549 research outputs found

    Selective Decoding in Associative Memories Based on Sparse-Clustered Networks

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    Associative memories are structures that can retrieve previously stored information given a partial input pattern instead of an explicit address as in indexed memories. A few hardware approaches have recently been introduced for a new family of associative memories based on Sparse-Clustered Networks (SCN) that show attractive features. These architectures are suitable for implementations with low retrieval latency, but are limited to small networks that store a few hundred data entries. In this paper, a new hardware architecture of SCNs is proposed that features a new data-storage technique as well as a method we refer to as Selective Decoding (SD-SCN). The SD-SCN has been implemented using a similar FPGA used in the previous efforts and achieves two orders of magnitude higher capacity, with no error-performance penalty but with the cost of few extra clock cycles per data access.Comment: 4 pages, Accepted in IEEE Global SIP 2013 conferenc

    Hemodynamic responses in human multisensory and auditory association cortex to purely visual stimulation

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    BACKGROUND: Recent findings of a tight coupling between visual and auditory association cortices during multisensory perception in monkeys and humans raise the question whether consistent paired presentation of simple visual and auditory stimuli prompts conditioned responses in unimodal auditory regions or multimodal association cortex once visual stimuli are presented in isolation in a post-conditioning run. To address this issue fifteen healthy participants partook in a "silent" sparse temporal event-related fMRI study. In the first (visual control) habituation phase they were presented with briefly red flashing visual stimuli. In the second (auditory control) habituation phase they heard brief telephone ringing. In the third (conditioning) phase we coincidently presented the visual stimulus (CS) paired with the auditory stimulus (UCS). In the fourth phase participants either viewed flashes paired with the auditory stimulus (maintenance, CS-) or viewed the visual stimulus in isolation (extinction, CS+) according to a 5:10 partial reinforcement schedule. The participants had no other task than attending to the stimuli and indicating the end of each trial by pressing a button. RESULTS: During unpaired visual presentations (preceding and following the paired presentation) we observed significant brain responses beyond primary visual cortex in the bilateral posterior auditory association cortex (planum temporale, planum parietale) and in the right superior temporal sulcus whereas the primary auditory regions were not involved. By contrast, the activity in auditory core regions was markedly larger when participants were presented with auditory stimuli. CONCLUSION: These results demonstrate involvement of multisensory and auditory association areas in perception of unimodal visual stimulation which may reflect the instantaneous forming of multisensory associations and cannot be attributed to sensation of an auditory event. More importantly, we are able to show that brain responses in multisensory cortices do not necessarily emerge from associative learning but even occur spontaneously to simple visual stimulation

    AI of Brain and Cognitive Sciences: From the Perspective of First Principles

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    Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation. Despite these powerful applications, there are still many tasks in our daily life that are rather simple to humans but pose great challenges to AI. These include image and language understanding, few-shot learning, abstract concepts, and low-energy cost computing. Thus, learning from the brain is still a promising way that can shed light on the development of next-generation AI. The brain is arguably the only known intelligent machine in the universe, which is the product of evolution for animals surviving in the natural environment. At the behavior level, psychology and cognitive sciences have demonstrated that human and animal brains can execute very intelligent high-level cognitive functions. At the structure level, cognitive and computational neurosciences have unveiled that the brain has extremely complicated but elegant network forms to support its functions. Over years, people are gathering knowledge about the structure and functions of the brain, and this process is accelerating recently along with the initiation of giant brain projects worldwide. Here, we argue that the general principles of brain functions are the most valuable things to inspire the development of AI. These general principles are the standard rules of the brain extracting, representing, manipulating, and retrieving information, and here we call them the first principles of the brain. This paper collects six such first principles. They are attractor network, criticality, random network, sparse coding, relational memory, and perceptual learning. On each topic, we review its biological background, fundamental property, potential application to AI, and future development.Comment: 59 pages, 5 figures, review articl

    Course 13 Of the evolution of the brain

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    The Penicillin for the Emergency Department Outpatient treatment of CELLulitis (PEDOCELL) trial: update to the study protocol and detailed statistical analysis plan (SAP)

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    Background: Cellulitis is a painful, potentially serious, infectious process of the dermal and subdermal tissues and represents a significant disease burden. The statistical analysis plan (SAP) for the Penicillin for the Emergency Department Outpatient treatment of CELLulitis (PEDOCELL) trial is described here. The PEDOCELL trial is a multicentre, randomised, parallel-arm, double-blinded, non-inferiority clinical trial comparing the efficacy of flucloxacillin (monotherapy) with combination flucloxacillin/phenoxymethylpenicillin (dual therapy) for the outpatient treatment of cellulitis in the emergency department (ED) setting. To prevent outcome reporting bias, selective reporting and data-driven results, the a priori-defined, detailed SAP is presented here. Methods/design: Patients will be randomised to either orally administered flucloxacillin 500 mg four times daily and placebo or orally administered 500 mg of flucloxacillin four times daily and phenoxymethylpenicillin 500 mg four times daily. The trial consists of a 7-day intervention period and a 2-week follow-up period. Study measurements will be taken at four specific time points: at patient enrolment, day 2-3 after enrolment and commencing treatment (early clinical response (ECR) visit), day 8-10 after enrolment (end-of-treatment (EOT) visit) and day 14-21 after enrolment (test-of-cure (TOC) visit). The primary outcome measure is investigator-determined clinical response measured at the TOC visit. The secondary outcomes are as follows: lesion size at ECR, clinical treatment failure at each follow-up visit, adherence and persistence of trial patients with orally administered antibiotic therapy at EOT, health-related quality of life (HRQoL) and pharmacoeconomic assessments. The plan for the presentation and comparison of baseline characteristics and outcomes is described in this paper. Discussion: This trial aims to establish the non-inferiority of orally administered flucloxacillin monotherapy with orally administered flucloxacillin/phenoxymethylpenicillin dual therapy for the ED-directed outpatient treatment of cellulitis. In doing so, this trial will bridge a knowledge gap in this understudied and common condition and will be relevant to clinicians across several different disciplines. The SAP for the PEDOCELL trial was developed a priori in order to minimise analysis bias

    Network analysis of the cellular circuits of memory

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    Intuitively, memory is conceived as a collection of static images that we accumulate as we experience the world. But actually, memories are constantly changing through our life, shaped by our ongoing experiences. Assimilating new knowledge without corrupting pre-existing memories is then a critical brain function. However, learning and memory interact: prior knowledge can proactively influence learning, and new information can retroactively modify memories of past events. The hippocampus is a brain region essential for learning and memory, but the network-level operations that underlie the continuous integration of new experiences into memory, segregating them as discrete traces while enabling their interaction, are unknown. Here I show a network mechanism by which two distinct memories interact. Hippocampal CA1 neuron ensembles were monitored in mice as they explored a familiar environment before and after forming a new place-reward memory in a different environment. By employing a network science representation of the co-firing relationships among principal cells, I first found that new associative learning modifies the topology of the cells’ co-firing patterns representing the unrelated familiar environment. I fur- ther observed that these neuronal co-firing graphs evolved along three functional axes: the first segregated novelty; the second distinguished individual novel be- havioural experiences; while the third revealed cross-memory interaction. Finally, I found that during this process, high activity principal cells rapidly formed the core representation of each memory; whereas low activity principal cells gradually joined co-activation motifs throughout individual experiences, enabling cross-memory in- teractions. These findings reveal an organizational principle of brain networks where high and low activity cells are differentially recruited into coactivity motifs as build- ing blocks for the flexible integration and interaction of memories. Finally, I employ a set of manifold learning and related approaches to explore and characterise the complex neural population dynamics within CA1 that underlie sim- ple exploration.Open Acces

    The hippocampus and entorhinal cortex map events across space and time

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    The medial temporal lobe supports the encoding of new facts and experiences, and organizes them so that we can infer relationships and make unique associations during new encounters. Evidence from studies on humans and animals suggest that the hippocampus is specifically required for our ability to form these internal representations of the world. The mechanism by which the hippocampus performs this function remains unclear, but electrophysiological recordings in the hippocampus support a general model. One component of this model suggests that the cortex represents places, times, and events separately, and then the hippocampus generates conjunctive representations that connect the three. According to this hypothesis, the hippocampus binds places and events to an existing relational structure. This dissertation explores how item and place associations develop within cortex, and then examines the relational structure that organizes these events within the hippocampus. The first study suggests that contrary to previous models, events and places are bound together outside of the hippocampus in the entorhinal cortex and perirhinal cortex. The second study shows that this relational scaffold may be embodied by a continually changing code that permits both the association and separation of information across the continuum of time. The final study suggests that the hippocampus and entorhinal cortex contain qualitatively different time codes that may act in a complementary fashion to bind events and places and relate them across time. Overall, these studies support a theory wherein time is encoded in a range of brain regions that also contain conjunctive item and position information. In these regions, conjunctive representations of items, places, and times are organized not only by their perceptual similarity but also their temporal proximity
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