Memristive stochastic plasticity enables mimicking of neural synchrony: Memristive circuit emulates an optical illusion.
Sci Adv
; 3(10): e1700849, 2017 10.
Article
in En
| MEDLINE
| ID: mdl-29075665
ABSTRACT
The human brain is able to integrate a myriad of information in an enormous and massively parallel network of neurons that are divided into functionally specialized regions such as the visual cortex, auditory cortex, or dorsolateral prefrontal cortex. Each of these regions participates as a context-dependent, self-organized, and transient subnetwork, which is shifted by changes in attention every 0.5 to 2 s. This leads to one of the most puzzling issues in cognitive neuroscience, well known as the "binding problem." The concept of neural synchronization tries to explain the problem by encoding information using coherent states, which temporally patterns neural activity. We show that memristive devices, that is, a two-terminal variable resistor that changes its resistance depending on the previous charge flow, allow a new degree of freedom for this concept a local memory that supports transient connectivity patterns in oscillator networks. On the basis of the probability distribution of the resistance switching process of Ag-doped titanium dioxide memristive devices, a local plasticity model is proposed, which causes an autonomous phase and frequency locking in an oscillator network. To illustrate the performance of the proposed computing paradigm, the temporal binding problem is investigated in a network of memristively coupled self-sustained van der Pol oscillators. We show evidence that the implemented network allows achievement of the transition from asynchronous to multiple synchronous states, which opens a new pathway toward the construction of cognitive electronics.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Brain
/
Neural Networks, Computer
/
Models, Neurological
/
Neuronal Plasticity
Type of study:
Prognostic_studies
Limits:
Animals
/
Humans
Language:
En
Journal:
Sci Adv
Year:
2017
Document type:
Article
Affiliation country:
Germany