Synapses In Human Brain Research Articles

Energy-efficient flexible photoelectric device with 2D/0D hybrid structure for bio-inspired artificial heterosynapse application

The booming artificial intelligence has led to an urgent demand for high-efficient information processing systems. Inspired by the interconnected synapses in human brain, we constructed a novel low-dimensional flexible hybrid photoelectric-modulated artificial heterosynapse with sub-femtojoule energy consumption (0.58 fJ/spike in long-term potentiation (LTP) and 0.86 fJ/spike in long-term depression (LTD)) and ultrafast response (50 ns), which is 10 5 folds faster than human brain (10 ms). The device synergistically utilizes the remarkable photoelectric properties of a 2D MoSSe channel and a 0D BPQD trap layer to achieve a better computing architecture. The artificial synapse successfully emulates neuromorphic functions under both electric and light stimuli. More importantly, the multi-terminal heterosynaptic plasticity can be modulated effectively by three factors in a cumulative/subtractive way, resembling biological synapses affected by an external neuromodulator, enabling higher order LTP correlations (percentage of increase is ~203% compared with electric modulation) and multiple memory states. The performance of the device was unaffected by substrate bending, indicating the robust stability and high flexibility under mechanical strains. Moreover, the Pavlov’s dog classical conditioning experiments were performed to realize associative learning with the synaptic device. These results highlight a new approach for constructing highly efficient wearable neuromorphic computing systems based on mixed low-dimensional structures. • The 2D MoSSe/0D BPQDs hybrid structure for artificial heterosynapse was reported firstly, and the device exhibits reliable flexibility. • Ultralow power consumption of 0.58 fJ/spike in long-term-potentiation. • Ultrafast programing and erasing speed of 50 ns in flexible neuron-transistor. • By virtue of heterosynaptic characteristics, the modulation range of conductance could be enlarged to ~203% compared with pure-electric modulation.

NeuroMem: Analog Graphene-Based Resistive Memory for Artificial Neural Networks

Artificial Intelligence (AI) at the edge has become a hot subject of the recent technology-minded publications. The challenges related to IoT nodes gave rise to research on efficient hardware-based accelerators. In this context, analog memristor devices are crucial elements to efficiently perform the multiply-and-add (MAD) operations found in many AI algorithms. This is due to the ability of memristor devices to perform in-memory-computing (IMC) in a way that mimics the synapses in human brain. Here, we present a novel planar analog memristor, namely NeuroMem, that includes a partially reduced Graphene Oxide (prGO) thin film. The analog and non-volatile resistance switching of NeuroMem enable tuning it to any value within the RON and ROFF range. These two features make NeuroMem a potential candidate for emerging IMC applications such as inference engine for AI systems. Moreover, the prGO thin film of the memristor is patterned on a flexible substrate of Cyclic Olefin Copolymer (COC) using standard microfabrication techniques. This provides new opportunities for simple, flexible, and cost-effective fabrication of solution-based Graphene-based memristors. In addition to providing detailed electrical characterization of the device, a crossbar of the technology has been fabricated to demonstrate its ability to implement IMC for MAD operations targeting fully connected layer of Artificial Neural Network. This work is the first to report on the great potential of this technology for AI inference application especially for edge devices.

Studying synapses in human brain with array tomography and electron microscopy

Postmortem studies of synapses in human brain are problematic because of the axial resolution limit of light microscopy and the difficulty in preserving and analyzing ultrastructure with electron microscopy (EM). Array tomography (AT) overcomes these problems by embedding autopsy tissue in resin and cutting ribbons of ultrathin serial sections. Ribbons are imaged with immunofluorescence, allowing high-throughput imaging of tens of thousands of synapses to assess synapse density and protein composition. The protocol takes ~3 d per case, excluding image analysis, which is done at the end of the study. Parallel processing for transmission electron microscopy (TEM) using a protocol modified to preserve the structure in human samples allows complementary ultrastructural studies. Incorporation of AT and TEM into brain banking is a potent way of phenotyping synapses in well-characterized clinical cohorts in order to develop clinicopathological correlations at the synapse level. This will be important for research in neurodegenerative disease, developmental disease and psychiatric illness.

Increased asynchronous GABA release causes more inhibition in human epileptic brain?

Increased asynchronous GABA release causes more inhibition in human epileptic brain?