Ay1. Compared to the brain, digital processors use
a. about the same amount of energy to carry out equivalent computations
b. more energy to carry out computations
c. less energy to carry out computations
AY2. Which of the following is true:
a. computers carry out digital computations while the brain carries out
analogue computations
b. computers carry out analogue computations while the brain carries out
digital computations
c. computers and the brain both carry out digital computations
d. computers and the brain both carry out analogue computations
e. none of the above
AY3. T/F: There is a global clock in the brain, just like in digital computers
a. True
b. False
AY4. What is NOT a challenge for neuromorphic computation?
a. Fabrication variability and operating noise
b. Voltages used to set neuron parameters do not directly correspond to those
of the mathematical description of the neuron
c. All computations have to synchronize with a global clock
d. Only a small number of state variables can be observed
e. Internal parameters cannot be set with arbitrary precision (often just on or
off)
AY5. T/F: Implementation of cognitive functions in neuromophic engineering
medium is challenging due to the fact that most common algorithms proposed for
solving cognitive tasks are incompatible with neuromorphic circuits.
a. True
b. False
(a, b, and arguably 3 can all be correct)
DM1. In Dr. Neftci’ lecture, we saw a mechanical model of a neuron, which featured
a bucket that tipped its contents only if two upstream buckets tipped their contents
into it simultaneously. What phenomena in neurons does this configuration of
buckets represent?
a. Temporal summation
b. Spatial summation
c. Integration
d. Inhibitory post synaptic currents
e. None of the above
(Though not stated by Neftci, c could be a right answer is general)
DM 2. Which of the following is not a goal of neuromorphic engineering?
a. To understand the computational properties of biological neural systems
using analog circuits implemented in standard CMOS VSLI technology
b. To exploit the known properties of biological systems to design and
implement efficient devices for engineering applications.
c. To demonstrate the possibility for simulating biology with simple physics.
d. All of the above are goals of neuromorphic engineering.
e. Neither a, b, nor c are goals of neuromorphic engineering.
DM 3. True or False: Neuromorphic circuits exploit the physics of silicon to imitate
the biophysics of neurons using sub-threshold circuits.
a. True
b. False
DM 4. True or False: Neuromorphic engineering has thus far failed to deliver
genuinely intelligent neuromorphic machines
a. True
b. False
(poorly phrased)
DM 5. Which of the following is not a challenge for neuromorphic approaches
a. They are subject to fabrication variability and operating noise.
b. Their parameters cannot be set with arbitrary precision.
c. Voltages used to set neuron parameters do not directly correspond to those
of the mathematical description of the neuron.
d. Only a small number of state variables can be observed.
e. A neuromorphic model is often capable of expressing more functionally
relevant states than the phenomena being modeled.
(poorly phrased)
WC1. Which level of analysis corresponding to a "middle-out" approach in designing
neuromorphic information processing system?
a.
b.
c.
d.
e.
Computation
Algorithm
Implementation
Probability
All of the above.
WC2. To perform an operation, digital silicon processors typically use much more
energy than the brain.
a. True
b. Fals
(too specific)
WC3. sWTA is an intermediate abstract layer that couples the behavioral model to
the neuromorphic hardware.
a. True
b. False
WC4. One goal of neurimorphic engineering is to exploit the known properties of
biological systems to design and implement efficient devices for engineering
applications.
a. True
b. False
(redundant)
WC5. What is the challenge to find "algorithm" for neuromorphic spiking neurons?
a. Large number of state variables can be observed
b. They are subject to fabrication variability and operating noise.
c. Their parameters can be set with arbitrary precision
d. Voltages used to set neuron parameters do directly correspond to those of
the mathematical description of the neuron.
e. All of the above.
(too specific)
BT1. The Semantic Pointer Architecture Unified Networks (SPAUN) can solve ___
different cognitive task; however, it requires around __________ neurons.
a. 6; 2.5 million
b. 6; 3.5 million
c. 8; 2.5 million
d. 8; 3.5 million
e. 10; 2.5 million
(do not use in conunction with AY4)
BT2. Which of the following is NOT a reason why there’s no algorithm for
neuromorphic spiky neurons?
a. Only a small number of state variables can be observed
b. The voltages cannot be set with arbitrary precision
c. Can only tell where the spike is coming from, but not what connection it
makes
d. Subject to fabrication variability and noise
e. Voltages used to set neuron parameters do not directly correspond to those
of the mathematical description of the neuron.
(b is poorly phrased)
BT3. What is the purpose of neuromorphic engineering?
a. To understand the computational properties of systems using engineered
circuits.
b. To use devices to design and implement devices for engineering purposes.
c. To be able to use circuitry designs to understand the individual synaptic
pathways that each biological neuronal system makes in our brains.
d. a and b
e. All the above
(too hard)
BT4. True or False: Neurons are fast compared to digital circuits; therefore, it’s
necessary to use address-events to isolate neuronal pathways for better
understanding.
a. True
b. False
(too vague)
BT5. True or False: Cognitive neuromorphic engineering incorporates top-down and
bottom-up approaches; in a sense, it takes on a somewhat “middle-approach”
method.
a. True
b. False
(incorrect; ad all seem right)
JS 1. Which problem limits the current use of the “neural engineering framework” to
develop computationally powerful networks?
a. They vary with fabrication and often have high operating noise.
b. Voltages used in these artificial neurons do not corresponde to voltages in
real biological neurons.
c. Only a small number of states variables in the network are observable.
d. Their parameters cannot be set with arbitrary precision.
e. None of the above.
(too specific to the speaker’s point of view)
JS 2. The difficulty in designing neuromorphic information processing systems arises
at which of Marr’s Three Levels of Analysis?
a. Computation
b. Algorithmic
c. Implementational
d. A & C
e. All of the above.
(too specific)
JS 3. A knowledgeable researcher can easily build a state machine with only a few
lines of code that can perform successfully in which of the following tasks?
a. Facial emotion identification task
b. 12AX task
c. Visual Flanker task
d. Neural compilation task
e. None of the above.
JS 4. Horizontal cells in the retina inhibit their neighbors in order to reduce noise of
the signal traveling from the retina to the brain. This protocol is most similar to the
function provided in which of the following neuromorphic network component?
a. Very-Large-Scale Integration system
b. Asynchronous Communication Protocol
c. Soft Winner-Takes-All Network
d. SPAUN
e. BlueGene
JS 5. The human brain relies on ______ processes and is ______ throughout life,
while digital processors rely on ______ processes and are ______ after fabrication
a. deterministic; plastic; deterministic; frozen
b. stochastic; frozen; deterministic; plastic
c. deterministic; plastic; stochastic; frozen
d. stochastic; plastic; deterministic; frozen
e. deterministic; frozen; stochastic; plastic
(do not use in conjunction with WC2)
JS 6. True or False: The human brain takes several orders of magnitude less energy to
perform an operation than a silicon microchip.
a. True
b. False
(controversial)
KC1. Neurons are slow compared to digital circuits
a. True
b. False
(redundant)
KC2. Why is there no algorithm for Neuromorphic spiking neurons?
a. They are subject to fabrication variability and operating noise.
b. Their parameters cannot be set with arbitrary precision.
c. Only a small number of state variables can be observed
d. All of the above
e. None of the above
(too specific)
KC3. The 12AX task requires many cognitive capabilities including attention, working
memory, rule abstraction, decision making.
a. True
b. False
KC4. What is a nonlinear behavior of the sWTA (soft winner-take-all) network?
a. Single network
b. Noise reduction
c. Selective amplification
d. Multi-modal primers
e. None of the above
KC5. What is the sWTA?
a. A network that takes inputs from the brain and applies them to an algorithm.
b. An intermediate abstract layer that couples the behavioral model to the
Neuromorphic hardware.
c. A neuronal network
d. All of the above
e. None of the above
(VLSI is only one kind of neuromorphic circuit)
SD1: What does the term neuromorphic describe?
a. Very Large Scale Integration (VLSI)
b. Very Small Scale Integration (VSSI)
c. Large Scale Computation (LSC)
d. Small Scale Computational Integration (SSCI)
(redundant)
SD2: Which of the following characterizes neuromorphic engineering?
a. To understand the computational properties of biological neural systems
using analog circuits implemented in standard CMOS VLSI technology.
b. To exploit the known properties of biological systems to design and
implement efficient devices for engineering applications.
c. To replicate the functional processes of the mouse brain in with a computer
algorithm to model aspects of cognition.
d. Both a and b
(too vague)
SD3: True / False: The brain uses fundamentally different computational principles
than a digital processor.
a. True
b. False
(controversial)
SD4: True / False: Neurons are fast compared to digital circuits.
a. True
b. False
(too specific to the speaker)
SD5: What was an example of a simple cognitive task used with neuromorphic
spiking neurons?
a. Go-No go Task
b. 12AX
c. sWTA
d. SPAUN
LS1. Dr. Neftci showed a video of some cups filling with water and then tipping.
Which of the following was he trying to illustrate?
a. A physical model of a neuron called a hydroneuron
b. Equilibrium between intracellular and extracellular concentrations of fluids
c. A way to get silicon to behave like ion channels
d. All of the above
e. None of the above
LS2. Which of the following is true of neuromorphic engineering?
a. It is a discipline which aims to understand the computational properties of
biological neural systems using analog circuits
b. It is a discipline which aims to exploit the known properties of biological
systems to design and implement efficient devices for engineering applications
c. It is a discipline whose primary aim is to digitally model neurons and attractor
networks
d. All of the above
e. a and b only
(seems tautological: the brain is a circuit)
LS3. Which of the following would be problematic when building a brain with
physical circuits using the same communication principle as the brain
a. The brain is not understood well enough to build physical circuits that will
perform computations anything close to brain-like
b. The physical circuit would be far too large
c. The circuit will be able to keep track of time and space as accurately as a
brain could
d. The circuit will never be able to do face recognition
e. None of the above are problems
(the focus is more on “history of science”)
LS4. True or false: In the past decade, neuromorphic engineers have made great
advances in the field of cognition.
a. True
b. False
(redundant)
LS5. Algorithms for neuromorphic spiking systems are problematic for which of the
following reasons?
a. They are subject to operating noise
b. Only a small number of state variables can be observed
c. Voltages used to set neuron parameters do not directly correspond to those
of the mathematical description of the neuron
d. all of the above
e. none of the above