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A new theoretical framework argues that the long-standing split between computational functionalism and biological naturalism misses how real brains actually compute. The authors propose “biological computationalism,” the idea that neural computation is inseparable from the brain’s physical, hybrid, and energy-constrained dynamics rather than an abstract algorithm running on hardware. In this view, discrete neural events […]

A new theoretical framework argues that the long-standing split between computational functionalism and biological naturalism misses how real brains actually compute. The authors propose “biological computationalism,” the idea that neural computation is inseparable from the brain’s physical, hybrid, and energy-constrained dynamics rather than an abstract algorithm running on hardware. In this view, discrete neural events

A new theoretical framework argues that the long-standing split between computational functionalism and biological naturalism misses how real brains actually compute. The authors propose “biological computationalism,” the idea that neural computation is inseparable from the brain’s physical, hybrid, and energy-constrained dynamics rather than an abstract algorithm running on hardware. In this view, discrete neural events

Some individuals rely heavily on visual and sound cues when making decisions, and this sensitivity can lead to persistent maladaptive choices. When cue–outcome associations shift, these individuals struggle to update their beliefs, continuing to follow outdated signals even when doing so becomes risky.​ 

Some individuals rely heavily on visual and sound cues when making decisions, and this sensitivity can lead to persistent maladaptive choices. When cue–outcome associations shift, these individuals struggle to update their beliefs, continuing to follow outdated signals even when doing so becomes risky.​  Read more at Cerebratech ​ 

Some individuals rely heavily on visual and sound cues when making decisions, and this sensitivity can lead to persistent maladaptive choices. When cue–outcome associations shift, these individuals struggle to update their beliefs, continuing to follow outdated signals even when doing so becomes risky.​  Read more at Cerebratech ​  Read more at Cerebratech ​ 

People instinctively mimic others’ facial expressions, but new research shows we do this far more with joyful faces than with sadness or anger—and that the intensity of mimicry predicts how much we trust someone. Across three experiments using EMG and behavioral tasks, participants copied smiles more readily and rated smiling individuals as more attractive, confident,

People instinctively mimic others’ facial expressions, but new research shows we do this far more with joyful faces than with sadness or anger—and that the intensity of mimicry predicts how much we trust someone. Across three experiments using EMG and behavioral tasks, participants copied smiles more readily and rated smiling individuals as more attractive, confident,

uilt and shame arise from different cognitive triggers and rely on distinct neural systems to guide compensatory behavior. Using a controlled game that manipulated both harm and responsibility, researchers showed that guilt is more strongly driven by the severity of harm caused, while shame is more strongly shaped by how responsible someone feels for that

uilt and shame arise from different cognitive triggers and rely on distinct neural systems to guide compensatory behavior. Using a controlled game that manipulated both harm and responsibility, researchers showed that guilt is more strongly driven by the severity of harm caused, while shame is more strongly shaped by how responsible someone feels for that