Neuronal dynamics

…is complemented by growing interest in neuronal dynamics. We used tetrode technique to study in hippocampal CA1 activity how spatial representations and neuronal dynamics are affected by environmental and task complexity and by rats’ prior learning experience. Each neuronal ensemble was recorded in four recording sessions: a session where a rat was exposed to a stationary rat-sized robot and a session with the robot slowly moving, were flanked by two sessions without the robot. Some rats were trained to avoid a location define

Sixty years after the discovery of a slow monotonic drift in electroencephalographic recordings preceding voluntary self-paced actions ("the readiness potential"), its physiological underpinnings remain elusive. A classical interpretation holds that readiness potential onset reflects the decision to act, with the drift thereafter proceeding deterministically to movement onset. However, more recent analyses suggest that the readiness potential's monotonicity may be an artifact of trial averaging; rather than a slow, deterministic process, fast stochastic processes underlie self-paced decisions.

…to what extent encoding in OFC neural dynamics generalize across contexts, or are context-specific, by analyzing chronic Neuropixels recordings over consecutive sessions in which rats performed two related, but distinct, decision-making tasks. In

Reservoir computing facilitates the integration of high-dimensional spatiotemporal dynamics with information processing [1]. Here we investigated the correlation between neuronal dynamics and machine learning task performance, utilizing a cultured neuronal network with a modular structure. The results show that the modularity of the neuronal network enhances classification performance in tasks involving multiple speech signals [3].Figure 1 outlines the experimental setup, employing a modular cultured neuronal network of rat cortical neurons on a patterned substrate. Neural activity was measure

…the behavioral impacts and whole-brain neuronal dynamics.Here, we

The central tendency bias, or contraction bias, is a phenomenon where the judgment of the magnitude of items held in working memory (WM) is biased towards the average of past observations. It is assumed to be an optimal strategy by the brain, and commonly thought of an expression of the brain’s ability to learn the statistical structure of sensory inputs. On the other hand, recency biases such as serial dependence are also commonly observed, and are thought to reflect the content of WM. Recent results from an auditory delayed comparison task in rats, suggest that both biases may be more relate

…on the accumulated evidence encoded in neuronal firing rates. However, the correspondence between accumulated evidence and neuronal dynamics is only on aggregate. The choice-related dynamics of individual neurons are heterogeneous

…their applicability to real brain dynamics. Typical efforts to address this mismatch add complexity to increasingly unwieldy models. Here, we take a different approach; by reducing the complexity of a biological cortical culture, we aim to distil the essential factors of neuronal dynamics and plasticity. We leverage recent advances in growing neurons from human induced pluripotent stem cells (hi

…changes, with unclear consequences for neuronal dynamics and function. Here we show that synapses can interact such that excitatory currents are naturally normalised and balanced by inhibitory inputs. This happens when classical spike-timing dependent synaptic plasticity rules are extended by additional mechanisms that incorporate the influence of neighbouring synaptic currents and regulate the amplitude of efficacy changes accordingly. The resulting control of excitatory plasticity by inhibitory activation, and vice versa, gives rise t