Biology subjects

Piantadosi, S.

Publications and source records attributed to Piantadosi, S..

6 recordsLinked to original sources

bioRxiv2026

A number simplex in the human medial temporal lobe

Humans handle numbers nimbly, suggesting a richer neural manifold structure than the prevalent mental number line model. In populations of medial temporal lobe (MTL) neurons in humans performing two simple tasks (dot counting and arithmetic), we find robust neural coding of numerosity that results in high dimensional, simplex-shaped manifolds. This shape affords more flexibility than a linear manifold due to its high shattering dimensionality and expressibility. Dot arrays and Arabic numerals evoked distinct simplicial population codes, yet they were linked by a linearly transferable latent structure within the same task. We find similar simplicial geometry of number representations in large language models (LLMs). Moreover, subjects internally computed arithmetic results were decodable during the calculation period, with decoding accuracy correlating with individual mathematical capacity. Finally, linear transformations of simplicial operand representations modeled the brains conversion of operands into decodable results, suggesting that the brains arithmetic procedures have some resemblance to the attention architecture of LLMs. Together, these findings establish a high dimensional representational foundation for numerical cognition in the brain.

neuroscience↗

bioRxiv2026

Semantic axes in the brain support analogical representations

ABSTRACTIn language models of word meaning, directions in the embedding space often correspond to semantic features that can be reused across different words. For example, a single direction corresponding to gender may differentiate word pairs like "boy/girl", "uncle/aunt" and "king/queen". Here we show that the same principle governs semantically driven neural responses in the human brain. We recorded populations of single neurons during podcast listening and identified word sets with consistent meaning differences. Across fifteen sets, including gender, plural, and negation, we observed consistent vectorial directions, resulting in parallelogram structures within the neural manifold. Deviation from parallelism in large language models (LLMs) predicted corresponding deviations in brain-derived parallelism. Among pronouns, vectors corresponding to case, number and person exhibited parallelogram structures individually and, collectively, obeyed the principle of commutativity, resulting in a prismatic structure. Finally, different semantic variables were preferentially associated with discrete groups of neurons, consistent with energy-efficiency theories. Together, these results establish a geometric foundation for the neural encoding of word meaning.

neuroscience↗

bioRxiv2024

Endogenous opioids facilitate stress-induced binge eating via an insular cortex-claustrum pathway

Stress has been shown to promote the development and persistence of binge eating behaviors. However, the neural circuit mechanisms for stress-induced binge-eating behaviors are largely unreported. The endogenous dynorphin (dyn)/kappa opioid receptor (KOR) opioid neuropeptide system has been well established to be a crucial mediator of the anhedonic component of stress. Here, we aimed to dissect the basis of dynorphinergic control of stress-induced binge-like eating behavior. We first established a mouse behavioral model for stress-induced binge-like eating behaviors. We found that mice exposed to stress increased their food intake of familiar palatable food (high fat, high sugar, HPD) compared to non-stressed mice. Following a brain-wide analysis, we isolated robust cFos-positive cells in the Claustrum (CLA), a subcortical structure with highly abundant KOR expression, following stress-induced binge-eating behavior. We report that KOR signaling in CLA is necessary for this elevated stress-induced binge eating behavior using local pharmacology and local deletion of KOR. In vivo calcium recordings using fiber photometry revealed a disinhibition circuit structure in the CLA during the initiation of HPD feeding bouts. We further established the dynamics of endogenous dynorphinergic control of this behavior using a genetically encoded dynorphin biosensor, Klight. Combined with 1-photon single-cell calcium imaging, we report significant heterogeneity with the CLA population during stress-induced binge eating and such behavior attenuates local dynorphin tone. Furthermore, we isolate the anterior Insular cortex (aIC) as the potential source of endogenous dynorphin afferents in the CLA. By characterizing neural circuits and peptidergic mechanisms within the CLA, we uncover a pathway that implicates endogenous opioid regulation stress-induced binge eating.

neuroscience↗

bioRxiv2020

Envelope Simulation: A New Adaptive Method for Dose Optimization/* Layout-provided Styles */div.standard { margin-bottom: 2ex;}

We present a flexible and general adaptive experimental design for dose finding clinical trials. This method can be applied in sterotypical settings such as determining a maximum tolerated dose, when the dose response relationship is complex, or when the response is an arbitrary quantitative measure. Our design generalizes dose finding methods such as the continual reassessment method (CRM), modified CRM, and estimation with overdose control (EWOC). Similar to those, our design requires a working mathematical model, which assures efficiency, low bias, and a higher fraction of dose selected near the optimum compared to purely operational designs. Unlike typical model based designs that always employ the same model, our method allows individual dose response models tailored to the circumstance. Simulations are also integral to our design allowing it to account for both known and unknown effects of dose on outcome. This method is applicable to general dose finding problems such as those encountered with modern targeted anti-cancer agents, immunotherapies, and titrations against biomarker outcome measures. The method can also support improvements in the design of the experiment being conducted by providing a platform for concurrent simulations to assess the influence of projected design points. Although we present the design in the context of clinical trials, it is equally applicable to experiments with non-human subjects.

cancer biology↗

bioRxiv2019

The Neural Basis of Predictive Pursuit

It remains unclear how and to what extent non-human animals make demanding on-the-fly predictions during pursuit. We studied this problem in a novel laboratory pursuit task that incentivizes prediction of future prey positions. We trained three macaques to perform joystick-controlled pursuit of prey that followed intelligent escape algorithms. Subjects reliably aimed towards the preys likely future positions, indicating that they generate internal predictions and use those predictions to guide behavior. We then developed a generative model that explains real-time pursuit trajectories and showed that our subjects use prey position, velocity, and acceleration to make predictions. We identified neurons in the dorsal anterior cingulate cortex (dACC) whose responses track these three variables. These neurons multiplexed prediction-related variables with a distinct and explicit representation of the preys future position. Our results provide a clear demonstration that the brain can explicitly represent future predictions and highlight the critical role of anterior cingulate cortex for future-oriented cognition.\n\nOne-sentence summaryIn a dynamic pursuit environment, monkeys actively predict future prey positions and dACC neurons encode these future positions.

neuroscience↗

bioRxiv2017

Beyond Reward Prediction Errors: Human Striatum Updates Rule Values During Learning

Humans naturally group the world into coherent categories defined by membership rules. Rules can be learned implicitly by building stimulus-response associations using reinforcement learning (RL) or by using explicit reasoning. We tested if the striatum, in which activation reliably scales with reward prediction error, would track prediction errors in a task that required explicit rule generation. Using functional magnetic resonance imaging during a categorization task, we show that striatal responses to feedback scale with a \"surprise\" signal derived from a Bayesian rule-learning model and are inconsistent with RL prediction error. We also find that striatum and caudal inferior frontal sulcus (cIFS) are involved in updating the likelihood of discriminative rules. We conclude that the striatum, in cooperation with the cIFS, is involved in updating the values assigned to categorization rules when people learn using explicit reasoning.

neuroscience↗