Some aspects of this complex process, such as integration at the level of individual dendritic branches, have been extensively studied. But other aspects, such as how inputs from multiple branches are combined, and the kinetics of that integration have not been systematically examined. Using a 3D digital holographic photolysis technique to overcome the challenges posed by the complexities of the 3D anatomy of the dendritic arbor of CA1 pyramidal neurons for conventional photolysis, we show that integration on a single dendrite is fundamentally different from that on multiple dendrites. Multibranch integration occurring at oblique and basal dendrites allows somatic action potential firing of the cell to faithfully follow the driving stimuli over a significantly wider frequency range than what is possible with single branch integration. However, multibranch integration requires greater input strength to drive the somatic action potentials. This tradeoff between sensitivity and temporal precision may explain the puzzling report of the predominance of multibranch, rather than single branch, integration from in vivo recordings during presentation of visual stimuli.

Individual thin dendritic branches are fundamental functional units in the nervous system (Branco and Hausser, 2011). Experimental data support the concept that they can operate as quasi-independent processing and signaling units capable of non-linear behavior (Mel, 1993; Wei et al., 2001). In combination with their parent dendritic branches, these thin distal dendrites can function in two distinct modes (Gasparini and Magee, 2006; Katz et al., 2009). If distributed synaptic inputs arrive on multiple distal branches, the depolarization on each branch may be below the threshold for recruiting local active conductances in a regenerative manner and yet be sufficient to trigger a somatic sodium spike. This is sometimes referred to as the traditional “integrate and fire” model (Abbott, 1999), the “synaptic democracy” model (Yuste, 2011), and the “global” model of integration.

Abstract. Intelligence describes the general cognitive ability level of a person. It is one of the most fundamental concepts in psychological science and is crucial for the effective adaption of behavior to varying environmental demands. Changing external task demands have been shown to induce reconfiguration of functional brain networks. However, whether neural reconfiguration between different tasks is associated with intelligence has not yet been investigated. We used functional magnetic resonance imaging data from 812 subjects to show that higher scores of general intelligence are related to less brain network reconfiguration between resting state and seven different task states as well as to network reconfiguration between tasks. This association holds for all functional brain networks except the motor system and replicates in two independent samples (n = 138 and n = 184). Our findings suggest that the intrinsic network architecture of individuals with higher intelligence scores is closer to the network architecture as required by various cognitive demands. Multitask brain network reconfiguration may, therefore, represent a neural reflection of the behavioral positive manifold – the essence of the concept of general intelligence. Finally, our results support neural efficiency theories of cognitive ability and reveal insights into human intelligence as an emergent property from a distributed multitask brain network.

The plumbing goes deep.

Summary: A new study has identified a brain protein, vesicular nucleotide transporter (Vnut), as essential for regulating mood and motivation in mice. When Vnut was removed from brain cells called astrocytes, the mice displayed higher anxiety, depression-like behavior, and decreased motivation, especially in females.

This effect was linked to reduced dopamine, a key molecule for motivation and positive mood. These findings suggest Vnut plays a vital role in dopamine regulation, with potential implications for understanding mood disorders.