ISLAND - An integrated setup for in-vitro optogenetic experiments using AI to localize stimulation with a feedback of electrophysiological signals


In the ERC-AdG BACKUP project we would like to exploit optogenetics to write engrams in neuronal cultures in-vitro. ISLAND aims at developing an integrated and intelligent platform which should allow to write and read engrams in neuronal cultures.

The reading part of the setup will be done by sampling the electrophysiological activity of the culture using microelectrode array (MEA) technology which is highly time- and space- resolved. The writing part will be executed by optogenetic techniques using an optical setup allowing spatially-patterned light such as digital light processor (DLP) or integrated photonic circuit (IPC).

The core of ISLAND will be to integrate those two parts in a closed-loop, by developing processing and control units. The processing unit will collect the electrical signals from MEA as a feedback of the neuronal activity and will map the neurons in the network according to their electrophysiological activity. The control system will then activate the corresponding pattern of stimuli in the optical setup according to the network’s map and the assignment.

ISLAND is a strong multidisciplinary project combining neuroscience, electronics and photonics with the usage of Deep-Learning techniques.



EPIQUS: Electronic-photonic integrated quantum simulator platform


EPIQUS aims to demonstrate a cheap, easy-to-use, performant Quantum Simulator (QS) based on full integration of silicon nitride photonics with silicon electronics. The core objective of EPIQUS is to set a cornerstone technology – demonstrate the
first breakthrough device - which will simulate quantum mechanical problems in a compact device operating at ambient temperatures.
Our vision is to develop a Quantum Simulator by bringing onto a unique semiconductor platform the mature silicon microelectronic (CMOS, digital) and the silicon nitride quantum micro-photonic functionalities. Within EPIQUS we will develop a 3D-integrated quantum simulator hardware, where (1) a photonic quantum interference circuit, hosting (1a) scalable entangled photon sources (pumped by a NIR pulsed diode laser to produce on-chip photon pairs via nonlinear four wave mixing), (1b) the state
preparation stage and (1c) the 16 qubit reconfigurable quantum interference circuit, will be monolithically integrated on the same Si chip with (2) scalable arrays of single photon avalanche detectors (Silicon SPADs) operating at ~ 850nm and at
room temperatures. Around this, our consortium will build an integrated system, in which on the “software level” a quantum algorithm will sustain the quantum simulation results from the hardware. In this last, a custom Analog chip will control the QS
module by managing the pulsed pump laser, phase shifters (needed to reconfigure the QS) and the SPADs in order to control actively the quantum optical circuit. Finally, the output data will be handled by the digital chip to feed the software
algorithm. EPIQUS will envision scalability up to 50 qubits using the proposed breakthrough technology.
The EPIQUS consortium will be based on several groups from EU countries and one non-EU partner with diverse expertise, ranging from material, device, photonic and electronic circuit engineering, microfabrication technology, quantum optics and
spectroscopy, information technologies.

PELM: Photonic Extreme Learning Machine: from neuromorphic computing to universal optical interpolant, strain gauge sensor and cancer morphodynamic monitor.

The PELM project aims at demonstrating machine learning photonic devices. Within a single neuromorphic computing architecture, different platforms are specialized to given tasks by their specific characteristics. Starting from a common theoretical algorithm where matrices of optical computational nodes constitute a neural network, innovative proof-of-concept prototypes are realized such as:

  1. Silicon integrated sequence of optical micro-ring resonators for photonic neuromorphic computing;
  2. Semiconductor nanowire metasurfaces for arbitrary optical function synthesis suitable for flat lenses in computer tablet or smartphone applications;
  3. Liquid polymeric droplet whispering gallery mode resonator for sensitive strain gauge sensing;
  4. Biological spherical resonators for cancer detection and morphodynamics monitoring.

The unique combination of skilled physicists, engineers and biologists- from both universities and research centers- guarantees the achievement of these ambitious goals. Complementary competences in photonic integrated devices, complex systems, linear and nonlinear optical measurements, bio-physics, and semiconductor technology allow developing various platforms for the photonic extreme learning machines and their validation on killer applications.



BACKUP: Unveiling the relationship between brain connectivity and function by integrated photonics


Objectives BACKUP tackles the challenges of realizing a hybrid neuromorphic intelligent network where photonic circuitry provides both the core computing power as well as the interface to biological neurons and electronic circuitry provides both the required I/O control and the platform where algorithms (i.e., deep learning networks) emulate the biological network. After realizing a massive reservoir-computing photonic network based on a complex topology and a neuron/integrated photonic circuit interface where light controls both the topological connections (synapses) and the activity of the biological neurons, BACKUP will develop:
1. dynamic memories in photonic integrated circuits (PIC) using reservoir-computing network (RCN);
2. time-series forecasting for both noisy and chaotic inputs;
3. an artificial network (software-implemented) which emulates the physical hybrid network;
4. a hybrid network where biologic and artificial networks collaborate to jointly solve computation tasks;
5. artificial memory engrams to understand the cellular base of memory and the neuronal plasticity during learning;
6. hybrid circuits controlling neuronal hyperexcitability and seizure-induced plastic changes.
All these are extremely high-risk activities with extremely groundbreaking objectives. However, strong scientific and societal motivations – the limit of standard computers and the impact of neurological disorders on the population – motivate this research.
Recent progresses in photonics, computer science, deep learning, time series analysis, optogenetics and neurophysiology support my ambitions.

Q@TN - Quantum Science and Technology in Trento

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  1. Aligning all Trentino actors in the field of quantum science and technology (QST) and developing a common strategy
  2. Covering most aspects of QST merging the relevant expertise of the Partner Institutions
  3. Singling out Trentino as a reference point at European level in the area of QST

Q@TN operates within the framework of the newly launched Quantum Technologies Flagship. Q@TN coordinates the scientific and technological research and the high education in QST in Trentino, increasing the impact of the activity already carried out by local researchers in strategic areas of quantum science. Q@TN aims to attract further resources from national and international funding organisations.