CMOS-Memristor Dendrite Threshold Circuits

Non-linear neuron models overcomes the limitations of linear binary models of neurons that have the inability to compute linearly non-separable functions such as XOR. While several biologically plausible models based on dendrite thresholds are reported in the previous studies, the hardware implementation of such non-linear neuron models remain as an open problem. In this paper, we propose a circuit design for implementing logical dendrite non-linearity response of dendrite spike and saturation types. The proposed dendrite cells are used to build XOR circuit and intensity detection circuit that consists of different combinations of dendrite cells with saturating and spiking responses. The dendrite cells are designed using a set of memristors, Zener diodes, and CMOS NOT gates. The circuits are designed, analyzed and verified on circuit boards.Comment: Zhanbossinov, K. Smagulova, A. P. James, CMOS-Memristor Dendrite Threshold Circuits, 2016 IEEE APCCAS, Jeju, Korea, October 25-28, 201

Computing threshold functions using dendrites

Neurons, modeled as linear threshold unit (LTU), can in theory compute all thresh- old functions. In practice, however, some of these functions require synaptic weights of arbitrary large precision. We show here that dendrites can alleviate this requirement. We introduce here the non-Linear Threshold Unit (nLTU) that integrates synaptic input sub-linearly within distinct subunits to take into account local saturation in dendrites. We systematically search parameter space of the nTLU and TLU to compare them. Firstly, this shows that the nLTU can compute all threshold functions with smaller precision weights than the LTU. Secondly, we show that a nLTU can compute significantly more functions than a LTU when an input can only make a single synapse. This work paves the way for a new generation of network made of nLTU with binary synapses.Comment: 5 pages 3 figure

Action selection in the striatum: Implications for Huntington's disease

Although the basal ganglia have been widely studied and implicated in signal processing and action selection, little information is known about the active role that the striatal microcircuit plays in action selection in the basal ganglia-cortical-thalamic loops. To address this knowledge gap we use a large scale three dimensional spiking model of the striatum, combined with a rate coded model of the basal ganglia-cortical-thalamic loop, to asses the computational role the striatum plays in action selection. We identify robust transient phenomena generated by the striatal microcircuit, which temporarily enhances the difference between two competing cortical inputs. We show that this transient is sufficient to modulate decision making in the basal ganglia-thalamo-cortical circuit. We also find that the transient selection originates from a novel adaptation effect in single striatal projection neurons, which is amenable to experimental testing. Finally, we compared transient selection with models implementing classical steady-state selection. We challenged both forms of model to account for recent reports of paradoxically enhanced response selection in Huntington's disease patients. We found that steady-state selection was uniformly impaired under all simulated Huntington's conditions, but transient selection was enhanced given a sufficient Huntington's-like increase in NMDA receptor sensitivity. I propose a mechanistic underpinning to a novel neural compensatory mechanism, responsible for improved cognition in severe neuro-degeneration. Thus, our models provide an intriguing hypothesis for the mechanisms underlying the paradoxical cognitive improvements in manifest Huntington's patients, which is consistent with recent behavioural data

Dendritic Integration and Reciprocal Inhibition in the Retina

The mammalian retina is capable of signaling over a vast range of mean light levels (~10^10). Such a large dynamic range is achieved by segregating signals into contrasting pathways and utilizing excitatory and inhibitory neural circuits. The goal of this study was to elucidate subcellular mechanisms responsible for shaping dendritic computation and reciprocal inhibition within the retinal circuitry. Amacrine cells make up a unique class of inhibitory interneurons which lack anatomically distinct input and output structures. Although these interneurons clearly play important roles in complex visual processing, there is relatively little known about the ~30 subtypes. A17 amacrine cells have been shown to shape the time course of visual signaling in vivo. Intuition might suggest that a wide field (~400 µm) interneuron, such as A17, would provide long range lateral inhibition or center surround inhibition. However, using multi-disciplinary approaches, we have uncovered multiple mechanisms which underlie dendritic integration and synaptic transmission in A17 that allow it to respond with a high degree of synapse specificity. Additionally, these mechanisms work in concert with post-synaptic mechanisms to extend the dynamic range of reciprocal inhibition in the inner retina

Steep, Spatially Graded Recruitment of Feedback Inhibition by Sparse Dentate Granule Cell Activity

The dentate gyrus of the hippocampus is thought to subserve important physiological functions, such as 'pattern separation'. In chronic temporal lobe epilepsy, the dentate gyrus constitutes a strong inhibitory gate for the propagation of seizure activity into the hippocampus proper. Both examples are thought to depend critically on a steep recruitment of feedback inhibition by active dentate granule cells. Here, I used two complementary experimental approaches to quantitatively investigate the recruitment of feedback inhibition in the dentate gyrus. I showed that the activity of approximately 4% of granule cells suffices to recruit maximal feedback inhibition within the local circuit. Furthermore, the inhibition elicited by a local population of granule cells is distributed non-uniformly over the extent of the granule cell layer. Locally and remotely activated inhibition differ in several key aspects, namely their amplitude, recruitment, latency and kinetic properties. Finally, I show that net feedback inhibition facilitates during repetitive stimulation. Taken together, these data provide the first quantitative functional description of a canonical feedback inhibitory microcircuit motif. They establish that sparse granule cell activity, within the range observed in-vivo, steeply recruits spatially and temporally graded feedback inhibition

Subcellular information processing in the olfactory system

The nervous system is tasked with the challenge of processing a variety of sensory stimuli from the environment with limited coding space and energy consumption. Recent findings challenge the traditional view of the neuron as the elementary functional unit of the nervous system, in which dendrites mainly serve as input sites, and action potential propagation through axons generates output. Instead, individual neurites have emerged as the single functional unit capable of computing inputs and generating outputs locally. Despite recent advances, the link between the mechanisms that facilitate local computations and their behavioural relevance remains unclear. I addressed this problem in Drosophila Melanogaster. The anatomical organisation of the mushroom body, a brain region associated with learning, has a compartmentalised architecture that forms the basis for local computations. My project studied subcellular signalling in the mushroom body and its role in memory formation, with emphasis on the non-spiking APL neuron that is involved in sparse odour coding and memory formation, to determine if it operates locally. To investigate this, I addressed the following points. 1. I investigated the nature of activity spread in the APL neuron. I found that input to the APL neuron evokes activity that attenuates as it propagates, supporting local computations. 2. I characterised the spatial nature of inhibition from the APL neuron onto mushroom body neurons. I found that the inhibition had a strong local effect that diminished with distance. 3. I sought to determine if there are spatial differences in the APL neuron’s response to electric shock, and if plasticity in the APL neuron is similarly spatially distinct. I found that electric shock responses are spatially distinct, but my data on plasticity was inconclusive. 4. I investigated the effects of local muscarine signalling on Kenyon cell odour responses. I found that muscarine signalling has spatially distinct effects

Asynchronous Inhibition in Neocortical Microcircuits

Neurons are constantly integrating information from external and internal sources, causing them to spike at particular times. The exact timing of spikes is determined by a neuron's intrinsic properties, as well as the interplay between local excitatory and inhibitory inputs. Although inhibitory interneurons have been extensively studied, their contribution to neuronal integration and spike timing remains poorly understood. To elucidate the functional role of GABAergic interneurons during cortical activity, we combined molecular identification of interneurons, two photon imaging and electrophysiological recordings in mouse thalamocortical slices. In this preparation, cortical UP states, a network state characterized by prolonged periods of depolarization and synchronized spiking, can be evoked by thalamic stimulation and can also occur spontaneously. To assay the role of inhibition, we first characterized the firing properties of Parvalbumin (PV) and Somatostatin (SOM) interneurons during UP states activity, and found a higher probability and rate of spiking in these two subtypes compared to excitatory cells. These subtypes did not display differential timing of activation during the evoked response. Furthermore, calcium imaging showed low correlations among PV and SOM interneurons, indicating that neurons sharing these neurochemical markers do not coordinate their firing. Intracellular recordings confirmed that nearby interneurons, known to be electrically coupled, do not display more synchronous spiking than excitatory cells, suggesting that this coupling may not function to synchronize the activity of interneurons on fast time scales¬¬¬. After characterizing inhibitory interneuron outputs, we next studied the timing and correlation of inhibitory inputs, which we isolated from excitatory inputs by voltage clamping at the reversal for excitation (0mV) or inhibition (-70mV). In both thalamically triggered and spontaneous activations, IPSCs between cell pairs were remarkably well correlated, with correlation coefficients reaching over .9 in some cases. This high degree of correlation has previously been assumed to be due to interneuron synchrony, but our population imaging and paired recordings did not support this view. In addition, we found that the connection rate between interneurons is very high (~80%), and quantal analysis revealed that each IPSC recorded in neighboring cells during an UP state could be due to a single presynaptic interneuron. Therefore, we explain the high IPSCs correlations in nearby pyramidal cells are emerging from the common input from individual interneurons, rather than from synchronization of interneuron activity across the population. In a final set of experiments, we found that a partial pharmacological block of inhibitory signaling increased EPSC correlations. Our data support a model in which inhibitory neurons do not fire in a correlated fashion but have strong, dense connections to pyramidal neurons that serve to prevent local excitatory synchrony during UP states. This would mean that inhibition may not, as previously thought, serve to synchronize the firing of excitatory cells, but have precisely the opposite effect, decorrelating their activity by breaking down their coordinated firing. This is consistent with the hypothesis that pyramidal cells are carrying out an essentially integrative function in the circuit and that interneurons expand the temporal dynamic range of this integration

Cortical And Subcortical Mechanisms For Sound Processing

The auditory cortex is essential for encoding complex and behaviorally relevant sounds. Many questions remain concerning whether and how distinct cortical neuronal subtypes shape and encode both simple and complex sound properties. In chapter 2, we tested how neurons in the auditory cortex encode water-like sounds perceived as natural by human listeners, but that we could precisely parametrize. The stimuli exhibit scale-invariant statistics, specifically temporal modulation within spectral bands scaled with the center frequency of the band. We used chronically implanted tetrodes to record neuronal spiking in rat primary auditory cortex during exposure to our custom stimuli at different rates and cycle-decay constants. We found that, although neurons exhibited selectivity for subsets of stimuli with specific statistics, over the population responses were stable. These results contribute to our understanding of how auditory cortex processes natural sound statistics. In chapter 3, we review studies examining the role of different cortical inhibitory interneurons in shaping sound responses in auditory cortex. We identify the findings that support each other and the mechanisms that remain unexplored. In chapter 4, we tested how direct feedback from auditory cortex to the inferior colliculus modulated sound responses in the inferior colliculus. We optogenetically activated or suppressed cortico-collicular feedback while recording neuronal spiking in the mouse inferior colliculus in response to pure tones and dynamic random chords. We found that feedback modulated sound responses by reducing sound selectivity by decreasing responsiveness to preferred frequencies and increasing responsiveness to less preferred frequencies. Furthermore, we tested the effects of perturbing intra-cortical inhibitory-excitatory networks on sound responses in the inferior colliculus. We optogenetically activated or suppressed parvalbumin-positive (PV) and somatostatin-positive (SOM) interneurons while recording neuronal spiking in mouse auditory cortex and inferior colliculus. We found that modulation of neither PV- nor SOM-interneurons affected sound-evoked responses in the inferior colliculus, despite significant modulation of cortical responses. Our findings imply that cortico-collicular feedback can modulate responses to simple and complex auditory stimuli independently of cortical inhibitory interneurons. These experiments elucidate the role of descending auditory feedback in shaping sound responses. Together these results implicate the importance of the auditory cortex in sound processing