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At least 901 records · Page 50Linked to original sources
PubMed2005

Contingency awareness in human aversive conditioning involves the middle frontal gyrus.

In contrast to the wealth of data describing the neural mechanisms underlying classical conditioning, we know remarkably little about the mechanisms involved in acquisition of explicit contingency awareness. Subjects variably acquire contingency awareness in classical conditioning paradigms, in which they are able to describe the temporal relationship between a conditioned cue and its outcome. Previous studies have implicated the hippocampus and prefrontal cortex in the acquisition of explicit knowledge, although their specific roles remain unclear. We used functional magnetic resonance imaging to track the trial-by-trial acquisition of explicit knowledge in a concurrent trace and delay conditioning paradigm. We show that activity in bilateral middle frontal gyrus and parahippocampal gyrus correlates with the accuracy of explicit contingency awareness on each trial. In contrast, amygdala activation correlates with conditioned responses indexed by skin conductance responses (SCRs). These results demonstrate that brain regions known to be involved in other aspects of learning and memory also play a specific role, reflecting on each trial the acquisition and representation of contingency awareness.

Adult↗
PubMed1999

Internal representation in neural networks used for classification of patient anaesthetic states and dosage.

In this study we aimed to explore the ability of artificial neural networks (ANN) to classify patient anaesthetic states and dosage. Surgical data obtained under different states of anaesthesia and dose levels were modelled via this approach. It is shown that inferential parameters can be used to determine the patient anaesthetic states and drug dosage. In addition to demonstrating the capability of ANN for classification we were interested in the internal representations that are developed automatically by networks while they are learning their processing task. An unsupervised learning procedure of clustering via which the classes are inferred from the data and a supervised learning technique of discrimination via which to construct a classification of the known categories were applied to analyse the performance of the ANN. Discriminant analysis (DA) was also utilised to optimise the network architecture.

Anesthesia↗
PubMed1997

Invariant face and object recognition in the visual system.

Neurophysiological evidence is described, showing that some neurons in the macaque temporal cortical visual areas have responses that are invariant with respect to the position, size and view of faces and objects, and that these neurons show rapid processing and rapid learning. A theory is then described of how such invariant representations may be produced in a hierarchically organized set of visual cortical areas with convergent connectivity. The theory proposes that neurons in these visual areas use a modified Hebb synaptic modification rule with a short-term memory trace to capture whatever can be captured at each stage that is invariant about objects as the object changes in retinal position, size, rotation and view. Simulations are then described which explore the operation of the architecture. The simulations show that such a processing system can build invariant representations of objects.

Animals↗
PubMedDate not supplied

Recursive self-organizing maps.

This paper explores the combination of self-organizing map (SOM) and feedback, in order to represent sequences of inputs. In general, neural networks with time-delayed feedback represent time implicitly, by combining current inputs and past activities. It has been difficult to apply this approach to SOM, because feedback generates instability during learning. We demonstrate a solution to this problem, based on a nonlinearity. The result is a generalization of SOM that learns to represent sequences recursively. We demonstrate that the resulting representations are adapted to the temporal statistics of the input series.

Algorithms↗
PubMed1981

Effect of familiarity of Multielement matching.

The effect of stimulus familiarity on physical matching was examined in three experiments. In Experiment 1, subjects matched English and Armenian letters. String length varied from one to three items. Familiarity had no effect when two single items were compared, but it had increasingly marked effects with two- and three-item strings. The pattern of same/different responses and serial position effects implicated the comparison process for three-item matches. Experiment 2 varied stimulus onset asynchrony to assess the contribution of familiarity to speeding up encoding and/or to maintaining a representation in memory; only two-item strings were used. Encoding Armenian letters required more time than encoding English, but there was no additional decrement due to holding the representation in memory. In Experiment 3, one group of subject learned names for the Armenian letters and another group practiced drawing the letters. The availability of names did not decrease the familiarity effect. These data suggest that familiarity invariably has a strong effect on the encoding process and influences comparison processes when task requirements are sufficiently demanding.

Adult↗
PubMed1999

Memory retrieval and suppression: the inhibition of situation models.

When people retrieve newly learned facts on a recognition test, they are often increasingly slowed by the number of other newly learned facts that have a concept in common with the probed fact. This is called the fan effect. Assuming that people are using situation models of the learned information, the author considers whether the inhibition of competing representations is one of the processes involved in the fan effect. Evidence was found for negative priming of related but irrelevant situation models, thus supporting the idea that the inhibition of highly related memory traces is used in long-term memory retrieval. As such, this is a form of retrieval-based inhibition.

Adult↗
PubMed2001

Forming classes by stimulus frequency: behavior and theory.

Visual classification is the way we relate to different images in our environment as if they were the same, while relating differently to other collections of stimuli (e.g., human vs. animal faces). It is still not clear, however, how the brain forms such classes, especially when introduced with new or changing environments. To isolate a perception-based mechanism underlying class representation, we studied unsupervised classification of an incoming stream of simple images. Classification patterns were clearly affected by stimulus frequency distribution, although subjects were unaware of this distribution. There was a common bias to locate class centers near the most frequent stimuli and their boundaries near the least frequent stimuli. Responses were also faster for more frequent stimuli. Using a minimal, biologically based neural-network model, we demonstrate that a simple, self-organizing representation mechanism based on overlapping tuning curves and slow Hebbian learning suffices to ensure classification. Combined behavioral and theoretical results predict large tuning overlap, implicating posterior infero-temporal cortex as a possible site of classification.

Adult↗
PubMed1997

The hippocampus and memory for orderly stimulus relations.

Human declarative memory involves a systematic organization of information that supports generalizations and inferences from acquired knowledge. This kind of memory depends on the hippocampal region in humans, but the extent to which animals also have declarative memory, and whether inferential expression of memory depends on the hippocampus in animals, remains a major challenge in cognitive neuroscience. To examine these issues, we used a test of transitive inference pioneered by Piaget to assess capacities for systematic organization of knowledge and logical inference in children. In our adaptation of the test, rats were trained on a set of four overlapping odor discrimination problems that could be encoded either separately or as a single representation of orderly relations among the odor stimuli. Normal rats learned the problems and demonstrated the relational memory organization through appropriate transitive inferences about items not presented together during training. By contrast, after disconnection of the hippocampus from either its cortical or subcortical pathway, rats succeeded in acquiring the separate discrimination problems but did not demonstrate transitive inference, indicating that they had failed to develop or could not inferentially express the orderly organization of the stimulus elements. These findings strongly support the view that the hippocampus mediates a general declarative memory capacity in animals, as it does in humans.

Animals↗
PubMedDate not supplied

Firing characteristics of deep layer neurons in prefrontal cortex in rats performing spatial working memory tasks.

Single cells were recorded with 'tetrodes' in regions of the rat medial prefrontal cortex, including those which are targets of hippocampal afferents, while rats were performing three different behavioral tasks: (i) an eight-arm radial maze, spatial working memory task, (ii) a figure-eight track, delayed spatial alternation task, and (iii) a random food search task in a square chamber. Among 187 recorded units, very few exhibited any evidence of place-specific firing on any of the behavioral tasks, except to the extent that different spatial locations were related to distinct phases of the task. Furthermore, no prefrontal unit showed unambiguous spatially dependent delay activity that might mediate working memory for spatial locations. Rather, the cells exhibited diverse correlates that were generally associated with the behavioral requirements of performing the task. This included firing related to intertrial intervals, onset or end of trials, selection of specific arms on the eight-arm radial maze, delay periods, approach to or departure from goals, and selection of paths on the figure-eight track. Although a small number of cells showed similar behavioral correlates across tasks, the majority of cells showed no consistent correlate when recorded across multiple tasks. Furthermore, some units did not exhibit altered firing patterns in any of the three tasks, while others showed changes in firing that were not consistently related to specific behaviors or task components. These results are in agreement with previous lesion and behavioral studies in rats that suggest a prefrontal cortical role in encoding 'rules' (i.e. structural features) or behavioral sequences within a task but not in encoding allocentric spatial information. Given that the hippocampal projection to this cortical region is capable of undergoing LTP, our data lead to the hypothesis that the role of this projection is not to impose spatial representations upon prefrontal activity, but to provide a mechanism for learning the spatial context in which particular behaviors are appropriate.

Action Potentials↗
PubMed2025

Efficient detection and characterization of targets of natural selection using transfer learning.

Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data have been developed to uncover these adaptive signatures. Convolutional neural networks (CNNs) are particularly effective for this task, as they handle large data arrays while maintaining element correlations. However, shallow CNNs may miss complex patterns due to their limited capacity, while deep CNNs can capture these patterns but require extensive data and computational power. Transfer learning addresses these challenges by utilizing a deep CNN pre-trained on a large dataset as a feature extraction tool for downstream classification and evolutionary parameter prediction. This approach reduces extensive training data generation requirements and computational needs while maintaining high performance. In this study, we developed TrIdent, a tool that uses transfer learning to enhance detection of adaptive genomic regions from image representations of multilocus variation. We evaluated TrIdent across various genetic, demographic, and adaptive settings, in addition to unphased data and other confounding factors. TrIdent demonstrated improved detection of adaptive regions compared to recent methods using similar data representations. We further explored model interpretability through class activation maps and adapted TrIdent to infer selection parameters for identified adaptive candidates. Using whole-genome haplotype data from European and African populations, TrIdent effectively recapitulated known sweep candidates and identified novel cancer, and other disease-associated genes as potential sweeps.

Journal Article↗
PubMedDate not supplied

[Proposal for a new descriptive psycho-physiopathological model of schizophrenia].

We present the conclusions of a study of pattern recognition in an intermittent luminous stimulation. This stimulation was stable on the one hand and on the other hand on fixed time basis (S.L.I. pulsations emitted by two flickers) and other associated tests (reaction time, Rorschach Test, etc). We have compared a population of 30 schizophrenics (French classification) and a reference group of 53 adult subjects of both sexes. We have not divided the patients into subclasses according to their symptoms. We have noticed in a significant manner the following signs: great vigilance at the beginning, decreasing very quickly, low attentiveness, a slowness of perception and motion, a weakness in the elaboration of decision processus, certain difficulties in defining the classification of objects, a modified perception of colours, a very feeble distinction of pertinent signals and of noise, an invasion by the internal stimulus, unbalanced compared to "outside", as in sensory deprivation, a great weakness in the processus of habituation and learning, a loss of the redundancy and the constancy of the outside world (or troubles of the internal coherency, as defined by Varela). The closure, the temporal troubles (historical and present) of the integration of signals are sufficient to explain these results. A model explains the deduced hypothesis on two levels: 1) historical: the troubles of habituation and learning prevent the formation of the inner stimulus (or image, representation); 2) present: closure, ambivalence (Gödel), troubles of associations, difficulties in detecting what is pertinent, hallucinations (a "delirious" internal stimulus). The specific brain-channels seem to be normal, on the contrary the non-specific channels and the channels of integration seem troubled. The temporal trouble of "present" seems to be located on a precocious precategorical iconic level. This descriptive model does not prejudge the etiology of the disease (bibliography).

Adult↗
PubMed1998

Spatio-temporal influences at the neural level of object recognition.

In late 1988, Miyashita published work reporting recordings of single cells in the inferotemporal cortex of the macaque monkey (Miyashita 1988 Nature 335 817-20). He described the responses of neurons to a sequence of random fractal pattern images, and how many of the neurons tested were seen to respond strongly to a subset of the images on the basis of sequence presentation order, i.e. appearance in time, rather than their spatial similarity. In this work, I describe a local Hebb-like learning rule which in conjunction with a simple feedforward neural architecture is capable of replicating the type of temporal-order association apparent in the cells from which he made recordings. The paper also advances reasons for requiring such learning by describing its possible role in establishing transformation invariant representations of objects.

Animals↗
PubMed1998

The integration of a novice user interface into a professional modeling tool.

This paper describes a software tool, the Oncology Thinking Cap (OncoTCAP) and reports on our efforts to develop a novice user interface to simplify the task of describing biological models of cancer and its treatment. Oncology Thinking Cap includes a modeling tool for making relationships explicit and provide dynamic feedback about the interaction between cancer cell kinetics, treatments, and patient outcomes. OncoTCAP supports student learning by making normally invisible processes visible and providing a representational tool that can be used to conduct thought experiments. We also describe our novice interface and report the results of initial usability testing.

Cell Cycle↗
PubMed2001

The central nervous system stabilizes unstable dynamics by learning optimal impedance.

To manipulate objects or to use tools we must compensate for any forces arising from interaction with the physical environment. Recent studies indicate that this compensation is achieved by learning an internal model of the dynamics, that is, a neural representation of the relation between motor command and movement. In these studies interaction with the physical environment was stable, but many common tasks are intrinsically unstable. For example, keeping a screwdriver in the slot of a screw is unstable because excessive force parallel to the slot can cause the screwdriver to slip and because misdirected force can cause loss of contact between the screwdriver and the screw. Stability may be dependent on the control of mechanical impedance in the human arm because mechanical impedance can generate forces which resist destabilizing motion. Here we examined arm movements in an unstable dynamic environment created by a robotic interface. Our results show that humans learn to stabilize unstable dynamics using the skillful and energy-efficient strategy of selective control of impedance geometry.

Adaptation, Physiological↗
PubMed2001

Episodic-like memory in animals: psychological criteria, neural mechanisms and the value of episodic-like tasks to investigate animal models of neurodegenerative disease.

The question of whether any non-human species displays episodic memory is controversial. Associative accounts of animal learning recognize that behaviour can change in response to single events but this does not imply that animals need or are later able to recall representations of unique events at a different time and place. The lack of language is also relevant, being the usual medium for communicating about the world, but whether it is critical for the capacity to represent and recall events is a separate matter. One reason for suspecting that certain animals possess an episodic-like memory system is that a variety of learning and memory tasks have been developed that, even though they do not meet the strict criteria required for episodic memory, have an 'episodic-like' character. These include certain one-trial learning tasks, scene-specific discrimination learning, multiple reversal learning, delayed matching and non-matching tasks and, most recently, tasks demanding recollection of 'what, where and when' an event happened. Another reason is that the neuronal architecture of brain areas thought to be involved in episodic memory (including the hippocampal formation) are substantially similar in mammals and, arguably, all vertebrates. Third, our developing understanding of activity-dependent synaptic plasticity (which is a candidate neuronal mechanism for encoding memory traces) suggests that its expression reflects certain physiological characteristics that are ideal components of a neuronal episodic memory system. These include the apparently digital character of synaptic change at individual terminals and the variable persistence of potentiation accounted for by the synaptic tag hypothesis. A further value of studying episodic-like memory in animals is the opportunity it affords to model certain kinds of neurodegenerative disease that, in humans, affect episodic memory. An example is recent work on a transgenic mouse that over-expresses a mutation of human amyloid precursor protein (APP) that occurs in familial Alzheimer's disease, under the control of platelet derived (PD) growth factor promoter (the PDAPP mouse). A striking age- and amyloid plaque-related deficit is seen using a task in which the mice have to keep changing their memory representation of the world rather than learn a single fact.

Alzheimer Disease↗
PubMed2001

An autoassociative neural network model of paired-associate learning.

Hebbian heteroassociative learning is inherently asymmetric. Storing a forward association, from item A to item B, enables recall of B (given A), but does not permit recall of A (given B). Recurrent networks can solve this problem by associating A to B and B back to A. In these recurrent networks, the forward and backward associations can be differentially weighted to account for asymmetries in recall performance. In the special case of equal strength forward and backward weights, these recurrent networks can be modeled as a single autoassociative network where A and B are two parts of a single, stored pattern. We analyze a general, recurrent neural network model of associative memory and examine its ability to fit a rich set of experimental data on human associative learning. The model fits the data significantly better when the forward and backward storage strengths are highly correlated than when they are less correlated. This network-based analysis of associative learning supports the view that associations between symbolic elements are better conceptualized as a blending of two ideas into a single unit than as separately modifiable forward and backward associations linking representations in memory.

Association Learning↗
PubMed1998

Do viewpoint-dependent mechanisms generalize across members of a class?

Evidence for viewpoint-specific image-based object representations have been collected almost entirely using exemplar-specific recognition tasks. Recent results, however, implicate image-based processes in more categorical tasks, for instance when objects contain qualitatively different 3D parts. Although such discriminations approximate class-level recognition. they do not establish whether image-based representations can support generalization across members of an object class. This issue is critical to any theory of recognition, in that one hallmark of human visual competence is the ability to recognize unfamiliar instances of a familiar class. The present study addresses this questions by testing whether viewpoint-specific representations for some members of a class facilitate the recognition of other members of that class. Experiment 1 demonstrates that familiarity with several members of a class of novel 3D objects generalizes in a viewpoint-dependent manner to cohort objects from the same class. Experiment 2 demonstrates that this generalization is based on the degree of familiarity and the degree of geometrical distinctiveness for particular viewpoints. Experiment 3 demonstrates that this generalization is restricted to visually-similar objects rather than all objects learned in a given context. These results support the hypothesis that image-based representations are viewpoint dependent, but that these representations generalize across members of perceptually-defined classes. More generally, these results provide evidence for a new approach to image-based recognition in which object classes are represented as cluster of visually-similar viewpoint-specific representations.

Adult↗
PubMed2006

Context fear learning in the absence of the hippocampus.

Lesions of the rodent hippocampus invariably abolish context fear memories formed in the recent past but do not always prevent new learning. To better understand this discrepancy, we thoroughly examined the acquisition of context fear in rats with pretraining excitotoxic lesions of the dorsal hippocampus. In the first experiment, animals received a shock immediately after placement in the context or after variable delays. Immediate shock produced no context fear learning in lesioned rats or controls. In contrast, delayed shock produced robust context fear learning in both groups. The absence of fear with immediate shock occurs because animals need time to form a representation of the context before shock is presented. The fact that it occurs in both sham and lesioned rats suggests that they learn about the context in a similar manner. However, despite learning about the context in the delay condition, lesioned rats did not acquire as much fear as controls. The second experiment showed that this lesion-induced deficit could be overcome by increasing the number of conditioning trials. Lesioned animals learned normally after multiple shocks, regardless of freezing level or trial spacing. The last experiment showed that animals with complete hippocampus lesions could also learn about the context, although the same lesions produced devastating retrograde amnesia. These results demonstrate that alternative systems can acquire context fear but do so less efficiently than the hippocampus.

Amnesia, Retrograde↗