ConnectomeA connectome (kəˈnɛktoʊm) is a comprehensive map of neural connections in the brain, and may be thought of as its "wiring diagram". An organism's nervous system is made up of neurons which communicate through synapses. A connectome is constructed by tracing the neuron in a nervous system and mapping where neurons are connected through synapses. The significance of the connectome stems from the realization that the structure and function of the human brain are intricately linked, through multiple levels and modes of brain connectivity.
Cognitive impairmentCognitive impairment is an inclusive term to describe any characteristic that acts as a barrier to the cognition process or different areas of cognition. Cognition, also known as cognitive function, refers to the mental processes of how a person gains knowledge, uses existing knowledge, and understands things that are happening around them using their thoughts and senses. A cognitive impairment can be in different domains or aspects of a person's cognitive function including memory, attention span, planning, reasoning, decision-making, language (comprehension, writing, speech), executive functioning, and visuospatial functioning.
Cognitive developmentCognitive development is a field of study in neuroscience and psychology focusing on a child's development in terms of information processing, conceptual resources, perceptual skill, language learning, and other aspects of the developed adult brain and cognitive psychology. Qualitative differences between how a child processes their waking experience and how an adult processes their waking experience are acknowledged (such as object permanence, the understanding of logical relations, and cause-effect reasoning in school-age children).
Retrograde signalingRetrograde signaling in biology is the process where a signal travels backwards from a target source to its original source. For example, the nucleus of a cell is the original source for creating signaling proteins. During retrograde signaling, instead of signals leaving the nucleus, they are sent to the nucleus. In cell biology, this type of signaling typically occurs between the mitochondria or chloroplast and the nucleus. Signaling molecules from the mitochondria or chloroplast act on the nucleus to affect nuclear gene expression.
AttentionAttention is the concentration of awareness on some phenomenon to the exclusion of other stimuli. It is a process of selectively concentrating on a discrete aspect of information, whether considered subjective or objective. William James (1890) wrote that "Attention is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought. Focalization, concentration, of consciousness are of its essence.
NeuroplasticityNeuroplasticity, also known as neural plasticity, or brain plasticity, is the ability of neural networks in the brain to change through growth and reorganization. It is when the brain is rewired to function in some way that differs from how it previously functioned. These changes range from individual neuron pathways making new connections, to systematic adjustments like cortical remapping. Examples of neuroplasticity include circuit and network changes that result from learning a new ability, information acquisition, environmental influences, practice, and psychological stress.
Inhibitory postsynaptic potentialAn inhibitory postsynaptic potential (IPSP) is a kind of synaptic potential that makes a postsynaptic neuron less likely to generate an action potential. IPSPs were first investigated in motorneurons by David P. C. Lloyd, John Eccles and Rodolfo Llinás in the 1950s and 1960s. The opposite of an inhibitory postsynaptic potential is an excitatory postsynaptic potential (EPSP), which is a synaptic potential that makes a postsynaptic neuron more likely to generate an action potential.
GABAergicIn molecular biology and physiology, something is GABAergic or GABAnergic if it pertains to or affects the neurotransmitter gamma-aminobutyric acid (GABA). For example, a synapse is GABAergic if it uses GABA as its neurotransmitter, and a GABAergic neuron produces GABA. A substance is GABAergic if it produces its effects via interactions with the GABA system, such as by stimulating or blocking neurotransmission. A GABAergic or GABAnergic agent is any chemical that modifies the effects of GABA in the body or brain.
Cognitive flexibilityCognitive flexibility is an intrinsic property of a cognitive system often associated with the mental ability to adjust its activity and content, switch between different task rules and corresponding behavioral responses, maintain multiple concepts simultaneously and shift internal attention between them. The term cognitive flexibility is traditionally used to refer to one of the executive functions. In this sense, it can be seen as neural underpinnings of adaptive and flexible behavior.
Magnetic resonance imagingMagnetic resonance imaging (MRI) is a medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes of the body. MRI scanners use strong magnetic fields, magnetic field gradients, and radio waves to generate images of the organs in the body. MRI does not involve X-rays or the use of ionizing radiation, which distinguishes it from computed tomography (CT) and positron emission tomography (PET) scans.
Neural networkA neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.
Residual neural networkA Residual Neural Network (a.k.a. Residual Network, ResNet) is a deep learning model in which the weight layers learn residual functions with reference to the layer inputs. A Residual Network is a network with skip connections that perform identity mappings, merged with the layer outputs by addition. It behaves like a Highway Network whose gates are opened through strongly positive bias weights. This enables deep learning models with tens or hundreds of layers to train easily and approach better accuracy when going deeper.
