Search

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility., Author summary Neuroscience is experiencing a rapid growth of data streams characterizing composition, connectivity, and activity of brain networks in ever increasing details. Data-driven modeling will be essential to integrate these multimodal and complex data into predictive simulations to advance our understanding of brain function and mechanisms. To enable efficient development and sharing of such large-scale models utilizing diverse data types, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is already supported by several popular tools for model building, simulations, and visualization. It is free and open for everyone to use and build upon and will enable increased efficiency, reproducibility, and scientific exchange in the community.

A combined behavioral and brain imaging study shows how sensory awareness and stimulus visibility can influence the dynamics of decision-making in humans., Human decisions are based on accumulating evidence over time for different options. Here we ask a simple question: How is the accumulation of evidence affected by the level of awareness of the information? We examined the influence of awareness on decision-making using combined behavioral methods and magneto-encephalography (MEG). Participants were required to make decisions by accumulating evidence over a series of visually presented arrow stimuli whose visibility was modulated by masking. Behavioral results showed that participants could accumulate evidence under both high and low visibility. However, a top-down strategic modulation of the flow of incoming evidence was only present for stimuli with high visibility: once enough evidence had been accrued, participants strategically reduced the impact of new incoming stimuli. Also, decision-making speed and confidence were strongly modulated by the strength of the evidence for high-visible but not low-visible evidence, even though direct priming effects were identical for both types of stimuli. Neural recordings revealed that, while initial perceptual processing was independent of visibility, there was stronger top-down amplification for stimuli with high visibility than low visibility. Furthermore, neural markers of evidence accumulation over occipito-parietal cortex showed a strategic bias only for highly visible sensory information, speeding up processing and reducing neural computations related to the decision process. Our results indicate that the level of awareness of information changes decision-making: while accumulation of evidence already exists under low visibility conditions, high visibility allows evidence to be accumulated up to a higher level, leading to important strategical top-down changes in decision-making. Our results therefore suggest a potential role of awareness in deploying flexible strategies for biasing information acquisition in line with one's expectations and goals., Author Summary When making a decision, we gather evidence for the different options and ultimately choose on the basis of the accumulated evidence. A fundamental question is whether and how conscious awareness of the evidence changes this decision-making process. Here, we examined the influence of sensory awareness on decision-making using behavioral studies and magneto-encephalographic recordings in human participants. In our task, participants had to indicate the prevailing direction of five arrows presented on a screen that each pointed either left or right, and in different trials these arrows were either easy to see (high visibility) or difficult to see (low visibility). Behavioral and neural recordings show that evidence accumulation changed from a linear to a non-linear integration strategy with increasing stimulus visibility. In particular, the impact of later evidence was reduced when more evidence had been accrued, but only for highly visible information. By contrast, barely perceptible arrows contributed equally to a decision because participants needed to continue to accumulate evidence in order to make an accurate decision. These results suggest that consciousness may play a role in decision-making by biasing the accumulation of new evidence.

We compared conscious and nonconscious processing of briefly flashed words using a visual masking procedure while recording intracranial electroencephalogram (iEEG) in ten patients. Nonconscious processing of masked words was observed in multiple cortical areas, mostly within an early time window (, Author Summary What is the neural signature of the conscious perception of a visual stimulus? To address this question, we recorded neural activity directly from the brains of human subjects (who were undergoing neural surgery for medical reasons). This rare opportunity afforded greater spatial and temporal resolution than noninvasive methods used previously to probe the neural basis of consciousness. We compared neural activity concomitant with conscious and nonconscious processing of words by using a visual masking procedure that allowed us to manipulate the conscious visibility of briefly masked words. Nonconscious processing of words elicited short-lasting activity across multiple cortical areas, including parietal and visual areas. In sharp contrast, only consciously perceived words were accompanied by long-lasting effects (>200 ms) across a great variety of cortical sites, with a special involvement of the prefrontal lobes. This sustained pattern of neural activity was characterized by a specific increase of coherence between distant areas, suggesting conscious perception is broadcasted widely across the cortex., A neural signature of the conscious perception of words by humans is readable in intracranial electrophysiological recordings, which afford relatively high spatial- and temporal-resolution measurements of neural activity.

Parsing a mental operation into components, characterizing the parallel or serial nature of this flow, and understanding what each process ultimately contributes to response time are fundamental questions in cognitive neuroscience. Here we show how a simple theoretical model leads to an extended set of predictions concerning the distribution of response time and its alteration by simultaneous performance of another task. The model provides a synthesis of psychological refractory period and random-walk models of response time. It merely assumes that a task consists of three consecutive stages-perception, decision based on noisy integration of evidence, and response-and that the perceptual and motor stages can operate simultaneously with stages of another task, while the central decision process constitutes a bottleneck. We designed a number-comparison task that provided a thorough test of the model by allowing independent variations in number notation, numerical distance, response complexity, and temporal asynchrony relative to an interfering probe task of tone discrimination. The results revealed a parsing of the comparison task in which each variable affects only one stage. Numerical distance affects the integration process, which is the only step that cannot proceed in parallel and has a major contribution to response time variability. The other stages, mapping the numeral to an internal quantity and executing the motor response, can be carried out in parallel with another task. Changing the duration of these processes has no significant effect on the variance.