Stephen E. Clarke

Generation and transplantation of reprogrammed human neurons in the brain using 3D microtopographic scaffolds

Cell replacement therapy with human pluripotent stem cell-derived neurons has the potential to ameliorate neurodegenerative dysfunction and central nervous system injuries, but reprogrammed neurons are dissociated and spatially disorganized during transplantation, rendering poor cell survival, functionality and engraftment in vivo. Here, we present the design of three-dimensional (3D) microtopographic scaffolds, using tunable electrospun microfibrous polymeric substrates that promote in situ stem cell neuronal reprogramming, neural network establishment and support neuronal engraftment into the brain. Scaffold-supported, reprogrammed neuronal networks were successfully grafted into organotypic hippocampal brain slices, showing an ∼3.5-fold improvement in neurite outgrowth and increased action potential firing relative to injected isolated cells. Transplantation of scaffold-supported neuronal networks into mouse brain striatum improved survival ∼38-fold at the injection site relative to injected isolated cells, and allowed delivery of multiple neuronal subtypes. Thus, 3D microscale biomaterials represent a promising platform for the transplantation of therapeutic human neurons with broad neuro-regenerative relevance.

Contrast coding in the electrosensory system: parallels with visual computation

To identify and interact with moving objects, including other members of the same species, an animals 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.

Speed-invariant encoding of looming object distance requires power law spike rate adaptation

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.

A neural code for looming and receding motion is distributed over a population of electrosensory ON and OFF contrast cells.

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.

Calcium influx through N-type channels and activation of SK and TRP-like channels regulates tonic firing of neurons in rat paraventricular thalamus

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.

Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise

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.

Neural coding strategies for extracting motion estimates from electrosensory contrast

Object saliency is based on the relative local-to-background contrast in the physical signals that underlie perceptual experience. Extracting meaningful stimulus representations from these contrast patterns constitutes a serious inverse problem for neural coding, where many different stimulus features map into a scalar firing rate. This decoding problem is even more acute for neurons whose dynamics are characterized by fixed timescales, which produce distinct firing rate responses to different temporal parameterizations of a stimulus [1]. By studying how looming object distance is extracted from electrosensory contrast, we demonstrate that power law adaptation in the primary electroreceptor afferents of A. leptorhynchus transforms the firing rate, yielding a code for stimulus intensity (distance) that is invariant to the rate of change of intensity with respect to time (speed). As such, estimates of both object distance and approach speed are effectively parsed into distinct measures of an electroreceptor afferent’s firing rate [1]. Despite its important role in neural coding, adaptation suffers a serious caveat for encoding natural inputs: it generates skewed responses when signal intensity changes from increasing to decreasing (or vice versa). As predicted by generic models of spike-frequency adaptation, we report a skew in the electroreceptor afferent firing rate upon motion reversal, introducing further ambiguity into the estimation of object distance from electrosensory contrast [2]. The electrosense compensates for the skewed firing rate by combining the activity of downstream ON and OFF cells into a population rate code characterized by paradoxical responses to local contrast. Under both positive and negative contrast conditions, motion reversal induces a coding switch between ON and OFF cells, whose combined instantaneous firing rates cooperatively produce a symmetric representation of object motion. Whereas the firing rates of the individual ON and OFF cells convey scalar information, such as object distance, their sequential activation over longer timescales encode changes in motion direction.