Philosophy and Memory Traces defends two theories of autobiographical memory. One is a bewildering historical view of memories as dynamic patterns in fleeting animal spirits, nervous fluids which rummaged through the pores of brain and body. The other is new connectionism, in which memories are 'stored' only superpositionally, and reconstructed rather than reproduced. Both models, argues John Sutton, depart from static archival metaphors by employing distributed representation, which brings interference and confusion between memory traces. Both raise urgent issues about control (...) of the personal past, and about relations between self and body. Sutton demonstrates the role of bizarre body fluids in moral physiology, as philosophers from Descartes and Locke to Coleridge struggled to control their own innards and impose cognitive discipline on 'the phantasmal chaos of association'. Going on to defend connectionism against Fodor and critics of passive mental representations, he shows how problems of the self are implicated in cognitive science. (shrink)

Theories of language production propose that utterances are constructed by a mechanism that separates linguistic content from linguistic structure, Linguistic content is retrieved from the mental lexicon, and is then inserted into slots in linguistic structures or frames. Support for this kind of model at the phonological level comes from patterns of phonological speech errors. W present an alternative account of these patterns using a connectionist or parallel distributed proceesing (PDP) model that learns to produce sequences of phonological features. The (...) model's errors exhibit some of the properties of human speech errors, specifically, properties that have been attributed to the action of phonological rules, frames, or other structural generalizations. (shrink)

The default view in the epistemology of forgetting is that human memory would be epistemically better if we were not so susceptible to forgetting—that forgetting is in general a cognitive vice. In this paper, I argue for the opposed view: normal human forgetting—the pattern of forgetting characteristic of cognitively normal adult human beings—approximates a virtue located at the mean between the opposed cognitive vices of forgetting too much and remembering too much. I argue, first, that, for any finite cognizer, a (...) certain pattern of forgetting is necessary if her memory is to perform its function well. I argue, second, that, by eliminating clutter from her memory store, this pattern of forgetting improves the overall shape of the subject’s total doxastic state. I conclude by reviewing work in psychology which suggests that normal human forgetting approximates this virtuous pattern of forgetting. (shrink)

Figure 1: A pr ototyp ical exa mple of a three-layer feed forward network, used by Plunkett and M archm an (1 991 ) to simulate learning the past-tense of En glish verbs. The inpu t units encode representations of the three phonemes of the present tense of the artificial words used in this simulation. Th e netwo rk is trained to produce a representation of the phonemes employed in the past tense form and the suffix (/d/, /ed/, or /t/) (...) used on regular verbs. To run the network, each input unit is assigned an activation value o f 0 or 1 , dep ending on whethe r the featu re is present or not. Eac h input unit is conne cted to each of the 30 hidden units by a we ighted conn ection and p rovid es an inp ut to each hidden unit equal to the product of the input unit's activation and the weight. Each hidd en unit's activation is then determined by summing ov er the va lues co ming fro m each inp ut unit to deter mine a netinput, and then applying a non-linear function (e.g., the logistic function 1/(1+e^netinput). Th is whole proced ure is. (shrink)

Rumelhart and McClelland's chapter about learning the past tense created a degree of controversy extraordinary even in the adversarial culture of modern science. It also stimulated a vast amount of research that advanced the understanding of the past tense, inflectional morphology in English and other languages, the nature of linguistic representations, relations between language and other phenomena such as reading and object recognition, the properties of artificial neural networks, and other topics. We examine the impact of the Rumelhart and McClelland (...) model with the benefit of 25 years of hindsight. It is not clear who “won” the debate. It is clear, however, that the core ideas that the model instantiated have been assimilated into many areas in the study of language, changing the focus of research from abstract characterizations of linguistic competence to an emphasis on the role of the statistical structure of language in acquisition and processing. (shrink)

Starting from Marr's ideas about levels of explanation, a theory of the data structures and access processes in human memory is demonstrated on 10 tasks. Functional characteristics of human memory are captured implementation-independently. Our theory generates a multidimensional task classification subsuming existing classifications such as the distinction between tasks that are implicit versus explicit, data driven versus conceptually driven, and simple associative (two-way bindings) versus higher order (threeway bindings), providing a broad basis for new experiments. The formal language clarifies the (...) binding problem in episodic memory, the role of input pathways in both episodic and semantic (lexical) memory, the importance of the input set in episodic memory, and the ubiquitous calculation of an intersection in theories of episodic and lexical access. (shrink)

Neural network models of memory are notorious for catastrophic interference: Old items are forgotten as new items are memorized (French, 1999; McCloskey & Cohen, 1989). While working memory (WM) in human adults shows severe capacity limitations, these capacity limitations do not reflect neural network style catastrophic interference. However, our ability to quickly apprehend the numerosity of small sets of objects (i.e., subitizing) does show catastrophic capacity limitations, and this subitizing capacity and WM might reflect a common capacity. Accordingly, computational investigations (...) (Knops, Piazza, Sengupta, Eger & Melcher, 2014; Sengupta, Surampudi & Melcher, 2014) suggest that mutual inhibition among neurons can explain both kinds of capacity limitations as well as why our ability to estimate the numerosity of larger sets is limited according to a Weber ratio signature. Based on simulations with a saliency map‐like network and mathematical proofs, we provide three results. First, mutual inhibition among neurons leads to catastrophic interference when items are presented simultaneously. The network can remember a limited number of items, but when more items are presented, the network forgets all of them. Second, if memory items are presented sequentially rather than simultaneously, the network remembers the most recent items rather than forgetting all of them. Hence, the tendency in WM tasks to sequentially attend even to simultaneously presented items might not only reflect attentional limitations, but also an adaptive strategy to avoid catastrophic interference. Third, the mean activation level in the network can be used to estimate the number of items in small sets, but it does not accurately reflect the number of items in larger sets. Rather, we suggest that the Weber ratio signature of large number discrimination emerges naturally from the interaction between the limited precision of a numeric estimation system and a multiplicative gain control mechanism. (shrink)

Cognitive systems face a tension between stability and plasticity. The maintenance of long‐term representations that reflect the global regularities of the environment is often at odds with pressure to flexibly adjust to short‐term input regularities that may deviate from the norm. This tension is abundantly clear in speech communication when talkers with accents or dialects produce input that deviates from a listener's language community norms. Prior research demonstrates that when bottom‐up acoustic information or top‐down word knowledge is available to disambiguate (...) speech input, there is short‐term adaptive plasticity such that subsequent speech perception is shifted even in the absence of the disambiguating information. Although such effects are well‐documented, it is not yet known whether bottom‐up and top‐down resolution of ambiguity may operate through common processes, or how these information sources may interact in guiding the adaptive plasticity of speech perception. The present study investigates the joint contributions of bottom‐up information from the acoustic signal and top‐down information from lexical knowledge in the adaptive plasticity of speech categorization according to short‐term input regularities. The results implicate speech category activation, whether from top‐down or bottom‐up sources, in driving rapid adjustment of listeners' reliance on acoustic dimensions in speech categorization. Broadly, this pattern of perception is consistent with dynamic mapping of input to category representations that is flexibly tuned according to interactive processing accommodating both lexical knowledge and idiosyncrasies of the acoustic input. (shrink)

We argue that atomistic learning?learning that requires training only on a novel item to be learned?is problematic for networks in which every weight is available for change in every learning situation. This is potentially significant because atomistic learning appears to be commonplace in humans and most non-human animals. We briefly review various proposed fixes, concluding that the most promising strategy to date involves training on pseudo-patterns along with novel items, a form of learning that is not strictly atomistic, but which (...) looks very much like it ?from the outside? (shrink)

This article argues that rapid eye movement (REM) dreaming is elaborative encoding for episodic memories. Elaborative encoding in REM can, at least partially, be understood through ancient art of memory (AAOM) principles: visualization, bizarre association, organization, narration, embodiment, and location. These principles render recent memories more distinctive through novel and meaningful association with emotionally salient, remote memories. The AAOM optimizes memory performance, suggesting that its principles may predict aspects of how episodic memory is configured in the brain. Integration and segregation (...) are fundamental organizing principles in the cerebral cortex. Episodic memory networks interconnect profusely within the cortex, creating omnidirectional “landmark” junctions. Memories may be integrated at junctions but segregated along connecting network paths that meet at junctions. Episodic junctions may be instantiated during non–rapid eye movement (NREM) sleep after hippocampal associational function during REM dreams. Hippocampal association involves relating, binding, and integrating episodic memories into a mnemonic compositional whole. This often bizarre, composite image has not been present to the senses; it is not “real” because it hyperassociates several memories. During REM sleep, on the phenomenological level, this composite image is experienced as a dream scene. A dream scene may be instantiated as omnidirectional neocortical junction and retained by the hippocampus as an index. On episodic memory retrieval, an external stimulus (or an internal representation) is matched by the hippocampus against its indices. One or more indices then reference the relevant neocortical junctions from which episodic memories can be retrieved. Episodic junctions reach a processing (rather than conscious) level during normal wake to enable retrieval. If this hypothesis is correct, the stuff of dreams is the stuff of memory. (shrink)