Showing papers by "Simon J. Thorpe published in 2017"

Waking Up Buried Memories of Old TV Programs.

Abstract: Although it has been demonstrated that visual and auditory stimuli can be recalled decades after the initial exposure, previous studies have generally not ruled out the possibility that the material may have been seen or heard during the intervening period. Evidence shows that reactivations of a long-term memory trace play a role in its update and maintenance. In the case of remote or very long-term memories, it is most likely that these reactivations are triggered by the actual re-exposure to the stimulus. In this study we decided to explore whether it is possible to recall stimuli that could not have been re-experienced in the intervening period. We tested the ability of French participants (N = 34, 31 female) to recall 50 TV programs broadcast on average for the last time 44 years ago (from the 60’s and early 70’s). Potential recall was elicited by the presentation of short audiovisual excerpts of these TV programs. The absence of potential re-exposure to the material was strictly controlled by selecting TV programs that have never been rebroadcast and were not available in the public domain. Our results show that 6 TV programs were particularly well identified on average across the 34 participants with a median percentage of 71.7% (SD = 13.6, range: 48.5% - 87.9%). We also obtained 50 single case reports with associated information about the viewing of 23 TV programs including the 6 previous ones. More strikingly, for 2 cases, retrieval of the title was made spontaneously without the need of a four-proposition choice. These results suggest that re-exposures to the stimuli are not necessary to maintain a memory for a lifetime. These new findings raise fundamental questions about the underlying mechanisms used by the brain to store these very old sensory memories.

Method, digital electronic circuit and system for unsupervised detection of repeating patterns in a series of events

Abstract: A method of performing unsupervised detection of repeating patterns in a series (TS) of events (E21, E12, E5...), comprising the steps of: a) Providing a plurality of neurons (NR1 - NRP), each neuron being representative of W event types; b) Acquiring an input packet (IV) comprising N successive events of the series; c) Attributing to at least some neurons a potential value (PT1 - PTP), representative of the number of common events between the input packet and the neuron; d) Modify the event types of neurons having a potential value exceeding a first threshold T L ; and e) generating a first output signal (OS1 - OSP) for all neurons having a potential value exceeding a second threshold T F , and a second output signal, different from the first one, for all other neurons. A digital electronic circuit and system configured for carrying out such a method.

Digital electronic circuit and system implementing a spiking neural network for performing unsupervised detection of patterns

Abstract: A digital electronic circuit (SNN) implementing a spiking neural network comprising: an input unit, (IU) for receiving a series of digital signals (ES) representing respective events and for generating a data packet (PK) representative of N contiguous signals of the series, with 1≤N≤M; - a memory (NM) storing data defining a plurality of neurons, comprising for each neuron a set of binary weights (BWV); - a match calculating unit (MCU), connected to said input unit and said memory, configured for computing, for at least some of the neurons, a potential value (PT) representative of a match between said data packet and said binary weights; and for generating a series of output signals (OS) indicative of neurons having a potential value exceeding a threshold TF, called firing threshold; and - a learning unit (LU), for modifying the set of binary weights of neurons having a potential value exceeding a threshold TL, called learning threshold.