45 research outputs found
Recurrence is required to capture the representational dynamics of the human visual system.
The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object processing is commonly viewed and studied as a feedforward process. Here, we measure and model the rapid representational dynamics across multiple stages of the human ventral stream using time-resolved brain imaging and deep learning. We observe substantial representational transformations during the first 300 ms of processing within and across ventral-stream regions. Categorical divisions emerge in sequence, cascading forward and in reverse across regions, and Granger causality analysis suggests bidirectional information flow between regions. Finally, recurrent deep neural network models clearly outperform parameter-matched feedforward models in terms of their ability to capture the multiregion cortical dynamics. Targeted virtual cooling experiments on the recurrent deep network models further substantiate the importance of their lateral and top-down connections. These results establish that recurrent models are required to understand information processing in the human ventral stream
Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders
Recurrent connections in the visual cortex are thought to aid object
recognition when part of the stimulus is occluded. Here we investigate if and
how recurrent connections in artificial neural networks similarly aid object
recognition. We systematically test and compare architectures comprised of
bottom-up (B), lateral (L) and top-down (T) connections. Performance is
evaluated on a novel stereoscopic occluded object recognition dataset. The task
consists of recognizing one target digit occluded by multiple occluder digits
in a pseudo-3D environment. We find that recurrent models perform significantly
better than their feedforward counterparts, which were matched in parametric
complexity. Furthermore, we analyze how the network's representation of the
stimuli evolves over time due to recurrent connections. We show that the
recurrent connections tend to move the network's representation of an occluded
digit towards its un-occluded version. Our results suggest that both the brain
and artificial neural networks can exploit recurrent connectivity to aid
occluded object recognition.Comment: 13 pages, 5 figures, accepted at the 28th International Conference on
Artificial Neural Networks, published in Springer Lecture Notes in Computer
Science vol 1172
Where Nothing Happened: The Experience of War Captivity and Levinas’s Concept of the ‘There Is’
This article takes as its subject matter the juridico-political space of the prisoner of war (POW) camp. It sets out to determine the nature of this space by looking at the experience of war captivity by Jewish members of the Western forces in World War II, focusing on the experience of Emmanuel Levinas, who spent 5 years in German war captivity. On the basis of a historical analysis of the conditions in which Levinas spent his time in captivity, it argues that the POW camp was a space of indifference that was determined by the legal exclusion of prisoners from both war and persecution. Held behind the stage of world events, prisoners were neither able to exercise their legal agency nor released from law into a realm of extra-legal violence. Through a close reading of Levinas’s early concept of the ‘there is’ [il y a], the article seeks to establish the impact on prisoners of prolonged confinement in such a space. It sets out how prisoners’ subjectivity dissolved in the absence of meaningful relations with others and identifies the POW camp as a space in which existence was reduced to indeterminate, impersonal being
On the causes of economic growth in Europe: why did agricultural labour productivity not converge between 1950 and 2005?
The objective of this study is to make a further contribution to the debate on the causes of economic growth in the European Continent. It explains why agricultural labour productivity differences did not converge between 1950 and 2005 in Europe. We propose an econometric model, one combining both proximate and fundamental causes of economic growth. The results show that the continuous exit of labour power from the sector, coupled with the increased use of productive factors originating in other sectors of the economy, caused the efficiency of agricultural workers to rise. However, we offer a complete explanation of the role played by institutions and geographical factors. Thus, we detect a direct and inverse relation between membership of the EU and the Communist bloc and the productivity of agricultural labour. In addition, strong support for agriculture affected productivity negatively
The role of war in deep transitions: exploring mechanisms, imprints and rules in sociotechnical systems
This paper explores in what ways the two world wars influenced the development of sociotechnical systems underpinning the culmination of the first deep transition. The role of war is an underexplored aspect in both the Techno-Economic Paradigms (TEP) approach and the Multi-level perspective (MLP) which form the two key conceptual building blocks of the Deep Transitions (DT) framework. Thus, we develop a conceptual approach tailored to this particular topic which integrates accounts of total war and mechanisms of war from historical studies and imprinting from organisational studies with the DT framework’s attention towards rules and meta-rules. We explore in what ways the three sociotechnical systems of energy, food, and transport were affected by the emergence of new demand pressures and logistical challenges during conditions of total war; how war impacted the directionality of sociotechnical systems; the extent to which new national and international policy capacities emerged during wartime in the energy, food, and transport systems; and the extent to which these systems were influenced by cooperation and shared sacrifice under wartime conditions. We then explore what lasting changes were influenced by the two wars in the energy, food, and transport systems across the transatlantic zone. This paper seeks to open up a hitherto neglected area in analysis on sociotechnical transitions and we discuss the importance of further research that is attentive towards entanglements of warfare and the military particularly in the field of sustainability transitions
Lost in Culture: C&A’s Failure in the United States, 1946-1964
In 1945–46, the Brenninkmeijer family, owner of the C&A retail group, discussed to set up a new business in New York. C&A was a thriving Dutch clothing retailer who had successfully set up subsidiaries in Germany (1911) and Britain (1922). After World War II, the political situation in Europe, especially the threat of communism, endangered C&A’s business model. The future, both for the operative retailing business and the family’s wealth, seemed to be in the United States, the safe haven of capitalism. Entering the US mass retail market faced several problems. The notorious lack of hard currency was more of a technical problem, which was quickly overcome. The sheer size of the American market and the number of potent competitors were a true challenge. A team of Brenninkmeijers with a lot of experience of the British market explored the situation in the United States and convinced the rest of the family entrepreneurs in spring 1946 daring the venture. This article describes the various leadership challenges faced by the Brenninkmeijers, their actions, and why they failed in the end because they underestimated the cultural differences between the US market and the European markets