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Advances in machine learning coupled with the abundances of training data has facilitated the deep learning era, which has demonstrated its ability and effectiveness in solving complex detection and recognition problems. In general application areas with elements of machine learning have seen exponential growth with promising new and sophisticated solutions to complex learning problems. In computer vision, the challenge related to the detection of known objects in a scene is a thing of the past. With the tremendous increase in detection accuracies, some close to that of human detection, there are several areas still lagging in computer vision and machine learning where improvements may call for more architectural designs. In this paper, we propose a physiologically inspired model for scene understanding that encodes three key components: object location, size and category. Our aim is to develop an energy efficient artificial intelligent model for naturalistic scene understanding capable of deploying on a low power neuromorphic hardware. We have reviewed recent advances in deep learning architecture that have taken inspiration from human or primate learning systems and provided direct to future advancement on deep learning with inspiration from physiological experiments. Upon a review of areas that have benefitted from deep learning, we provide recommendations for enhancing those areas that might have stalled or grinded to a halt with little or no significant improvement. [ABSTRACT FROM AUTHOR]

Metacognition refers to the ability to be aware of one's own cognition. Ample evidence indicates that metacognition in the human primate is highly dissociable from cognition, specialized across domains, and subserved by distinct neural substrates. However, these aspects remain relatively understudied in macaque monkeys. In the present study, we investigated the functionality of macaque metacognition by combining a confidence proxy, hierarchical Bayesian meta-d′ computational modelling, and a single-pulse transcranial magnetic stimulation technique. We found that Brodmann area 46d (BA46d) played a critical role in supporting metacognition independent of task performance; we also found that the critical role of this region in meta-calculation was time-sensitive. Additionally, we report that macaque metacognition is highly domain-specific with respect to memory and perception decisions. These findings carry implications for our understanding of metacognitive introspection within the primate lineage. Use of transcranial magnetic stimulation in macaques reveals a potential role for Brodmann area 46d (BA46d) in supporting metacognition, or the ability to be aware of one's own thoughts. [ABSTRACT FROM AUTHOR]

A recent virtual-lesion study using inhibitory repetitive transcranial magnetic stimulation (rTMS) confirmed the causal behavioral relevance of the precuneus in the evaluation of one's own memory performance (aka mnemonic metacognition). This study's goal is to elucidate how these TMS-induced neuromodulatory effects might relate to the neural correlates and be modulated by individual anatomical profiles in relation to meta-memory. In a within-subjects design, we assessed the impact of 20-min rTMS over the precuneus, compared to the vertex, across three magnetic resonance imaging (MRI) neuro-profiles on 18 healthy subjects during a memory versus a perceptual task. Task-based functional MRI revealed that BOLD signal magnitude in the precuneus is associated with variation in individual meta-memory efficiency. Moreover, individuals with higher resting-state functional connectivity (rs-fcMRI) between the precuneus and the hippocampus, or smaller gray matter volume in the stimulated precuneal region exhibit considerably higher vulnerability to the TMS effect. These effects were not observed in the perceptual domain. Thus, we provide compelling evidence in outlining a possible circuit encompassing the precuneus and its mnemonic midbrain neighbor the hippocampus at the service of realizing our meta-awareness during memory recollection of episodic details. Highlights: TMS disrupts the correlation between BOLD activity and meta-memory ability. TMS effect is modulated by rs-fcMRI between precuneus and hippocampus. Individuals with greater precuneal gray matter volume more immune to TMS effect. [ABSTRACT FROM AUTHOR]

The fractionation view holds that distinct cognitive operations are mediated by subregions of the inferior parietal lobule (IPL). Within IPL, we hypothesised that retrieval-related activity in different parts of the right supramarginal gyrus (rSMG) may be modulated differentially by information acquired via different combinations of attention signals at encoding. We had two groups of participants watch a 42-min TV episode and, after a 24-hr delay, perform a temporal-order judgment task during fMRI. Each retrieval trial comprised three images presented sequentially, requiring participants to judge the temporal order between the first and last images while ignoring the second image ('distractor'). We manipulated the bottom-up factor by presenting distractors that were extracted from either an event-boundary or a non-boundary of the movie. The top-down factor was manipulated by instructing one group perform a segmentation task reporting the event-boundaries at encoding, while the other group watched the movie passively. Across groups, we found that the stimulus-related factor modulated retrieval activation in the anterior rSMG (areas PFt and PFop), whereas the goal-related influence of prior segmentation interacted with this effect in the middle rSMG (area PF), demonstrating IPL segregation during retrieval as a function of prior bottom-up vs. top-down attention signals. [ABSTRACT FROM AUTHOR]