Stephen E. Clarke, PhD, is a postdoctoral scholar in the Brain Interfacing Lab, Department of Bioengineering. He obtained a BSc in Mathematics from the University of New Brunswick, and a PhD in Neuroscience from the University of Ottawa. His research draws on combined experimental and computational expertise to explore neuronal information processing on multiple scales, and across species. His long-term research goals involve application of closed-loop brain machine interface technologies as a platform for neurorehabilitation and repair in motor and cognitive systems, leveraging both insights from basic neuroscience and exciting new implant technologies.
Research Interests: Sensory and Motor Systems Neuroscience, Computational Neuroscience, Cellular and Molecular Neuroscience, Applied Mathematics, Neurorehabilitation and Repair.
Bachelor of Science, University of New Brunswick (2010)
Doctor of Philosophy, University of Ottawa (2017)
Cellular and network mechanisms may generate sparse coding of sequential object encounters in hippocampal-like circuits.
The localization of distinct landmarks plays a crucial role in encoding new spatial memories. In mammals, this function is performed by hippocampal neurons that sparsely encode an animal's location relative to surrounding objects. Similarly, the dorsal lateral pallium (DL) is essential for spatial learning in teleost fish. The DL of weakly electric gymnotiform fish receives both electrosensory and visual input from the preglomerular nucleus (PG), which has been hypothesized to encode the temporal sequence of electrosensory or visual landmark/food encounters. Here, we show that DL neurons in the Apteronotid fish and in the Carassius auratus (goldfish) have a hyperpolarized resting membrane potential combined with a high and dynamic spike threshold that increases following each spike. Current-evoked spikes in DL cells are followed by a strong small-conductance calcium-activated potassium channel (SK) mediated after-hyperpolarizing potential (AHP). Together, these properties prevent high frequency and continuous spiking. The resulting sparseness of discharge and dynamic threshold suggest that DL neurons meet theoretical requirements for generating spatial memory engrams by decoding the landmark/food encounter sequences encoded by PG neurons. Thus, DL neurons in teleost fish may provide a promising, simple system to study the core cell and network mechanisms underlying spatial memory.Significance Statement To our knowledge, this is first study of the intrinsic physiology of teleost pallial (DL) neurons. Their biophysical properties demonstrate that DL neurons are sparse coders with a dynamic spike threshold leading us to suggest that they can transform time-stamped input into spatial location during navigation. The concept of local attractors (bumps) that potentially move 'across' local recurrent networks has been prominent in the neuroscience theory literature. We propose that the relatively simple and experimentally accessible DL of teleosts may be the best preparation to examine this idea experimentally and to investigate the properties of local (excitatory) recurrent networks whose cells are endowed with, e.g., slow spike threshold adaptation dynamics.
View details for DOI 10.1523/ENEURO.0108-19.2019
View details for PubMedID 31324676
- Analog Signaling With the "Digital" Molecular Switch CaMKII FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2018; 12
Feedback Synthesizes Neural Codes for Motion
2017; 27 (9): 1356–61
In senses as diverse as vision, hearing, touch, and the electrosense, sensory neurons receive bottom-up input from the environment, as well as top-down input from feedback loops involving higher brain regions [1-4]. Through connectivity with local inhibitory interneurons, these feedback loops can exert both positive and negative control over fundamental aspects of neural coding, including bursting [5, 6] and synchronous population activity [7, 8]. Here we show that a prominent midbrain feedback loop synthesizes a neural code for motion reversal in the hindbrain electrosensory ON- and OFF-type pyramidal cells. This top-down mechanism generates an accurate bidirectional encoding of object position, despite the inability of the electrosensory afferents to generate a consistent bottom-up representation [9, 10]. The net positive activity of this midbrain feedback is additionally regulated through a hindbrain feedback loop, which reduces stimulus-induced bursting and also dampens the ON and OFF cell responses to interfering sensory input . We demonstrate that synthesis of motion representations and cancellation of distracting signals are mediated simultaneously by feedback, satisfying an accepted definition of spatial attention . The balance of excitatory and inhibitory feedback establishes a "focal" distance for optimized neural coding, whose connection to a classic motion-tracking behavior provides new insight into the computational roles of feedback and active dendrites in spatial localization [13, 14].
View details for DOI 10.1016/j.cub.2017.03.068
View details for Web of Science ID 000400741700026
View details for PubMedID 28457872
Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise
JOURNAL OF NEUROPHYSIOLOGY
2016; 115 (1): 530–45
Encoding behaviorally relevant stimuli in a noisy background is critical for animals to survive in their natural environment. We identify core biophysical and synaptic mechanisms that permit the encoding of low-frequency signals in pyramidal neurons of the weakly electric fish Apteronotus leptorhynchus, an animal that can accurately encode even miniscule amplitude modulations of its self-generated electric field. We demonstrate that slow NMDA receptor (NMDA-R)-mediated excitatory postsynaptic potentials (EPSPs) are able to summate over many interspike intervals (ISIs) of the primary electrosensory afferents (EAs), effectively eliminating the baseline EA ISI correlations from the pyramidal cell input. Together with a dynamic balance of NMDA-R and GABA-A-R currents, this permits stimulus-evoked changes in EA spiking to be transmitted efficiently to target electrosensory lobe (ELL) pyramidal cells, for encoding low-frequency signals. Interestingly, AMPA-R activity is depressed and appears to play a negligible role in the generation of action potentials. Instead, we hypothesize that cell-intrinsic voltage-dependent membrane noise supports the encoding of perithreshold sensory input; this noise drives a significant proportion of pyramidal cell spikes. Together, these mechanisms may be sufficient for the ELL to encode signals near the threshold of behavioral detection.
View details for DOI 10.1152/jn.00786.2015
View details for Web of Science ID 000369061900045
View details for PubMedID 26561607
View details for PubMedCentralID PMC4760475
Contrast coding in the electrosensory system: parallels with visual computation
NATURE REVIEWS NEUROSCIENCE
2015; 16 (12): 733–44
To identify and interact with moving objects, including other members of the same species, an animal's nervous system must correctly interpret patterns of contrast in the physical signals (such as light or sound) that it receives from the environment. In weakly electric fish, the motion of objects in the environment and social interactions with other fish create complex patterns of contrast in the electric fields that they produce and detect. These contrast patterns can extend widely over space and time and represent a multitude of relevant features, as is also true for other sensory systems. Mounting evidence suggests that the computational principles underlying contrast coding in electrosensory neural networks are conserved elements of spatiotemporal processing that show strong parallels with the vertebrate visual system.
View details for DOI 10.1038/nrn4037
View details for Web of Science ID 000365285600008
View details for PubMedID 26558527
The neural dynamics of sensory focus
2015; 6: 8764
Coordinated sensory and motor system activity leads to efficient localization behaviours; but what neural dynamics enable object tracking and what are the underlying coding principles? Here we show that optimized distance estimation from motion-sensitive neurons underlies object tracking performance in weakly electric fish. First, a relationship is presented for determining the distance that maximizes the Fisher information of a neuron's response to object motion. When applied to our data, the theory correctly predicts the distance chosen by an electric fish engaged in a tracking behaviour, which is associated with a bifurcation between tonic and burst modes of spiking. Although object distance, size and velocity alter the neural response, the location of the Fisher information maximum remains invariant, demonstrating that the circuitry must actively adapt to maintain 'focus' during relative motion.
View details for DOI 10.1038/ncomms9764
View details for Web of Science ID 000366294400003
View details for PubMedID 26549346
View details for PubMedCentralID PMC4659932
A Neural Code for Looming and Receding Motion Is Distributed over a Population of Electrosensory ON and OFF Contrast Cells
JOURNAL OF NEUROSCIENCE
2014; 34 (16): 5583–94
Object saliency is based on the relative local-to-background contrast in the physical signals that underlie perceptual experience. As such, contrast-detecting neurons (ON/OFF cells) are found in many sensory systems, responding respectively to increased or decreased intensity within their receptive field centers. This differential sensitivity suggests that ON and OFF cells initiate segregated streams of information for positive and negative sensory contrast. However, while recording in vivo from the ON and OFF cells of Apteronotus leptorhynchus, we report that the reversal of stimulus motion triggers paradoxical responses to electrosensory contrast. By considering the instantaneous firing rates of both ON and OFF cell populations, a bidirectionally symmetric representation of motion is achieved for both positive and negative contrast stimuli. Whereas the firing rates of the individual contrast detecting neurons convey scalar information, such as object distance, it is their sequential activation over longer timescales that track changes in the direction of movement.
View details for DOI 10.1523/JNEUROSCI.4988-13.2014
View details for Web of Science ID 000334926000019
View details for PubMedID 24741048
View details for PubMedCentralID PMC6608223
Calcium influx through N-type channels and activation of SK and TRP-like channels regulates tonic firing of neurons in rat paraventricular thalamus
JOURNAL OF NEUROPHYSIOLOGY
2013; 110 (10): 2450–64
The thalamus is a major relay and integration station in the central nervous system. While there is a large body of information on the firing and network properties of neurons contained within sensory thalamic nuclei, less is known about the neurons located in midline thalamic nuclei, which are thought to modulate arousal and homeostasis. One midline nucleus that has been implicated in mediating stress responses is the paraventricular nucleus of the thalamus (PVT). Like other thalamic neurons, these neurons display two distinct firing modes, burst and tonic. In contrast to burst firing, little is known about the ionic mechanisms modulating tonic firing in these cells. Here we performed a series of whole cell recordings to characterize tonic firing in PVT neurons in acute rat brain slices. We found that PVT neurons are able to fire sustained, low-frequency, weakly accommodating trains of action potentials in response to a depolarizing stimulus. Unexpectedly, PVT neurons displayed a very high propensity to enter depolarization block, occurring at stimulus intensities that would elicit tonic firing in other thalamic neurons. The tonic firing behavior of these cells is modulated by a functional interplay between N-type Ca(2+) channels and downstream activation of small-conductance Ca(2+)-dependent K(+) (SK) channels and a transient receptor potential (TRP)-like conductance. Thus these ionic conductances endow PVT neurons with a narrow dynamic range, which may have fundamental implications for the integrative properties of this nucleus.
View details for DOI 10.1152/jn.00363.2013
View details for Web of Science ID 000327423600018
View details for PubMedID 24004531
Speed-invariant encoding of looming object distance requires power law spike rate adaptation
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2013; 110 (33): 13624–29
Neural representations of a moving object's distance and approach speed are essential for determining appropriate orienting responses, such as those observed in the localization behaviors of the weakly electric fish, Apteronotus leptorhynchus. We demonstrate that a power law form of spike rate adaptation transforms an electroreceptor afferent's response to "looming" object motion, effectively parsing information about distance and approach speed into distinct measures of the firing rate. Neurons with dynamics characterized by fixed time scales are shown to confound estimates of object distance and speed. Conversely, power law adaptation modifies an electroreceptor afferent's response according to the time scales present in the stimulus, generating a rate code for looming object distance that is invariant to speed and acceleration. Consequently, estimates of both object distance and approach speed can be uniquely determined from an electroreceptor afferent's firing rate, a multiplexed neural code operating over the extended time scales associated with behaviorally relevant stimuli.
View details for DOI 10.1073/pnas.1306428110
View details for Web of Science ID 000323069200087
View details for PubMedID 23898185
View details for PubMedCentralID PMC3746935