Cerebellar models of associative memory: Three papers from IEEE COMPCON spring 1989

Three papers are presented on the following topics: (1) a cerebellar-model associative memory as a generalized random-access memory; (2) theories of the cerebellum - two early models of associative memory; and (3) intelligent network management and functional cerebellum synthesis

From Parallel Sequence Representations to Calligraphic Control: A Conspiracy of Neural Circuits

Calligraphic writing presents a rich set of challenges to the human movement control system. These challenges include: initial learning, and recall from memory, of prescribed stroke sequences; critical timing of stroke onsets and durations; fine control of grip and contact forces; and letter-form invariance under voluntary size scaling, which entails fine control of stroke direction and amplitude during recruitment and derecruitment of musculoskeletal degrees of freedom. Experimental and computational studies in behavioral neuroscience have made rapid progress toward explaining the learning, planning and contTOl exercised in tasks that share features with calligraphic writing and drawing. This article summarizes computational neuroscience models and related neurobiological data that reveal critical operations spanning from parallel sequence representations to fine force control. Part one addresses stroke sequencing. It treats competitive queuing (CQ) models of sequence representation, performance, learning, and recall. Part two addresses letter size scaling and motor equivalence. It treats cursive handwriting models together with models in which sensory-motor tmnsformations are performed by circuits that learn inverse differential kinematic mappings. Part three addresses fine-grained control of timing and transient forces, by treating circuit models that learn to solve inverse dynamics problems.National Institutes of Health (R01 DC02852

Sensory Prediction or Motor Control? Application of Marr–Albus Type Models of Cerebellar Function to Classical Conditioning

Marr–Albus adaptive filter models of the cerebellum have been applied successfully to a range of sensory and motor control problems. Here we analyze their properties when applied to classical conditioning of the nictitating membrane response in rabbits. We consider a system-level model of eyeblink conditioning based on the anatomy of the eyeblink circuitry, comprising an adaptive filter model of the cerebellum, a comparator model of the inferior olive and a linear dynamic model of the nictitating membrane plant. To our knowledge, this is the first model that explicitly includes all these principal components, in particular the motor plant that is vital for shaping and timing the behavioral response. Model assumptions and parameters were systematically investigated to disambiguate basic computational capacities of the model from features requiring tuning of properties and parameter values. Without such tuning, the model robustly reproduced a range of behaviors related to sensory prediction, by displaying appropriate trial-level associative learning effects for both single and multiple stimuli, including blocking and conditioned inhibition. In contrast, successful reproduction of the real-time motor behavior depended on appropriate specification of the plant, cerebellum and comparator models. Although some of these properties appear consistent with the system biology, fundamental questions remain about how the biological parameters are chosen if the cerebellar microcircuit applies a common computation to many distinct behavioral tasks. It is possible that the response profiles in classical conditioning of the eyeblink depend upon operant contingencies that have previously prevailed, for example in naturally occurring avoidance movements

Hierarchically Clustered Adaptive Quantization CMAC and Its Learning Convergence

No abstract availabl

Neural Dynamics of Autistic Behaviors: Cognitive, Emotional, and Timing Substrates

What brain mechanisms underlie autism and how do they give rise to autistic behavioral symptoms? This article describes a neural model, called the iSTART model, which proposes how cognitive, emotional, timing, and motor processes may interact together to create and perpetuate autistic symptoms. These model processes were originally developed to explain data concerning how the brain controls normal behaviors. The iSTART model shows how autistic behavioral symptoms may arise from prescribed breakdowns in these brain processes.Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624

Monoamine influences in cerebellar memory consolidation

An association between climbing fibre and mossy fibre/parallel fibre inputs to the Purkinje cell is critical for cerebellar learning. In addition to these two major afferent systems, the cerebellum also receives a range of neuromodulatory inputs; most prominent are the noradrenergic and serotonergic afferents. Early theoretical and empirical accounts support a role for noradrenergic input as providing an essential third, consolidation signal in learning. In comparison to the glutamatergic afferents very little is known about the anatomy, physiology and behavioural aspects of the neuromodulatory afferents. The distributions by cell type of β1- and β2-adrenoceptors in the cerebellar cortex and nuclei and of α1-adrenoceptors in the cerebellar cortex, are shown for the first time. Earlier work demonstrated the necessity for β-adrenoceptor activation in consolidation of classical conditioning of the nictitating membrane response (NMR). Here, a dissociation of β1- and β2-adrenoceptor expression was shown. β1-adrenoceptors are restricted to Purkinje cells and β2-adrenoceptors are restricted to Bergmann glial cells. The cerebellar cortical distributions of noradrenergic and serotonergic afferents were compared. In cortical vermis, individual noradrenergic afferents were limited in their medial-lateral extent to less than 300 µm but were more extended in the rostral-caudal plane by up to 800 µm. Serotonergic afferents ran orthogonal to the noradrenergic afferents, with extents up to 900 µm in the medial-lateral plane but less than 200 µm in the rostral-caudal plane. Recent work has demonstrated a critical role for Purkinje cell mGlu7 activation in regulating the pause in Purkinje cell simple spike activity believed to be the cellular mechanism underpinning the conditioned eyelid blink/ NMR. Attempts were made to assess the specific function of the β1-adrenoceptor and mGlu7 in consolidation and performance of NMR conditioning, respectively. However, methodological constraints left these questions unresolved. It is concluded that the noradrenaline consolidation signal may target limited cortical territories and modulate Purkinje cells or Bergmann glial cells. In contrast, the serotonin signal is diffuse and targets multiple cortical regions simultaneously to fulfil a role in cerebellar processing distinct from that of noradrenergic signalling

Feedback control of cerebellar learning

The ability to anticipate future events and to modify erroneous anticipatory actions is crucial for the survival of any organism. Both theoretical and empirical lines of evidence implicate the cerebellum in this ability. It is often suggested that the cerebellum acquires “expectations” or “internal models”. However, except in a metaphorical sense, the cerebellum, which consists of a set of interconnected nerve cells, cannot contain “internal models” or “have expectations”. The aim of this thesis is to untangle these metaphors by translating them back into neurophysiological cause and effect relationships. This task is approached from within the paradigm of classical conditioning, in which a subject, through repeated presentations of a conditional stimulus, followed by an unconditional stimulus, acquires a conditioned response. Importantly, the conditioned response is timed so that it anticipates the unconditioned response. Available neurophysiological evidence suggests that Purkinje cells, in the cerebellar cortex, generate the conditioned response. In addition, Purkinje cells provide negative feedback to the IO, which is a relay for the unconditional stimulus, via the nucleo-olivary pathway. Purkinje cells can therefore regulate the intensity of the signal derived from the unconditional stimulus, which, in turn, decides subsequent plasticity. Hence, as learning progresses, the IO signal will become weaker and weaker due to increasing negative feedback from Purkinje cells. Thus, in an important sense, learning induced changes in Purkinje cell activity constitute an “expectation” or “anticipation” of a future event (the unconditional stimulus), and, consistent with theoretical models, future learning depends on the accuracy of this expectation. Paper 1 in this thesis show that learned changes in Purkinje cells influences subsequent IO activity. The second paper show that, depending on the number of pulses it contains, the signal from the IO to the Purkinje cells can either cause acquisition or extinction. In the third paper we present evidence that can potentially help explain overexpectation, a behavioral phenomenon, which have for long been elusive. Collectively these papers advance our understanding of the feedback mechanisms that govern cerebellar learning and it proposes a potential solution to some long standing behavioral conundrums