflection of value. Because the orbitofrontal cortex is known to encode subjective value, the team ran a battery of control analyses. Variance partitioning showed that the upcoming decision explained unique variance in neural activity beginning 400 milliseconds before the choice, over and above anything accounted for by subjective value. An offer-balanced analysis, restricted to ambiguous offers that participants sometimes approached and sometimes avoided, preserved the opposing medial and lateral signals. A two-stage residual regression that first stripped out reward and punishment information left the anatomical gradient intact, while neither reward nor punishment encoding itself showed any medial-lateral organization. The decision signal, in other words, was genuinely about the choice, not merely about the stakes.

The mirrored activity raised an obvious question: were the two regions talking to each other? Noise correlation analysis across 486 electrode pairs found 63 pairs whose trial-to-trial fluctuations were anticorrelated, 45 of which survived Bonferroni correction. These pairs were not random; one electrode sat near the medial orbital sulcus and the other significantly farther lateral, with a mean separation of nearly 18 millimeters. Granger causality tests detected short-lag directed influences in both directions for most pairs, and direct electrical stimulation of the medial region evoked cortico-cortical potentials in 20 of 25 lateral electrodes, while stimulating lateral tissue evoked responses in 20 of 22 medial electrodes. Together, the findings demonstrate functional connectivity across the axis, consistent with, though not proof of, the mutual inhibition that theoretical models of binary choice require.

To give the data a computational shape, the team adapted a two-node mean-field model in which a medial plus node and a lateral minus node inhibit each other. Rewards excite the plus node and punishments inhibit it, and the system settles into one of two attractor basins: a high-activity approach state or a low-activity avoid state. When reward and punishment inputs compete, the model becomes bistable, with two shallow basins separated by an unstable point, and the network stochastically flips between states. Parameter optimization, fitted only to behavior and never to neural data, predicted that single-trial dynamics should alternate between discrete states and that the switching should intensify as conflict rises. Penalizing bistability in the model produced systematically worse behavioral fits, suggesting the brain really does exploit this unstable regime.

The neural data matched those predictions with remarkable fidelity. A Lasso-regularized logistic decoder, trained on high-frequency activity in the 600 milliseconds before the button press, predicted the upcoming choice with 65.5 percent accuracy, significantly above chance in all six participants, and still reached 60.5 percent when value was residualized out. Electrodes with positive decoding coefficients clustered medially and those with negative coefficients laterally, recapitulating the encoding gradient. Applied at 10-millisecond resolution, the decoder exposed rapid, discrete alternations between approach-like and avoid-like states within single trials, each lasting on average about 72 milliseconds. These were not gradual ramps: the magnitude of the neural transient accompanying a switch into the approach state was identical whether the switch came early or late in the trial, favoring discrete attractor dynamics over noisy evidence accumulation of the kind described in perceptual decision models.

State occupancy became biased toward the eventual choice only in the final 450 to 500 milliseconds before the response, and the number of states visited per trial and the rate of transitions both rose robustly with decision conflict, even within a fixed pre-decision window that controlled for reaction time. The findings carry clinical weight as well as theoretical ones. The orbitofrontal cortex is an emerging stimulation target for refractory depression, and previous work found that high-frequency stimulation of the lateral, but not medial, orbitofrontal cortex improved mood in patients with epilepsy. In the new framework, suppressing the lateral node would shut down activity tuned toward avoidance, offering a mechanistic account of why that intervention works and pointing toward more refined anatomical targets. For now, the study delivers something rarer: a live view of the mind changing its own, one flickering neural state at a time.

Subject of Research: Medial and lateral orbitofrontal cortex contributions to human approach-avoidance decision-making measured with intracranial electroencephalography

Article Title: Intracranial recordings in humans reveal differential contributions of medial and lateral orbitofrontal cortex to approach–avoidance decision-making

Article References: Starkweather, C. K., Willbrand, E. H., Sellers, K., Hullett, P. W., Krystal, A. D., Lee, A. M., Weiner, K. S., Willie, J. T., Brunner, P., Hsu, M., Chang, E. F., & Knight, R. T. (2026). Intracranial recordings in humans reveal differential contributions of medial and lateral orbitofrontal cortex to approach–avoidance decision-making. Nature Neuroscience. https://doi.org/10.1038/s41593-026-02444-4

Image Credits: AI Generated

DOI: 10.1038/s41593-026-02444-4

Keywords: orbitofrontal cortex, approach-avoidance conflict, decision-making, intracranial EEG, high-frequency activity, attractor dynamics, prospect theory, loss aversion, mutual inhibition, stereotactic electroencephalography, neural decoding, Nature Neuroscience

The research team set out to test whether the famous separation principle holds equally along the full length of the hippocampus, a seahorse-shaped structure deep in the brain that is essential for storing memories of places and events. Neuroscientists have long divided the hippocampus into a dorsal pole, which in rodents and humans is heavily involved in fine-grained spatial and cognitive processing, and a ventral pole, which is more intimately connected with emotion, stress, and fear circuitry. The two regions differ in their connectivity, their gene expression profiles, and even the electrical properties of their principal neurons. Yet most theories of memory encoding were built on data from the dorsal end, leaving a crucial question unanswered: does the emotional half of the hippocampus follow the same coding rules as the cognitive half?

To find out, the researchers turned to a state-of-the-art combination of behavioral design and miniaturized calcium imaging. They implanted tiny microscopes onto the heads of mice and tracked the activity of hundreds of individual neurons in CA1 — the hippocampus’s main output layer — in both the dorsal and ventral regions simultaneously. Each mouse learned to associate one experimental context, designated context A, with mild foot shocks, while a second, visually distinct context B remained neutral and safe. The animals responded exactly as expected, freezing with fear in context A and exploring calmly in context B. But the neural story underneath that behavior proved far more surprising than any textbook prediction.

When the researchers compared the population activity patterns — the combined firing fingerprints of all recorded neurons — before and after fear conditioning, they found that both dorsal and ventral CA1 changed their representations of the shock-paired environment. Fear learning literally rewrote the spatial map. The critical difference was magnitude. In ventral CA1, the representational shift was substantially larger than in dorsal CA1, and the size of the shift scaled with how strongly each mouse froze: the more the animal feared the context, the more dramatically its ventral map had reorganized. The dorsal maps also changed, but they retained their hallmark quality of staying crisp and stable across repeated exposures.

The real challenge to the canonical theory came during discrimination testing, when mice were shuttled between the threatening and neutral contexts. In dorsal CA1, the two context representations remained clearly distinct, exactly as pattern separation theory demands. In ventral CA1, however, the opposite occurred: the representations of the dangerous and the safe environment became more similar to each other. Rather than pushing the two memories apart to prevent interference, fear learning in the ventral hippocampus pulled them together, creating a zone of overlap between the neural code for threat and the neural code for safety.

The authors interpret this overlap through the mathematical language of attractor dynamics — a framework borrowed from theoretical neuroscience in which stable patterns of network activity behave like valleys in an energy landscape. A neural representation, on this view, is a basin into which activity naturally settles, and the deeper and more sharply separated the basins, the more energy it takes to jump between them. Before fear conditioning, both dorsal and ventral CA1 hold well-separated context representations, and switching between them requires crossing a substantial energy barrier. After conditioning, dorsal CA1’s landscape is essentially unchanged. But ventral CA1’s landscape flattens: the basin corresponding to the threatening context widens and migrates closer to the neutral one, opening more entry points and lowering the energy required to fall into the fear state.

The consequence of this shallower landscape is speed, and the study demonstrates it directly. By analyzing how quickly each region reinstated the threatening context representation when mice transitioned back into context A, the researchers found that ventral CA1 expressed the fear-context code faster and more strongly than dorsal CA1. Even more striking, the relative dominance of the threatening versus neutral representation in ventral CA1 predicted how much each mouse actually froze — a direct link between the geometry of neural codes and the expression of fear behavior. When mice moved into the neutral context, the same logic ran in reverse: ventral CA1 showed the most rapid and pronounced suppression of the threatening representation among the regions examined, consistent with overlapping codes being quick to both engage and disengage.

It is tempting to see this as a computational trade-off, and the authors make that trade-off explicit. Pattern separation and pattern completion have always been two sides of the same coin in hippocampal theory: separating representations guards against interference, while allowing representations to blend permits a memory to be triggered by partial or ambiguous cues. The ventral hippocampus, this work suggests, tilts the balance heavily toward completion. For an animal whose survival depends on detecting danger quickly, the cost of occasionally mistaking a safe context for a dangerous one may be far smaller than the cost of failing to recognize a lethal threat in time. Rapid retrieval of fear memories, even at the price of some discriminative precision, may be an evolutionarily rational bargain.

The findings also help resolve a long-standing tension in the literature on hippocampal fear. Earlier work showed that ventral CA1 contains ensembles whose correlated activity retrieves contextual fear memories, that ventral hippocampal projections to the prefrontal cortex and amygdala regulate anxiety and avoidance, and that inactivating the ventral hippocampus alters fear expression and extinction. What remained unclear was how these emotional functions coexisted with the region’s evident role in spatial coding. The new results propose a unifying principle: the ventral hippocampus encodes space, but it warps its spatial codes in the service of valence, reshaping them so that emotionally significant environments become easier to summon from memory.

The implications extend beyond basic science. Overlapping or overly generalized context representations are a suspected hallmark of maladaptive fear in conditions such as post-traumatic stress disorder, where innocuous environments come to trigger full-blown threat responses. If the ventral hippocampal mechanism described here generalizes to humans, therapies aimed at restoring separability between threat and safety codes — rather than merely dampening fear output — could offer a more targeted route to treatment. For now, the study delivers its most memorable lesson in the cleanest terms: sometimes the brain remembers better not by keeping memories apart, but by letting danger and safety share the same neural ground, ready to tip into fear the instant the world turns threatening.

Subject of Research: How fear learning reshapes spatial context representations in the ventral versus dorsal hippocampus to enable rapid fear memory retrieval in mice

Article Title: Overlapping representations in the ventral hippocampus support rapid fear memory retrieval

Article References: Rozeske, R. R., Runtz, L., Lee, J. Q., Keinath, A. T., Sossin, A., & Brandon, M. P. (2026). Overlapping representations in the ventral hippocampus support rapid fear memory retrieval. Nature Neuroscience. https://doi.org/10.1038/s41593-026-02435-5

Image Credits: AI Generated

DOI: 10.1038/s41593-026-02435-5

Keywords: hippocampus, fear conditioning, memory retrieval, place cells, calcium imaging, attractor dynamics, pattern separation, ventral CA1, dorsal CA1, neuroscience, spatial memory, contextual fear