Current Opinion in Behavioral Sciences最新文献

Cortico-cortical paired-associative stimulation (ccPAS) is an advanced dual-site transcranial magnetic stimulation technique that exploits the Hebbian principle to induce plastic changes in functional networks and modulate interactions between cortical brain regions. This review summarizes the growing body of ccPAS research on network dynamics underpinning visual perception. Studies revealed a functional dissociation within cortico-cortical connections in the visual system, where distinct hierarchically organized circuits shape diverse aspects of visual processing, including motion perception, emotion recognition, and metacognitive judgments. Prospective applications integrating ccPAS with neuroimaging techniques such as EEG/MEG hold promise for fine-tuning interventions and gaining deeper insights into visual system network dynamics and functional architecture, with potential clinical applications in neurological and psychiatric conditions.

Transcranial electrical stimulation (tES) has garnered significant attention as a non-invasive neuromodulation technique with promising therapeutic potential for various neurological and neuropsychiatric conditions. However, considerable variability in response to tES both between and within-individuals is a prevailing issue. This review explored recent advancements in optimising tES through individualised protocols that consider individual head anatomy, neural oscillatory activities and dynamic changes in the neurophysiology of the stimulated brain. Real-time monitoring and closed-loop systems allow adaptive adjustments of stimulation parameters in response to ongoing brain activity, which holds promise for enhancing tES effectiveness and overcoming the challenge of inter-session response variability. Overall, the reviewed literature highlights the emerging trend towards individualised tES protocols as a means to unlock the full potential of tES in research and clinical use. While promising, further research is warranted to establish standardised methodologies and validate the efficacy of individually tailored tES protocols to realise its full potential.

Repetitive negative thinking (RNT) is a transdiagnostic construct that encompasses rumination and worry, yet what precisely is shared between rumination and worry is unclear. To clarify this, we develop a meta-control account of RNT. Meta-control refers to the reinforcement and control of mental behavior via similar computations as reinforce and control motor behavior. We propose rumination and worry are coarse terms for failure in meta-control, just as tripping and falling are coarse terms for failure in motor control. We delineate four meta-control stages and risk factors increasing the chance of failure at each, including open-ended thoughts (stage 1), individual differences influencing subgoal execution (stage 2) and switching (stage 3), and challenges inherent to learning adaptive mental behavior (stage 4). Distinguishing these stages therefore elucidates diverse processes that lead to the same behavior of excessive RNT. Our account also subsumes prominent clinical accounts of RNT into a computational cognitive neuroscience framework.

Ultrasound neuromodulation is a promising technology that could revolutionize study and treatment of brain conditions ranging from mood disorders to Alzheimer’s disease and stroke. An understanding of how ultrasound directly modulates specific ion channels could provide a roadmap for targeting specific neurological circuits and achieving desired neurophysiological outcomes. Although experimental challenges make it difficult to unambiguously identify which ion channels are sensitive to ultrasound in vivo, recent progress indicates that there are likely several different ion channels involved, including members of the K2P, Piezo, and transient receptor potential (TRP) channel families. A recent result linking TRP melastatin 2 channels in the hypothalamus to the induction of torpor by ultrasound in rodents demonstrates the feasibility of targeting a specific ion channel in a specific population of neurons.

Multiple sclerosis (MS) is a neurodegenerative, inflammatory, and demyelinating disease of the central nervous system affecting approximately 2.8 million people worldwide. Cerebellar dysfunction in MS presents with ataxia, ocular movement disorders, tremor, dysmetria, as well as cognitive deficits. Magnetic resonance imaging has improved our understanding of cerebellar dysfunctions in MS and their relation to motor and cognitive impairment. In this short review, we discuss current literature and recent progress in the field of cerebellar dysfunction in MS.

Diffusion magnetic resonance imaging (dMRI) is sensitive to the mobility of water in tissue and sensitive to cell geometry and organization in the central nervous system — providing unique insight into both local microstructure and white matter connectivity. Most dMRI methods were developed for studying cerebral white matter but can provide useful information about cerebellar white and gray matter. However, the small size and intricate structure of the cerebellum poses challenges for dMRI. In this review, we discuss these challenges, recent advancements in methodology, and insights from cerebellar applications of novel dMRI methods. While many limitations still remain and should be considered in conclusions regarding microstructure and connectivity, carefully designed experiments and analyses can provide new insight into behavioral and pathological aspects of cerebellar structure and function.

Cognitive flexibility, a cornerstone of human cognition, enables us to adapt to shifting environmental demands. This brain function has been widely explored using computational modeling, although oftentimes these models focus on the operational dimension of cognitive flexibility and do not retain a sufficient level of neurobiological detail to lead to electrophysiological or neuroimaging insights. In this review, we explore recent advances and future directions on neurobiologically plausible computational models of cognitive flexibility. We first cover progress in recurrent neural network models trained to perform flexible cognitive tasks, followed by a discussion on how whole-brain or large-scale brain network models have approached the distributed nature of flexible cognitive functions. Ultimately, we propose here a hybrid framework in which both modeling philosophies converge, advocating for a balanced approach that merges computational power with realistic spatiotemporal dynamics of brain activity, and explore early examples in this direction.

Mystical-like states of consciousness may arise in different contexts, two of the most well-known being drug-induced psychedelic experiences and near-death experiences, which arise in potentially life-threatening contexts. We suggest and review emerging evidence that the former may model the latter in laboratory settings. This suggestion is based on their phenomenologically striking similarities. In addition, this paper highlights crucial directions and relevant questions that require future research in the field, including the challenges associated with their study in laboratory settings and their neurophysiological underpinnings.

Task switching procedures are widely used to assess the processes supporting executive function and cognitive control, but there is wide variation in what subjects are required to do during these procedures and a lack of consensus about what, exactly, constitutes a task switch. The methodological variation in task switching experiments has revealed diverse factors that affect the magnitude of switch costs, thereby enriching our understanding of cognitive control. For example, the empirical phenomena uncovered by these procedures indicate that specific stimulus feature information is integrated with abstract task information in the representations that guide behavior. This insight has motivated theoretical and empirical work examining the close relationship between cognitive control and task representation.