It is not known whether the variability of neural activity in the cerebral cortex carries information or reflects noisy underlying mechanisms. In an examination of the reliability of spike generation using recordings from neurons in rat neocortical slices, the precision of spike timing was found to depend on stimulus transients. Constant stimuli led to imprecise spike trains, whereas stimuli with fluctuations resembling synaptic activity produced spike trains with timing reproducible to less than 1 millisecond. These data suggest a low intrinsic noise level in spike generation, which could allow cortical neurons to accurately transform synaptic input into spike sequences, supporting a possible role for spike timing in the processing of cortical information by the neocortex.
Markov kinetic models were used to synthesize a complete description of synaptic transmission, including opening of voltage-dependent channels in the presynaptic terminal, release of neurotransmitter, gating of postsynaptic receptors, and activation of second-messenger systems. These kinetic schemes provide a more general framework for modeling ion channels than the Hodgkin-Huxley formalism, supporting a continuous spectrum of descriptions ranging from the very simple and computationally efficient to the highly complex and biophysically precise. Examples are given of simple kinetic schemes based on fits to experimental data that capture the essential properties of voltage-gated, synaptic and neuromodulatory currents. The Markov formalism allows the dynamics of ionic currents to be considered naturally in the larger context of biochemical signal transduction. This frame, work can facilitate the integration of a wide range of experimental data and promote consistent theoretical analysis of neural mechanisms from molecular interactions to network computations.
Granule cells are axonless local interneurons that mediate lateral inhibitory interactions between the principal neurons of the olfactory bulb via dendrodendritic reciprocal synapses. This unusual arrangement may give rise to functional properties different from conventional lateral inhibition. Although granule cells spike, little is known about the role of the action potential with respect to their synaptic output. To investigate the signals that underlie dendritic release in these cells, two-photon microscopy in rat brain slices was used to image calcium transients in granule cell dendrites and spines. Action potentials evoked calcium transients throughout the dendrites, with amplitudes increasing with distance from soma and attaining a plateau level within the external plexiform layer, the zone of granule cell synaptic output. Transient amplitudes were, on average, equal in size in spines and adjacent dendrites. Surprisingly, both spine and dendritic amplitudes were strongly dependent on membrane potential, decreasing with depolarization and increasing with hyperpolarization from rest. Both the current-voltage relationship and the time course of inactivation were consistent with the known properties of T-type calcium channels, and the voltage dependence was blocked by application of the T-type calcium channel antagonists Ni2+ and mibefradil. In addition, mibefradil reduced action potential-mediated synaptic transmission from granule to mitral cells. The implication of a transiently inactivating calcium channel in synaptic release from granule cells suggests novel mechanisms for the regulation of lateral inhibition in the olfactory bulb.
The neuromodulator serotonin (5-HT) has been implicated in a variety of functions that involve patience or impulse control. Many of these effects are consistent with a long-standing theory that 5-HT promotes behavioral inhibition, a motivational bias favoring passive over active behaviors. To further test this idea, we studied the impact of 5-HT in a probabilistic foraging task, in which mice must learn the statistics of the environment and infer when to leave a depleted foraging site for the next. Critically, mice were required to actively nose-poke in order to exploit a given site. We show that optogenetic activation of 5-HT neurons in the dorsal raphe nucleus increases the willingness of mice to actively attempt to exploit a reward site before giving up. These results indicate that behavioral inhibition is not an adequate description of 5-HT function and suggest that a unified account must be based on a higher-order function.
Serotonin has widespread, but computationally obscure, modulatory effects on learning and cognition. Here, we studied the impact of optogenetic stimulation of dorsal raphe serotonin neurons in mice performing a non-stationary, reward-driven decision-making task. Animals showed two distinct choice strategies. Choices after short inter-trial-intervals (ITIs) depended only on the last trial outcome and followed a win-stay-lose-switch pattern. In contrast, choices after long ITIs reflected outcome history over multiple trials, as described by reinforcement learning models. We found that optogenetic stimulation during a trial significantly boosted the rate of learning that occurred due to the outcome of that trial, but these effects were only exhibited on choices after long ITIs. This suggests that serotonin neurons modulate reinforcement learning rates, and that this influence is masked by alternate, unaffected, decision mechanisms. These results provide insight into the role of serotonin in treating psychiatric disorders, particularly its modulation of neural plasticity and learning.
SUMMARYAND CONCLUSIONS1. The spread of electrical signals in pyramidal neurons from the CA1 field of rat hippocampus was investigated through multicompartmental modeling based on three-dimensional morphometric reconstructions of four of these cells. These models were used to dissect the electrotonic architecture of these neurons, and to evaluate the equivalent cylinder approach that this laboratory and others have previously applied to them. Robustness of results was verified by the use of wide ranges of values of specific membrane resistance (R,) and cytoplasmic resistivity.2. The anatomy exhibited extreme departures from a key assumption of the equivalent cylinder model, the so-called "3/2 power law. ' ' 3. The compartmental models showed that the frequency distribution of steady-state electrotonic distances between the soma and the dendritic terminations was multimodal, with a large range and a sizeable coefficient of variation. This violated another central assumption of the equivalent cylinder model, namely, that all terminations are electrotonically equidistant from the soma. This finding, which was observed both for "centrifugal"(away from the soma) and ' 'centripetal" (toward the soma) spread of electrical signals, indicates that the concept of an equivalent electrotonic length for the whole dendritic tree is not appropriate for these neurons.4. The multiple peaks in the electrotonic distance distributions, whether for centrifugal or centripetal voltage transfer, were clearly related to the laminar organization of synaptic afferents in the CA1 region.5. The results in the three preceding paragraphs reveal how little of the electrotonic architecture of these neurons is captured by a simple equivalent cylinder model. The multicompartmental model is more appropriate for exploring synaptic signaling and transient events in CA1 pyramidal neurons.6. There was significant attenuation of synaptic potential, current, and charge as they spread from the dendritic tree to the soma. Charge suffered the least and voltage suffered the most attenuation. Attenuation depended weakly on R, and strongly on synaptic location. Delay of time to peak was more distorted for voltage than for current and was more affected by R,.7. Adequate space clamp is not possible for most of the synapses on these cells. Application of a somatic voltage clamp had no significant effect on voltage transients in the subsynaptic membrane.8. The possible existence of steep voltage gradients within the dendritic tree is consistent with the idea that there can be some degree of local processing and that different regions of the neuron may function semiautonomously. These spatial gradients are potentially relevant to synaptic plasticity in the hippocampus, and they also suggest caution in interpreting some neurophysiological results.
Weber's law states that the discriminability between two stimulus intensities depends only on their ratio. Despite its status as the cornerstone of psychophysics, the mechanisms underlying Weber's law are still debated, as no principled way exists to choose between its many proposed alternative explanations. We studied this problem training rats to discriminate the lateralization of sounds of different overall level. We found that the rats' discrimination accuracy in this task is level-invariant, consistent with Weber's law. Surprisingly, the shape of the reaction time distributions is also level-invariant, implying that the only behavioral effect of changes in the overall level of the sounds is a uniform scaling of time. Furthermore, we demonstrate that Weber's law breaks down if the stimulus duration is capped at values shorter than the typical reaction time. Together, these facts suggest that Weber's law is associated to a process of bounded evidence accumulation. Consistent with this hypothesis, we show that, among a broad class of sequential sampling models, the only robust mechanism consistent with reaction time scale-invariance is based on perfect accumulation of evidence up to a constant bound, Poisson-like statistics, and a power-law encoding of stimulus intensity. Fits of a minimal diffusion model with these characteristics describe the rats performance and reaction time distributions with virtually no error. Various manipulations of motivation were unable to alter the rats' psychometric function, demonstrating the stability of the just-noticeable-difference and suggesting that, at least under some conditions, the bound for evidence accumulation can set a hard limit on discrimination accuracy. Our results establish the mechanistic foundation of the process of intensity discrimination and clarify the factors that limit the precision of sensory systems.
Essential features of the world are often hidden and must be inferred by constructing internal models based on indirect evidence. Here, to study the mechanisms of inference we established a foraging task that is naturalistic and easily learned, yet can distinguish inference from simpler strategies such as the direct integration of sensory data. We show that both mice and humans learn a strategy consistent with optimal inference of a hidden state. However, humans acquire this strategy more than an order of magnitude faster than mice. Using optogenetics in mice we show that orbitofrontal and anterior cingulate cortex inactivation impact task performance, but only orbitofrontal inactivation reverts mice from an inference-based to a stimulus-bound decision strategy. These results establish a cross-species paradigm for studying the problem of inference-based decision-making and begin to dissect the network of brain regions crucial for its performance.
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