Dynamics of neural population responses in prefrontal cortex indicate changes of mind on single trials.

Curr Biol

Department of Neurobiology, Stanford University School of Medicine, Fairchild Building D209, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Beckman Center, 279 Campus Drive, Room B202, Stanford, CA 94305, USA.

Published: July 2014

Decision making is a complex process in which different sources of information are combined into a decision variable (DV) that guides action [1, 2]. Neurophysiological studies have typically sought insight into the dynamics of the decision-making process and its neural mechanisms through statistical analysis of large numbers of trials from sequentially recorded single neurons or small groups of neurons [3-6]. However, detecting and analyzing the DV on individual trials has been challenging [7]. Here we show that by recording simultaneously from hundreds of units in prearcuate gyrus of macaque monkeys performing a direction discrimination task, we can predict the monkey's choices with high accuracy and decode DV dynamically as the decision unfolds on individual trials. This advance enabled us to study changes of mind (CoMs) that occasionally happen before the final commitment to a decision [8-10]. On individual trials, the decoded DV varied significantly over time and occasionally changed its sign, identifying a potential CoM. Interrogating the system by random stopping of the decision-making process during the delay period after stimulus presentation confirmed the validity of identified CoMs. Importantly, the properties of the candidate CoMs also conformed to expectations based on prior theoretical and behavioral studies [8]: they were more likely to go from an incorrect to a correct choice, they were more likely for weak and intermediate stimuli than for strong stimuli, and they were more likely earlier in the trial. We suggest that simultaneous recording of large neural populations provides a good estimate of DV and explains idiosyncratic aspects of the decision-making process that were inaccessible before.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4191655PMC
http://dx.doi.org/10.1016/j.cub.2014.05.049DOI Listing

Publication Analysis

Top Keywords

decision-making process
12
individual trials
12
changes mind
8
trials
5
dynamics neural
4
neural population
4
population responses
4
responses prefrontal
4
prefrontal cortex
4
cortex indicate
4

Similar Publications

Introduction: There is a lack of clinical evidence supporting the decision-making process between high tibial osteotomy (HTO) and unicomparmental knee arthroplasty (UKA) in gray zone indication, such as moderate medial osteoarthritis with moderate varus alignment. This study compared the outcomes between HTO and UKA in such cases and assessed the risk factor for not maintaining clinical improvements.

Materials And Methods: We retrospectively reviewed 65 opening-wedge HTOs and 55 UKAs with moderate medial osteoarthritis (Kellgren-Lawrence grade ≥ 3 and Ahlback grade < 3) and moderate varus alignment (5°< Hip-Knee-Ankle angle < 10°) over 3 years follow-up.

View Article and Find Full Text PDF

Introduction: The aim of this study was to establish an international consensus statement on the indications for the addition of a patellofemoral joint arthroplasty (PFJA) in patients with a unicondylar knee arthroplasty (UKA) and symptomatic progression of patellofemoral compartment osteoarthritis.

Materials And Methods: A systematic review of the literature was conducted, and the results used to inform the development of a statement by an expert working group. This was then evaluated and modified, using a Delphi process, by members of the European Knee Society (EKS).

View Article and Find Full Text PDF

Acute diverticulitis (AD), an inflammatory complication of diverticulosis, affects around 4% of individuals with diverticulosis, with increased incidence in older populations. This study aims to assess the impact of sarcopenia, the age-related loss of muscle mass, on the clinical decision-making and outcomes of patients with AD. A retrospective study was conducted on 237 patients admitted to the Emergency Department (ED) between January 2014 and February 2022.

View Article and Find Full Text PDF

Characterization of Hazelnut Trees in Open Field Through High-Resolution UAV-Based Imagery and Vegetation Indices.

Sensors (Basel)

January 2025

Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.

The increasing demand for hazelnut kernels is favoring an upsurge in hazelnut cultivation worldwide, but ongoing climate change threatens this crop, affecting yield decreases and subject to uncontrolled pathogen and parasite attacks. Technical advances in precision agriculture are expected to support farmers to more efficiently control the physio-pathological status of crops. Here, we report a straightforward approach to monitoring hazelnut trees in an open field, using aerial multispectral pictures taken by drones.

View Article and Find Full Text PDF

The use of Deep Learning algorithms in the domain of Decision Making for Autonomous Vehicles has garnered significant attention in the literature in recent years, showcasing considerable potential. Nevertheless, most of the solutions proposed by the scientific community encounter difficulties in real-world applications. This paper aims to provide a realistic implementation of a hybrid Decision Making module in an Autonomous Driving stack, integrating the learning capabilities from the experience of Deep Reinforcement Learning algorithms and the reliability of classical methodologies.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!