Mental rotation-related neural interactions between gender and cognitive strategy A long-standing history of research has focused on the differences between men and women in cognitive tasks, including that men would be more accurate and faster than women in mental rotation (MR). This advantage suggests that men would use an object-based cognitive strategy (OBS) to perform MR, whereas women would rely more on an effector-based cognitive strategy (EBS). To test this hypothesis, participants in the present study performed MR using OBS and EBS (plus a control condition) while their brain activity was recorded using fMRI. As sex hormones have often been reported to influence spatial ability, we also assessed the relationship between MR and testosterone levels and digit ratio. Behavioral results showed that (1) men performed faster MR than women in the OBS and control conditions, (2) men were more accurate than women in the OBS condition, and (3) women performed better in OBS than the other two conditions. No relationship was found between MR and testosterone or digit ratio. fMRI data showed that women in the OBS condition had greater activation than men in the inferior frontal and somatosensory cortices. Salivary testosterone levels had no effect on whole-brain activity. Combining behavioral and brain imaging data, these findings suggest that the additional somatosensory activation found in women during OBS somehow affects their MR, preventing the use of a purely spatial strategy and promoting the use of body-based sensorimotor processing, which would result in lower accuracy. These results support that gender differences in MR would be better explained by considering their relationship with the cognitive strategies used to perform MR.
Dorsomedial and ventromedial prefrontal cortex lesions differentially impact social influence and temporal impulsivity The medial prefrontal cortex (mPFC) has long been associated with economic and social decision-making in neuroimaging studies. Several debates question whether different ventromedial PFC (vmPFC) and dorsomedial PFC (dmPFC) regions have specific functions or whether there is a gradient supporting social and non-social cognition. Here, we tested an unusually large sample of rare participants with focal damage to mPFC (N = 33), individuals with lesions elsewhere (N = 17), and healthy controls (N = 71) (total N = 121). Participants completed a temporal discounting task to estimate their baseline discounting preferences before learning the preferences of two other people, one who was more temporally impulsive and one more patient. We used Bayesian computational models to estimate baseline discounting and susceptibility to social influence after learning others’ economic preferences. mPFC damage increased susceptibility to impulsive social influence compared to healthy controls and increased overall susceptibility to social influence compared to those with lesions elsewhere. Importantly, voxel-based lesion-symptom mapping (VLSM) of computational parameters showed that this heightened susceptibility to social influence was attributed specifically to damage to the dorsomedial prefrontal cortex (dmPFC, area 9). In contrast, lesions in the vmPFC (areas 13 and 25) and ventral striatum were associated with a preference for seeking more immediate rewards. We show that the dmPFC is causally implicated in susceptibility to social influence, with distinct ventral portions of mPFC involved in temporal discounting.
Cortical development in the structural model and free energy minimization A model of neocortical development invoking Friston’s Free Energy Principle is applied within the Structural Model of Barbas et al. and the associated functional interpretation advanced by Tucker and Luu. Evolution of a neural field with Hebbian and anti-Hebbian plasticity, maximizing synchrony and minimizing axonal length by apoptotic selection, leads to paired connection systems with mirror symmetry, interacting via Markov blankets along their line of reflection. Applied to development along the radial lines of development in the Structural Model, a primary Markov blanket emerges between the centrifugal synaptic flux in layers 2,3 and 5,6, versus the centripetal flow in layer 4, and axonal orientations in layer 4 give rise to the differing shape and movement sensitivities characteristic of neurons of dorsal and ventral neocortex. Prediction error minimization along the primary blanket integrates limbic and subcortical networks with the neocortex. Synaptic flux bypassing the blanket triggers the arousal response to surprising stimuli, enabling subsequent adaptation. As development progresses ubiquitous mirror systems separated by Markov blankets and enclosed blankets-within-blankets arise throughout neocortex, creating the typical order and response characteristics of columnar and noncolumnar cortex.
Structural influences on synaptic plasticity: The role of presynaptic connectivity in the emergence of E/I co-tuning Cortical neurons are versatile and efficient coding units that develop strong preferences for specific stimulus characteristics. The sharpness of tuning and coding efficiency is hypothesized to be controlled by delicately balanced excitation and inhibition. These observations suggest a need for detailed co-tuning of excitatory and inhibitory populations. Theoretical studies have demonstrated that a combination of plasticity rules can lead to the emergence of excitation/inhibition (E/I) co-tuning in neurons driven by independent, low-noise signals. However, cortical signals are typically noisy and originate from highly recurrent networks, generating correlations in the inputs. This raises questions about the ability of plasticity mechanisms to self-organize co-tuned connectivity in neurons receiving noisy, correlated inputs. Here, we study the emergence of input selectivity and weight co-tuning in a neuron receiving input from a recurrent network via plastic feedforward connections. We demonstrate that while strong noise levels destroy the emergence of co-tuning in the readout neuron, introducing specific structures in the non-plastic pre-synaptic connectivity can re-establish it by generating a favourable correlation structure in the population activity. We further show that structured recurrent connectivity can impact the statistics in fully plastic recurrent networks, driving the formation of co-tuning in neurons that do not receive direct input from other areas. Our findings indicate that the network dynamics created by simple, biologically plausible structural connectivity patterns can enhance the ability of synaptic plasticity to learn input-output relationships in higher brain areas.
Collective dynamics in spiking neural networks: A systematic review This study aims to review recent research on the collective behaviour of excitatory and inhibitory (E-I) spiking neural networks. The research methodology used is Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedures, comprising three primary stages: an initial search for literature in the SCOPUS database, a screening process based on specific inclusion and exclusion criteria, and a review of the selected literatures. Out of 491 documents from 2014 to 2024, 6 research papers are qualified for review. Four distinct dynamical states have been identified: synchrony, irregular behaviour, stationary state, and oscillatory dynamics. Our review findings suggest that the collective dynamics of E-I spiking neurons stem from the interaction of intrinsic neuronal characteristics, balance mechanisms, and the type of external stimuli. Additionally, the widespread use of Quadratic Integrate-and-Fire (QIF) neurons in the literature highlights its significance as a robust candidate for exploring collective behaviours in large-scale neuronal networks.
Synapses learn to utilize stochastic pre-synaptic release for the prediction of postsynaptic dynamics Synapses in the brain are highly noisy, which leads to a large trial-by-trial variability. Given how costly synapses are in terms of energy consumption these high levels of noise are surprising. Here we propose that synapses use noise to represent uncertainties about the somatic activity of the postsynaptic neuron. To show this, we developed a mathematical framework, in which the synapse as a whole interacts with the soma of the postsynaptic neuron in a similar way to an agent that is situated and behaves in an uncertain, dynamic environment. This framework suggests that synapses use an implicit internal model of the somatic membrane dynamics that is being updated by a synaptic learning rule, which resembles experimentally well-established LTP/LTD mechanisms. In addition, this approach entails that a synapse utilizes its inherently noisy synaptic release to also encode its uncertainty about the state of the somatic potential. Although each synapse strives for predicting the somatic dynamics of its postsynaptic neuron, we show that the emergent dynamics of many synapses in a neuronal network resolve different learning problems such as pattern classification or closed-loop control in a dynamic environment. Hereby, synapses coordinate themselves to represent and utilize uncertainties on the network level in behaviorally ambiguous situations.
Coupling of saccade plans to endogenous attention during urgent choices The neural mechanisms that willfully direct attention to specific locations in space are closely related to those for generating targeting eye movements (saccades). However, the degree to which the voluntary deployment of attention to a location necessarily activates a corresponding saccade plan remains unclear. One problem is that attention and saccades are both automatically driven by salient sensory events; another is that the underlying processes unfold within tens of milliseconds only. Here, we use an urgent task design to resolve the evolution of a visuomotor choice on a moment-by-moment basis while independently controlling the endogenous (goal-driven) and exogenous (salience-driven) contributions to performance. Human participants saw a peripheral cue and, depending on its color, either looked at it (prosaccade) or looked at a diametrically opposite, uninformative non-cue (antisaccade). By varying the luminance of the stimuli, the exogenous contributions could be cleanly dissociated from the endogenous process guiding the choice over time. According to the measured time courses, generating a correct antisaccade requires about 30 ms more processing time than generating a correct prosaccade based on the same perceptual signal. The results indicate that saccade plans elaborated during fixation are biased toward the location where attention is endogenously deployed, but the coupling is weak and can be willfully overridden very rapidly.
Neurobiology Research on Neurodegenerative Disorders The aim of the following Special Issue was to call for research in the field of neurodegenerative disorders (NDDs). Despite the growing interest in this field over the past few decades, the unquestionable progress in understanding the mechanisms underlying NDDs and numerous attempts to find effective therapies, many questions remain unanswered. Moreover, since it is not possible to reverse the progressive degeneration of neurons in various regions of the central nervous system (CNS), NDDs are still considered incurable. As such, further research is warranted. The scope of this Special Issue covers articles on diagnostics, mechanisms underlying NDDs, and new or modified therapeutic strategies.
Despite the decreasing trend in dementia observed recently in North America and Europe [1], given population growth and ageing trends, the number of people affected by dementia is expected to increase worldwide [1]. This makes dementia a rapidly growing global public health problem. To meet this challenge, new studies are being designed and attempts are being made to develop new treatments. Numerous studies have been conducted to test the effectiveness of various substances in treating dementia, including Alzheimer’s disease (AD), using animal models of the disease. Various doses and routes of administration have been tested in different studies. The results of two such studies are presented in this Special Issue. Lu et al. investigated mechanisms at the base of the neuroprotective action of Apelin-13 (Contribution 1), the endogenous ligand of the apelin receptor (APJ) involved in processes in the CNS such as inflammation, oxidative stress, apoptosis, and autophagy. The researchers used a streptozotocin (STZ)-induced model of AD, in which STZ (3 mg/kg) was injected into the lateral ventricles of C57BL/6J mice. The above model is a widely used model of sporadic AD. The results showed that the intranasal administration of Apelin-13 (1 mg/kg) improved cognitive function in AD mice. The functional outcome correlated with the enhancement of synaptic plasticity and the attenuation of oxidative stress. The authors conclude that intranasal administration of Apelin-13 may prove to be a promising therapeutic strategy for neurodegenerative diseases such as AD.