Stochastic Memristive Interface for Neural Signal Processing

We propose a memristive interface consisting of two FitzHugh–Nagumo electronic neurons connected via a metal–oxide (Au/Zr/ZrO2(Y)/TiN/Ti) memristive synaptic device. We create a hardware–software complex based on a commercial data acquisition system, which records a signal generated by a presynaptic electronic neuron and transmits it to a postsynaptic neuron through the memristive device. We demonstrate, numerically and experimentally, complex dynamics, including chaos and different types of neural synchronization. The main advantages of our system over similar devices are its simplicity and real-time performance. A change in the amplitude of the presynaptic neurogenerator leads to the potentiation of the memristive device due to the self-tuning of its parameters. This provides an adaptive modulation of the postsynaptic neuron output. The developed memristive interface, due to its stochastic nature, simulates a real synaptic connection, which is very promising for neuroprosthetic applications.

Paired feed-forward excitation with delayed inhibition allows high frequency computations across brain regions

The transmission of high-frequency temporal information across brain regions is critical to perception, but the mechanisms underlying such transmission remain unclear. Long-range projection patterns across brain areas are often comprised of paired feedforward excitation followed closely by delayed inhibition, including the thalamic triad synapse, thalamic projections to cortex, and projections within hippocampus. Previous studies have shown that these joint projections produce a shortened period of depolarization, sharpening the timing window over which the postsynaptic neuron can fire. Here we show that these projections can facilitate the transmission of high-frequency computations even at frequencies that are highly filtered by neuronal membranes. Further, they can coordinate computations across multiple brain areas, even amid ongoing local activity. We suggest that paired feedforward excitation and inhibition provides a hybrid signal - carrying both a value and a clock-like trigger - to allow circuits to be responsive to input whenever it arrives.

Presynaptic MAST kinase controls opposing postsynaptic responses to convey stimulus valence in Caenorhabditis elegans

Presynaptic plasticity is known to modulate the strength of synaptic transmission. However, it remains unknown whether regulation in presynaptic neurons can evoke excitatory and inhibitory postsynaptic responses. We report here that the Caenorhabditis elegans homologs of MAST kinase, Stomatin, and Diacylglycerol kinase act in a thermosensory neuron to elicit in its postsynaptic neuron an excitatory or inhibitory response that correlates with the valence of thermal stimuli. By monitoring neural activity of the valence-coding interneuron in freely behaving animals, we show that the alteration between excitatory and inhibitory responses of the interneuron is mediated by controlling the balance of two opposing signals released from the presynaptic neuron. These alternative transmissions further generate opposing behavioral outputs necessary for the navigation on thermal gradients. Our findings suggest that valence-encoding interneuronal activity is determined by a presynaptic mechanism whereby MAST kinase, Stomatin, and Diacylglycerol kinase influence presynaptic outputs.

Excitatory and inhibitory intracortical circuits for orientation and direction selectivity

The computations performed by a neuron arise from the functional properties of the circuits providing its synaptic inputs. A prime example of these computations is the selectivity of primary visual cortex (V1) for orientation and motion direction. V1 neurons in layer 2/3 (L2/3) receive input mostly from intracortical circuits1, which involve excitation2-9 and inhibition10-12. To understand how an L2/3 neuron achieves its selectivity, therefore, one must characterize the functional organization of both its excitatory and inhibitory presynaptic ensembles. Here we establish this organization, and show how it predicts orientation selectivity and reveals a new cortical circuit for direction selectivity. We identified the presynaptic partners of pyramidal neurons in mouse V1 through rabies monosynaptic tracing1,13, and imaged the functional properties of the postsynaptic neuron and of its presynaptic ensemble. Excitatory presynaptic neurons were predominantly tuned to the postsynaptic neuron’s preferred orientation. Excitation and inhibition described an inverted Mexican hat, with inhibitory presynaptic neurons densest near the postsynaptic neuron and excitatory ones distributed more distally. Excitation and inhibition also differed in laminar origin: inhibitory presynaptic neurons concentrated in L2/3 while excitatory ones dominated in L4. The distribution of excitatory neurons in visual space was coaxial with the postsynaptic neuron’s preferred orientation and lay upstream of the neuron’s preferred direction. Inhibitory presynaptic neurons, instead, clustered more symmetrically around the postsynaptic neuron and favoured locations downstream of its preferred direction. These results demonstrate that L2/3 neurons obtain orientation selectivity from co-tuned neurons in L4 and beyond, and enhance it by contrasting an elongated excitatory input with a concentric inhibitory input. Moreover, L2/3 neurons can obtain direction selectivity through visually offset14 excitation and inhibition. These circuit motifs resemble those seen in the thalamocortical pathway15-20 and in direction selective cells in the retina21,22, suggesting that they are canonical across brain regions.

Modeling the short-term dynamics of in vivo excitatory spike transmission

Information transmission in neural networks is influenced by both short-term synaptic plasticity (STP) as well as non-synaptic factors, such as after-hyperpolarization currents and changes in excitability. Although these effects have been widely characterized in vitro using intracellular recordings, how they interact in vivo is unclear. Here we develop a statistical model of the short-term dynamics of spike transmission that aims to disentangle the contributions of synaptic and non-synaptic effects based only on observed pre- and postsynaptic spiking. The model includes a dynamic functional connection with short-term plasticity as well as effects due to the recent history of postsynaptic spiking and slow changes in postsynaptic excitability. Using paired spike recordings, we find that the model accurately describes the short-term dynamics of in vivo spike transmission at a diverse set of identified and putative excitatory synapses, including a thalamothalamic connection in mouse, a thalamocortical connection in a female rabbit, and an auditory brainstem synapse in a female gerbil. We illustrate the utility of this modeling approach by showing how the spike transmission patterns captured by the model may be sufficient to account for stimulus-dependent differences in spike transmission in the auditory brainstem (endbulb of Held). Finally, we apply this model to large-scale multi-electrode recordings to illustrate how such an approach has the potential to reveal cell-type specific differences in spike transmission in vivo. Although short-term synaptic plasticity parameters estimated from ongoing pre- and postsynaptic spiking are highly uncertain, our results are partially consistent with previous intracellular observations in these synapses.Significance StatementAlthough synaptic dynamics have been extensively studied and modeled using intracellular recordings of post-synaptic currents and potentials, inferring synaptic effects from extracellular spiking is challenging. Whether or not a synaptic current contributes to postsynaptic spiking depends not only on the amplitude of the current, but also on many other factors, including the activity of other, typically unobserved, synapses, the overall excitability of the postsynaptic neuron, and how recently the postsynaptic neuron has spiked. Here we developed a model that, using only observations of pre- and postsynaptic spiking, aims to describe the dynamics of in vivo spike transmission by modeling both short-term synaptic plasticity and non-synaptic effects. This approach may provide a novel description of fast, structured changes in spike transmission.

Inferring causal connectivity from pairwise recordings and optogenetics

To study how the brain works, it is crucial to identify causal interactions between neurons, which is thought to require perturbations. However, when using optogenetics we typically perturb multiple neurons, producing a confound - any of the stimulated neurons can have affected the postsynaptic neuron. Here we show how this produces large biases, and how they can be reduced using the instrumental variable (IV) technique from econometrics. The interaction between stimulation and the absolute refractory period produces a weak, approximately random signal which can be exploited to estimate causal connectivity. When simulating integrate-and-fire neurons, we find that estimates from IV are better than naïve techniques (R2= 0.77 vsR2= 0.01). The difference is important as the estimates disagree when applied to experimental data from stimulated neurons with recorded spiking activity. Presented is a robust analysis framework for mapping out network connectivity based on causal neuron interactions.

Analyzing synaptic plasticity at the single cell level with STDP

Using patch clamp recordings in acutely isolated brain slices allows to investigate molecular processes that are involved in long-term potentiation (LTP) and long-term depression (LTD) at the level of a single postsynaptic neuron. Via the pipette solution in the recording pipette, it is possible to apply inhibitors of signaling cascades selectively into the postsynaptic neuron to unravel the molecular mechanisms of synaptic plasticity. In recent years, LTP research has been increasingly focused on induction protocols for LTP and LTD that rely on a minimal number of repeated synaptic stimulations at low frequency to induce synaptic plasticity. This is where spike timing-dependent plasticity (STDP) comes into play. STDP can be induced by repetitive pairings of action potential firing in presynaptic (first neuron) – and postsynaptic (second synaptically connected) neurons, that occurs with a delay of roughly 5–20 ms in forward or backward manner. While forward pairing with short positive time delays (“pre before post”) leads to LTP, backward pairing (“post before pre”) leads to LTD. In addition to the exact sequence and timing of pre- and postsynaptic spiking, the presence of neuromodulatory transmitters in the extracellular space (e. g., dopamine, acetylcholine, noradrenaline) and the synaptic release of intercellular mediators of synaptic plasticity (e. g., BDNF, endocannabinoids) critically regulate the outcome of STDP protocols. In this review we focus on the role of these mediators and modulators of synaptic plasticity in STDP.

General Psychopharmacology

Initial development of neuropsychiatric medications relied heavily on serendipitous discovery rather than targeted drug designs. Nowadays, drug discovery targets include receptors, enzymes, and transporters. The human brain comprises many neurons, each being connected to other neurons via synapses. Neurotransmission occurs when a presynaptic neuron projects its terminal segment to form a connection or synapse with an adjacent postsynaptic neuron. When stimulated, neurotransmitters that are stored in small vesicles in the presynaptic neuron are released into an interneuronal gap called the synaptic cleft. Serotonin, dopamine, norepinephrine, γ-amino butyric acid, glutamate, and acetylcholine are among the primary neurotransmitters and chemicals that play important roles in neuropsychiatric functions. As such, they are often common targets of drug development. Grasping the basics of neurotransmission, enzyme degradation, and receptor and transporter pharmacology is essential in understanding today’s FDA-approved pharmaceuticals. This neuropharmacology primer will allow the rational and appropriate clinical selection of pharmacotherapy and accurate anticipation of clinical effects following use. This review contains 1 figure and 45 references Key Words: acetylcholine, dopamine, γ-amino butyric acid, glutamate, neurotransmission, norepinephrine, pharmacology, psychiatric medications, psychopharmacology, receptor, serotonin