View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.     

Lesions in the Central Nucleus of the Amygdala: Discriminative Avoidance Learning, Discriminative Approach Learning, and Cingulothalamic Training-Induced Neuronal Activity

The amygdala is critically involved in discriminative avoidance learning. Large lesions of the amygdala block discriminative avoidance learning and abolish cingulothalamic training-induced neuronal activity. These results indicated that amygdalar processing is critical for cingulothalamic plasticity. The larger lesions did not allow differentiation of the specific functioning of various amygdalar nuclei. Anatomical analysis showed that damage in the central (CE) nucleus of the amygdala was correlated with the severity of the behavioral deficit. The present study was carried out to determine whether smaller lesions, centered in the CE nucleus, would impair discriminative avoidance learning and block cingulothalamic plasticity. In addition, the possible role of the CE nucleus in appetitively motivated discriminative approach learning was examined for the first time. New Zealand White rabbits with CE nuclear lesions were first trained in the discriminative approach task. After attaining asymptotic performance, discriminative avoidance training sessions were alternated with continuing approach training sessions, one session each day. The rabbits with lesions were severely impaired in avoidance learning but showed no impairment of approach learning. Surprisingly, the attenuating effects of the lesions on cingulothalamic training-induced neuronal activity were more prevalent during approach learning than during avoidance learning. These results indicated that avoidance learning can be impaired by lesions centered in the CE nucleus that leave cingulothalamic plasticity largely intact and that the CE nucleus is involved in extra-cingulothalamic learning processes.     

On the emergence of modern humans

The emergence of modern humans with their extraordinary cognitive capacities is ascribed to a novel type of cognitive computational process (sustained non-routine multi-level operations) required for abstract projectuality, held to be the common denominator of the cognitive capacities specific to modern humans. A brain operation (latching) that allows this novel computational process is proposed as well as a physics-inspired mechanism that could explain its rather recent emergence without invoking unlikely genetic or structural changes.     

自尊的认知神经机制

自尊是个体对自己总体的情感性评价。自尊有助于促进个体的心理健康,帮助个体应对威胁,具有重要的适应价值。近年来随着社会认知神经科学的兴起,关于自尊的认知神经机制的研究日益增多,主要涉及三个方面:1)自尊与大脑的结构(如海马体积、前扣带回等区域的灰质体积)和功能(静息态下的默认网络活动以及脑区之间的功能联结性)存在一定的关联;2)自尊调节大脑对威胁的反应,与高自尊个体相比,低自尊个体面对威胁时产生更强的防御性反应,自尊通过影响个体面对威胁时的大脑活动帮助个体更好地应对威胁;3)自我评价过程涉及大脑前额叶、眶额叶、扣带回等多个脑区,自尊调节个体在自我评价过程中的大脑活动。总之,自尊作为个体重要的人格特质,与大脑的结构、功能以及活动状态等都具有一定的关系;这些发现在一定程度上揭示了自尊的神经机制,加深了对自尊及其功能的理解。