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2.
PLoS Comput Biol ; 19(6): e1011104, 2023 Jun.
Article in English | MEDLINE | ID: mdl-37289753

ABSTRACT

To interpret the sensory environment, the brain combines ambiguous sensory measurements with knowledge that reflects context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages knowledge about the statistical structure of the task to maximize decision accuracy, including knowledge about the dynamics of the environment. We show that its decisions are biased by the dynamically changing task context. The magnitude of this decision bias depends on the observer's continually evolving belief about the current context. The model therefore not only predicts that decision bias will grow as the context is indicated more reliably, but also as the stability of the environment increases, and as the number of trials since the last context switch grows. Analysis of human choice data validates all three predictions, suggesting that the brain leverages knowledge of the statistical structure of environmental change when interpreting ambiguous sensory signals.


Subject(s)
Brain , Decision Making , Humans , Bayes Theorem , Uncertainty , Bias
3.
Nat Neurosci ; 24(7): 998-1009, 2021 07.
Article in English | MEDLINE | ID: mdl-34017131

ABSTRACT

The ability to adapt to changes in stimulus statistics is a hallmark of sensory systems. Here, we developed a theoretical framework that can account for the dynamics of adaptation from an information processing perspective. We use this framework to optimize and analyze adaptive sensory codes, and we show that codes optimized for stationary environments can suffer from prolonged periods of poor performance when the environment changes. To mitigate the adversarial effects of these environmental changes, sensory systems must navigate tradeoffs between the ability to accurately encode incoming stimuli and the ability to rapidly detect and adapt to changes in the distribution of these stimuli. We derive families of codes that balance these objectives, and we demonstrate their close match to experimentally observed neural dynamics during mean and variance adaptation. Our results provide a unifying perspective on adaptation across a range of sensory systems, environments, and sensory tasks.


Subject(s)
Adaptation, Physiological/physiology , Models, Neurological , Neurons/physiology , Animals , Brain/physiology , Humans
4.
Elife ; 72018 07 10.
Article in English | MEDLINE | ID: mdl-29988020

ABSTRACT

Behavior relies on the ability of sensory systems to infer properties of the environment from incoming stimuli. The accuracy of inference depends on the fidelity with which behaviorally relevant properties of stimuli are encoded in neural responses. High-fidelity encodings can be metabolically costly, but low-fidelity encodings can cause errors in inference. Here, we discuss general principles that underlie the tradeoff between encoding cost and inference error. We then derive adaptive encoding schemes that dynamically navigate this tradeoff. These optimal encodings tend to increase the fidelity of the neural representation following a change in the stimulus distribution, and reduce fidelity for stimuli that originate from a known distribution. We predict dynamical signatures of such encoding schemes and demonstrate how known phenomena, such as burst coding and firing rate adaptation, can be understood as hallmarks of optimal coding for accurate inference.


Subject(s)
Action Potentials , Models, Neurological , Neurons/physiology , Sensory Receptor Cells/physiology , Adaptation, Physiological , Bayes Theorem , Humans
5.
Hepatogastroenterology ; 45(24): 2123-6, 1998.
Article in English | MEDLINE | ID: mdl-9951877

ABSTRACT

BACKGROUND/AIMS: Proctocolectomy with ileoanal anastomosis (IAA) has proved to be the most suitable surgical treatment for ulcerative colitis. The aim of this study was to compare the results of IAA according to the evolution of surgical procedures and particularly to compare the results of stapled versus hand-sewn anastomosis. METHODOLOGY: From 1984 to 1996, 37 men and 31 women were operated on in our centre for ulcerative colitis. The anastomosis between the J pouch and the dentate line was handsewn in 35 patients (group 1) and stapled in 33 patients (group 2). RESULTS: The mean operative time was significantly shorter in group 2 as compared with group 1 (265+/-59 vs. 323+/-53, p<0.01, respectively), whereas morbidity and functional results were comparable in both groups. In 10 patients with stapled IAA, a diverting ileostomy was not performed and the morbidity in this group did not increase. CONCLUSIONS: These results suggest that stapled IAA anastomosis is a safe procedure. The stapling technique of IAA simplifies total excision of the rectum and could mean that a diverting ileostomy is not necessary.


Subject(s)
Colitis, Ulcerative/surgery , Proctocolectomy, Restorative/methods , Adult , Female , Humans , Male , Middle Aged , Postoperative Complications/etiology , Reoperation , Retrospective Studies , Surgical Staplers , Suture Techniques , Treatment Outcome
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