Search results for "cognitive neuroscience"

Interference of left and right cerebellar rTMS with procedural learning.

2004

Abstract Increasing evidence suggests cerebellar involvement in procedural learning. To further analyze its role and to assess whether it has a lateralized influence, in the present study we used a repetitive transcranial magnetic stimulation interference approach in a group of normal subjects performing a serial reaction time task. We studied 36 normal volunteers: 13 subjects underwent repetitive transcranial magnetic stimulation on the left cerebellum and performed the task with the right (6 subjects) or left (7 subjects) hand; 10 subjects underwent repetitive transcranial magnetic stimulation on the right cerebellum and performed the task with the hand ipsilateral (5 subjects) or contral…

Chemogenetic Suppression of the Subthalamic Nucleus Induces Attentional Deficits and Impulsive Action in a Five-Choice Serial Reaction Time Task in M…

2020

The subthalamic nucleus (STN), a key component of the basal ganglia circuitry, receives inputs from broad cerebral cortical areas and relays cortical activity to subcortical structures. Recent human and animal studies have suggested that executive function, which is assumed to consist of a set of different cognitive processes for controlling behavior, depends on precise information processing between the cerebral cortex and subcortical structures, leading to the idea that the STN contains neurons that transmit the information required for cognitive processing through their activity, and is involved in such cognitive control directly and dynamically. On the other hand, the STN activity also …

Transcranial magnetic stimulation and neuroplasticity

1998

We review past results and present novel data to illustrate different ways in which TMS can be used to study neural plasticity. Procedural learning during the serial reaction time task (SRTT) is used as a model of neural plasticity to illustrate the applications of TMS. These different applications of TMS represent principles of use that we believe are applicable to studies of cognitive neuroscience in general and exemplify the great potential of TMS in the study of brain and behavior. We review the use of TMS for (1) cortical output mapping using focal, single-pulse TMS; (2) identification of the mechanisms underlying neuroplasticity using paired-pulse TMS techniques; (3) enhancement of th…

2018

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that allows the modulation of cortical excitability as well as neuroplastic reorganization using a weak constant current applied through the skull on the cerebral cortex. TDCS has been found to improve motor performance in general and motor learning in particular. However, these effects have been reported almost exclusively for unimanual motor tasks such as serial reaction time tasks, adaptation tasks, or visuo-motor tracking. Despite the importance of bimanual actions in most activities of daily living, only few studies have investigated the effects of tDCS on bimanual motor skills. The objectives …

A cooperating strategy for objects recognition

1999

The paper describes an object recognition system, based on the co-operation of several visual modules (early vision, object detector, and object recognizer). The system is active because the behavior of each module is tuned on the results given by other modules and by the internal models. This solution allows to detect inconsistencies and to generate a feedback process. The proposed strategy has shown good performance especially in case of complex scene analysis, and it has been included in the visual system of the DAISY robotics system. Experimental results on real data are also reported.

Mimicking biological mechanisms for sensory information fusion

2013

Current Artificial Intelligence systems are bound to become increasingly interconnected to their surrounding environment in the view of the newly rising Ambient Intelligence (AmI) perspective. In this paper, we present a comprehensive AmI framework for performing fusion of raw data, perceived by sensors of different nature, in order to extract higher-level information according to a model structured so as to resemble the perceptual signal processing occurring in the human nervous system. Following the guidelines of the greater BICA challenge, we selected the specific task of user presence detection in a locality of the system as a representative application clarifying the potentialities of …

Editorial

2021

This Special Issue of Cognitive System Research on Biologically Inspired Cognitive Architectures: Papers from the Tenth Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2019) have solicited and collected research papers in all domains of science and technology that directly or indirectly may help us to make an advance toward the BICA Challenge, which is to implement the top essential functionality of the human mind in a machine. Overall, the volume presents a pleasant overview with contributions from many countries depicting all major topics in BICA Challenge research. Personally, I am very pleased to have served as guest editor, and I am convinced that…

An architecture for observational learning and decision making based on internal models

2013

We present a cognitive architecture whose main constituents are allowed to grow through a situated experience in the world. Such an architectural growth is bootstrapped from a minimal initial knowledge and the architecture itself is built around the biologically-inspired notion of internal models. The key idea, supported by findings in cognitive neuroscience, is that the same internal models used in overt goal-directed action execution can be covertly re-enacted in simulation to provide a unifying explanation to a number of apparently unrelated individual and social phenomena, such as state estimation, action and intention understanding, imitation learning and mindreading. Thus, rather than…

Video object recognition and modeling by SIFT matching optimization

2014

In this paper we present a novel technique for object modeling and object recognition in video. Given a set of videos containing 360 degrees views of objects we compute a model for each object, then we analyze short videos to determine if the object depicted in the video is one of the modeled objects. The object model is built from a video spanning a 360 degree view of the object taken against a uniform background. In order to create the object model, the proposed techniques selects a few representative frames from each video and local features of such frames. The object recognition is performed selecting a few frames from the query video, extracting local features from each frame and looki…

A general theoretical framework for designing cognitive architectures: Hybrid and meta-level architectures for BICA

2012

In this paper, we will discuss hybrid architectures in which different processing modules coexist and cooperate in a principled way. A fundamental and essential role is played by modules performing meta-computation, i.e., computation about computation itself. Meta-level architectures, therefore, become an essential complement of hybrid architectures for biologically inspired cognitive architectures (BICA). Engineering and modeling BICAs is a hard task due to the lack of techniques for developing and implementing their features. We propose a new concept of intelligent agent as a useful abstraction for developing BICAs and having means for representing all the involved entities together with …